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Claritas helps companies find customers. Through our podcasts we hope to help you better understand consumers, why they buy, and how they prefer to interact with you. We'll explore topics important to today's marketers so we can get you one step closer to your next customer.
Monique: [00:00:00] Hello and welcome to the Marketing Insider, a podcast for marketers focused on finding and targeting their ideal customers at scale. I'm your host, Monique Ruiz. This month's episode is almost a continuation of the conversation we had last month where we talked about campaign execution, but we're taking a slight step back and starting at the beginning.
Today, we're talking audiences, activation and acquisition. Because first of all, who doesn't love alliteration? So what does this mean? Well, it's a little bit of who are your best customers and prospects? What does it take to pique their interest enough to shuffle them down the marketing funnel? From awareness to consideration, then how do you actually acquire or convert them to paying customers, clients, or members?
To help me answer these questions and a lot more, I'm excited to [00:01:00] welcome Don Carly to the podcast. Don is the president and co-founder of NEMA Hunter Incorporated, and a consultant to branding and strategy firms on topics related to precision marketing. Done. Welcome to the Marketing Insider.
Don: Hi, Monique.
It's a pleasure to be here. Thank you so much. Happy to
Monique: have you. Yeah, so you wear a bunch of different hats and you've been a great partner to CITAs for many, many years. Working closely with our financial services team in particular. Yeah. But this is your first time on our podcast, so I'd love if you can give our listeners a little bit of insight into your areas of expertise and what clients come to you to help them achieve.
Well, thank
Don: you. Um, well, first of all, it's, it's been a pleasure working with Claritas in that, in the earlier part of my career, I, I was responsible for strategy and marketing at, uh, Xerox. Mm-hmm. And particularly b2b, um, where we had great technology for personalization. With the advent of digital [00:02:00] printing, we were now able to create.
Transaction billing for banks and credit unions. That didn't say dear customer, it said, dear Monique, and Right. It also included your current balance and an offer just for you. Um, what we didn't have at the time was the kind and quality of data that's now available through platforms like Claritas.
Mm-hmm. Where not only can I identify audiences in the United States based on. A whole array of demographic and psychographic and product usage characteristics, but I can leverage the identity graph to not just identify them, but to engage them and track the metrics associated with conversion. And that is absolutely amazing.
Um, I only wish that in the years when I was, you know, leading precision marketing, uh, for Xerox, I had these tools at my disposal.
Monique: [00:03:00] Yeah. And, uh, I will link in the description box, uh, some more information on identity graphs. For anybody listening that is kind of like, what is that? What's that about? We're covering a lot of ground with our questions today, but let me start off by doing a general marketplace.
Look back with you. Sure. What is different about the customer journey now that we're three years post the beginning of Covid when all industries were experiencing disruption to some degree.
Don: Yeah. It's got so many things. Yeah. Um, but I, I think the most important is that,
Changed the relationship between workers in the workplace. Mm-hmm. For one, so work from home or work from wherever is seriously now not an option, but in fact a requirement. Right. We just saw recently New York City had to. Relent on its pressure [00:04:00] that all workers had to be in the office five days a week and said, okay, alright, three days.
Um, so that's a big change because when we talk about engaging audiences in an error with numerous digital channels of communication, it's important to understand when they're digitally. At home rather than in a place of work. Right. And especially when you're trying to reach them as business people. But every business person is a consumer and has a consumer identity.
So the ability now to reach people where they are in their home, um, and when they want to be reached the way they want to be reached mm-hmm. About topics that are of interest to them. Rather than being intrusive and, and, um, superfluous to, yeah, to their real needs, I think is a breakthrough as a, a sea change that we've seen in the past three years.[00:05:00]
That's one. Um, the second is of course, I. You know, digital connectivity has improved dramatically in the past three years. We're now seeing 5G starting to actually reach practical, um, degrees of availability and bandwidth. Mm-hmm. Um, and that's changed the kinds of media that we can serve. At the re the, the conference for, uh, XR and VR people were marveling at the fact that you're now able to start streaming on 5g.
Mm-hmm. Um, virtual reality, augmented reality experiences. And Apple was supposed to drop its new blended reality headsets. Um, which again, combined with 5G communications changes. How do we engage the consumer? Yes. Where do we engage the consumer? It isn't necessarily, um, in a, in a physical location with a branch, if you're a financial services firm, it's now a digital branch, right?
A virtual branch. And it, it could just as easily be knowing. Who is using a [00:06:00] particular social media channel or a particular digital? Channel to, um, engage with financial services as an example. Mm-hmm. Hmm. So that, I mean, I think the, the third party cookie, um, issue also changed. I mean, we were told just before Covid or just as Covid was, um, uh, starting to manifest as something more than just a, you know, a flu-like interference to something of a global pandemic.
Right. There was a great deal of talk. And announcements by Apple and Google that they were going to be eliminating third party cookies and that, that did put a lot of people in a panic. They relented a bit and not, haven't gone away, but it's been put off a bit. Mm-hmm. But I think it did, it, it did change the awareness of marketers, the importance of first party data, second, third party data and, and identity graphs.
Um, and you know, it's been easier for me as a consultant to talk to clients about the [00:07:00] value of an identity graph mm-hmm. Of having, of having, um, third party data with the kind of coverage that we do and with the kind of depth that we do on so many different demographic and psychographic and product usage behaviors and intents.
So that's, that's been a real change.
Monique: Yeah, it's all of those linkages. I know for me personally, there are a few brands or software or industries that I personally look to a lot more than I did in 2019 before the pandemic. So, and I'm not an outlier in that change in behavior. You know, everybody's in that same boat, so you have to.
Look at potentially targeting a new audience in this way. So, so what, as a brand, what considerations do you need to make, uh, to ensure that you are reaching those ones that offer the most opportunity for you? Yeah.
Don: Well, uh, with, I work with a number of financial services brands and in particular in the credit union space, which is quite interesting to me because credit unions don't have [00:08:00] customers.
They have members. Members, yep. And, and their value proposition is quite different from the value proposition of banks. Mm-hmm. Where you have shareholders that are, you know, not necessarily, uh, in the position of having interests that are aligned with the member or consumer rather. Um, whereas if you're a, if you're a member of a credit union, uh, you are an owner.
And you have a voice that you wouldn't have with a, a more traditional bank. So the first thing I start with is tell me about your members. And it's amazing to me how often they really can't tell me about their members. Mm-hmm. They don't realize that there's information beyond when they became a member and what their current deposits are and whether or not they.
Borrowed or whether or not they've made a deposit in a cd, that if they append cycle segment data from [00:09:00] Claritas to their members, they can now gain insights. Granted, these are insights that are often at the level of a census tracted, um, not necessarily at the level of an individual, right? But.
Nonetheless, it allows you to say, well, who are your best customers by your own measure? And then what other things can we know about them through third party data and segmentation, using cycle segments or prism segments from Claritas? Mm-hmm. Having done that, we can say, well, let's see where people other than your members, with those same characteristics live in physical space.
And frankly, increasingly, where do they live in digital Oh, yeah. Terms.
Monique: Yeah.
Don: Because it's the metaverse it. Well, you know, it it, it has changed. Banking has changed. I mean, you asked me one of the things that's changed. Yeah. When, when I, I first started working with a [00:10:00] credit union about four years ago when everything about their expansion was about new branches.
Mm. Mm-hmm. And then Covid came, and all the branches were closed. Yeah. So how do you expand? People are learned to bank online. They learned to use virtual teller, uh, ATMs with visual, um, video tellers. Right. Um, if they were gonna use anything at all. Um, people didn't wanna come into the office and handle money, so they got com comfortable with, you know, digital check deposits and Yeah.
And digital transfers. Mm-hmm. Wow. They also began to spend more time online, so, And become more comfortable with it. Um, so, you know, I, it starts with who's your best customer, because in all likelihood, your next best customer is someone who either is referred by your current member mm-hmm. Or is, has high degrees of similarity in terms of their demographics, their psychographics, [00:11:00] and their product usage, right?
Financial services, product usage, or even consumer product usage. Uh, rather than, you know, using an older approach of spray and pray advertising. Yeah. To build unaided and aided awareness at considerable cost. Mm-hmm.
Monique: Yes. And unfortunately, there's still a lot of people that do that, but, you know, it's, it kind of goes with, do they, that's okay.
Yeah.
Don: There, there's a place for, there's a place for brand advertising That's true. Yes. To, you know, if, if you think of it in terms of the journey, the customer journey. What has changed? Another thing that's changed is in the past the, the customer would often, or the prospect would often be interacting with a person, in person at some point in the middle of their journey.
And by journey, I mean it begins when they realize they have a problem or a need. Mm-hmm. But they don't know if [00:12:00] their need is unique or there are others like them. So they begin to do research well, and you know, if you were milling around in public, you might ask a friend at a club or whatever, but now we're all online.
So people start going to pick the social media channel, um, and they ask for advice, yes, I've had this problem. Am I alone? And they find out they're not. Well, how did you solve the problem? Then they start talking about a white paper or a webinar or a podcast, or they say, you should check out this company, this brand.
And the fact is that 80% of the decision of the discussions about the solution never take place in a face-to-face exchange with the companies that are ultimately going to be vying for the decision. Mm-hmm. They're being done digitally and with people that may not be known other than through a, a LinkedIn group or a a Facebook group or Right.
An Instagram feed. [00:13:00] Or something along those lines. So in that regard, the journey has changed. It's increasingly digital and it's increasingly, um, making the, the conversion step more challenging if you have not developed any engagement. With the prospect. Mm-hmm. Until they've pretty much gotten down to, well, I've narrowed the field.
It's really between banks a, bank B, and credit union C. Right. And now it's, it's all about interest rates and terms, and we'd like to think we're rational, but the fact is that a lot of decision making in purchasing, whether it's for business or for. For, for consumer personal use is emotional. Oh yeah. Yeah.
And you know, companies that don't understand that journey and how to engage an [00:14:00] audience with a high likelihood of making a decision for whatever product or service it is that they are offering are going to be left out of that part of that consumer's brain. Right. They're, they're not gonna have an emotional connection to the brand.
They're not gonna have a personal connection to the seller in this case. They're gonna look at it very transactionally and, and unfortunately it, it becomes a race to the bottom then. Mm-hmm. For most brands. Mm-hmm. So, Yeah,
Monique: you and I were talking about this when we were discussing getting together for this podcast, so I wanna bring the listeners in on the conversation.
What's the difference between having market insights and having voice of customer data to help inform your marketing strategy?
Don: Well, it's a phenomenal question, and so I, I tend to approach it in, in, um, looking at market insight as [00:15:00] data about a market. Seen from above. Okay. Seen, you know, think of it as I'm, I'm flying above the audience.
Mm-hmm. And I'm looking down and I'm counting how many there are and I'm counting where they're clustering. And I'm counting. It's quantitative by and large voice of the customer. On the other hand, especially when it's gathered through ethnographic studies or focus groups or even surveys, becomes far more qualitative.
And it is as much about how people feel and how they engage with you in physical space or digital space, um, through body language and through, uh, you know, emojis and other aspects that don't really show up in a quantitative assessment of how many households are there in this zip code of census code, right?
Yep. How many households that have a. Investible, um, [00:16:00] uh, in investible assets of at least a quarter of a million dollars and an annual income of a quarter of a million dollars and two children and have owned their house for at least five years. So market insight to me is very much about the quantitative aspects of the number of potential customers, the number of current customers, the market share that my brand has relative to other.
Brands competing for the same decisions. Mm-hmm. Um, metrics like aided and unaided awareness or consideration, set consideration rates. It might also be looking at a market in terms of quantitative metrics like net promoter scores. Um, I voice of customer very different. So now, you know, as I was saying earlier, I, I, I, I work with a, a, a branding and design, um, agency in New York called Auto Brand Lab.
That is very much about looking at the, the. The audience that audiences that we address holistically. We use a combination of [00:17:00] quantitative and qualitative methods of an analysis of third party data like the, the Claritas data set that mm-hmm. Allows me to do what, what is called a total segment market analysis, where I can identify an audience in a zip code that are members of two or three or, or more cycle segments, and then I can.
Query the data set for the households in the census, tracts in that area to say, tell me about how many of them own a home versus rent. How many of them have children over the age of 16 versus children, younger children? Tell me how many have IRA accounts, how many, and I can start to build logical, uh, cases for why.
Households with certain set of characteristics that are largely quantitative. Market insights would be in market for a product or a service [00:18:00] that I believe will satisfy a need that I believe they have or likely to have based on those characteristics. Mm-hmm. That however isn't Voice of customer, right?
Yeah. Voice of customer literally requires either, Putting yourself in their shoes. And we often do that through ethnographic studies where again, with today's technology, I don't have to be physically with them, but I can get their permission to have them use an application on their smartphone and take me shopping with them.
Mm-hmm. Or to let me spend time with their family and understand what a day in the life is like and what. Their ways of describing or reacting to certain stimuli are, are not just likely to be. Uh, it may also be quantitative or what I call quantitative research. Where, and I'll, I'll, I'll give an example.
We did [00:19:00] this recently with a credit union client that has a quarter of a million members and they identified a a dozen cycle segments that were. Not only their best customers currently, but also had the best propensity or, or likelihood of being customers or members that would contribute to the sustainability and future of, of the credit union.
Okay, so I, we, we said, well, we know that there are 300,000 potential new members in the boroughs of Brooklyn and Queens that meet these criteria. But Brooklyn and Queens are very different from Nassau and Suffolk counties. Compositionally, demographically, um, you know, we're talking about different age groups, different ethnicities.
Mm-hmm. Um, different political orientations, vastly different. So can we use the same language, the [00:20:00] same imagery in our outreach to engage them? How would we find out? That doesn't really reveal itself in the data that you have access to through market insights in, in, in a platform, whether it's Claritas or any other.
So, but we can now acquire an audience. We can say, out of the 300,000, let's pick 50,000. Mm-hmm. And rather than making an offer to them, let's invite them to participate. In an ethnographic study. Oh, okay. Okay. And we may now wind up having a hundred people out of that 50,000 that. We'll pay an incentive to.
Mm-hmm. And we'll be able to do a, a, a one or two or three day ethnographic study with them to literally understand how they go about their lives in making decisions. Yeah. Um, another would be to say with [00:21:00] a larger audience, that same 50,000 having learned something. First person, voice of customer, actual, you know, language they use and.
And experiences that they shared with us. Now let's pick an audience of, let's say a thousand out of the 50,000. And instead of doing an ethnographic study, let's field a qualitative survey. Mm. Very interesting. Um, in, in that we're able to now take advantage of platforms that can take natural language.
Ingest it into a large language model. Oh, yes. And, and this is how it works. We can ask a question about, when you think of credit unions, what brands come to mind? Mm-hmm. And we get an open-end. Now, typically as a market analyst, I would wind up with a thousand responses. Right. And it would be up to me [00:22:00] to determine whether they were similar or dissimilar and how they should be grouped.
So there's a. Potential for me as the researcher introducing bias, but now, as soon as they enter it, the natural language processing capability picks it up in real time. Mm-hmm. Runs it through a large language model and says, Hmm, there were f five other things that seem similar. Mm-hmm. So as quickly as you sit, hit, submit it now comes back and says, Monique, um, you said Brand X.
Does another person said this, do they mean the same thing? Uh, and yes or no? Simple question. Right? Right. And and what that does is it disambiguate the answers. Yeah. But the second thing it says is, if you have one more minute, some other people said this about the brand. Mm-hmm. Do you agree or disagree?
Simple answer. It's, you know, it could [00:23:00] be a a five point scale or, or, or three point scale or a seven point scale, but it will, it will do that one or two or three times as much as you have tolerance for. What that does is it takes all of that bias of the researcher out of it because it's doing that same thing to a hundred people in real time.
So that. And again, this is kind of geeky, but it's, it's using a, a different kind of statistical analysis called Besian Inference to now have the group itself make sure that Proposition A and proposition B are clear. Two different things. And if they do mean the same thing, then it just becomes one proposition.
And if there are things that are said about brand A by. A statistically significant number of people in the group. It allows the group to determine whether they agree or disagree. Right. Wow. And it [00:24:00] captures all those open ends on, you know, why did you make the decision or what will keep you from making the decision?
I don't have to predetermine the choices, but the platform does help the group. Mm-hmm. Through crowdsourcing and then with machine learning and natural language processing, translate voice of the customer into terms that are now also market insight.
Monique: Right, right. It's full circle. Yes.
Don: So that now tells us when we go into create the campaign to actually reach 50,000 people.
Mm-hmm. It helps us understand. What to say, right? How to say it. Yep. Who, how to differentiate not only the message and the image, but even the channel or the time of day or the day of week when in an omnichannel campaign we can conduct in-flight analysis of [00:25:00] impressions. Mm-hmm. Engagements and conversions for each variation for each.
Sub-segment of our audience of 50,000 and optimize the campaign's performance in flight.
Monique: I think you just gave our listeners a whole marketing plan out there.
Don: Oh, it and, and. As as, as exciting as that is to a marketer to, to be able to finally solve Wanna maker's dilemma. Yeah. Yeah. I know half of my marketing works, I just don't know which half.
We can now be very clear about what aspects of our marketing efforts are in fact working. Right, and using the same kind of market insights thinking when we field a campaign to 50,000 people. We're also kind of like a clinical trial, maintaining a control group. Mm-hmm. That isn't exposed to the [00:26:00] campaign.
So after the campaign is complete, we wait 30 days. Mm-hmm. And we ask the client to provide us with a list of the actual conversions that took place. Not just the clickthroughs. Right. Not just the people who filled out the form. Yeah. But the people who actually opened an account, made a deposit, took out a loan, and we do a matchback analysis.
And we do a lift analysis. Mm-hmm. Which allows us to see how effectively we addressed our target audience, how much of the conversion that occurred during that time period came from the audience that we identified and engaged, versus others who came through other channels. Mm-hmm. And we're able to look at not only who made a deposit or who took out a loan, but who became a member.
Maybe they didn't go so far as to take out a loan or open a, [00:27:00] you know, a a, a big account, but they did become a member. Yeah. And, and as a marketer, I always have to think about what, well, what was my business intent? Was it to get somebody to deposit a hundred dollars or was it. To convince them that this brand should be trusted and become part of their life for life, so that I now look at that member in terms of their lifetime value.
Mm-hmm. And not a simple transaction value. Right. Right. And I can now begin to justify what for some is seen as a disproportionately high cost for precision marketing, but the way I like to put it to clients is, Okay, so you've just been bitten by a snake. How much is the anti-venom worth to you? It's, it's not expensive when you think of it in terms of lifetime value.
[00:28:00] Yes. So if you're looking at the cost of a spray and campaign without knowing what you actually converted as a function of that campaign, And you haven't calculated the lifetime value of that customer or member, you really can't say that it was a good value. It may have in fact been very expensive, right?
I mean, it is expensive as saying to someone, well, you've, you've, you've now got a very exotic disease and we could give you tetracycline and, and, and it costs, you know, pennies a pill, but. 50% chance it might work. 50% it won't. Yeah. Or you know, we could create a monoclonal antibody that's targeting that specific disease just for you, and yeah, it would cost $10,000, [00:29:00] but we can tell you at a 99% confidence level plus minus two, that it will cure.
What ails you? I'd be trying
Monique: to find that 10,000.
Don: Exactly. So again, it's all a matter of how you frame it. Right. Um, and that's a long way of answering your question, but that that's the difference between market insight and voice of customer. And I think it's the difference between precision marketing and anything else.
Monique: Right, right. Okay, Don, this is going to be a long conversation. I can feel it, which is a great thing. But what I think we'll do is turn this into a two-part episode. We're at a pretty good place to break now. So listeners, if you're tuning in as this episode releases, check back next week for part two. Of our audience's activation and acquisition conversation.
And if you're not listening as this releases, check out the description box for a direct link to part two.[00:30:00]