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As marketers, we should be using data to paint a clearer picture for us about the people who are already buying from us, as well as get a better understanding of who’s likely to become our next customer. It’s those patterns that will help us get with where we want to go next with our marketing. Phil Case explains how data driven information can really accelerate our understanding of who our customer is and how to best engage and interact with them.
Using First Party Data to Better See Your Customers Episode Summary
Using Data to Understand Customers
- Many brands rely on generic personas without empirical data on actual customers.
- Placing a data pixel (Google, Meta, etc) collects behavioral data; enriching with CDPs adds demographics and psychographics.
- First-party data on current customers is extremely valuable but underutilized. Can enrich with third-party data via CDPs.
- This enriched data helps create audience segments and tailor messaging and experiences.
Optimizing the Customer Journey
- Study customer journeys to understand gaps in research and purchase process.
- Use email and ads to “nudge” customers during gaps back into purchase cycle.
- AI and predictive modeling can help identify patterns and opportunities within customer journeys.
- Google Analytics can provide insight into typical conversion paths.
Key Takeaways
- There is often a disconnect between how brands think about reaching customers versus the reality shown by data.
- Placing a data pixel on your website can provide insights on customer behavior and demographics within 15-30 days.
- First-party data from your own customers is extremely valuable but underutilized.
- Customer data platforms (CDPs) can enrich first-party data with third-party data to paint a clearer picture of customers.
- Use enriched data to create targeted ad campaigns and landing pages tailored to specific audience segments and their needs/values.
- Study customer journeys to understand gaps and opportunities to nudge customers along the path to purchase. AI and predictive modeling can help.
Topics:
Using Data to Understand Customers
- Many brands rely on generic personas without empirical data on actual customers.
- Placing a data pixel (Google, Meta, etc) collects behavioral data; enriching with CDPs adds demographics and psychographics.
- First-party data on current customers is extremely valuable but underutilized. Can enrich with third-party data via CDPs.
- This enriched data helps create audience segments and tailor messaging and experiences.
Optimizing the Customer Journey
- Study customer journeys to understand gaps in research and purchase process.
- Use email and ads to “nudge” customers during gaps back into purchase cycle.
- AI and predictive modeling can help identify patterns and opportunities within customer journeys.
- Google Analytics can provide insight into typical conversion paths.
Using First Party Data to Better See Your Customers Episode Transcript
Rich: My guest today is the president of Max Connect Digital, where he oversees agency growth, client relationships, strategy, and brand. Previously, he was the managing partner of Fluid Advertising, where he grew the agency from 4 to over 35 full time employees in a six-year period.
In 2018, he helped launch the Utah Outdoor Association to support the outdoor industry in, you guessed it, Utah. He has worked in just about every industry,, with hundreds of brands and took an international biotech company public on the NASDAQ back in 2020. Afflicted or blessed with a bit of ADHD, he’s curious about everything, loves to learn about businesses, meet new people, and strike up conversations.
He plays the piano in his spare time, enjoys being with his wife and kids, traveling to new places, and seems to never stop moving. He’s an outdoor adventurer enthusiast, passionate mountain biker, and back country skier. But today we’ll be talking about how to use data driven information to get a better picture of your customers with Phil Case. Phil, welcome to the podcast.
Phil: Thank you for having me, Rich.
Rich: So tell me a little bit. You talk about empirical data, you talk about data driven information. What’s the wrong way, or what’s wrong with the way that we’re creating personas today in marketing?
Phil: You know, it’s interesting as we began an engagement with a brand, we’ll typically say, “Send us your brand assets. What do you know about your customer?” And we’ll get some really nice flower presentation decks. And there’ll be Clarissa and there’ll be, you know, here’s Michael, and they’ll talk about these audience archetypes. And we’ll say, ‘Well, how did you come about this?”
And sometimes there’s customer interviews like, “Based on some of the research that we’ve done.” But most of the time we’ll say, what do you know about those that are actually purchasing your product? And when we begin to drill down, there doesn’t seem to be kind of an underlying foundation of empirical data. Some of the larger brands, yes. But by and large, those small to medium businesses struggle with that, largely because of costs and often they don’t know how to do it.
And when I begin to describe, “Did you know you can place an audience pixel on your website within 15 to 30 days, actually know how they’re behaving, shopping offline, online, understanding what types of cars they drive, what kind of homes they live in, what they value?” Their eyes kind of light up and they say, “You can do that?”
And so I just think that there’s a little bit of a disconnect relative to how we’re thinking about reaching our customer. And, and how brands are going about surmising some of those facts versus reality.
Rich: So when you talk about adding the pixel to a website, are you talking about like a Meta pixel or Google pixel, or is it something else entirely?
Phil: So yeah, kind of yes to all the above. There’s a variety of technologies any brands can use. If they’re leveraging any sort of DSP or trade desk, including Meta, that you can begin to collect some data, even in Google analytics, it will begin to tell you about what interest or affiliations or in market segments are your top converting audiences and what else are they looking for online.
So even Google will begin to categorize this for you. In addition to that, there’s a lot of other services, as I mentioned, that brands can place a data pixel. We like to call it an ‘audience data pixel’ that will begin to capture who these individuals are and what they’re doing before and after a purchase on their site.
Rich: So with these, is this how we get better data? Because you know, in this day and age, you just hear so much about the death of cookies, the death of third-party data. So are these still effective, or are there better methods to be gathering this type of data?
Phil: Thank you. Yeah, no, great question. So when you begin to think about the death of cookies, it is a very slow death, kind of dinosaur style. And Google’s been making threats for years, they haven’t followed through. Well, in 2024 we know that 1% of all Chrome users will begin to be in that kind of cookie list environment, so to speak. Now that’s cookie lists from sharing cookies outside of Google.
But within the Google ecosystem, which is quite broad, as we know, programmatic display and, YouTube and other video pre roll placements at Google, they’re going to continue to share data. But as we continue to have privacy at a heightened awareness for consumers, there’s many other ways to go about it. And I’ll kind of give you a few examples.
So the first party data of any company is probably the most underutilized data in the marketing realm today as we know it. And I know you’re more than familiar with that. But there are so many powerful platforms. For instance, here’s 10,000 individuals that have purchased our product that have come back and purchased again that we would consider some sense of customer loyalty. We can take that data set, we can plug it into a live ramp, we can begin to do data enriching, and we can begin to understand other attributes about these individuals. And this is all in a cookie-less world. And so there’s a tremendous opportunity of leveraging first party data.
We have brands that as we visit with them, they’re actively doing customer panels, customer interviews, post purchase, and being able to better understand not just the quantitative, but the qualitative side of things as well. So your own customer data will always be your best friend. And it’s the best friend that most brands aren’t fully leaning into.
Rich: And if I’m understanding you correctly, there’s the data that we can collect off of our websites, but also we need to go deeper than that. And we need to be talking to current and past customers and clients, and getting some real deeper understanding of who they are, maybe how they found us, and what was the decision-making process. Am I correct in that understanding?
Phil: Yeah, that’s right. I mean, their digital journey will give us some signals about them behaviorally. And as you suggested, from pixels to cookies, as there’s limitations that are beginning to be put in place much more than has been previously. There has also on the opposite side sprung up so many wonderful platforms that we can do so much data enriching and understanding.
I don’t know how familiar with CDPs, customer data platforms, but that is an excellent way to begin to segment, to store, to learn, and enrich. Everything about your current customer data set that will inform you on what your audience personas truly look like. And again, that kind of stand by or that proven and true interviewing a customer, having a one off, bringing him into the office, doing a focus group that continues to be of high value today.
Rich: Bill, I have to admit I’m not very familiar with the term CDP, customer data platform. Can you just give me kind of like the fifth grader entry level explanation of what that’s all about and how I might use it in my business?
Phil: We live in a complicated world today of data. And so you have analytics, which is anonymized data. It’s noncustomer specific. We have Shopify data. We have CRM data such as a Salesforce and HubSpot. A CDP kind of sits in between where it’s integrated, for instance, with a Salesforce. So Salesforce is going to tell you, how has this customer interacted with you as a brand or as an organization?
What the CDP will tell you is what else can we learn about this customer and how they behave, and actually pulling outside data sources with Experian and American Express and Visa to actually do some matching of those personas. And so you go knowing, let’s say 14 things, about that individual. You know their first name, last name, organization, all of the address information, email, even social media profiles.
What if you could take those 14 values around that customer and enrich it to 30? What if you could see other preferential behavior? What if you could data match based on credit history, score, net worth, household income, et cetera.
So that’s what CDPs are intended for, where it’s able to integrate your own customer data. It’s able to sit in the middle as somewhat of an arbiter of this data and protect it, and then bring in and layer other third-party data sources to enrich what you actually know about that individual.
And then, in addition to that, it will allow you to look at patterns. It will allow you through AI and machine learning to see in your CRM you’re understanding the data this way. CDPs have some fantastic technology where you can dive a little bit deeper relative to how often did this individual purchase, and what were the causal factors for that, and what’s predicted in terms of what they’ll do next.
And so you can take a three- or four-person audience segment or personas and potentially stratify that out to nine or ten where useful, just to be a little bit more specific and being able to serve up a unique customer journey.
Rich: So if I’m understanding correctly, the CDPs can you, I think you call the data enrichment and basically paint a better picture, a clearer picture for us about the people who are already buying from us.
But it also sounds like as it starts to fill in some of these gaps, it’ll also help us get a better understanding of who’s likely to become our next customer. If we start to see certain patterns in there, or the machine learning in AI starts to see different patterns in there, it might help us even with where we want to go next with our marketing.
Phil: That’s right. And again, it’s almost like the new age technology of when we’re building audience personas. This is what the best and brightest minds and brands are doing today. Now, there may be some cost restrictions, but you know, there’s several from first time to lytics to segment that are somewhat reachable. There’s going to be some that are more enterprise level that just from a [inaudible] perspective are out of reach for many brands. But many of these from an introductory perspective, it’s similar to a CRM cost. And it can, I think, really accelerate understanding of who your customer is and how to best engage and interact with them.
Rich: Very interesting stuff. So if we have this better picture, how do you recommend we start to use this data to be able to attract and convert more of our ideal customers?
Phil: Yeah, no, excellent question. So there is a brand, I won’t mention their name today. But when we began to work with them, they had just a smorgasbord of products, and they had somebody in mind relative to kind of the development of each product. But the way they expressed that on the website, the way they expressed it in the campaigns, they often were saying, “Here’s how you can use this product”, but they weren’t often speaking to lifestyle. They weren’t connecting emotionally. They were speaking of formant or they were speaking of function.
And so when we’ve seen brands do this well and where eventually we helped this organization go was relative to, you really have four different segments of your audience. There’s this overlanding segment. There’s this RV segment. There’s this prepper segment. And then there’s just an emergency preparedness of sorts and just your normal mom and pop.
And we started to develop ad campaigns and messages that really met the needs of what problem or challenge that they had and what they were trying to solve for. And so as we put ourselves with some of this empirical data in their shoes to say, what is it this consumer is trying to achieve by purchasing this product? We can begin to, rather than merely direct them to a product page to go buy, we can direct them to a page that is relevant to them. Where there might be a video and they see somebody just like them in the outdoors pulling an RV saying, oh, that’s how I recharge my RV. That’s why I can live off the grid for five days. And you have testimonials that are related to that.
You then can say, you know what, here is a product, but here’s five more that you might have interest in as well. And so you stop thinking about marketing of please come and buy a product rather. We have an entire platform that supports you as an audience segment that we want to be relevant for.
And we’re going to emotionally starting with why tell our story that really becomes your story and help you understand the value of the product we offer. And so I think as we shift marketing, I mean, so often we’re running campaigns where it’s, here’s a product we’re trying to move and here’s three ads. And the variances between those have very little to do with audience and mostly have to do with just a potential offer, how we’re trying to frame the conversation. But I think as we can enrich our ad campaigns, both visually as well as our audience placement and who we’re speaking to and who we’re targeting, coupled with a really powerful message as they reach those landing pages that just fit their lifestyle, I think we’ll put people at ease. I think we’ll streamline that customer journey. And I think there’ll be less friction from a path of purchase.
Rich: Interesting. I’m sure there are a lot of people out there who say, “Look, that sounds cool. It also sounds enterprise level. I don’t have the money, or I don’t have the client data. If I know that a certain percentage of my people came through SEO, why do I need to know more?” What’s your counter argument to that belief?
Phil: Yeah. I do think that there’s probably an enterprise way of doing it, but there’s also probably an SMB way of doing it. I don’t think it needs to be that complicated. You still want to have a good funnel when people get to your site, your homepage is always going to be your most visited page, for instance. And so just making sure that showing here’s our mission, vision, values, and what’s important to us and why we created this product and how it can resonate with you. And then just a simple path to purchase.
That’s always going to be kind of that basic, they’re coming in from SEO. They’re coming in buying. But as you begin to look at growth strategies, one of those key aspects of growth strategies is to identify what those commonalities among your 10,000 person customer database are, And you’re going to find that there’s going to be kind of one or two lifestyles or use cases or audience segments that just tend to stand out. And choose one of those and try it out.
We’re not talking enterprise level. We’re just saying it’s good old-fashioned marketing. How do you appeal to the mom that’s 38 years old with a couple of kids and she’s buying your product to feel just a little bit younger or to find relief for her day. Go speak to her, make sure that it’s authentic, make sure that you run this past a female audience that’s in a similar situation. Make sure that your placement relates to those individuals that your landing page, that your ads all kind of have that corollary call to action and emotional tie in. And I think you’ll be surprised your ability to spend marketing dollars and to see an ever-increasing return. And the marginal gains off of that, I think ultimately become significant over time.
It’s to say if on our website, we’re normally achieving a 2% conversion rate for all visitors, what if we could devise a campaign and what if we saw a lift to 3% or 5% just because we were more thoughtful and we just put a little bit more effort into tailoring the message, the journey, the experience to the lifestyle and use case of that individual. I think you’d be amazed the kind of list that that can provide.
Rich: It definitely sounds like it. My only concern here is, it sounds like this is a very linear progression, but we both know that people are incredibly messy in their decision-making process. So how do we really, if we start taking some of these steps, whether we’re using a CDP or not, we take some of these steps that are just good marketing, and maybe we do see a lift. But is there a way that we can kind of understand a little bit more about the customer journey so that we know that one particular element we did was outperforming another one, or just to continually, how do we keep on maximizing that ROI we’re getting?
Phil: Excellent question. And so I’m going to continue to speak to that kind of SMB audience of sorts. It’s interesting, relevant to the customer journey. There’s a lot of technology and data that we use as an agency. I’m sure, Rich, you have recommendations yourself. We have found, so we actually built a platform called Kudos that maps that customer journey. Where if, as you look at, and we’ve had great success. So them coming from Meta, them coming from Google, them coming from video, pre roll display. What we’ve observed at studying millions of journeys over the last couple of years, that it’s just what you’ve said. It’s more circuitous, it’s messy, it’s nonlinear, it’s circular in some sense.
And usually as brands we think, they came, they saw, they bought, and they left. And our goal is just to get them to buy again. What actually happens is, they came and they saw because they saw a video or an add on Meta, and then they left, and they didn’t buy. And then they came back via direct. And then they came back via SEO. And then they came back via a Google ad. And after usually five to seven, eight touchpoints, you get some sort of traction, and there’s a conversion event or some sort of purchase. And it doesn’t stop there.
I think so often we think about a customer journey, and we think, what was the path to purchase. And I think brands are missing out on what’s the post purchase path to purchase again. I mean, your easiest next transaction is always going to be your current customer base. And I think so often we’re so fixated on that first purchase of the customer, we’re not providing enough personalization and value for that customer’s next purchase and the next. And so any sort of modeling we’ve seen, we always recommend looking ahead and almost anticipating what that next cell would be. And what are we doing in our SMS and our email nurturing campaigns and via CRM. If they purchase this, you might also be interested in y? And so I think number one, that’s a tremendous opportunity that that most brands kind of forego.
From a customer journey perspective, there’s some fantastic tools baked into Google Analytics 4. It was easier to find in Universal Analytics, but you can still get it, and it’s called ‘top conversion paths’. So you can actually go and sort in data filters and say, how did people come to purchase? Now, this might be the first time and you’re going to need to rely on your CRM for kind of the second, third and fourth time, but you can actually analyze every purchase that has come through and what those common paths are. How to roll that data up and to see, oh, I can see that, you know, they came from here to here to here to here to here and then bought.
And so that starts to strengthen at least your assumptions and understanding of what that customer journey was. So I think Google Analytics is an excellent resource that is far underutilized. GA4 is a gold mine of data that is often really hard to access because the interface isn’t great yet. But if you dig deep into the user explorer and to ‘top conversion paths’, there’s just a litany of information there that you can glean.
Rich: So if I’m understanding you correctly, Max Connect Digital offers a CDP, usually at an enterprise level. Is that kind of what you guys are doing?
Phil: So I would say it’s like a CDP. We just have done enough of customer attribution and journey mapping, and many agencies do this, so we’re not the only ones. But yeah, you actually have the ability to visualize in real time that customer journey and actually review and say, I want to see individuals that over the last 30 days somehow were touched by these types of advertising. What does their journey look like?
And what’s just fascinating about that, and this would be true of any agency that did this, is that you see people come to the site and it’s almost like they go hot and heavy for a day or two and they’re on the site five or six times. And then they kind of almost go cold sometimes for a week or two. And then they come back again and it’s almost like they did another deep dive. And sometimes this cycle repeats a few times before that first purchase and then the next purchase.
But what’s fascinating is we look at those kind of gaps and we have to imagine maybe their kid got sick. Maybe they got busy with work. Maybe they left on vacation. We’re human beings, we’re as unpredictable as it comes. And so it’s almost fun to put yourself in the shoes of that customer. To study this data on a qualitative sense, you almost just have compassion for marketers to recognize that it’s really not that easy. You’re trying to deal with sometimes irrational people, convincing them to make a rational purchase decision, even though something happened in their life that it’s going to take them a few more times to come back.
And so yeah, we do try to visualize that journey. And again, we’re just pulling data from various paid platforms and analytics and search console that anyone has access to.
Rich: Interesting. And I think it is interesting because we did talk about, humans are irrational creatures and life does get in the way of a lot of decision making. And I know from my own experiences, I might go hot and heavy into researching a new table saw, and then I just get busy with other things and there’s no point in doing any more research. And then a month or two or six later I’m like, oh yeah, table saw, and I get back into it.
Do you think that as you’re looking at it using a tool like yours, you start to see maybe some common patterns, I would guess. And you mentioned GA4 a few times, and one of the things that they talk about GA4 is it’s much better at predicting data. With all the privacy rules that are in place, it’s just better about calling out trends as they’re happening or before they happen. And is that some of the benefits we get at looking at a tool like this or pulling in this empirical data, is we start to see certain paths through the woods or in the grass that then we can start to make sure that we’re putting our marketing messages in the right place.
Like if there’s always going to be a gap, is there an email drip campaign that can fill in that gap to lure them back? Are those some of the lessons that we can take away? And what are maybe some of the other lessons we can take away from looking at a tool like that?
Phil: Yeah. No, thank you for that comment. I would say that I think so often as brands we, from an email data capture perspective, sometimes we’re not as quick as we ought to be. And we all hate that you go to a site and you immediately get a pop up, and it’s a 10% off newsletter subscription.
But to be honest, that might be the best play a brand ever has. Because if it can capture data early on, suddenly to your point, those gaps that, and it’s probably not lack of interest, it’s just life getting in the way. And it’s almost like that little prodding on the shoulder to say, hey, do you remember when you were interested in a table saw? Here’s how great this could be. And here’s the kind of projects you could do. And it’s almost that romanticizing what this purchase could mean for your lifestyle that we almost just need reminders. And if brands do that well, and if it’s personalized and utilizing some of that site data or add data and being able to surmise what that next step would have been and predict that, I think humans appreciate that. I think we appreciate getting those little reminders of, oh yeah, I was going to do that, and you did see I was interested.
To come back to your question. Some of the things that we’re infusing into our Kudos platform is some of that predictive modeling. But going to GA4, again, what GA4 is trying to do, and I think why Google did that big revamp on their platform, is you start to kind of see where that consumer is being led. And I don’t feel like it’s fully baked yet, and I feel like AI right now, I probably haven’t invested the time to truly grasp the power of it.
We’re utilizing it throughout our agency, but I do think that there’s a tremendous opportunity for AI here to say, here is a thousand different customer journeys and path to purchase or individuals that didn’t purchase. And what are the patterns? What are some of the commonalities? What were the acceleration points? What was the creative or the channels or the touch points that spurred them to purchase or when they didn’t purchase? And what can we learn? I think this is a tremendous opportunity for machine learning.
No one, no human needs to go through hundreds of thousands of journeys to go study this themselves technology camp. And I think GA4 is starting to get us there, but you’re exactly right. How do we lessen those gaps? How do we not interrupt, but appropriately remind and tap on the shoulder and bring individuals kind of back into that purchasing cycle, and remove some of those gaps and just kind of flatten that out somewhat? And I think AI, coupled with where GA4 is headed, is definitely way to way to go.
Rich: Phil, this has been really interesting. If people want to learn more about you, if they want to learn more about Max Connect Digital, where can we send them online?
Phil: LinkedIn primarily for social media just @PhilCase. And then our website is just MaxConnect.com.
Rich: All right. And we’ll have those links in the show notes, so you can check out Phil and his platform. Phil, thank you very much for teaching me something new today. I’m always excited about that. I appreciate you coming by and sharing your expertise.
Phil: Great to be with you, Rich. Thank you.
Show Notes:
Phil Case and his team at Max Connect understand the importance of collecting customer data to better understand them, and to therefore elevate their marketing strategies in a more personalized way. Be sure to connect with Phil on LinkedIn.
Rich Brooks is the President of flyte new media, a web design & digital marketing agency in Portland, Maine, and founder of the Agents of Change. He’s passionate about helping small businesses grow online and has put his 25+ years of experience into the book, The Lead Machine: The Small Business Guide to Digital Marketing.