Avoiding Segmentation Snafus

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Marketers may think they have the right segmentation strategy. But do they? Here’s how to ensure that customer segments are real world, not contrived

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Avoiding Segmentation SnafusMarketers may think they have the right segmentation strategy. But do they? Here’s how to ensure that customer segments are real world, not contrived

By Cindy Waxer

For all of marketing’s technological advancements, customer segmentation is still one of the most popular ways of iden-tifying customer needs and creating targeted marketing

campaigns. “Customer segments ensure that a brand is delivering the most relevant message to a consumer,” says Michael Benedek, CEO of online data company Datonics. “They also play a role in ensuring a positive experience for a prospective customer.”

But the way in which brands slice and dice customer groups is also a source of heated debate.

“This is an area which, in many ways, is still driven by Mad Men, not math men,” says Tim Barker, CEO of data intelligence provider DataSift. Rather than rely on clean and accurate data to determine “the ideal buyer,” Barker says, many brands are still living in “a bygone decade where customer segments were driven by stereotypes and gut instinct.”

That’s a shame given the enormous opportunities pre-sented by carefully carved segments. Just ask David Scamehorn, VP of analytics for Olson 1to1, a loyalty and CRM agency. Scamehorn cites one retail client that offered blanket discounts to a wide array of customer personas in an effort to increase traffic to its stores. That is, until the retailer re-segmented its customers based on their predicted future value. Next, it determined the discount required to increase transactions among these different seg-ments. The result: The retailer increased marketing campaign ROI by 30% year-over-year, all by simply tailoring offers to seg-ments that are the most profitable.

But not all brands take the time to rethink their segmentation strategies. They should. Stale segments can result in negative re-percussions. “Inaccurate segments can lead to some serious con-sequences, such as wasted budgets, poor brand reputation, and negative brand image,” Benedek says. “Customers want relevant ad messages because the irrelevant messages are irritating and a nuisance.”

Yet poorly conceived customer segments continue to dominate the marketing industry — a predicament perpetuated by a wide variety of common mistakes.

“Customers want relevant ad

messages because irrelevant messages

are irritating and a nuisance”

Not a magic bulletOne such mistake is the presumption that customer segments can fix broken business practices.

“Segmentations really aren’t designed to be these precision tools that will help you optimize incremental lift, or upsell and cross-sell products,” says Andy Wilder, VP of analytics at global marketing company Epsilon. “They’re really about differentiating your custom-er base.”

Olson 1to1’s Scamehorn agrees. He says marketers must avoid thinking “of a single segmentation scheme as being able to solve all of a brand’s business problems.” Rather, custom-er segmentation is a starting point for developing a deeper understand-ing of an organization’s customers.

Another common mistake market-ers make is determining the optimal size of a segment. Data analytics has made it easier than ever to cre-ate tiny subsets of consumers for one-to-one marketing. For example, an algorithm may recommend exactly what items need to be pushed into an online shopper’s cart to encourage a purchase. But there’s a danger in becoming too granular.

“Analytics groups love their data, so we always tend to show too much detail too quickly,” Scamehorn says. As a result, a brand may spend an enormous amount of time targeting a tiny group of custom-ers with low revenue potential.

The secret, Wilder points out, is to strike a balance between linear and granular segments.

“The segments can’t be so small that you have so many of them that they become impractical for execution…but they also need to be large enough that they’re economically viable,” he says. “The segmentation still needs to apply to the vast majority of your customers.”

Marketers who rely only on

demographics to reach consumers

risk missing more than 70% of potential

mobile shoppers– Google

Size mattersIn addition to putting too much stock in segments, and underestimating the im-portance of size in segmentation, many marketers fail to use the right criteria for dividing customers into meaningful groups. For instance, Wilder points to one client that used demographic details such as age, gender, and geography to segment its customers. While these factors helped differentiate the groups on a surface level, many of their customers’ buying patterns and product preferences overlapped, thereby minimizing any truly distinguishing factors among the groups.

Customers segmented by demographic data “were all buying the same items and they were all doing the same things. They also had similar values, which rendered the segmentation ineffective,” Wilder says. “When we looked at what was meaningfully different [among the segments], what we found is that when you looked at customers’ spend, their value, and what they were buying, they looked different from an age, gender, and income perspective.”

Indeed, if the client had continued on the same course, Wilder says, “they would have come up with a lot of strategies around age and income, but they wouldn’t have moved the needle very much in terms of outcome.”

DON’T mistake personas built on qualitative insight with data-driven customer segments.

DON’T confuse segmentation with personalized targeting. The former allows for only basic personalization; using techniques such as predictive modeling and machine learning, the latter provides more advanced and relevant personalization.

DON’T segment for segmentation’s sake; always start with specific mar-keting objectives and use cases that the segmentation will support.

DO use segmentation to identify opportunities such as underserved customer groups.

DO set and track specific goals and KPIs for each different customer segment.

DO use customer segments to guide content and asset planning.

Source: Don’t Give Up on Customer Segmen-tation, by Srividya Sridharan, VP, research director, Forrester Research

6 Segmentation Do’s & Don’ts

Getting back on trackLuckily, there are best practices brands can put in place to avoid customer segmentation snafus. For starters, upfront legwork and preliminary testing of segments can go a long way toward detecting errors before a campaign’s launch.

“Conducting market research on who the customer is, as well as customers’ wants and needs, is an important step to take before determining the best segments for specific campaigns,” Datonics’ Benedek says. “It’s also wise to conduct test campaigns targeted at customer segments to measure response and behavior.”

DataSift’s Barker agrees.“The more you can build and test a seg-

ment, the more you can build confidence that your message works and that your campaign is going to work,” he says. “In an ideal world, we’d be testing all the time.”

But testing is only half the equation. Brands must also be able to respond quickly to the discoveries they make through testing.

“You might find a market segment really embracing your product that you hadn’t anticipated,” Barker says. “From there it becomes more of an agile marketing approach where you can evaluate the segments that are engaging or purchasing, and then use that to build and extend your creative messaging.”

Looking beyond the four corners of your marketing department can also enhance the value of customers’ segments. For example, cross-referencing the behavior of certain segments against those of a third-party data provider or competitor can help validate segments and reveal inconsistencies.

“Marketers should be checking target customer behavior against a lookalike data provided by a third-party data vendor,” Benedek adds. “For example, do the customers that arrived to a marketer’s shopping cart fit into segment A, B, or C of a data provider?”

“In an ideal world, we’d

be testing all the time”

Take your timePerhaps the hardest lesson to learn when it comes to segmentation is patience. In today’s fast-paced world of marketing automation and fleeting customer trends, the temptation to create and roll out segments quickly can be overwhelming. But that’s a mistake, Wilder says.

“One of the greatest injustices of segmentation is sometimes they take a little while,” he says. “Their gestation period is longer than a predictive model, so to see the fruits of your labor you need to be disciplined and pa-tient with your activities. You want to see if, over the course of time, you’re making a difference and you’re changing the customer experience.”

Beyond testing, it’s also wise to regularly revisit customer segments to make sure they reflect a brand’s most up-to-date customer base and product offerings.

So, how often should marketers re-examine their segments? In many instances, that de-pends on the brand and industry. For example, Wilder points to a client that relies on a wide va-riety of product SKUs to segment its customers.

“The reality is they’re coming up with new SKUs constantly, so they need to revisit their segmentation frequently...to be in tune with what’s going on with their segments,” he says. “Otherwise, a customer who buys from a new product category won’t get classified.”

Other reasons to re-examine segments include product releases, global ex-pansion, new loyalty programs, or fundamental changes in a brand’s business approach. Ultimately, Olson 1to1’s Scamehorn says, it’s all about “determining whether the segmentation you built is still providing value and insight for better decision-making.”

For some, this requires monthly reassessments. For others, quarterly reviews of customer segments are sufficient. But no matter how often marketers slice and dice their data, today’s brands can’t afford to base campaigns on ill-conceived customer segments.

80%: Executives surveyed who rank

their satisfaction with customer

segmentation as a 4 out of a possible 5, where 5 equals

the highest level of satisfaction

– Bain & Company

A bright future for the science of segmentation Thanks to today’s big data revolution, the art of customer segmentation is facing a drastic over-haul. For decades factors such as age, gender, and geography helped marketers divide con-sumers into neatly packaged groups. But sophisticated algorithms and computer models are changing all that, enabling brands to create tiny “segments of one” for uber-niche marketing.

“We’ve come a long way, mainly because there’s a wealth of behavioral data that simply didn’t exist or wasn’t available to analyze 20 years ago,” DataSift’s Barker says. “Segmenta-tion has really grown with the big data industry, especially over the past few years.”

Analytics may displace most hunches and gut instinct, but big data isn’t a surefire recipe for perfect customer segments. For one, inaccurate, messy, and outdated data can wreak havoc on a segment’s applicability.

“Clean data is paramount,” Datonics’ Benedek says. “It’s extremely important to leverage accurate data and monitor a data set over time and adjust as needed. Working with trust-ed data providers helps to mitigate the potential for data inaccuracies.”

Having a data scientist on staff can also help minimize the risk of inadequate data sets.“A marketing analyst is a must-have on the bench of every CMO these days,” Barker

says. Better yet, he adds, easy-to-use software programs are increasingly doing the work of data scientists, making it easier than ever for brands to embrace data analytics to support their segmentation strategy.

Segmentation Usage and Satisfaction Among Executives Surveyed

Source: Bain & Company