The cookie collapse has shaken up the world of digital advertising, forcing marketers to come up with new ways to gather data and reach their target audience. In this article, we take a closer look at how savvy marketers are adapting to the changes in privacy laws and finding innovative solutions to overcome the challenges posed by the cookie collapse. From alternative data sources to cutting-edge technology, we explore the ways in which marketers are ensuring they can continue to provide a personalized and relevant experience for their users while respecting privacy standards.

The “cookie apocalypse” will mean the end of an era for digital marketing as we know it. We’ll discuss with digital analytics expert & CEO of Provalytics Jeff Greenfield how savvy marketers are adjusting and what strategies and marketing technologies these organizations are implementing right now to thrive in the new normal.

Hugh Macken:
And good afternoon everyone. My name is Hugh Macken. I’m with VMR Communications and I’m joined by my co-host Danielle Milliken.

Danielle Milliken:
Hello.

Hugh Macken:
And we are here with a very special guest who I’ll introduce momentarily. And our topic today is the Future of Digital Advertising in a Cookie-Less World. And we’ll be looking at what the future is going to look like and how digital marketers can and should adjust to what is really a rapidly changing landscape for digital advertising. As I said, we do have a special guest. His name is Jeff Greenfield.

Jeff is an expert in all things digital measurement and he is an acclaimed expert. He’s been featured in many, many mainstream news outlets for his expertise. I recently watched an interview, you did Jeff, on Bloomberg and was just really impressed. We’ve known each other for several years. Jeff is the CEO of Provalytics. And Jeff, if you wouldn’t mind, I mean your resume is so long, I think you’d be better at summarizing your background. Would you, first of all welcome, and please tell us more about yourself and your background in digital measurement and analytics?

Jeff Greenfield:
Thank you so much Hugh, and Danielle as well.  In terms of my background that’s applicable for the audience today is I started on the brand side specifically doing branded entertainment, these large scale programs for brands that really get the word out. But that was back in the early 2000s and back then there was no way to measure anything. The measurement was really lost. People started moving towards digital because you could actually measure clicks and that was really cool. But then digital advertising got so complicated and it was really tough to figure out what was working and what wasn’t working.  So in 2008 I started a company called C3 Metrics. C3 was the leading multi-touch attribution company for enterprise clients. So we’re talking folks like JP Morgan, US Bank, a ton of folks in the pharma and the financial services space who spend a substantial sum each year on marketing.

And for them it’s very difficult to figure out what was working and what wasn’t. And it was an interesting time because we were able to get the entire digital trail back then we had tags that were on Facebook, even on Amazon for a period of time, even YouTube, we could collect all of this data and it was really incredible. So we had a full deterministic methodology of figuring out where you should spend your next marketing dollar to get the biggest bang for your buck, if you will. And then all of a sudden things, the world changed and Facebook stopped allowing tags, YouTube stopped allowing tags and that wasn’t a big deal. But now we’re living in a world where there’s so many different channels that don’t allow you to measure, not clicks, but the impression, which is that when somebody gets exposed or sees an ad.  And so you don’t have independent ways of measuring that. So I exited C3 Metrics at the end of 2019 and started looking at the landscape to see what was going on out there. And that’s when I started Provalytics. And Provalytics is the next generation of attribution that works incredibly well and was designed for this new privacy centric cookie-less future that we have. And that’s part of the reason why cookie-less is coming up is it all revolves around privacy and stuff like that. So it’s coming… 2023 and 2024 are going to be very interesting years with all of the changes that are coming up. And I’ll leave it right there with that, Hugh.

Hugh Macken:
No, sounds good. So Jeff, if you wouldn’t mind just elaborate a little bit on at a very high level what some of those privacy changes are from a technical standpoint. And I want to look at the browser level at the OS level. Apple for example, with its privacy policies. So cookies, third party cookies being deprecated, identity solutions being proposed by the likes of the trade desk and being adopted, unified ID 2.0. So tell us a little bit more about what changes are going to be happening on the technical side. And then I’d love to talk about of ways that marketers can adjust on the technical side, but also ways that marketers can adjust on the strategic side. So how might marketers align more closely with media? But let’s just start off with what are all of the technical changes that are happening with, just give us a bird’s eye view.

Jeff Greenfield:
Sure. I’m going to give a little history with this and go back to something that was called GDPR, which was the start of all of this. And GDPR is the European version of privacy controls. And the way the whole internet has always worked is that the internet was free and the reason it was free was because of advertising and everyone was automatically opted in. And GDPR came out and said, “Guess what?” People are not automatically opted in. And if you have a list of people that have said, “Hey, I want to get your newsletter,” you have to assume that none of them are on your list and you have to email them and ask them for permission. So that caused a ripple effect because there were a lot of companies that had built businesses on identity stitching, meaning connecting someone who was at their work computer with their iPad at home and their mobile device.

And they had stitched together all of these different identities. So when GDPR came out, it ripple effect occurred where a bunch of companies that were operating internationally shut down their European operation because it was so stringent it would be starting brand new again even though they had been operating for a half a dozen years. So the next legislative thing that came about was in California, the CCPA. Now if you notice and if you have a website, you should already have this, there’s a button or a link down at the bottom that says, “Do not sell my personal information.” So California came out with this law that says you have to have a link at the bottom of your website for California residents where they can access their information, they can ask you to amend it or they can ask you to delete it.

And the regulation states that you have to have a form that people can fill out and also allow for an 800 number. So when this first came out, a lot of people thought it wasn’t that big of a deal, but California just recently fined a very large retailer for this. So they’re getting very serious about that. But shortly after that, Nevada came out with another law and Maryland came out with another one. So from an internet regulation standpoint of view, there’s pending legislation in at least 40 states for how you deal with people’s information. And that ties right in to how the internet has always operated. Now it and the operations have to do with cookies. Now if you notice when you go to Amazon, you log right into Amazon if you’re not using your phone and you go there, they know you, they know all your stuff.

That’s called a first party cookie. A first party cookie is the type of cookie that the site you’re on, the one that shows up in that URL bar where you type in whatever site that is, a first party cookie is written by them. So if you go to the New York Times and you log in, New York Times can read and write their own cookies. But the internet and all of advertising was built on third party cookies. And what that means is that when you’re on the New York Times, there’s a bunch of other vendors and ads that are there that are dropping cookies that are from different domains. And the reason they’re doing that is if I’m an advertising company and you’re on the New York Times and then you go to the Wall Street Journal, I want to know that you’re also at the Wall Street Journal.

If I show one of my ads so I can control things like reach and frequency. And that’s how the whole internet has always functioned. Now, Apple has always operated in their own ecosystem and privacy has been a very important component to the entire company. So in their Safari browser, they’ve shut off third party cookies for a very long time. They’ve been gone for a very long time. And to marketers, most marketers just said, “That’s okay,” because there’s more Android people than there are Safari, so it was no big deal. And that occurred both on the browser and on your cell phone as well too. Firefox, which is a small percentage of the browser community, they also shut off third party cookies. And then the big announcement is Chrome, was supposed to do it next year, but it’s being pushed to 2024, Chrome has about 65-70% of the market.

So what that means is that the way advertising has worked, the way you have targeted, the way you’ve measured is going to be completely different in the next year to year and a half. And we always talk about, and Hugh and I have talked about this for years, the concept of digital transformation. And most companies have gone through a digital transformation. Well guess what? I hate to say this. There’s another one coming and it involves how you target, but also how you measure. So the other bad news that goes along with this is that the number one metrics that everyone uses is Google Analytics. And everyone has years and years of data in there. And it’s great how you can go in and see your historical data. Well next July 1st, July 1st, 2023, Google has said that platform will stop taking in data. It will no longer accept new data and you have to use their new product, which is GA4.
Now, I don’t understand why a company the size of Google can’t just change the code and have it all secured in there, but they are unable to do that. So what that means is that you have to change a code on your website, which is no big deal for some people. But the other big issue is that the reports in GA4 look completely different. You don’t know where your conversion report is and all of these things. And so now there’s a learning curve. So if you have a small company or even a medium size or large company, not only do you have to pay to get the code change, but you also have to go through a whole new training. So the next year to year and a half is going to be a major transformation that’s going to have to go forward.

Hugh Macken:
And so Jeff, what I hear you talking about really are two different aspects in a way of digital marketing. On the one hand measurement. So how do we do measurement? The way we do measurement going forward is going to change. And then the issue of audience targeting. And really there’s the identity resolution issue that relates to both of those issues. So on the one hand, we want to be able to measure the effectiveness of our advertising and the ability to do identity resolution effectively has aided us in doing that. At the same time, audience targeting cookies, third party cookies have enabled that. So that too will be impacted. Is that fair to say that it’s really those two areas primarily that will be impacted? And really the challenge before us is putting forth technology infrastructure that will allow us to adjust to the changing environment and then also strategies that will help us to adjust as well.

I’m just struck by how many articles I read about how to solve the problem of audience targeting and reaching audiences. Do you think it makes sense in terms of adjusting to the changes from a strategy standpoint for organizations to be maybe asking a fundamentally different question, which is what are different ways in which, what are different models we can use to do more effective advertising? Because at the end of the day, what matters for the CMO say at an institution, say a higher ed institution or an e-commerce provider, isn’t the ability ultimately to target audiences? Ultimately it’s the effectiveness of their advertising that really matters. So are there other ways of going about that? And we’ve spoken quite a bit about the idea of aligning with media. What do you see as the future from a strategy standpoint and a modeling standpoint to adjust?

Jeff Greenfield:
Well, and that’s part of the big adjustment that’s going to go on Hugh, which is that most marketers today in the digital realm are addicted to the granularity of data that they’ve been brought up on. A great example is my daughter. My daughter ran marketing for a large auto dealer group. And I remember her telling me a couple years ago, “It’s pretty amazing. I can go into Facebook, I can target Ford F-150 leaseholders whose lease is going to expire in six months.” I’m like, “That’s pretty granular.” Well that’s all gone. And so for a lot of digital natives who have never done planning and large scale, both in traditional and digital media, a lot of them are feeling like they’re being choked a bit because it’s like, “How am I supposed to work with this broadness?” But the reality is that the research has shown that this level of granularity that we’ve gotten so addicted to, it’s like we’re in the middle of the forest and we can’t see the trees, that old analogy. We’re in too deep and we’re too addicted as marketers to this granularity of data.

Now remember, third party cookies are going away, first party are not. So what that means is, in the example I gave of the New York Times and the Wall Street Journal, and there’s all sorts of other specialty publications out there, they have paywalls up that require people to sign up or people will sign up on the email. And what they’re doing is that they are mining that data and building up really great segments internally. So I think one of the things that’s going to happen is that when we had this explosion of ad tech, we had a move towards exchanges like the trade desk, but some of the earlier ones were all of the buys were done on these exchanges where if I’m the New York Times, I don’t have any people selling ads. What I’ve got is I’ve got ads that are all going through an exchange, but now we’re moving into a world where doing direct buys have a huge benefit because of the level of data that they have.

So for example, if you’re like a college or university and you’re focused on applications and enrollments, you can go and do a buy on Google and Facebook, but you start to dig into your data and you start to look at, you may have 20 different degree programs and there may be one on nursing that’s very, very popular. Well, there’s a lot of specialty publications out there that you can go to and do direct buys on that specialize in nursing and nursing careers. That would be great to flow into this strategy. So I think that’s part of it from the targeting aspect of where folks are going to have to start thinking because that granularity of data is, it’s not even available now and it’s going to be even less over the next year or so.

Danielle Milliken:
Yeah. So Jeff, you made a comment about direct buys and how that’s going to become the future of digital marketing. So can you speak a little bit more to that in the sense that how companies can maybe adjust what they’re doing? Like their team. How they might need to adjust their teams and their roles moving forward to make sure that they’re ready for this landscape change, whatever that might be.

Jeff Greenfield:
Well, I think one of the best things that a company can do is the difference between direct buys and the exchange buys all has to do when you’re negotiating. So sending your head buyer or the person who’s handling it out for a course on negotiation and researching online, what are the types of things that you can get with a direct buy? Because with a direct buy, you can negotiate a package where you’ve got ads on the site, they push out a couple of newsletters, maybe they do an advertorial for you as well, customized content.

And Hugh and I have talked before, and he’s even showed me examples of some of the work that you guys have done with really, really cool email capture that goes right into the client’s CRM, which is amazing and these types of deals are all out there. But I think the key is trying to figure out what’s available and then also negotiating the best deal because it’s a whole different world versus just buying ads and spending money. This you have to plan. That’s the other thing, is the time that’s involved too. And there’s a lot of work that goes into planning these types of campaigns.

Danielle Milliken:
For sure.

Hugh Macken:
For sure. Yeah, no, that makes sense. So Jeff, if you would speak a little bit about the key components of a marketing technology stack. So again, imagine you’re speaking to a CMO at a university say, and they’re trying to figure out, “Okay, what are the key components that we need marketing?” So I’m thinking like CDP, DMP, data warehouse, like Snowflake. What are a platform like Provalytics or there’s, I believe Oracle has a product in relation to measurement and analytics as well. So what are the key components that you would recommend to help marketers adjust to this new landscape?

Jeff Greenfield:
So the first thing is that I would set with the CMO, the understanding that Google Analytics, which 99% of marketers use, is an awesome web analytics platform. Meaning it does a really good job of once people end up at your site, you can see what they do on your site and you can see where they came from. Now anyone who’s dug into GA or even GA four, you will notice that 80% of the people come in, it’s called organic, they just show up. And the problem is from a marketer’s standpoint of view is that if you’re using Google Analytics to plan your media buys you’re doing the wrong thing. There’s no ifs, ands, or buts about it. Most marketers know that you have to fill the top of your funnel. There’s that AIDA, awareness, interest, desire, and action. And in order to fill that funnel, that awareness, you have to put messages out there, they can be targeted, but the broader, the better, as long as it’s within your target or your geo that you want to be at.

And what you really want to know is when you look in Google Analytics, what is driving, how did those people find out about my site to come directly in? Another way to look at it is that most larger brands will spend money in Google and what they call brand search so that when you type in the name of the company or the university, you’ll see them listed there first. Well how are people coming through brand search? Because Google Analytics will show you, “Hey, brand search is converting really well. Wow, you’re getting a lot of leads from brand search.” But it’s because brand search people already know about you in order to search. So you have to ask yourself, I really want to know who’s driving, what is driving brand search? What is behind that? And now for smaller marketers, one of the best ways to do it, so I’ll give a solution for smaller marketers first.

For smaller marketers, you want to do a little research into something called regression analysis. And regression is all about trying to figure out what’s the causation behind these things. And what you would do is you would take all of your channels that you’re spending on and you would look at how many impressions you’re producing and how many clicks each hour. And then you would run regression analysis between that and your brand search click. So you can see who’s actually driving brand search because that’s your top of the funnel drivers and that’s where you want to spend. Now for larger folks and larger players like a university, you need a platform that can automatically grab that impression data, not only analyze it, but have the proof behind it that it actually works. And you see this is a huge distinction. One of the biggest problems with most attribution and all of these platforms is they do a really good job of reporting about what happened last week, yesterday or last month.
But they don’t do a really good job of planning, which is what we’ve been talking about a lot. And planning is all about forecasting and saying, if you do this, you’re going to get this much money in return. And what’s really important with that is to be able to predict what the return will be on investment and then putting your money where your mouth is and showing confidence scores for that, which is what we do at Provalytics. And very few analytics platforms, if any, actually do that. And that’s important because remember at the end of the day you want to know how are people finding out about me?

That’s where you want to spend your dollars. It’s very easy to spend close to the bottom of the funnel. Google search is easy, Facebook retargeting is a great place to be. And then of course, as we talked about specialty publications that you can go to, these are great, but how do you fill that top of the funnel? In order to do that, you have to have a platform that can do it or you have to do a hand analysis to figure out what is driving your brand search, what is driving your organic traffic.

Hugh Macken:
Yeah, no makes sense. And I mean you’ve mentioned branding quite a bit and I wonder, are we going to see a pivot here on the digital side to where digital marketers start actually focusing on branding as opposed to just constantly focusing on direct response? I just read an interesting article recently on Airbnb and how they invested in branding and it really paid off with respect to direct response. So what’s your thought on that? Are we going to see more of a shift toward branding on the digital side?

Jeff Greenfield:
I sure hope so. And I’ve mentioned this book before, I’ll just hold it up right here. The book is called Lemon, It’s by Orlando Wood from the IPA in the UK. It’s available on Amazon, full color. It’s amazing. And what the author has done is he has researched the effectiveness of ads and what they’ve seen is they’ve seen an increase since 2006 in what they call short-termism. And short-termism is spending closer to where the transaction is. So it started, because in 2005, most brands, all they had was a brand. There was no performance divisions or anything like that. But when digital started coming out, they started testing and then they built up teams. And now there’s for large brands, they spent a lot on branding, but they spend even more on performance marketing. And look at like CPG, how close to the sale can you get?

Well now not only can I be on Amazon, but I can also be on Walmart. And if I’m tied when someone puts a competitive product in their basket, I can push out an ad that will compel them to buy mine as well or to switch it out for a discount. That’s a lot of money being spent almost at the point of purchase. And that’s what you call a rise in short-termism. And it’s directly correlated to a decrease in ad effectiveness since 2006. Brands definitely need to invest more money, especially now as they say the R word, the recession. And at the ANA masters a couple weeks ago down in Florida, the big thing that everyone was talking about is that marketers and CMOs are going to have more pressure than ever on their marketing budgets to prove to their CFO that if I do this, I’m going to get this. And to be able to plan effectively and forecast and then of course actually hit those numbers. That’s the other problem is that if you don’t execute, you’re definitely not going to hit your forecasts.

Hugh Macken:
For sure. Yeah. So you’ve talked about this model, Jeff, in terms of demonstrating the effectiveness of the advertising, this new model that is a hybrid between media mix modeling and multi-touch attribution. Would you mind just explaining that in simple terms in terms of, well first of all, what is multi-touch attribution? What’s media mix modeling or marketing mix modeling and what’s this hybrid that you’ve been talking that you’ve been talking with me about?

Jeff Greenfield:
Yeah, absolutely. So we’ll start with marketing mix modeling, MMM, because it’s been around since the sixties and seventies and M is typically uses regression modeling that I talked about earlier. And it looks at all of your channels. Now remember this was developed before digital. So companies would do an annual marketing mix modeling where they would look at their TV, radio, print, direct mail, out of home and they would do an analysis and regression towards sales numbers. And then the output of that MMA model was to say, here’s how much budget you should allocate to each of these channels for your sales to continue to move up. And that was great. Now of course what happened is that companies didn’t do them every year. They would skip a couple years and they would just focus on the budget allocations from years prior. And then digital marketing came along and when they integrated digital marketing as a channel into it, since they didn’t understand digital marketing, the output would say spend more on brand search and on affiliate.

Now of course we all know that as we talked about before, brand search is only from people who are already knowing about you. You can’t spend more on brand search to get more and you can’t spend more on affiliate. They all happen as a result of all the other activity. So multi-touch attribution started around 2007 because digital marketing had become, at that time somewhat complicated because you had display, you had search, you had search across multiple platforms and how do you figure things out? And Multitouch attribution said, we’re going to collect all of the data, every bit of granular touchpoints, whereas MMM only took in aggregated data, sometimes monthly, sometimes daily, but primarily large scale privacy centric data, whereas MTA was all user level data, it all model it instead of regression use machine learning. Because if you do regression with that amount of data, it will take forever, forever to get it done.

But machine learning, you can teach the machines and we’ve got great technology. One of them has been around for hundreds of years called Bayesian, which is just incredible because it thinks, and it works the same way that human beings think because we are constantly updating the way we think. So when you think about self-driving cars that aren’t here yet, self-driving cars are always getting smarter, the more obstacles that they face. And that’s the same way with machine learning for marketing attribution. So MTA would take all of that data, put it into a Bayesian model, and it would constantly be updated every single day, sometimes throughout the day with the most updated result of what was going on right at the moment and historical. And that worked great. And the greatest thing about MTA versus MMA is that you weren’t just limited to sales. You could have multiple KPIs at C3 metrics.
We had some clients with 25 or 30 different conversion events because there were different teams that were interested in different things. Some teams were interested in traffic to a particular site that was their KPI, other folks were leads, other folks were actual enrollments when talking about EDU clients here. So that was really great and also it did really well with digital. But since MTA was built on being a deterministic model, MTA fell flat with TV and radio and then podcasts as they started to explode, it was like there’s nothing for anyone to click on. How do you measure this?

Hugh Macken:
Right, right.

Jeff Greenfield:
Yeah. And that was the big problem. The other big issue with multi-touch attribution is that there was no incrementality, so there was no measurement of, it would tell you where to spend more, but it didn’t tell you how much more business you would get.
And marketers always had this question of, “Well, what happened if I didn’t do that? Wouldn’t I get those sales anyway?” And that’s the basis of incrementality. Luckily marketing mix modeling is all based about the contribution that each tactic, but an MMM word, it’s all about the channel. So there is incrementality in MMM, but it’s at a channel level. And so what I wanted to do is I wanted to merge these two together. I wanted to take something that was always on, used some of the MMM background so that you could incorporate not just digital media, but also TV, radio, CTV, podcast, print, direct mail, bring it all together, and not just to sales but to multiple KPIs. And so now what Provalytics is the Venn diagram, if you will, of MTA and MMM. The basis is MMM, but it’s a whole new way of modeling that uses machine learning at scale.

We’re able to take in aggregated daily data from Facebook and from the platforms down to a creative level. And we’re not limited to just pushing out channel level recommendations, but we’re pushing out granular recommendations so that channel managers will know exactly how to allocate based upon their goals. And the forecasting we’re doing is incredible. If I had a team of 500 statisticians running through, because our models, when clients will give us what are their goals for a forecast, how far out do you want to go? Do you want to go 30, 60, 90, 180 days out? What is your risk quotient? How much are you actually willing to increase or decrease a tactic? And what do you want your budget to be? Do you want it to be the same? Do you want to go up 10%, 25% or do you want to go down? And then what our platform will do is go through and run hundreds of thousands of simulations and we’ll export out the optimum plan, meaning, “Hey, this is the amount of money you’re spending, here’s the ultimate, ultimate, this is going to get your biggest bang for your buck.”

Now, in all the years of me doing this, I have never seen any marketer take on all recommendations. They never, ever do. So this forecast is based on a perfect scenario. And so what ends up happening is that clients will take one or two of them, but you don’t actually know what day they put it in at and what the spend is every day. So what Provalytics does, and right now we’re starting to get a lot of the October data from our clients. Most clients send us data monthly. We have a few that send it to us weekly. But what we’ll do is we’ll borrow from MMM and we’ll do a technique called a holdout. So we will hold out and remove all of the sales data and all of the KPI numbers for each day for the last 30 days. And all we will give to our model, to Provalytics is the impressions and the clicks and the spend.

That’s all we’ll give. And then what marketers are able to look at is see how well the model predicted the outcome. And all models I should say are wrong, some are useful. And what clients are seeing is it’s for certain KPIs, the model is spot on. For others it’s not because it’s not perfect. But what happens over time is that since it’s machine learning, it gets smarter and smarter over time. And that’s another thing I’ll mention is that traditionally marketing mix modeling, you need to have three years worth of data in order to build out a model. And this is one of the other problems with MMM is that it becomes a whole project. It’s a lot of work to put this whole thing together. And so that’s why folks don’t do it more than once a year and sometimes skip years.
With Provalytics since it was built on the basis of MMM, but we borrow from the world of MTA, we can start with as little as the last three months. The more data we have, the better. So for customers of ours right now that we’re moving forward, what are we? Eight or nine business days away from when the Black Friday sales start. When we have the historical data from last year, we’ve been able to give them plans for how to execute to get the biggest bang for their buck for this upcoming Black Friday. So the more data we have, the better, but we don’t need three years worth of data. That can be overkill for our models.

Hugh Macken:
Interesting. Wow. And just in the last couple of minutes that we have, Jeff, how would you say a CDP would tie into all of this? A CDP customer data platform, obviously very useful from the standpoint of audience targeting, but with respect to measurement, is there a role that a CDP can play? Does a platform like Provalytics integrate with CDPs? How does that factor into all this?

Jeff Greenfield:
Yeah, and you stated it, One of the best advantages of a CDP is that it allows you to leverage that first party data you have, your first party cookie data. So similar to Google Analytics, which looks at how people traverse your site, a CDP is taking that and putting it on steroids, and it allows you to create unique segments within them. Now the cool thing about segments is that obviously you have a segment of people who have purchased, you have people that are multiple purchasers. If you’re in retail and then you have people that show up, maybe fill out a popup, but don’t go all the way through, let’s say in the case of EDU, the lead process, they don’t want to just subscribe to a newsletter or you just have a ton of people who just show up and then leave.
And so one of the advantages with the CDP is you can create unique customer segments, and then what you can do is you can link those segments to your media buys so that you’re buying the multi shoppers, you’re buying the existing customers to bring them back for retargeting. You’re buying the folks who showed up but didn’t actually fill out a form or anything. And then you can do it on the conversion side to see how many of those people who showed up but didn’t fill out a form, who then were exposed to later advertising ended up purchasing. And what we do with those segments is that becomes a dimension within our model. So now when you think about multiple KPIs, you can look at, let’s say those folks who show up and don’t do anything, but let’s say the segment is they have to spend at least three and a half minutes on the site and you’ve tracked how they’ve converted.

Well, with Provalytics, we can track which media is driving them and what levers to push if you want to increase their conversion rate. So those segments are really important. The other type of dimension that’s also available in Provalytics is geo. So a lot of folks just like to look at the entire, let’s say the continental US, but there’s a lot of brands that target differently. The best one that comes to mind is Southwest Airlines. They are regionally based. All of their ads are regionally purchased. Even their television, they do not buy national TV. For them, they would want to look at things in a region by region basis, and Provalytics is built from the ground up to include that.

Hugh Macken:
Interesting. Wow. So lots to consider for those of us who are trying to make sense of all of this. And Jeff, your perspective definitely is invaluable. I’d love to have you back on again soon to talk.

Jeff Greenfield:
Oh, it’d be my pleasure. Hugh. Absolutely. Anytime.

Hugh Macken:
Yeah, for sure. Just to talk more about this new model that you still haven’t come up with a name for it. I’ve been going back and forth with different ideas.

Jeff Greenfield:
Well, the name that we’re using is, it’s Agile, so it’s not locked in like MMM. And I like the word impact versus incrementality and it’s modeling. So we’re going forward with the concept of AIM, “Agile Impact Modeling”. How do you like that?

Hugh Macken:
Agile Impact Modeling. All right, there you go.

Jeff Greenfield:
You like that, Hugh?

Hugh Macken:
Yeah.

Jeff Greenfield:
Good.

Hugh Macken:
I like it. Because honestly, I was going with something that was going to be MMM.

Jeff Greenfield:
It’s ad tech. We have to have an acronym, so we’ve got it now, AIM. AIM is the acronym.

Hugh Macken:
There you go. There you go. Oh my gosh, Jeff, it was just such a pleasure. Thank you so much for joining us and definitely thank you Danielle as well for joining us. And I want to thank Elijah Medcore, our producer who’s in behind the scenes. Thank you Elijah. And thanks be to God that we were able to make this happen. This is great.

Danielle Milliken:
Yeah.

Jeff Greenfield:
Absolutely. Thanks so much for having me.

Hugh Macken:
Hopefully we’ll be able to do this again. Yeah, thanks so much. And so just final thoughts would be for those who are interested in learning more about you, Jeff or Provalytics, so your website and the website for Provalytics?

Jeff Greenfield:
Yeah. So best website to go to is Provalytics, that’s P-R-O-V-A, prova, which is proof in Italian, lytics. So P-R-O-V-A-L-Y-T-I-C-S.com. And you can go there, fill out some information and get in contact with us. And if you want to chat with me, just go to jeffgreenfield.com is my personal website, jeffgreenfield.com.

Danielle Milliken:
Awesome.

Hugh Macken:
All right. Awesome. Great. All right, well thank you. Thank you so much again, Jeff.

Danielle Milliken:
Thanks Jeff.

Hugh Macken:
And have a great every week. Thanks everyone for joining us. Thank you.

Jeff Greenfield:
Thank you so much. Have a great day.

Danielle Milliken:
Bye.

Hugh Macken:
You too.

Jeff Greenfield:
Bye.

In this episode of the Marketing X Analytics podcast, we sit down with Jeff Greenfield, CEO of Provalytics and a leading decision maker in the marketing industry to discuss the role of data and analytics in driving successful marketing strategies. Greenfield highlights the importance of utilizing data to inform and guide marketing decisions, rather than relying solely on intuition and past experiences. They also delve into the challenges of implementing a data-driven approach, such as overcoming organizational resistance and ensuring data quality. Throughout the conversation, Greenfield emphasizes the need for decision makers to stay informed and up-to-date on the latest developments in marketing analytics, as technology continues to rapidly evolve.

Alexander Sofronas:
Hello, and welcome to the Marketing x Analytics podcast. I’m your host, Alex Sofronas. And today, I’m on with Jeff Greenfield. Jeff, would you like to introduce yourself?

Jeff Greenfield:
Yeah. Hey everyone. And Alex, thank you so much for having me here today. I’m Jeff Greenfield, CEO of Provalytics, formerly of C3 Metrics and formerly of a lot of other things that we may go into today, Alex.

Alexander Sofronas:
Very cool. So yeah. Talking about your career, how did you get started in the business world and what was your journey?

Jeff Greenfield:
Yeah. I did not have a linear path to get to where I am today and to move into the analytics space. It’s definitely been an interesting one. I went to college and I studied biochemistry. I was a biochemistry major, and really enjoyed the sciences and made the decision early on that I wanted to become a chiropractor. And so I went to chiropractic college in Los Angeles. This is back in the mid ’80s. And when I was there, I was able to as well dig into one of my kind of childhood dreams, as a kid, I got involved with magic and really loved it and did some performing in college. And when I moved to LA, things really took off and I was able to perform and work at The Magic Castle.

And I was not only going to school full-time, but also working full-time as a magician as well. And it was great because the type of magic I did was close up magic. It used my hands. And that, in my mind, jibed really well with chiropractic, which was about using your hands. And it was a great time. And I finished up school there and moved back east to the Massachusetts area, opened up a practice, had a home office, so I lived and worked in the same place and it was great. And then in the mid ’90s, I was involved in a car accident that damaged a nerve in my arm that made it so that I couldn’t take care of patients anymore.
And didn’t really know what I wanted to do. I was confused. You go to school for a long time and you’re good at something and you really love doing it because you’re helping people. And then all of a sudden, you can’t do it anymore. So I was a little bit lost, to be honest. And I decided that I needed to find myself, and magic was something that I had done before. So I took off about two years and traveled the country, doing magic at primarily colleges and a lot of businesses. If anyone listening was ever… When you went to college, if there were ever any activities that you went to that came from your student fee, those would go to pay someone like me to come on your campus. And it was through an organization called NACA that I was able to get exposed to all of the larger campuses around the country.

And I had a blast doing that. This was around the late ’90s. And when I started that, I realized that the internet had just really taken off, especially in college students. College students were really utilizing the internet in ’95, ’96. And so I was like, I need to get my own website. Now back then, very few people had websites. So I had no idea how to do this. So the local newspaper was advertising that they were making websites and I went to go meet with them and they took down all the information. They said, “Come back in two weeks, we’ve something to show you.” I went back in two weeks and they had gotten me web hosting and they had made some designs, but that was it. They said to come back next week.

And I did this throughout the whole summer. And at the end of the summer, they told me that they couldn’t figure it out, that they didn’t know how to do it. And I’m like, “Listen, you don’t understand. When you got me web hosting and you bought that domain for me…” And my first domain was magic-magic.com. “… I went and I bought ads in all of the college papers for these conferences that are starting next month. What am I supposed to do?” And they said, “Listen, there’s this program called Microsoft FrontPage. It’s like $699 at Staples. And it’s supposed to be able for you to do that. And if you can figure that out, if you could come back and let us know how to do it, because we can’t figure it out.”

So I got in my car and I drove to Staples, which was an hour away in Saugus Massachusetts. I was living in New Hampshire at the time. And I did something that I still to this day I’ve never done, which is, I did every single tutorial that was available. And back then, it came on a CD-ROM and it was a big thick book. And by the end of that weekend of digging in on this, I actually had a website. And what happened when I went on the road doing magic is that, since I was the one who made it, I would update it every week, and sometimes a couple times a week. And other performers started to notice and they said, “Hey, can you help me? Can you do something like this for me?” And my line to them was always the same thing. “Listen, I can help you do this, but this is not what I do. I’m on this journey to figure out what I’m going to end up doing next.”

And of course, at the end of the story is, after about a year or so of doing consulting, I was able to get off the road and spend all my time at home and not perform anymore. But then spending time just doing work on the internet, whether it was building websites or SEO type work and stuff like that. So I started along the journey there, and then it’s like I got more clients. People really wanted… The focus then became, I’ve got to be at the top of the search engines. And back then, it was go.com and altavista.com were the big ones. And there really wasn’t much that you could do besides build a bunch of, what they called, doorway pages.

So I created one of the first SaaS, a search engine optimization companies out there called Position Solutions. And we built it out right at the time when the real estate really started moving to the internet in the early 2000s. And it just took off. And it was cool because it utilized this black hat, if you will, technology called search engine cloaking. And it was really neat because folks could just list their keyword and the platform would go out and buy domains. And so for a lot of our clients, they would be like the top 20 results, the first two pages on any search engine, but they would be all from different domains.
Yes, it is a little black hat-ish, but it worked great, of course until the search engines figured it out. But by that point, I was on to something else. So I had this company. And then I was figuring out, “Hey, I think I want to get back into the entertainment business.” I missed the fun of not necessarily being on stage, but just being part of it. It’s a cool business to be part of. And I found out that there was an emerging practice called product placement and branded entertainment that was really, really cool. The idea about being able to put products in TV and film.

And so I went out to LA and started talking to some of the companies that were doing it and found that they were really good at getting it into a specific film or TV show, but they really didn’t know how to talk the language of advertising or be able to talk to agencies or brands or put together reports. So I built out a company called First Approach that focused on helping folks get into TV and film. And then that led me down the path of where clients would be in a TV show and they would be like, “Gosh, it would be really great if I could get them to hold this much longer or if they could say this.”

And I would always say to clients, “Well, if you want to do that, you got to buy the whole show or create your own entertainment,” which is what branded entertainment is. And so I then ended up with a couple of clients, having them produce an entire series of entertainment for them. One of them was a large faux reality TV show for an aesthetics company. And that was really exciting. And some of these gigs… And instead of this being, it was a company, but each one was a massive project. Some of them taking a year to a year and a half. And what I found is, after the fact, everyone was elated, everyone was excited, but it was very difficult to measure the effectiveness of this stuff, especially from a digital perspective, as more and more digital was coming out. There weren’t any hard metrics you could look at.

And I realized that that business was not going to be able to grow unless there was a way to accurately measure what was actually going on. And then that led me to the direction of analytics. I had a client, a publicly traded weight loss company, and the CEO wanted to scale his business. But every time they tried, they would level out and their CAC numbers, their cost to acquire a new customer would continue to rise. And so I came in and said, “Okay, I think there’s a way to figure this out.” What ended up happening is that they had a lots of display partners, all on a CPA basis, and they had all given them their pixels to fire on the conversion page.

And so it was a spray and pray technique where AOL and some of these networks, you could see the impression numbers just go up one day a week to a ridiculous number. They would put out a ton of cookies. And then they would all claim that they would win the conversion. And I used to say that the problem that they had is that every customer that came in would have five or six different fathers of mothers. They would all claim credit for. And that became the big problem. So I created a platform that enabled us to track impressions in real time, but then also, at the time of conversion, would selectively decide who should get credit, who was actually in the last position, who was in the first position, and who was in the middle.

And those folks, we would fire pixels for them to let them know, “Hey, they did a good job.” And that enabled this weight loss company to scale dramatically. And then that became the genesis of C3 Metrics. And C3 Metrics was one of the first multi touch attribution companies out there. At the time, the only company that was around was a company called ClearSaleing, which most people don’t even know about these days. ClearSaleing, the CEO was, his name was Adam, I think, Goldberg. Adam was a former SEM person at Google. And what he saw is that, he saw that clients that were buying non-branded keywords would all of a sudden do really well, but there was a long tail. But the problem was is that Google Analytics would say that those keywords weren’t working that well because they’re more upper funnel. And GA was just last click back then.

So he built out a company that utilized DoubleClick data. You had to use DoubleClick to use it. And it was only for search. It didn’t work across any other channels. And luckily for me, the first client that I had for C3 Metrics, this weight loss client, was in every single channel. So I was forced to build this out to be able to accommodate all of those. And then as a result, I was able to build the company up and scale it to where we had clients, everyone from JP Morgan to U.S. Bank, a lot of financial services and a lot of former clients. And I exited C3 in late 2019, right before the pandemic.

I’d been there for almost 12 years, and hadn’t done anything else, and sat back and said, “What do I want to do?” And I saw that there was… I really got fascinated by the small business world. Especially as the pandemic came on, it was the small businesses that were really hurt, the restaurants, the auto dealerships. And when you think of every local area, the auto dealerships, they’ve got the biggest piece of real estate. And those are the folks who used to advertise a lot in TV and radio and in print. And when they shifted to digital, that’s why we now see that all of our local apprentice started to downfall.

So I built out a lead generation product for the auto industry. And then I started having conversations with a colleague of mine that was the CEO of a company called WideOrbit. And they were all of local television, well over 6,000 stations. They’ve got about 90% market share. And that’s the sell side. Those are the publishers, if you will, but they didn’t have any buy side products. And so I agreed to come on board for about a year, to a year and a half and build them out a buy side product and a buy side division, which I did. And I left there last year. And then I said, “Okay, what am I going to do now?” And it was that same sort of thing about when I got injured and I couldn’t take care of patients anymore.

So I started having conversations with friends of mine that were in the industry, especially in the measurement space. And what I started to hear is that there was a lot of confusion, a lot of issues that are going on, and this was right around the time when GA4 was coming about and the bell was ringing that people needed to switch over. And that caused all sorts of interesting issues. And so I saw an opportunity there as this cookie apocalypses is near and very close, less than a year away at this point, as far as we know. And what that means is, it is going to be a whole new world of measurements.

So I built out a new company Provalytics to be able to handle where measurement’s at today and where it’s going in the future. So truly a future-proofed measurement solution, the next generation of attribution. So that’s where I’m at right now. It’s a long non-linear path, but you take it as it comes type of thing.

Alexander Sofronas:
Yeah. And it’s really interesting that you found the thread through all of your experiences. And one thing I noticed, which, it makes sense that you would be a CEO, is that you seem to be really good at decision making and seeing the options, seeing the opportunities and then making a big bet and then sticking to it. Would you say that decision making is one of your key skills in the role that you have?

Jeff Greenfield:
Absolutely. I think that’s one of the biggest… When you’re building a company, you’re moving sometimes at light speed. So you have to make decisions. But one of the most important things is you also have to realize that you’re going to make mistakes along the way. And as you have a team, you have to be the first to raise your hand and say, “I screwed up.” In fact, I would always say to my team, “Listen, we’re making hundreds of decisions a day and we’re all going to screw up.” And the only thing that I ask for anyone that works with me is that as soon as they screw up, don’t hide it. Just raise your hand because you can fix anything.

And then the other thing that I’m really good at as well is risk taking. My wife always says that I don’t have much fear when it comes to risk. And you definitely picked up on that. I’m definitely an all or nothing type person.

Alexander Sofronas:
Would you say that, that is the attitude that somebody needs to succeed as an entrepreneur?

Jeff Greenfield:
Yes. Yes. You have to be all in. Building a business is like having a successful relationship. You can’t be having a conversation with your partner or spouse and be thinking about something else and you expect that the relationship’s going to move on. And the same is true when you’re building a business. When you’re working and when you’re on, you have to be a 100% there. The hardest thing for me, and this is something that I’ve struggled with throughout the years and I’m starting to get better at it, is being able to turn off. And that’s always been tough, because I’ve always worked.

I work on vacation. I’m always thinking about business. And as you get older, you start to realize, “Hey, you really have to be able to turn off and disconnect.” And even just taking 20 minutes a day to yourself, to power down, if you will, and not think about anything is incredibly important. Because when you’re an entrepreneur, you’re always thinking, “I got to be doing something. I got to be working. I got to be doing something.” But I just read this story about this young guy who just won the Nobel peace prize in math. And no one thought he was good at math throughout college. He didn’t succeed in any of his classes. He didn’t even show up. But he ended up excelling at it. He was great at it.

But one of the takeaways that I read about him is that he only works three hours a day, because he is all in during those three hours and fully committed. And then afterwards, he’s exhausted. What I see with a lot of entrepreneurs, and I was guilty of this in the early days, is that you try to do everything. And what ends up happening is you try to do everything sometimes at once. And this concept of multitasking as you’re scaling a business will catch up with you very, very quickly, because you can do one thing really well, you can do two things kind of okay, but it doesn’t scale. And then eventually, what happens is you’re wearing too many hats and then everything is done kind of half ass. And then that’s when things start to fall apart.

Alexander Sofronas:
So how would you recommend an entrepreneur go about signing with an accelerator versus doing it on their own? What factors would play into the decision?

Jeff Greenfield:
I think it really depends upon what the accelerator brings to the table in terms of resources and relationships. Because as you’re scaling a startup, those relationships become really important because you don’t know what you’re going to need three months from now. And the accelerators bring with them a whole network of people that if you put the time into it, you may not have to tap one of those resources until two or three years in. But then when you do, they’re there for you.

So I think the deciding factor depends upon how large is your network, how strong are they as well? And then also what’s been your experience thus far. And so if I was young and I didn’t have any previous experience and I didn’t have much of a network, I would really look towards an accelerator because you can get all of those from that accelerator. But if you’ve been around the block for a while and you’ve got a network that you can tap that’s got everything you’ll need from the beginning till you scale, then you can go at it on your own.

One of the advantages once you’ve done something like this, you’re always going to make mistakes, but luckily… Well, not always, most of the time, you don’t make the same mistake again. And the key is that once you’ve done this a couple times, you can accelerate the process so much faster because you’ve been here, you’ve done it, and you know what to look for. For example, when it came to choosing things like payroll companies, at C3 Metrics, I used a company that I had used years ago when I was a chiropractor called Paychex. And the reason I used them is because, in payroll, there’s always screw ups. And the one thing you never want to screw up with is the payment of taxes and unemployment insurance.

And I had an experience with them where they messed something up and there were some penalties and they paid everything and they took care of everything. So I had a trusting relationship there. But what I did find is that, that was great for being a chiropractor where I scaled relatively small and over time, where you’re adding on one new person a month or every other month. But in a startup like C3, where some weeks, I would be adding three or four new people, Paychex was very slow. And what was happening is that it would be time for someone to get paid, Paychex couldn’t do the deposit in time, the direct deposit, and I would have to write a check. And some of these people were expecting direct deposit.

I remember several occasions, I would go to the ATM and take out cash from my account so they had money to pay for gas and rent. And I was like, “Okay, this is not going to fly in a modern day.” So I started looking around and researching them. And then I found this company called Gusto, gusto.com, which is phenomenal. It’s so easy to get set up. It’s so fast. They take care of everything. And so then after C3, I knew I didn’t have to research it. So I don’t need to put in the time to research a payroll company. I know exactly where to go in order to take care of that.

And so that’s the advantage. Whereas if you’ve never done this before, you have no idea, whereas an accelerator can provide you guidance in terms of what to do and provide a playbook of what’s worked in the past.

Alexander Sofronas:
So you’ve started B2B companies. And do you have any entrepreneurship advice specifically for starting a business to business company?

Jeff Greenfield:
Yeah. I think one of the most important things is that, typically when you start a company, you’re a solo entrepreneur, you’re by yourself. And I’ll go back to what I said earlier that it’s those relationships that are going to mean the most to you, especially in B2B, because you’re not trying to get a million or 10 million customers, you’re looking to get your first five and then 10 and then a 100. And depending upon what you’re selling a 100 maybe a huge company for you at that point.

And what happens is that as you start to build this up and you’re doing this all by yourself, you need a place to keep track of everything that you’re doing and especially the conversations that you’re having. And so you have to have a CRM. And a lot of times, I would recommend that if you’re thinking of starting a company and you haven’t gotten there yet, and you’re just in the early organization stage, you should have a CRM. In fact, I think any entrepreneur should always have a CRM and always keep it up to date. And I’ve used all of them.

Back in the day, I used SugarCRM because it was open source. It was awesome program. Salesforce, Zoho. And now there’s all these new ones like monday.com and lots of them. But my favorite that I use is close.com. Their product is phenomenal. They’ve got a great app, and it also works incredibly well in the browser. It includes SMS and phone calls. But what I like is how seamlessly it ties into your email, which is the center of everything. It also has built into a drip email campaigns and all sorts of stats and everything you would need from a CRM. And it’s perfect as you start to scale.

Once you get past like 20 employees, depending upon what your needs are, you can stick with it or you have to move on to something else. But I really like that one, because you have to have a place where you can keep track of your relationships, where it’s easy to take notes and it’s all there, part of that customer record. And the nice thing is that it lists everything in chronological orders. So you can go to any relationship that you have and see all of the email interactions that you’ve had, any meetings that you’ve had, everything will be in there. And it’s great. So I think the number one thing is you’ve got to have a CRM.

Alexander Sofronas:
What is the relationship you have as a CEO with the customers of your business for a small business, and how does that change as the business grows?

Jeff Greenfield:
Yeah. In the beginning, you’re the face of your business. You could even say that your first customers come in because of that relationship, especially in B2B, because of your ability to sell the sizzle, if you will. Because in the beginning, you’re not going to have a fully flushed out product. It never happens. There’s no way to build out a strong B2B product until you have at least the first 10 or 20 customers. And that feedback that you get from those customers… In fact, you don’t even want to call them customers, those first couple of folks are actually partners because they believe in you and they believe that you’re able to deliver, and they’re betting on the fact that the relationship that they have with you, you will make a 1000% certain that you’re going to deliver what you said you’re going to deliver. And that you’ll also be able to find out what things they like about it, what things they don’t like and what’s missing from it.

And that’s probably the most important thing is, what’s missing from the product. And what that enables you to do with those first couple of customers in the beginning is it really helps you to submit your vision of what the product is going to be. Because in the beginning, you may be building it all yourself. And you have ideas, but even your best ideas, all of a sudden when someone else comes in, who hasn’t been part of the ideation process, and they look at it, their needs could be completely different. And that’s part of where you start to figure out, “Okay, do I want to build a product or a consulting company?” Because what happens when you start to build a new business is you start to find people that say, “Hey, I could use 1/10th of that, but I need a bunch of other things over here.

And in the early days, for some folks, because of the need for cash, which is always a huge necessity, you may bob and weave a little bit between that product and the consulting. And a lot of folks feel like that there’s problems with that. I don’t have any problems with it at all. Whatever it takes for you to survive and keep the business going, that’s the only thing that matters in the early days, because those early days are the hardest. If you can get over those and start to develop a vision of what the company is, what the product is, then your role starts to shift to where you start to recruit people into your company that can help you fulfill that vision, because you can’t do everything. The manager at McDonald’s cannot serve everyone, make the hamburgers and the french fries and the shakes at the same time, maybe one person at a time, but not at scale.

And to build a business, you have to scale it. And that’s where your role starts to shift. And that’s tough for a lot of solo entrepreneurs, especially if you’ve had a successful business, and then all of a sudden on your own. And now it’s growing, which is what you want. And now you need help because all of a sudden, what happens is, you’ve got to trust people. And I was really bad at it in the early days, especially at C3. In the early days of C3 when there was only four employees, I wouldn’t allow anyone to write an email, send an email until I read it first.

So I would walk around and someone would lift their hand up to let me know they had an email, because every email that went out, even though it came from someone else, prior to that, all those emails were coming from me, and they were now emailing people that I had shepherded through, people who were my early partners in this. And so I wanted to make sure that the tone and the voice were there. But what ends up happening is you get to the point where you realize that, well, their tone and voice, it will actually work better with some people than your own. And that’s when you start to realize, “Wow, I need to let go of these things.”

And so I was able to let go. And that’s part of what happens with scaling is, you just have to trust and you have to understand that people are going to mess up. And as long as you have people on board that are not afraid to tell you, “Hey, I need some help here, I need to fix this, can you help me?,” then you’ll be able to scale. But your job definitely shifts to where you’re not going to be involved with customers day to day, you’re going to be involved with recruiting, you’re going to be more involved with product.

And there’ll be times where you get pulled over into one section of the business or another where problems… And it’s not necessarily problems, but where growing pains start to come in. And then all of a sudden, you have to take your CEO hat off and put on your customer hat again, or put on your product hat or your recruiting hat, whatever it is, wherever their problems are, and then start to figure out how can you make sure that problems don’t come up again. And really your job as CEO is to find a way every day, start thinking about how you can replace yourself, all the jobs that you’re doing. Because that’s the key, is to eventually get to the point where you bring in managers, where no one has to come to you for any issues, where you’ve got folks that know exactly what they’re doing, they understand the whole process and there’s no need for them to come to you unless it’s a really crazy problem.

And then that allows you to step back and spend the time on developing the bigger vision for the company and the ability to scale.

Alexander Sofronas:
That makes a lot of sense. That’s very interesting. I want to ask about the value to a business for an MMM model. So moving into the actual business functions or at least the functions of models in a business, in maybe a marketing organization, what is the value of an MMM model?

Jeff Greenfield:
Well, I think the value of any measurement in an organization is to tie the business KPIs to some sort of action. And in the case of marketing mix modeling, it’s the ability to tie marketing events and marketing expenditures to specific KPIs and to eventually to revenue. So that’s the big value there. And for years, companies used MMN models, and then we had the birth of attribution that came in and got everyone really excited because it addressed some of the, I don’t want to say deficiencies, but some of the limitations that there are in an MMN model.

Because when you think about MMM, it’s really top down, it’s big picture and it’s all about, “Hey, give me all of the data, everything you have for all of last year and I’m going to go and evaluate it, and we’re going to determine incrementality, and we’re going to look at your total media portfolio.” And there’s some great things about that because there’s no privacy concerns, which we’re living in an era now with all sorts of privacy, because MMM typically looks at aggregated data sets. But the problem is that it’s a backwards evaluation. You’re taking last year’s data. You’re only able in a MMM model to look at just sales, just a sales response, and you’re setting budgets and you’re saying, “Okay, last year, you spent X in digital, spend a little bit more, 10% more in TV.”

And that’s how it’s adjusted. It’s primarily used for setting budgets based upon past performance. But in most companies, you should do an MMM model every quarter to evaluate what’s happened. But most companies that I’ve dealt with, a lot of them were relying on an MMM model that was five years old, because it’s so much work to put one together, it takes so long to get the results back, and it’s a huge project. Multi touch attribution came in and said, “Hey, we’re going to do things from the bottom up. We’re going to start at the user level and aggregate up, because in a digital world, every single touchpoint can be accounted for. And instead of just doing this once a year or once a quarter, we’re going to hook up our pipes, put up some tags and we’re going to do this where it’s always on in real time. And instead of just looking at sales, we’re going to look at all your conversions, even some of your leading indicators.”

In the former world, a leading indicator is a visit to something they call a high value page, a page that a paid media doesn’t lead to, but someone only gets there if they’re researching a certain drug or a condition. And they use that. So that’s a leading indicator that you could correlate to revenue and scripts at some point. But with MTA, you could do that. You could do as many different conversions or KPIs as you want. But the problem that we ran into with MTA is that it was mainly digital, which is great because more money is going into digital than ever before, but even the direct to consumer companies, the new ones that are digital first, they’re starting to realize that there’s a point at which they can’t scale any further until they start to look at things like direct mail, maybe some radio or what we’re now calling audio, and then TV, and now we’re calling OTT or CTV.
And that’s where MTA started to struggle is, how do you bring these other channels in there? And so MMM has those advantages in this privacy world, but really the future is the merging, if you will, of the two of those. But for any organization, especially that’s spending a lot of money in marketing, you’ve got to have a way to measure because you’re working across all of these different channels. And let’s say you had $10 million in sales this month, and I’m working across, let’s say, Google, Facebook, Criteo, and maybe I’m doing some CTV as well, and then maybe also I’m doing stuff on The Trade Desk. So I have five different channels and I did $10 million in sales.

If I go to all of those platforms and aggregate all the data, it’ll probably say I did $50 million in sales. So there’s no deduplication across platforms. MMM and MTA, their job is to deduplicate so that you actually have a true CPA at a channel, but also a very granular level. And this is what MTA did is that, instead of just saying digital, MTA could get down to in the search world, campaign ad group, keyword match type ad level and tell you increase spend or decrease spend at that lower level. So it provided guidance to those channel managers in order to know where to move money around in order to hit their goals.

Alexander Sofronas:
Yeah. Those are some very interesting technologies, and they’ve definitely changed the way that marketing functions. I’m curious, when a company is deciding whether or not to use outside help when building complex data science models like MTA or MMM, how would a company weigh the factors for, do we hire data scientists or do we hire an agency?

Jeff Greenfield:
That’s a great question. And I think a lot of companies have struggled with that, especially as they scale. When I first started C3 Metrics back in 2008, when we would go into a company and we would ask to speak to their analytics team, it was usually the IT guy that they brought in. Because back then, there was one person who took care of all of the computers at the office and was also in charge of the web properties and anything to do with ads and things like that.

Over time, we’ve seen that shift where, especially larger companies are realizing that their own data is so valuable. And in order to truly understand it, they have to build out teams of internal resources, because the data requirements don’t just stop with marketing, they now extend into things like HR. Like the data requirements for HR these days is ridiculous, especially when you try to figure out all of these new questions because of the pandemic and work from home, there’s so much data there that a company can learn from in order to help better manage their team and improve their overall happiness score. And so smaller companies will tend to use an outside company.

Now what smaller companies tend to like, and we’ve seen this trend over the years, is they like productized thing. They like products because products are less intimidating than dealing with a consultancy or an agency where it’s all personalized. So for smaller companies, I would always recommend start searching around, do a little Google searching and start looking around for products that are already out there that can help you. Product Hunt is a great source for that. I’m always on Product Hunt, looking for new tools and stuff like that. But as you scale and you get bigger, one of the things that happens with data science models like MTA or even MMM is that, if you hire an agency or consultancy and you get back the results or you have a product company and you’ve got the results, who’s going to interpret them? Because getting results without turning them into action is a complete waste of investment.

And so what you have to have is you have to have someone that is essentially in charge of and spearheading those data efforts, who can then translate them into results for each of the people that are supposed to make changes. And then also be there to explain it to them. Now you could say that consultants can do that. Yes they can. They can explain things. But making certain that people actually do the changes and holding those people accountable, they can’t do that and they don’t do that. And so that’s why we’ve seen, over the last 15 years, as companies start to scale. And now you start to see, all you got to do is search on LinkedIn for jobs, where you’re looking for analytics directors, and you’re seeing all these listings, join our analytics team. Back in 2010, there were no analytics teams.

I remember one client of ours that we had, Carbonite. There was nobody. In fact, C3 Metrics came in and the marketing team is the one that dealt with the analytics product. And they didn’t know it because there was no analytics team. And then I remember there was one gentleman there, Matt, and there was a change in the marketing department and they didn’t know what to do with C3 with the data. And he said, “I’ll take it on. And so then he became our point of contact and I saw him incredibly take his team of one and build it to a team of 18 over the course of three years. And he did an incredible job of building out consensus in that organization, to where they understood the true value of data.

In fact, he reported directly to the CFO, and the CFO wouldn’t put out any reports or any information to the CEO until he talked to the analytics team. And that’s really where analytics belongs, is part of that CFO organization versus the marketing organization. Because at the CFO level, that’s where budgets get set, that’s where decisions are made, and that’s really where you want to be in an organization because that’s where you can affect the most change.

Alexander Sofronas:
So we talked about some of the technologies that a business will use, how they’ll build it. What do you think the future of marketing attribution looks like?

Jeff Greenfield:
Yeah, it doesn’t look like the past, without a doubt. I mean, when I first started C3 Metrics in 2008, we were actually able to grab the entire digital path. We had tags that were up on Facebook. Facebook took our tags. Amazon, amazon.com took our tags. We had everything. And so we were actually able to really map that entire path. So everything was deterministic. It was a lot of data, but truly incredible. And then all of a sudden… I’ll never forget it because there were a couple of us that were involved with Facebook in the early days. It was us at C3, Convertro, and Adometry. And there was a day when it was announced that Google was buying Adometry, and then three hours later, it was announced that AOL had acquired Convertro.
And then the next week, Facebook said, “We’re going to take down all the multi touch attribution tags,” because they originally saw it as wow, MTA is independent and they’re like this independent voice. And then when two of the larger, independent voices were purchased and acquired by two of their bigger competitors, they said, “Yeah, we’re not playing in this anymore.” So then all of a sudden, Facebook went from being a 100% deterministic to now being probabilistic. And that was okay for a couple of years because we had so much data on Facebook. We knew how it reacted with other channels, and we could add in those probabilistic, if you will, markers and our model.

But then all of a sudden, new wall garden started to come up. I think the biggest first one was YouTube, and Google moved away from having tags. We had tags that were on YouTube. Anytime someone would do a buy, so if you were seeing an ad, our tags would be there for that. And then what Google found is that so much of the traffic had shifted from a desktop environment to a mobile environment, that they wanted to do away with tags because they had so many tags that were there. And what they found is that even the fastest tags, the more there were, they were slowing things down and that was impacting user experience.
And so what they did at that point is they built out something called Ads Data Hub, which was an aggregated view, if you will, of data. So that instead of being able to get user level data, we would only be able to get aggregated data. And it was limited by geo so that you could never identify a specific user. And they followed the HIPAA guidelines so that if they ever moved into healthcare, this Ads Data Hub would be compliant with it. And so we were the first and the only multi touch attribution company utilizing Ads Data Hub. But then what happened is, very rapidly, other platforms started to come up, the TikToks of the world, and who else knows what else is going to come out there?

And then there started to become where we’ve got more holes than we have deterministic data. So now, things are very probabilistic in the MTA world. And it used to be, with things like CTV, it was great because you could get a file from the CTV provider, the publisher, of every household IP address that was exposed to an ad, and then the way you could tell effectiveness and add it into a user path is, we would then add that file into C3, and it would look up IP addresses and it would add that exposure right into the user path, which was incredible. But now what’s happened is, yes, those devices are in the household IP. So that dataset hasn’t changed. What has changed is the ability to collect proper IP addresses, because with iOS now, a lot of people are utilizing that Relay.

So if you log into your stats now, you’ll start to see more and more people from the middle of America and different IP addresses that don’t relate to that user being utilized, so the ability to match back CTV and OTT to visitors on a website, it doesn’t work the way it used to. And then, now what’s going to happen is, sometime next year, it was supposed to happen this year, but they pushed it off a year, is the upcoming cookie apocalypse. Now, this may not happen. There may be some governmental intervention that stops it from happening, but the trains left the station and it’s going to happen eventually, where there will be no more third party cookies.

So the ability to stitch together that user path is going to be gone. Now, everyone talks about, well, what about cookie list tracking methods? Yeah, there are cookie list tracking methods, but the walled gardens are going to see this as an end run. And remember, one of the major walled gardens is Google, and they control one of the major browsers. So any circumvention around in order to track users is going to be quickly squashed by the browsers. And I wouldn’t be surprised if in the next couple of years, because when you read all of the privacy regulations, IP addresses are considered to be PII data. And so one of the things that I think we’re going to start to see is, I think we’re going to start to see hiding of IP addresses by the browsers.
And this is shocking to me, as someone who built out a technology in 2008. Because I always saw the browsers as partners working with us together. I never saw them as having their own agenda. But they certainly do have their own agenda. And it’s at odds with multi touch attribution as it exists today. So I think because of all those holes, and because now that user path is going to be more probabilistic than deterministic, the future of marketing attribution is more of an aggregated view. And it’s more of a view where we’re looking at the merging, if you will, or the Venn diagram. If you were to take MTA and MMM and merge them together, the Venn diagram of it would look like a continuous, always on platform that utilizes not only attribution, so very granular, but also incrementality.

This is one of the things attribution didn’t have is, there was no incrementality and attribution like there is in MMM. But where you’re able to look at multiple conversions, multiple KPIs, you’re not just limited to digital, you can look at the total media portfolio, even things like print, and not have any privacy concerns at all. That’s really the future of marketing attribution. And that’s actually what I just described is what we’ve built over at Provalytics is this kind of merging of both worlds. Because what we end up with, with that, is we end up with the ability to accurately measure the effectiveness and the efficacy of all current channels and any future channel.

Because when you think about it, if something new came out, the TikToks of tomorrow come out and you’re going to buy something there, you’re going to be able to figure out what you bought. There’s a price that you paid for it. There’s a day that you got it on. There’s an impression count or engagement count or something. And that can be layered in to this type of model. So we’re talking about, that can handle all current and future channels, something that looks at not only the direct impact… And this is really, really important. This is one of the things that marketing mix does really well that attribution did not, which is that, when you’re buying ads, there’s that immediate impact. But what about the person who sees the ad and it paints a picture in their mind, but they don’t do anything.

And then they see another one and it paints a bigger picture, and it takes like, on the sixth impression, they finally did something. So that’s this indirect impact of marketing. And that’s something that’s called ad stock. There’s a long explanation on Wikipedia about ad stock, but it really is about this kind of long term lagged impact. And we know that it also happens… And ad stock came about because of TV and print. But we know also that that impact is there in digital. And it actually goes back to some of the early studies that Yahoo did. Now, I know everyone today looks at Yahoo like they’re a joke, but Yahoo in the day was the king.

And Yahoo had this great advantage because not only were they this major display network, not only did they have the most visited page, but they also owned and controlled a search engine. And so there was a study that was done with Quaker Oats. Quaker Oats did this homepage takeover of Yahoo. And back in the day, that was the thing. You do a homepage takeover for a day of Yahoo, everyone in the world is going to know about you. So they did a homepage takeover that talked about a healthy breakfast and healthy breakfast cereal. And of course you clicked on it and it took you to the Quaker Oat’s site.

And so what happened that day is Quaker Oak saw a ton of traffic come to their site. And of course, the next day, there wasn’t as much traffic, but it didn’t drop off entirely. It didn’t go back down to the level of that. It took time for that to get back down to the previous level. And what they also saw is that searches for healthy breakfast were dramatically up that day, but they stayed up for about 10 days till they finally got back down to that prior level.

And this coincides with a lot of the brand research that’s out there that says you get a one and a half times return from that branding because it lifts the overall number of people that are aware and it increases the size of your sales funnel, which is what we all want. So that’s really what we’re talking about here is that ad stock, and being able to understand it. When I buy an ad today, what is the impact? I want to know what the impact is today and tomorrow, but if there’s an impact a month later, I really want to know about that. And that’s something that marketing mix does really well. And that’s all part of Provalytics.

Alexander Sofronas:
So expanding on marketing attribution, how can AI change the way marketing attribution functions and the value that it can bring?

Jeff Greenfield:
Well, AI is a game changer because when it comes to attribution, really what you’re interested in is, unlike MMM, we want to know budgets, for what you should spend in a big budget over the next year or the next quarter. Really what I’m interested in is, “Hey, here’s where things are today. What is the absolute… what should I do with my money? How should I move it around?” Or, “I have an extra a $100,000 to spend this month, where’s the best place? Where am I going to get the biggest bang for my buck to spend these dollars?”

AI and the combination of that, obviously, with machine learning allows us instead of running like one simulation or to run hundreds of thousands of simulations, we can do all of these at the same time simultaneously. And actually at Provalytics, we use a technique called SUR, seemingly unrelated regressions, and that allows us to run all of this stuff all at the same time. And AI allows us to do that at a speed at which we’ve never been able to do before. And that’s what allows us today to take aggregated data, non-user level data, and model it and be able to get down to a level where a channel manager then knows how to allocate their spend.

If I’m a Google search person or if I’m a PLA person, I’ll know which PLAs are working and which ones are not, and where to increase spend, and where to decrease spend in order to hit my KPIs and my goals. So that’s the beauty about AI. One of the other biggest and most important things that’s also come as well is, with AI, and the ability to move so much faster, creative is really the name of the game. At the end of the day, everyone thinks you find the winning creative. And I find that so many agencies and so many brands, they stick with the same creative. And it’s a huge mistake.

If you’ve got a creative that’s working on Facebook and it’s got a blue background, there are a million different combinations of blue that look just like that, and you need to start testing them and you need to start doing this all at scale. And there’s some great companies out there that are doing an amazing job with that. The first one that comes to mind is Marpipe. They’ve got the ability where you give them your ad and they go in and create thousands of variations of not only fonts, but colors and pictures. And then they automatically add these to Facebook.

And obviously, because there’s all these unique IDs and things, these can all be tracked as well in any measurement platform that you have, whether it’s Provalytics or anything else. And they can come back and let you know which combination works. And it learns as well. So once it finds that something is working, then it keeps iterating upon that because there is no perfect creative in today’s world because people are so overexposed, you always have to be bobbing and weaving. This marketing game is like a boxing match, and you got to make it through each round. And in order to do that, you got to move around a lot.

Alexander Sofronas:
So earlier in the episode, I asked about the beginning of your career when the internet was still coming to prominence and it was particularly popular among college students. I want to ask about the current technology landscape and what are the opportunities that you see right now for the future that remind you of the opportunities you saw when the internet was just coming to prominence?

Jeff Greenfield:
As technology has become so prevalent… I remember the early days. And going back to what we talked about earlier when I was doing NACA and touring colleges, and I remember I had a PalmPilot, and I would use it to hook up to a phone line, to dial up, to be able to get my email. And then eventually, I had a PalmPilot that had a little wand that you would put up that could get a 1G signal so I could get my email. Back in those days, no one had email. I was one of the first people. And then all of a sudden, everybody had email. And now everybody has email, everybody has a smartphone. Technology is so involved with our lives. And not only that, but everyone is carrying around this, if you will, global knowledge in your pocket.

I mean, it’s really an incredible time that we live in. We have everything, and every book that’s ever been written, every philosopher’s thought, every fact that we want. If I want to know what the temperature is right now in Positano, Italy, I can Google it and have it on my fingertips. And so I think we live in a time where technology has become this pivot point in our life. And I see that in a lot of businesses. When I go in and I look at companies, I’m amazed at the number of tools that they are utilizing to run their business. And when SaaS first came out and SaaS products were first available, it was amazing because you didn’t have to go through this whole installation process. It was incredible.

But now, some of these companies have got 20 or 30 different tools that they’re using. So I think there’s an opportunity for some sort of auditing. And I hate to say it’s just another tool, but I think there’s an opportunity for an auditing technology or consultancy, if you will, that comes in and helps companies decide, are they getting the value from this that they should? And maybe that’s a role that analytics should play, because I really believe that every tool you use in your business, there should be a cost benefit where you look at that.

You see a lot of ad agencies today, and a lot of companies do this, especially services oriented companies, they have all their, every team member, even the CEO will track their time to figure out what client they’re working on. Because a lot of companies have been shocked to find out that clients that they’ve had that were paying them lots of money, sometimes they’re losing millions of dollars a year on it, but they didn’t know that till they started tracking time. And I think the same is true of a lot of the tools. A lot of the tools just become part of the culture, but they’re not actually giving any benefit.

So I think that there’s an opportunity there. I also think when I look at the landscape right now, in terms of measurement, we’re at this amazing point in time, we have all these things happening at once. Privacy is front and center, and whether it’s the cookie apocalypse, the iOS changes or who knows what else is coming, we’ve reached a point in the world where tracking users at an individual level, that’s not where the future is headed. So that’s the first thing that’s happened. And then the second thing along with that, and as a result of that, we have this shift from Google Analytics to GA4. And this is a monumental shift because Google Analytics is the most used marketing analytics platform out there. And whether it’s right or wrong, it’s what most marketing departments use to make their decisions, or at least guide them.

I hope that most folks listening to this know that brand search and affiliates don’t drive their business, even though that’s what GA says, but there’s a lot of folks who don’t know that. But one of the things that folks are dealing with right now is that, you log into GA and there’s that banner across that says, “As of July, there won’t be any more… Won’t be able to put any new data in here.” And so now, there’s this massive transition where we’ve got to transition companies over to GA4. And that’s great, but it’s like, people are now having to look at both systems, because they’re both running at the same time. Because as of next July, your historical data is still going to be there, so you’re going to have to look at GA, not GA4.

And there’s now people are starting to see there’s differences between the two. And let me tell you, if someone has been in this space for a long time, whenever people start to see discrepancies in the numbers, they start to lose faith in them. And so that is creating an opportunity right now in the technology landscape for any players to come in and start to provide a solution that works. One of the things that we know that is not going away, hopefully, is first party data. So if I have a website, it’s the data that I collect on that website, especially for people that are logged in or known customers.

So for eCommerce, where 75% of your business is returning customers, these are people you have on email list, you have their shipping address, you have everything about them. And you know every time they come to the website, because usually they’re logged in. So that first party data becomes very, very valuable. And there’s an opportunity. There’s a huge uptick in companies getting up and running with CDPs so that they can aggregate that data. And most importantly, not only aggregate on it, but also activate on it.

I also see though that, as we’re starting to move from this user level data to aggregated data, one of the big holes that I see is that people are not feeding the data back to the Googles and the Facebooks of the world and the LinkedIns of the world, especially in the B2B space, that they should. Most people have tags up. And so when a lead comes in, that goes into Google and Google rings the cash register and says, “All right, job well done. Good job, Google engine. Let’s keep it going.” And that’s how most companies do it. When they have a lead, that’s it, because then sales takes over.

Well, there’s a whole offline conversion process that you can actually easily enable with your CRM and with Zapier to just make it down and dirty and simple. So you don’t even have to build out the API, it’s already there for you to do. So that when that lead becomes a marketing qualified lead, obviously, someone who’s marketing qualified is probably worth at least 10 times more than just a regular lead, and then when they become sales qualified, they’re worth a lot more than that. And then when you actually close them, they’re worth a lot more. Even if that journey is months long, every time you change the stage in your CRM, you can set it so it automatically sends that information back to Google and back to Facebook. And there is a beta for LinkedIn to say, “Hey, that lead that you sent me before, I said it’s worth a one, it’s now worth a 10 or it’s worth a 100.”
And what will happen over time is that Google will realize, “Hey, there’s a lot of one leads, but they really like these leads that are 100s.” And over time, that’ll feed the Googles and the Facebooks of the world, and it will tell them how to optimize. And you will start to see, automatically, your lead quality will go up. It’s like, overnight, the leads that start to come in from your paid efforts, all of a sudden, your close rate is so much better. And it’s not that your sales team is doing a better job. It’s just that, your number one sales person, the one at the top of the funnel, the Googles and the Facebooks and the LinkedIns of the world, you’re actually giving them feedback so that they can actually find you leads that are more like the ones that you actually close.

So there’s an opportunity there because, as I talk to folks in the B2B space, and hell, even in the B2C space, if you have a subscription business, you should be feedbacking and sending that information on to Google, into Facebook every time someone subscribes, every single month, you should be updating them. Hell, you should be updating them every day or every hour as someone resubscribes, because the more frequent the information, the smarter they’re going to get, and you’ll see your costs start to decrease in terms of marketing.

Alexander Sofronas:
Moving on to leadership lessons, do you have any leadership lessons to share with the audience?

Jeff Greenfield:
I think the most important thing is, you have to develop empathy and understanding for people on your team. And we talked about this earlier that as an entrepreneur, especially as a solo entrepreneur, you’re doing all these jobs, and you want to make certain that people are doing them, and there’s trust issues that we all have, we have to understand that in order for our team to scale and do well, they’ve got to have a life. They’ve got to have a life outside of work. Even though you may not, they’ve got to have a life.

And so, you have to be able to know when to throttle up, but also when to throttle back and trust that they’re going to do a really good job. And the way you do that is to really understand them. And really, some leaders, they don’t really want to care about their people. I don’t want to be friends with my team. Like yeah, maybe you don’t want to be friends with them, but you want to know who they are, what they’re about, and you also want to know what really matters most to them. Because it may be that this person is only going to be part of your team for six months. And then at that point, you guys part ways and they go on and do bigger and better things. But during that six months, they may do incredible work for you.

So one of the things that you want to look at is, when you’re hiring people and you’re recruiting people, don’t look at it like you’re looking for someone to be with you for the next couple of years, because they may not. And even if they tell you they’re going to be, circumstances change in life. Look and see what this person can do for you today. And then it’s your job as a leader that once they’ve accomplished a goal with you, you then want to continue to challenge them so that they can continue to do great things. And that’s your job as a leader, is that as soon as you see someone has done really well in one role and they’re killing it, move them up, give them more responsibility. They can handle more.

This is how you retain people, is that as they continue to evolve with their skills, you need to get further out of the way, step back and do more vision type stuff and hand over the reins of your daily stuff to the folks that are able. And that’s tough for a lot of folks, but that’s the way that you are able to retain people and keep them on.

Alexander Sofronas:
And speaking of that work-life balance, a lot of what I’ve found to work for me is working at a job that is really fulfilling. And I want to ask if you have any advice for how somebody should find their passion in life, in terms of work.

Jeff Greenfield:
Yeah. Some people find it in the actual work that they do or the overall goal or vision of the company. But I think the way you find your passion at work is, you want to make sure that you work for people that you think are passionate, and that you think are caring. Because if you work for someone that is a really good leader, it’s going to impact everything you do. You’re going to feel so much better about it. And we’ve talked about this before, Alex, about how the leader at the top sets the tone for the entire company. And if the tone is off, everyone feels it. And even if it’s work that you’re passionate about, you’re going to hate it. You’re never going to have a good day there. And all of a sudden, you’re going to start looking for other things.

But when the tone is great at the top and the vision is clear, even if some of the busy work you don’t like and you’re not passionate about it, you’re passionate about the team. And I have a personal example of that with my daughter. My daughter, for years… And my daughter works in social media. She’s a social media manager for Paid. And she worked for years in the auto industry where she worked for a large dealer group, and all of her jobs after that were where CEOs were men. And men and women, we have different ways that we do things. That’s just a fact. And she did her job. She loved it. And then she got recruited, several months ago, by this B2B agency in Oakland called LQ Digital. And it’s a female led agency.

And immediately, she noticed a difference with the tone at the company, the vision at the company, the way that her boss talked to her, her interactions with everyone at the company. And I got to tell you, Alex, she’s doing the exact same work that she did when she was working at the auto dealer group and at the other companies, it’s exactly the same work, but she is so passionate about it now and loves all the work that she does, where it’s tough for her, even though she’s not an entrepreneur, it’s tough for her to stop working each day because she not only loves what she does, but she loves the people that she works with, and she loves the vision and just the leadership. And that’s made all of the difference for her.

And I think that’s really what it is. When you have someone that you work for that is an incredible leader that will take a bullet for you, that’s what you want. You want someone who’s going to be leading the charge, and not someone who’s going to be behind, yelling at you, telling you to work harder. You’ll do anything for that person. And that to me is where you find passion. Because, at the end of the day, even though we’re all doing this work, even if we’re remote, we’re interacting with people on Zoom calls or video calls or we get together. And it’s those interactions that fuel that passion. So I think, at the end of the day, it starts at the top.

Alexander Sofronas:
Final question. How can we hire better to make stronger teams?

Jeff Greenfield:
You only get stronger teams when you have diverse teams. You have to have diversity, especially as an entrepreneur. And when you’re starting a business, and even when you have a large business, it’s all about solving problems. And I experienced this firsthand at C3 Metrics, we were bootstrapped, didn’t have a lot of money, couldn’t even afford to run ads on LinkedIn, so I ran ads on Craigslist because they were cheaper, and hired people and paid them by the hour. And I made up ads, I copied ads from the internet that I saw, for different roles.

And we got to about 10 employees, and I looked around and I said, everyone here is white and straight male. And that’s when I realized that we all hire people that are like ourselves. That’s why larger companies, they get a whole recruiting team, that is typically, at any large company, you’ll see that the recruiting team is diverse, because people tend to go towards something that they know. And so, one of my struggles at the time there was like, we need some female input, because if it’s all straight white guys, 10 of us, and we have a problem to solve, they’re all going to get to the same answer that I would get to. I need different perspectives that will stretch my thinking as a leader. And that’s why you need diversity.

So I struggled for several months, trying to get to recruit women into the company. And I didn’t have any luck until… This is a crazy story. My wife and I, because we live here in New Hampshire, and right over the New Hampshire border is Kittery, Maine. And if anyone listening has ever been there, you’ll go to the Kittery outlet malls where there’s all these outlets. And my wife said, she had bought stuff from Lululemon before online, she’s like, “Let’s go to the Lululemon outlet. I’m curious to see what they have there.”

So we go in there, and of course, it’s busy as can be. It’s all women working there, and everyone’s smiling and everyone’s happy. And I’m like, “Okay, Lululemon has figured out how to recruit women.” And it’s not just because they’re selling to women, there’s got to be another reason. So I went online when I got back from Kittery and I looked, and I started searching and looking at Lululemon ads, and I realized that the language that they use, the way they’ve described the jobs and they described what you were going to be doing, was completely different than anything else I’d ever seen.

And that’s when I had the epiphany. I realized that these job descriptions were probably written by women. And all of the job descriptions that I had ever used before, that are on the internet, have been around for years and were all written by men. And so all I did is, I took my job descriptions and I started using some of the same language about how they felt about the job, using the word love a lot, because if you’re going to go work at someplace, you don’t want to be passionate, you got love it as well too.
And immediately, after I started running the new version of the ads, half the applicants were women. It was like overnight. And just by doing that, I was able to get a more diverse culture, where it turned out that we had a lot of women, a lot of people that weren’t straight, we had a diversity of backgrounds and opinions so that when we started sitting down as a group to solve problems, I would start hearing answers that I would’ve never come up with on my own.

And that’s where you get a real problem solving and real growth as an entrepreneur. When you start listening to people and they start coming up with solutions that you would never come up with, that’s an exciting time. And that’s why you have to have diversity and really focus on hiring people that are not like yourself, because you already have yourself. And if you’re an entrepreneur, you’re going to do the job of probably 20 people. So you got 20 of you. You don’t need more of you. You need people that are completely different.

Alexander Sofronas:
I want to thank you, Jeff, for coming on. This has been an excellent discussion. I learned so much.

Jeff Greenfield:
My pleasure, Alex. It’s been a pleasure. Thank you.

Alexander Sofronas:
Awesome. And thanks everyone for listening. We’ll talk to you soon.