Most brand managers or marketers think they know their customer. Maybe they have a high-level picture of who follows their brand on social media from a listening app. Or it’s a third-party summary from Nielsen audience or sales data. And then maybe they’ve gone out and held some focus groups with consumers who look like that to understand them a little better. Maybe they have personas!
Or maybe, they actually have pretty solid individual-level data about customers’ purchase history, website visits, calls to customer service, etc. And they analyze that to inform which offers and email versions they see.
But very few organizations understand customers on both an emotional / attitudinal level AND a transactional / behavioral level – down to the individual customer. GALE helps clients do that, to support ideation of experience design and targeted marketing campaigns that really hit home with distinct segments of customers.
I am going to circle back on this. But first, permit me a little aside to introduce the concept of Knowns and Unknowns, for marketers.
There are some consumers who, as marketers, we really know. At GALE, we call these our Known Knowns. We know who they are and what they buy or engage with. For instance, a retailer (hopefully) really knows its loyalty program members based on all their past purchases, logged-in visits to the online store or app, and maybe even some profile information they submitted when they signed up. And all that information is tied to an individual-level unique identifier like an email address. More importantly, the Known Known customer knows that the retailer knows them. And they expect that the retailer uses the information collected about them in smart ways to improve their experiences.
There are, of course, also Unknown Unknowns. Consumers who have never engaged with a brand or store in any way. Or maybe they have once or twice, but in untraceable ways. They paid cash. They checked out the website incognito. We have no PII (personally identifiable information) and even if we did, we don’t know much about them or what they care about. These are probably not in the target audience. Marketers don’t really expect business from them, and they don’t expect brands to recognize them. As marketers, for efficiency, we often put low priority on this group (unless they make up a giant share of transactions and revenue).
Then, there are two groups in the middle. Known Unknowns and Unknown Knowns. These groups are ones we’re close to being able to market to in personalized ways, but we’re not quite there. They deserve a post of their own. In my next post, I’ll describe these groups in more detail and ways of converting them to Known Knowns.
So, let’s get back to how we live up to the expectations of Known Knowns. How does GALE help marketers deliver better experiences to them, using data that has been collected about them?
First, we scrutinize first-party data about customers’ interactions with your brand. Stuff that might reside in the database where you store transaction history, or data you collect to populate a customer’s profile or account page. The kinds of variables that are relevant differ by industry, but often we’re interested in things that drive value to your business and that can be influenced by marketing offers, such as:
- Frequency of visit or purchase
- Average spend per visit
- Average number of items purchased per visit (or hours / days)
- Types of items purchased
- Perhaps even margins on the types of things they buy
- Times of day / days of week they visit and buy
- Channels they visit / buy through
- Locations visited
- Loyalty program enrollment
- App downloads
We can use artificial intelligence to find clusters of customers who behave in similar ways to each other. Our recent whitepaper, “The Art of Customer Segmentation,” dives into AI and clustering in detail. From there, we find customers who behave in relatively low-value ways vs. customers who do just one or two things a bit differently but are more valuable. This is our “aha moment” — we then create a powerful offer idea that will push them toward a new behavioral pattern that’s worth more.
At this point, we’d develop a brief for our creative team. Let’s imagine we’re running CRM for a fast-food chain. We need to get mid-afternoon weekday hamburger buyers to upgrade to full meal deals, and we need email copy. But we’re still missing a ton of information that our creatives need to create a compelling offer to entice that change. They’ll want to know:
- What channels are they on mid-day? Is email where we actually need to hit them?
- What do they love about your brand / burgers to start with? What emotions are associated with the snack break they have with you? How can you build on that?
- Why aren’t they trying full meals today? What barriers does the offer or copy have?
- Is it about price? (Offer discount). Is it about health? (Message indulgence). Do they actually think your fries are gross? (Unfortunately, creative alone can’t help here!)
- Do they actually have that kind of meal ALL THE TIME…except with a competitor? Why do they prefer a competitor for that meal?
- What does a group of people who all behave this way look like demographically? How does that tip off our channel choices and messaging tone? What range of relevant influencers or cultural references we might dial into?
These are a lot of questions requiring specific insights that you’re not likely to find just lying around the internet, and it’s definitely not in your first-party data. You have to ask for it. (Or make it up, which is a pretty common approach in traditional creative agencies. But, to the marketer reading this, we know you’re better than that!)
If you really have no idea, you might start with some qualitative research. But ideally you’re building up to ask in a structured survey — so you can append a decent volume of these new attitudes and emotions and competitor data back to everything else you know about individual customers. From here, you do some modelling to figure out what everyone who didn’t take the survey might have said if asked similar questions. And voila! We realized we have two super distinct groups who exhibit the same behaviors, but for different reasons. They are going to need completely different communication strategies. For example, we might find:
- A) College-age males who are looking for a fast and cheap protein fix after a gym workout. For them, we might design an offer to double up on burgers instead of adding fries and a drink. It’s not an email. It’s placed through Tinder.
- B) Moms treating kids to an after-school snack, knowing dinner is coming soon. We don’t think we’re going to get them to do weekday meals – our offer for them is to try us for a weekend dinner treat. We mail them a coupon book full of weekend-only offers. Direct mail works well here because, on the weekend, the whole family can partake. A book of several coupons helps establish a habit.
In sum, we work hard to get rich insights that blend (a) a quantitative assessment about behavior changes that can drive the most incremental value and (b) understanding of attitudes, emotions and context behind current behaviors or blocking desired behaviors. Together, those insights set us up for a well-informed plan of marketing investments — allocated against the right audiences and right channels for those audiences. And the right creative positioning to get attention and motivate action.
As mentioned earlier, I’ll follow up with a post about Known Unknowns, Unknown Knowns, and what it takes to convert them.
Director, CX Strategy & Insights