AI and CX: Are Customer Segments Still Necessary?
In our debut article for this Substack on How to Person(ai)fy Consumer Brands, we critiqued marketers’ propensity to cling to a one-size-fits-all Unique Selling Proposition (USP), despite the promise of more personalized customer experiences that can adapt the brand’s value proposition to different consumer profiles. We shared how AI is finally killing the USP, accelerating the shift to real-time experimentation with tools that are available today. We provided examples of brands that are capturing cost savings of more than 10 percent, even as they invest in AI-powered capabilities that are boosting marketing ROI by up to 50 percent.
But old habits like the USP die hard - which seems a perfect segue to a related question provoked by the widespread application of AI across the customer journey: Is the way we think about segmentation outdated, too?
AI compresses what used to take months - to develop insights, plan campaigns, develop creative content, and measure the campaign’s ROI - into just weeks, enabling agile, low-risk experimentation. AI makes it easier to design and run experiments across a far larger number of micro-segments, thin-slicing audiences in ways that approximate 1:1 personalization. Moreover, the optimal targeting of these micro-segments can be adapted on a continuous basis with far less effort and operational complexity than was possible even a few years ago.
If all this is now possible (and it is), why even bother with segments at all? If continuous experimentation is now possible at the press of a few buttons - if AI can democratize insights and power a completely bottom-up and flexible approach - aren’t segments themselves jejune, a kind of “USP-lite?”
No. You can keep calm: Segments are not going away.
It’s true that AI can fuel bottom-up planning that allows multiple micro-segments to emerge and evolve from continuous analysis of myriad datasets. But it’s equally true that customer segmentation retains value as a way of aligning different teams within the organization to design more emotionally engaging experiences.
In other words, just because one size doesn’t fit all, it doesn’t mean that marketing becomes a free-for-all. A both-and approach is required that fuses emotional connection with analytical and organizational rigor.
Segments Are Solutions
Let’s consider the case of a retailer with which we worked that we’ll call Treasure Trail. The retailer enjoys repeat traffic from bargain hunters - which for many years had been Treasure Trail’s umbrella customer segment.
The problem was, that singular focus was too narrow to encompass the emotional nuances that drew its wide range of customers to the brand. Treasure Trail was literally leaving money on the trail.
We helped the leadership team identify and align on a focused set of five customer personas, prioritizing an inner core of three personas that visit stores more frequently, and also two additional personas of more occasional shoppers that further contribute to the company’s revenue. Building deeper insights into these personas’ motivations and the emotions they feel along their shopping journey helped to drive improvements in the retailer’s advertising, website, social media presence, in-store marketing, and employee training.
But Treasure Trail didn’t stop there. Investments in first party data and the mar-tech stack allowed it to experiment continuously to win the trip, grow the basket, and deepen loyalty. The retailer began to optimize content for a broader set of micro-segments that ladder up to its personas. Along its learning journey, it doubled its return on ad spend (ROAS), grew shopping trips among target personas, and boosted customer lifetime value. Replacing its unitary customer concept with five customer personas provided a digestible framework that helped Treasure Trail profitably customize its marketing for multiple segments.
In the pre-AI era, the juice wasn’t worth the squeeze. Analytic power and human resources were too limited, scenario development too tentative, and the guesswork too risky for most companies. Now, AI enables continuous experimentation to optimize the right content for the right audience at the right time to evoke the right emotions along the customer journey. It allows companies to combine greater content variety with more precise targeting, creating a continuous feedback loop to optimize customer lifetime value.
In a world of seeming marketing abundance, strategic segments that are developed into richer personas still matter because they allow you to contribute better stories that realize your customers’ goals and motivations, and elevate how customers feel at peaks along the their journey with your brand, proactively designing love points that are more meaningful and memorable.
Many-Splendered Brand Love
We’re using the word “love” deliberately. Evoking emotions has always been a core focus for marketing. Even during the USP’s heyday, when brands relentlessly reinforced their claimed value through endless repetition, they aimed to reinforce an emotional connection with their customers.
But brands applied emotion only sparingly. Partly, this reflected the 20th Century propensity in brand marketing to focus on functional differentiation over customer experience, even as product and service commoditization advanced across categories, and partly it reflected marketers’ suspicion that emotions themselves were commodities. There are, they believed, only a limited number of emotions, only so many forms of happiness, or care, or family delight. Whatever the reasons, brands tended to bring emotion into their marketing mix only as part of their annual advertising campaign development process. They did not see emotion as something they could reinforce continuously across their customers’ journeys.
Yet how customers feel about themselves at peaks along their journey with a brand is what makes experiences - and thus the brand - memorable. Meaning, sharing, and community are what create brand love and loyalty. The more precise micro-segmentation that is now possible through AI-powered learning loops also allows marketers to experiment with iterative changes to content-based experiences to orchestrate the customer journey and drive measurable impact on desired customer emotions, which is the key to driving business outcomes.
(For more on how measurement of brand and CX go together, see Matt’s podcast with Ken Favaro, Chief Strategy Officer at Bera.ai, here.)
Aligning the Organization
Equally important, segments are not just about the external market. They are central to coordinating the many teams inside the enterprise that contribute to customers’ experiences with the brand.
Aligning on a focused set of personas is critical to guide strategic decisions about whom to target for experience design, whether for product launches, websites, mobile apps, loyalty programs, marketing campaigns, or other experiences designed to better engage customers at moments that matter. Marketers must make choices about who their primary vs. secondary design targets are - and, just as importantly, who are not the focus of their experience design efforts. Without such choice-making, brands won’t be able to answer (or adjust over time) the two core questions any lean startup must get right: Who is our target customer? And what is the right value proposition?
These questions are relevant even for larger, established brands. While micro-segments allow for thin-slicing marketing and marketing-adjacent activities to ever smaller audiences, it is not a practical way to drive strategic alignment for key design decisions, or to engage employees across the organization. An endless buffet does not necessarily make for a good meal. Indeed, it may just make diners bloated and sluggish.
Once you have alignment on the right personas to focus on and emotions to evoke, AI-powered insights can then be used to tap into differences across micro-segments to further optimize customer engagement through more tailored content experiences. AI solutions native to platforms like Salesforce and Optimove can be useful tools for this kind of journey orchestration.(For more on how CDP and journey orchestration platforms are evolving, see Matt’s podcast with Marty Kihn, head of strategy for marketing cloud at Salesforce here, as well as Matt’s podcast with Rony Vexelman, VP of Marketing at Optimove, here).
Marketers need to sustain focus on the core set of emotions their selected personas feel when engaging with their brand to guide their experience design efforts, even as they embrace agile experimentation to optimize targeting and creative variety for micro-segments.
Anchoring on a clearly defined set of personas makes it more productive for humans in the loop to interact with the AI. Without a clear definition of the personas upfront, it is harder to prompt the AI to recommend improvements to content-based experiences. A clearly defined set of personas focuses a team’s efforts and makes it easier to collaborate on design decisions.
Segments Foster Experimentation
AI tools also can mine data signals, including both structured data that goes beyond demographics to include customers’ digital footprints along their journeys, as well as unstructured data signals captured from customers’ conversations with your employees, with chatbots, and with each other.
Once a marketer has mapped customers to personas, it can use AI tools to define a larger number of micro-segments with which to experiment, representing variations of existing personas to further test the impact of introducing greater creative variety into content-based experiences. For old school direct-marketers, this should come as second nature: It’s the contemporary version of pitting test packages against the control.
As brand marketing teams develop ways to incorporate AI into an agile test-and-learn approach, they also can use AI tools like Wevo.ai to optimize content through the eyes of their personas (see Matt’s podcast with Nitzan Shaer, CEO of Wevo.ai, here).
Building deeper insights into the emotions that personas feel at peaks in the customer journey is valuable not only to reinforce the connection between CX and your brand. It also strengthens the connection between your consumers’ experience with you and your culture. Frontline employees, for example, are central to evoking customer emotions along the path to purchase and enabling a more personalized CX. By prioritizing the relationship between customers’ emotions and specific cultural behaviors in the enterprise, brands can create a virtuous cycle for employee habit-building.
You can also evolve your approach to customer listening using platforms like Qualtrics to create a feedback loop to further optimize your training, learning, and development efforts. This allows companies to move beyond chasing survey-based metrics like Net Promoter scores, to creating a continuous learning loop for behavior adoption.
AI is enabling rapid improvements in quality assurance for call centers to mine all calls rather than rely on listening to a random sample of calls and getting a small fraction of customers to complete post-call surveys. The opportunity goes well beyond call centers, leveraging AI to mine customer interactions with frontline employees across sales, customer success, and other employees who engage with customers on-premise across industries from hospitality to retail to healthcare to financial services.
Companies can leverage AI to power substantial improvements in both digital and human-to-human experiences. Realizing these opportunities requires a balanced approach to turn your personas into actionable micro-segments while reinforcing a culture of collaboration and continuous improvement. AI enables agile experimentation for your digital experiences. It also enables a continuous feedback loop for human-to-human experiences. As in many things, a best of both approach is often better.
Apply to join our mastermind group on “Experience as a Winning Strategy”
Interested in diving deeper with others on experience in marketing, sales, product development, and customer success? Join the mastermind group hosted by Matt and Randall that meets monthly. In addition to monthly, virtual meetings, members in the mastermind group receive 1:1 coaching, participation in workshops, and curated event experiences. Go to JourneySpark’s website to learn more and apply:
https://www.journeysparkconsulting.com/mastermind
Matthew Egol is the founder & CEO of JourneySpark Consulting, Podcast Host and author of The CX and Culture Connection: Creating a Growth Flywheel by Approaching Customer Experience and Culture Together. Previously, he was a partner in the Retail & Consumer practice at the consulting firms Booz & Company and PwC, where he specialized in customer experience, culture, and digital transformation.
Randall Rothenberg served for 15 years as the CEO of the IAB, the global trade association for digital marketing, media, and advertising, where he led the industry in public policy, technical standards, marketing, and thought leadership. Earlier in his career, he was the CMO and head of thought leadership at Booz & Company, a reporter and editor at The New York Times, and the author of Where the Suckers Moon: The Life and Death of an Advertising Campaign (Alfred A. Knopf, 1994).