Most brands think they know who their best customers are. Then they put their online and in-store data together and get a surprise.
Ryan Martin talks with Aaron Luxmoore, Head of Sales and Partnerships at Lexer, about how the platform has grown from a customer data platform (CDP) into an AI customer intelligence layer. Aaron explains why putting ChatGPT or Claude on top of fragmented data just gives you wrong answers faster, and why the same customer can show up as three different people.
He also covers why you shouldn't send every customer the same Black Friday discount, the quickest way to turn one-time buyers into repeat customers, and why Lexer doesn't charge per seat. Plus, how a LinkedIn post turned into Friends in Tech, a networking event with an 850-person list.
In this episode
Friends in Tech: how one LinkedIn post became an 850-person event list across the east coast, with no sponsors, no pitches and no clients invited
Lexer's evolution from CDP to an AI customer intelligence layer
The discover, decide, act, observe and learn loop, and why the platform is now used by CEOs, merchandisers and store teams, not just marketing
Bringing inventory, margins, store rosters and business context (like store closures) into the data
What usually brings a brand to Lexer: "we don't really know our customers", a loyalty program launch, or too many hours lost to spreadsheets
Omnichannel reality check: the customer who spent $2K online and $5K in store, and the "one-time buyers" who've actually bought again in store
Adding third-party data from Experian (likely income, home ownership, parent status)
Wrong answers, fast: the problem with putting AI over fragmented data, and the risk of tying everything to one LLM
How one customer with multiple email addresses can look like three different customers
Black Friday: why full-price buyers shouldn't get the same discount as everyone else
Lexi as "the brains behind Klaviyo": insight, then strategy, then the segment (around 75% of Lexer clients use Klaviyo)
Common objections, and why all-in-one platforms tend to be "jack of all trades, master of none"
Build vs buy: why building your own customer data layer usually takes two years and more people than expected
Implementation down from about six months to 6–12 weeks
Why Lexer doesn't charge per seat, and pricing based on the number of customer profiles
ROI examples: paying for a year's subscription just by turning one-time buyers into repeat buyers, and feeding top-5% audiences into Meta
Who buys: head of digital, CMO and CRM manager, and the champions who bring Lexer with them when they change jobs
Multi-brand groups: cross-selling across Cotton On, Cotton On Body and Typo
Who it's for: medium to large omnichannel retailers, increasingly smaller and e-commerce-only brands, plus hospitality clients
How to get a free demo using your own Shopify and email data
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