BrainTrust Query: Four New Approaches to Consumer Segmentation in a Digital and Social Age
Through a special arrangement, presented here for discussion is an excerpt of an article from the Joel Rubinson on Marketing Research blog.
Traditional consumer segmentation can be maddening. It is at the heart of marketing practice to group consumers into segments based on their needs and self-stated psychographic profiles, and to then attempt to target a high priority segment with new offerings and advertising. Yet it simply does not work that well because it is rarely very actionable.
In the digital and social age, here’s how that can change:
Segment moments. I am much more interesting to Ford or General Motors when I am looking to buy a car then right after I make a purchase, am I not? In a digital and social age, moments become directly targetable because I, the consumer, do things differently on my self-guided tour of the internet depending on my current goals, thereby giving out forensic signs. I seek out different content, I search for different terms, I like different things on Facebook, and different products show up on my frequent shopper data. All are highly targetable without needing to water things down with demographics.
Segment for ad targeting based on brand loyalties. Increasingly, digital and social data can be merged with frequent shopper data for ad targeting. (Facebook just cut a deal with Datalogix to do this, for example.) Rentrak and TRA have each merged TV viewing with frequent shopper data. The "so what" is that a marketer can now target their advertising to "switchables," those who buy your brand occasionally, but not most of the time. A much higher response to advertising and promotions comes from switchables than from those who are completely loyal to either you or some competitive brand.
Segment people as shoppers. Do I plan purchases or decide in-store? Do I like to explore to find new meal ideas? Do I like to sample the gourmet cheeses? Do I like to sniff the fragrances of air fresheners and shampoos? All of these have clear action implications for category adjacencies, store layouts and specific shopper promotions delivered in a customized way, increasingly via mobile apps. Is there a consumer attitudes segmentation that can claim the success of what dunnhumby did for Tesco in the U.K.? Not that I know of.
Segment people based on targetable interests and values. Analyze the interests, cultural values, and lifestyle characteristics available via Facebook or Google profiles and create segments on factors that reflect those actionable characteristics. Besides being able to readily act on such segmentation, every ad campaign becomes a test as the right segment should exhibit greater response.
Jim Stengel, the former CMO at Procter & Gamble said at a conference in October 2012, "Get close to the consumer and do something with it." Now with digital data and matching to frequent shopper data, we can finally "do something with it."
Discussion Questions
How should segmentation strategies be rethought to take advantage of digital and social connections? Which of the suggestions in the article appear more actionable and which less so?
To me, Joel’s points suggest that we do away with segmentation altogether. When we think about segments, we get caught up in names, cohesion, etc. Abandon that in favor of target-able moments. If I’m searching durables, like a car, I’m ripe for an ad—send me one. If you know that I go grocery shopping every Thursday, send me an ad for products on Wednesday. If you know that I shop Publix and Kroger and Whole Foods, send me a high value coupon (like Publix does) so that I’ll spend most of my money in your store.
These four approaches to consumer segmentation strategies are insightful and spot on! These concepts are focused upon understanding the shopper and where they are along their shopping journey and associating attributes to their state of mind at that particular point in the journey.
Attribution is a much more beneficial method to use in our digital landscape as opposed to consumer segmentation. Consumer segmentation is all about the brand point-of-view whereas attribution is all about understanding the shopper and her point-of-view.
Marketing tools will shift from traditional consumer segmentation combining customer profiles, marketing messages and branding to digital pathways to purchase which integrates a consumer’s order/browse/search history, product content and data relationships.
Consumers will be targeted by consumer data versus consumer profiles. Instead of using mass media we will use direct to the consumer. Instead of simply brand to consumer communications, we will have brand to consumer, consumer to brand, and consumer to consumer. A different world indeed.
Segmenting moments seems to be an actionable way to address people when they truly care about a product. I agree with Joel, “All are highly targetable without needing to water things down with demographics.” Targeting interests also allows marketers to connect to shoppers at an involved state as opposed to pushing ideas based on segments and perceived loyalties.
People generally don’t like to feel as though they’re being marketed to, and if they are, they want it to be meaningful and relevant. “Shoppers” is too vague and needs to be further segmented to make it an effective tool.
great thoughts about new ways to look at consumer segments. In particular I like “Segment moments.” Targeting a person who is searching for car data is far more valuable than promoting to people that may have just purchased.
I would also add Segment by Geo Location. To stay with the car example. If I know a consumer is at a car dealership near me, I can more effectively target a marketing campaign to that individual. I call this an “In The Moment Coupon” or said another way “In The Moment Offer.”
Brands understand that reaching the right person at the right time with the right offer is a win for everyone.
It is interesting that an article that supports customer segmentation starts by seemingly discounting customer segmentation. Similar to so many analytic exercises, the key to developing an actionable segmentation is to understand the business objectives. I would not build a customer segmentation around psychographics to understand customer moments. At the same time, customer moments are not necessarily going to help with product development in the same way that psychographic segments will.
I suspect what is driving Joel’s frustration is mismatching analytic marketing tools rather than the tool.
This article is correct in challenging us all to think, and think differently about segmentation, psychographics, demographics, etc. What I think is underpinning the discussion is the difference between causal and correlational data.
The “job-to-be-done” (behavioral and active pursuit) is what matters (causal) and NOT the social, geographic, race, income, etc. factors. Those are correlational and may help in choosing how to market, where to market, etc., but will be less effective than COMBINING it with the behavioral (not suggesting it is one or the other, it is both together).
These are some good suggestions, however, a couple, like “ad targeting based on brand loyalties” have actually been around for awhile, as in Catalina giving competitive coupons based upon purchase history.
Today, technology is quickly catching up to the business needs here. Companies can now integrate consumer segmentation predictive analytics into business applications. Marketing has GOT to be interlocked with IT. Consumer segmentation is an excellent first step for technical people entering into the marketing arena of predictive analytics. Using off-the-shelf software and existing transactional databases, companies can quickly generate segmentation models that form the basis for optimizing sales and marketing processes as well as provide a foundation for other predictive analytics.
However, integrating the statistical results into business processes can be difficult. There are great articles that provide guidance and a progressive procedure for deploying a segmentation model to business users.
I respect the thinking here. But it’s my experience that none of this fundamentally changes the targeting challenge.
As one point of observation, we’ve had these abilities in digital media for a decade. And yet, digital remains far underpriced. If this targeting delivered the power promised, then digital would have the economic muscle to be priced far closer to traditional media.
All that means something’s missing here and I think it’s the fallacy around behavioral observation (because that’s what all these approaches are based on). Just because someone exhibits a behavior doesn’t mean they are doing that thing for the reason you expect. They may search specific terms often to learn knowledge, for example, that helps them get a job—in other words make them a very, very poor prospect.
So my advice: Treat these theories as pure theories. Then test your way carefully to learn where they might offer the limited advantage they can bring. And avoid betting too much on them. There are significant flaws in what’s being touted by the digital business.
Why do marketers segment? Because they can! Unfortunately, people show an amazing disregard for segmentations, and may actually be “appropriately” members of several distinct and mutually exclusive “segments” in a single shopping trip.
However, segmentation is still a very worthwhile undertaking in understanding the shopping crowd, as long as you recognize a target individual may be switching labels on themselves with careless abandon. This emphasizes the need for targeting “in the moment,” which means that multiple different targeting strategies may be appropriate even on a single shopping trip. See, for example, “Three Purchase States (Modes of Purchase Hypothesis.)“
The ability to segment customers and strategies to do so are enhanced with data collection technology. More than ever, we have the ability to learn very specific information about our customers. Retailers are able to get closer and closer to their target customers, versus a “shot gun” approach. Using data taken from social connections, you can get very specific. For example, we can focus on virtually any criteria or combination of criteria; age, geographical location, hair color, height, etc.
Our market segmentation schemes from the 50’s and 60’s work fine for high level strategy, but fail at the tactical level. One of the key reasons is that the consumer has instant access to information and no longer must work through the Yellow Pages. A consumer researches cars on the internet, then purchases and now is researching something else — not car any more.
The new digital age has a short (maybe) one-month time period for an item. Showing a consumer a car advertisement after they purchased is a waste of money. To be effective in this new world, sellers need to identify consumers starting this cycle early and know when to move to the next consumer. We say in retail, all is local, but with consumers all is the individual. This individual has market segment components, but we must determine if they have a smartphone, tablet, income, age, technology experience, etc.
Segmentation is not a static process. Segments change, people move from one segment to others all the time and new segments get created. Understanding this is critical and I feel here’s where social media can play an important role. By “listening” to social media, marketers can redefine their customer segmentation. Of course this needs to have a robust analytics process in place. Segmenting based on interests is likely an approach through which this can be done.
I feel like digital and social segmentation should be based on context. Customers are always seeking for added personalization and relevancy in their research and shopping experiences. The key is to be up front and opt-in. Nobody wants to be spammed, so proper context is key. If somebody is searching Cadillacs, then by all means advertise Cadillacs on their Facebook page.