June 27, 2024
Photo by Anna Dziubinska on unsplash
Should Behavioral Segmentation Be the Primary Focus of Retailers?
In today’s rapidly shifting retail landscape, consumers are increasingly rejecting the traditional narratives that once dictated their purchasing behaviors. A significant change has been observed in how shoppers perceive retailers, particularly those seen as inflating prices while their executives enjoy substantial bonuses and stock payouts. This discontent has even been linked to the rising incidence of theft in stores, as frustrated consumers seek to claim what they feel is their fair share amidst widening economic disparities.
Consumers today are turning away from these idealized portrayals and rejecting traditional life stages that they increasingly find unattainable. High school graduations, college degrees, marriages, home and car ownership, and having children—milestones that once structured marketing strategies for retailers—are losing their relevance. Many people simply cannot afford these once-standard achievements, rendering these traditional targets less effective and representative of the broader demographic.
In response to these changes, retailers are pivoting towards behavioral segmentation, a strategy that more accurately reflects the diverse realities of today’s consumers. This method acknowledges the varied and complex lives people lead, moving beyond age-old demographic markers to focus on behavior patterns and personal circumstances.
This shift highlights a broader societal transformation where embracing the messiness of life becomes a form of resilience. As consumers navigate their way through economic uncertainty and shifting social norms, their purchasing decisions reflect a deeper understanding of their own realities. Retailers who recognize and adapt to these changes stand a better chance of connecting with their audiences in meaningful ways.
Foundationally, behavioral segmentation involves analyzing various customer behaviors to create more targeted and effective marketing campaigns. By examining factors such as purchase frequency, browsing habits, and engagement levels, businesses can develop a nuanced understanding of their customers. This approach allows for personalized marketing messages that resonate with each segment, ultimately leading to higher customer satisfaction and conversion rates.
Effective implementation of behavioral segmentation requires a strategic approach. Gathering comprehensive data on purchase history, website interactions, and social media activity is crucial. This data collection helps businesses understand customer behavior on a deeper level. Instead of creating numerous small segments, it’s beneficial to focus on a few key segments that align with marketing goals. This approach ensures more targeted and effective marketing efforts.
Personalizing marketing messages to resonate with specific behaviors and preferences of each segment is essential. Tailoring content, offers, and promotions to meet the unique needs of each segment significantly improves engagement and conversion rates.
Amazon personalizes email marketing by analyzing browsing and purchase history. This strategy results in targeted emails with product recommendations and discounts, boosting customer engagement and conversions.
Behavioral segmentation can be categorized in several ways. Purchase behavior involves categorizing customers based on their buying habits to identify loyal, frequent, and occasional buyers. This segmentation can lead to targeted promotions and loyalty programs. Engagement behavior focuses on analyzing interactions across various touchpoints such as websites and social media. This analysis helps understand customer interest and engagement levels, enabling businesses to develop more relevant communication strategies. Psychographic behavior, which looks at lifestyle, interests, and values, provides deeper insights into customer motivations and allows for highly personalized marketing campaigns.
Verizon and Hallmark utilize customer data and behavioral segmentation to categorize their user bases and tailor their offerings accordingly. Verizon examines data such as text message volume, call duration, and data consumption to categorize users into heavy, moderate, and light users. This segmentation allows Verizon to offer personalized pricing plans and services, such as unlimited data plans for heavy users and cost-effective plans for light users, thereby optimizing marketing efforts, improving customer satisfaction, and maximizing revenue.
Similarly, Hallmark collects customer contact details during online purchases and analyzes data like card category and purchase timing. This information is used to segment customers based on their shopping occasions, such as birthdays, anniversaries, or holidays. This segmentation enables Hallmark to target buyers with relevant products and promotions, enhancing customer engagement and sales.
BrainTrust
Melissa Minkow
Director, Retail Strategy, CI&T
Recent Discussions
Discussion Questions
How can retailers leverage behavioral segmentation to more effectively cater to consumers who no longer adhere to traditional life stages?
In what ways can behavioral segmentation help retailers develop more targeted and relevant marketing strategies that resonate with the diverse and evolving needs of today’s consumers?
How can adopting behavioral segmentation enhance customer satisfaction and loyalty for retailers, particularly in an era where traditional demographic markers are becoming less relevant?
Poll
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Behavioral segmentation is useful and is certainly superior to more crude segmentations such as age or demographics. However, much depends on how the data are to be used. If the segmentation is to drive basic marketing, such as understanding who to aim promotions at, then this is valuable. If it is to be used to make more strategic decisions then it likely needs to be augmented with a more nuanced understanding of what drives behaviors – the emotions, thoughts and beliefs that sit behind them.
Great insights! Beyond just behaviors, incorporating psychological factors like emotions and beliefs can provide a deeper understanding, leading to more effective and precise marketing strategies.
Retail marketers have been conducting segmentation efforts, including behavioral, psychographic and demographic, to refine their targeting for decades. What’s different today is the myriad of sources of data at retailers’ disposal. Furthermore, retailers have much more knowledge and importantly the tools to analyze the inputs to help find signals that aid in targeting. And while some traditional life stage segmentations still apply (e.g. buying a home, having a child, etc.), ultimately the holy grail is to resonate with each shopper as an individual. Notwithstanding the good progress that has been made on this front, it’s this still a work in progress.
In 1970, with my new MBA, working at Hefty, my first assignment was to explore psychographics and present it to the brand team. Great thinking, but the problem in 1970 was we didn’t have the tools to measure the implementation.
So true, Mark! I remember trying to do segmentation using the limited data available back in the 1990’s when I launched a GIS platform at a Fortune 500 company. It was so difficult with stale data that didn’t go very deep. Amazing how much data we have at our disposal today, and to personalize the analysis down to the individual!
Behavioral data should always be leveraged to help brands understand the ways in which the consumer wants to shop with them. Any time a retailer is only utilizing one type of data to have a view on the customer, they’re missing out on nuance and complexity. Shoppers in our most recent survey told us they’re most comfortable sharing behavioral data with retailers, so this is a very welcomed resource in today’s environment where data privacy is a top concern, but lifestage does certainly matter as well.
Firstly, by eliminating the “traditional narrative” in consumer behavior. Consumer behavior is an ever-changing variable, and retail strategies must constantly evolve. Second, use lifestyle research instead of life stages.
Demography will show you who bought your product. Lifestyle or psychographic data will demonstrate who will buy your product in the future.
Customers can be targeted psychographically via online marketing and CTV, and more importantly, the feedback received from these media platforms provides effectiveness and efficiency data that allows for constant refining of nedia, promotional programs, and offers.
While there may be some correlation between behavior and demographics (perhaps age and income more than ethnicity), it’s ultimately behavior that rings the register — or not. Segmentation by behavior is critical to avoid the trap of “all things to all people,” and to help the smart retailer appeal deeply to its most engaged customers.
Lifestyle/lifestage consumer segmentation has long been a foundational discipline in the CPG retail world. When crossed with the CRM and lifetime value insights available from frequent shopper programs and ecommerce sites, the available data far outpaces most organizations’ executional abilities.
The challenge comes when thousands of finely-differentiated individual shoppers all visit a retail establishment that must find ways to cater to all of them. Retailers have little choice but to condense them into a few manageable groups, based on shared needs and behaviors, and then execute accordingly in their stores.
One might argue that this was the exact genius of the major department stores in their heyday – apparel offerings grouped by gender, age group, price level, wearing occasion and merchandised accordingly. Merchants did this by instinct, back in the day. Today we use data analytics.
The big watchout here for retailers is to avoid depending too much on convenient classifications that are insufficiently diagnostic. Age demographics for example – Boomers, GenX, Millennials, Zees, Alphas – may seem scientific but they can mask the variability within each cadre. Every few months another market research company offers its own segmentation scheme, based surely on carefully executed research, that urges marketers to divide shoppers based on their attitudes.
While all of this is thought-provoking, and much is useful, it is sobering to also remember why we put the “mass” in mass retailing in the first place. Sometimes many of us like the same things! Personalization at scale (the much vaunted 1-to-1 marketing) is a laudable goal, until the added intricacy undermines the retailer’s ability to bring genuine value.
Finding the right balance between appealing to a wide audience and offering personalized experiences is key. Retailers can use data to understand what different groups of customers want while still providing valuable shopping experiences for everyone.
Shoppers are individuals and as such break all the rules of segmentation confinement.\
Demographics do a terrible job. But if that’s all you have, it’s better than assuming sameness.
Behavioral segmentation is a step forward, but I see it as more comforting to the marketer than the shopper.
What I’ve seen work best is data driven, rules-based marketing.
Yes, you need some sense of what you want to do as X when the shopper does Y, which entails some level of classification. But the biggest issue with responding to rather than addressing as a group is marketer fear. Responding to action is unpredictable and hard to report. So marketers take it back a level, create segments they can analyze, classify and track. Orderly. Productive. But missing opportunities to be even closer to shoppers.
Segmentation and data analysis are table-stakes today. Today’s sophisticated AI-algorithms can pinpoint insights that marketers dreamed about years ago. The key for retailers is to chart a path, a strategic journey that will increasingly provide patterns that can be leveraged across the enterprise, in marketing, store operations, supply chain and customer experience. If retailers embrace multiple data sources and ample tools at their disposal, they will find diamonds in the rough.
More data equates to more opportunity for analysis, as long as the analysis provides valuable input for effective decision-making. Heavier data analysis is possible thanks to today’s more powerful, AI-based platforms. Today’s data allows marketers to significantly refine their focus and messaging, much closer to the hypothetical nirvana of a market of one. As with all uses of consumer data, it’s also important for retailers to have boundaries, or at least feedback loops, when consumers have had enough of a retailers targeted marketing.
In addition, recipients of increased data and analysis can include marketing as the article notes, as well as other retailer functions such as planning (assortment, demand), fulfillment (location), and store operations (CX). It’s important for retailers to consider their full enterprises and sharing of intelligence to ensure all applicable functions are operating from the same set of data and assumptions.
I invented a new segmentation that is based on the probability that a consumer will choose your brand given a category purchase is made. Those with a 20-80% probability of choosing your brand called Movable Middles (usually 10-20% of category buyers) have been shown from 11 experiments to be 2-23 TIMES more responsive to advertising. audiences rich in Movable Middles have been show to be 2-2 1/2 times more responsive than those defined by demos or heaviness of category buying (and 5 times better than choosing audiences for conquest who do not buy your brand. IDs are best flagged on prior 12 months of behavior so it truly is a behavioral segmentation.
Proper behavior segmentation leads to a multitude of silos to attack. The major, sophisticated online retailers can do this. A store-based retailer would have challenges dealing with 30 to 40 or more differnet segments in their retail presentation.
Behavioral segmentation, indeed, has large value to retailers. It is a lofty objective to implement and use this science, but the irony lies in that so many retailers are still doing so many – more basic – things poorly, that behavioral segmentation would appear to be too sophisticated and too soon (too much, too early) for those retailers that have not gotten the basics right. This elite cadre has discussed those culprits ad nauseam in this and other forums.
Effective segmentation is mission-critical for retail marketers today. The question of whether consumers no longer adhere to traditional life stages is interesting but irrelevant. Consumer behavior has always been based on an untold variety of factors. Retailers neglected behavioral segmentation in the past not because it wasn’t valuable but because they lacked the tools to extract and process the data at scale. With consumers who don’t follow predictable patterns, the key is 1) getting data-driven behavioral insights in real-time, 2) knowing how to respond, and 3) responding. And while we’ve made great strides, we’ve got miles to go.
Retailers can leverage behavioral segmentation by focusing on customers’ actual behaviors, preferences, and purchase patterns rather than traditional life stages. By targeting actions like buying frequency, product preferences, and loyalty levels, retailers can personalize marketing efforts, offering tailored recommendations and incentives that resonate with diverse consumer needs and lifestyles.
Behavioral segmentation helps retailers create targeted marketing strategies by analyzing customer actions and preferences, enabling personalized offers and recommendations that address the varied and changing needs of today’s diverse consumers.
Adopting behavioral segmentation enhances customer satisfaction and loyalty by enabling retailers to personalize marketing efforts based on real consumer behaviors and preferences, making interactions more relevant and engaging amidst evolving demographics.
Thanks to data and the capabilities of AI (helping us interpret data), we are now able to segment customers into personas on a much higher and more sophisticated level. We’ve gone beyond creating personas based on what a customer buys. Now, we look at habits, frequency, browsing history, and more. Our customers are getting better personalized experiences than ever. This endears the customer to the retailer because of what I like to call the Cheers Principle… Customers want to go where “everybody knows their name” – and more!
BEHAVIORAL segmentation is typically the best singular segmentation scheme to understand past spending actions and to make better informed approaches to communication, assortment and promotional efforts. However, with the wealth of information available to retailers, the other segmentations should not be ignored.
Consider a grocery setting, GEOGRAPHIC segmentation can be used to showcase local sports teams, activities and products that are locally made or grown and even favorite recipes. DEMOGRAPHIC segmentation is important to consider and can line up to behavioral segmentations in the case of stores close to retirement communities or stores that are in College Towns or close to campus. Promotions and Assortment should appeal to the local demographic especially if the store in general skews widely vs. chain average. PSYCHOGRAPHIC segmentation provides the why behind the buy because it helps understand the personality, lifestyle and attitudes that drive store and brand choice. This can be great to use for appealing for missions such as entertainment trips, sporting events, etc.
But as some of the other BrainTrust commentators, likely the best way going forward is a 1 on 1 personalized segmentation scheme that uses predictive analytics driven by AI using all of the above-mentioned data and more to deliver a better customer experience.
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Behavioral segmentation is useful and is certainly superior to more crude segmentations such as age or demographics. However, much depends on how the data are to be used. If the segmentation is to drive basic marketing, such as understanding who to aim promotions at, then this is valuable. If it is to be used to make more strategic decisions then it likely needs to be augmented with a more nuanced understanding of what drives behaviors – the emotions, thoughts and beliefs that sit behind them.
Great insights! Beyond just behaviors, incorporating psychological factors like emotions and beliefs can provide a deeper understanding, leading to more effective and precise marketing strategies.
Retail marketers have been conducting segmentation efforts, including behavioral, psychographic and demographic, to refine their targeting for decades. What’s different today is the myriad of sources of data at retailers’ disposal. Furthermore, retailers have much more knowledge and importantly the tools to analyze the inputs to help find signals that aid in targeting. And while some traditional life stage segmentations still apply (e.g. buying a home, having a child, etc.), ultimately the holy grail is to resonate with each shopper as an individual. Notwithstanding the good progress that has been made on this front, it’s this still a work in progress.
In 1970, with my new MBA, working at Hefty, my first assignment was to explore psychographics and present it to the brand team. Great thinking, but the problem in 1970 was we didn’t have the tools to measure the implementation.
So true, Mark! I remember trying to do segmentation using the limited data available back in the 1990’s when I launched a GIS platform at a Fortune 500 company. It was so difficult with stale data that didn’t go very deep. Amazing how much data we have at our disposal today, and to personalize the analysis down to the individual!
Behavioral data should always be leveraged to help brands understand the ways in which the consumer wants to shop with them. Any time a retailer is only utilizing one type of data to have a view on the customer, they’re missing out on nuance and complexity. Shoppers in our most recent survey told us they’re most comfortable sharing behavioral data with retailers, so this is a very welcomed resource in today’s environment where data privacy is a top concern, but lifestage does certainly matter as well.
Firstly, by eliminating the “traditional narrative” in consumer behavior. Consumer behavior is an ever-changing variable, and retail strategies must constantly evolve. Second, use lifestyle research instead of life stages.
Demography will show you who bought your product. Lifestyle or psychographic data will demonstrate who will buy your product in the future.
Customers can be targeted psychographically via online marketing and CTV, and more importantly, the feedback received from these media platforms provides effectiveness and efficiency data that allows for constant refining of nedia, promotional programs, and offers.
While there may be some correlation between behavior and demographics (perhaps age and income more than ethnicity), it’s ultimately behavior that rings the register — or not. Segmentation by behavior is critical to avoid the trap of “all things to all people,” and to help the smart retailer appeal deeply to its most engaged customers.
Lifestyle/lifestage consumer segmentation has long been a foundational discipline in the CPG retail world. When crossed with the CRM and lifetime value insights available from frequent shopper programs and ecommerce sites, the available data far outpaces most organizations’ executional abilities.
The challenge comes when thousands of finely-differentiated individual shoppers all visit a retail establishment that must find ways to cater to all of them. Retailers have little choice but to condense them into a few manageable groups, based on shared needs and behaviors, and then execute accordingly in their stores.
One might argue that this was the exact genius of the major department stores in their heyday – apparel offerings grouped by gender, age group, price level, wearing occasion and merchandised accordingly. Merchants did this by instinct, back in the day. Today we use data analytics.
The big watchout here for retailers is to avoid depending too much on convenient classifications that are insufficiently diagnostic. Age demographics for example – Boomers, GenX, Millennials, Zees, Alphas – may seem scientific but they can mask the variability within each cadre. Every few months another market research company offers its own segmentation scheme, based surely on carefully executed research, that urges marketers to divide shoppers based on their attitudes.
While all of this is thought-provoking, and much is useful, it is sobering to also remember why we put the “mass” in mass retailing in the first place. Sometimes many of us like the same things! Personalization at scale (the much vaunted 1-to-1 marketing) is a laudable goal, until the added intricacy undermines the retailer’s ability to bring genuine value.
Finding the right balance between appealing to a wide audience and offering personalized experiences is key. Retailers can use data to understand what different groups of customers want while still providing valuable shopping experiences for everyone.
Shoppers are individuals and as such break all the rules of segmentation confinement.\
Demographics do a terrible job. But if that’s all you have, it’s better than assuming sameness.
Behavioral segmentation is a step forward, but I see it as more comforting to the marketer than the shopper.
What I’ve seen work best is data driven, rules-based marketing.
Yes, you need some sense of what you want to do as X when the shopper does Y, which entails some level of classification. But the biggest issue with responding to rather than addressing as a group is marketer fear. Responding to action is unpredictable and hard to report. So marketers take it back a level, create segments they can analyze, classify and track. Orderly. Productive. But missing opportunities to be even closer to shoppers.
Segmentation and data analysis are table-stakes today. Today’s sophisticated AI-algorithms can pinpoint insights that marketers dreamed about years ago. The key for retailers is to chart a path, a strategic journey that will increasingly provide patterns that can be leveraged across the enterprise, in marketing, store operations, supply chain and customer experience. If retailers embrace multiple data sources and ample tools at their disposal, they will find diamonds in the rough.
More data equates to more opportunity for analysis, as long as the analysis provides valuable input for effective decision-making. Heavier data analysis is possible thanks to today’s more powerful, AI-based platforms. Today’s data allows marketers to significantly refine their focus and messaging, much closer to the hypothetical nirvana of a market of one. As with all uses of consumer data, it’s also important for retailers to have boundaries, or at least feedback loops, when consumers have had enough of a retailers targeted marketing.
In addition, recipients of increased data and analysis can include marketing as the article notes, as well as other retailer functions such as planning (assortment, demand), fulfillment (location), and store operations (CX). It’s important for retailers to consider their full enterprises and sharing of intelligence to ensure all applicable functions are operating from the same set of data and assumptions.
I invented a new segmentation that is based on the probability that a consumer will choose your brand given a category purchase is made. Those with a 20-80% probability of choosing your brand called Movable Middles (usually 10-20% of category buyers) have been shown from 11 experiments to be 2-23 TIMES more responsive to advertising. audiences rich in Movable Middles have been show to be 2-2 1/2 times more responsive than those defined by demos or heaviness of category buying (and 5 times better than choosing audiences for conquest who do not buy your brand. IDs are best flagged on prior 12 months of behavior so it truly is a behavioral segmentation.
Proper behavior segmentation leads to a multitude of silos to attack. The major, sophisticated online retailers can do this. A store-based retailer would have challenges dealing with 30 to 40 or more differnet segments in their retail presentation.
Behavioral segmentation, indeed, has large value to retailers. It is a lofty objective to implement and use this science, but the irony lies in that so many retailers are still doing so many – more basic – things poorly, that behavioral segmentation would appear to be too sophisticated and too soon (too much, too early) for those retailers that have not gotten the basics right. This elite cadre has discussed those culprits ad nauseam in this and other forums.
Effective segmentation is mission-critical for retail marketers today. The question of whether consumers no longer adhere to traditional life stages is interesting but irrelevant. Consumer behavior has always been based on an untold variety of factors. Retailers neglected behavioral segmentation in the past not because it wasn’t valuable but because they lacked the tools to extract and process the data at scale. With consumers who don’t follow predictable patterns, the key is 1) getting data-driven behavioral insights in real-time, 2) knowing how to respond, and 3) responding. And while we’ve made great strides, we’ve got miles to go.
Retailers can leverage behavioral segmentation by focusing on customers’ actual behaviors, preferences, and purchase patterns rather than traditional life stages. By targeting actions like buying frequency, product preferences, and loyalty levels, retailers can personalize marketing efforts, offering tailored recommendations and incentives that resonate with diverse consumer needs and lifestyles.
Behavioral segmentation helps retailers create targeted marketing strategies by analyzing customer actions and preferences, enabling personalized offers and recommendations that address the varied and changing needs of today’s diverse consumers.
Adopting behavioral segmentation enhances customer satisfaction and loyalty by enabling retailers to personalize marketing efforts based on real consumer behaviors and preferences, making interactions more relevant and engaging amidst evolving demographics.
Thanks to data and the capabilities of AI (helping us interpret data), we are now able to segment customers into personas on a much higher and more sophisticated level. We’ve gone beyond creating personas based on what a customer buys. Now, we look at habits, frequency, browsing history, and more. Our customers are getting better personalized experiences than ever. This endears the customer to the retailer because of what I like to call the Cheers Principle… Customers want to go where “everybody knows their name” – and more!
BEHAVIORAL segmentation is typically the best singular segmentation scheme to understand past spending actions and to make better informed approaches to communication, assortment and promotional efforts. However, with the wealth of information available to retailers, the other segmentations should not be ignored.
Consider a grocery setting, GEOGRAPHIC segmentation can be used to showcase local sports teams, activities and products that are locally made or grown and even favorite recipes. DEMOGRAPHIC segmentation is important to consider and can line up to behavioral segmentations in the case of stores close to retirement communities or stores that are in College Towns or close to campus. Promotions and Assortment should appeal to the local demographic especially if the store in general skews widely vs. chain average. PSYCHOGRAPHIC segmentation provides the why behind the buy because it helps understand the personality, lifestyle and attitudes that drive store and brand choice. This can be great to use for appealing for missions such as entertainment trips, sporting events, etc.
But as some of the other BrainTrust commentators, likely the best way going forward is a 1 on 1 personalized segmentation scheme that uses predictive analytics driven by AI using all of the above-mentioned data and more to deliver a better customer experience.