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

What happens when a dietitian and a lawyer start a swimwear brand?

Ryan talks with Lyndi and Les Cohen, the husband-and-wife team behind Fearless Swimwear. Lyndi, known as The Nude Nutritionist, spent 15 years helping women with body image before deciding the swimsuit was a body image problem to solve.

They built in public, let their audience pick the brand name, cuts and colours, and launched to a 15,000-strong waitlist.

The pre-order sold out in 24 hours for $200K.

They also share the $100K sizing mistake that followed, the "magic sizing" that came out of their waitlist data, why they're stepping away from deep Black Friday discounts, and what Lyndi calls the "embarrassment tax" of building on social.

About The Host:

Ryan Martin is Founder of Remarkable Digital, a specialist eCommerce SEO marketing agency working with Australian Brands.

In this episode

• Packing orders at Thread Together, and a humbling start to the chat
• Why a dietitian who specialised in body image decided to start a swimwear brand
• Building an audience by "listening to the data": body image content beat healthy breakfast content
• Co-creation: letting the community choose the name, cuts, fabrics and colours, and why 100 poll votes is often enough
• A 15,000-woman waitlist, a $200K pre-order that sold out in 24 hours, and going straight to a 3PL
• Trademarks: buying the "Fearless" name for $3K, and the risk of trademark squatting in China
• Sourcing in China: 36 hours at Intertextile Shanghai, and why you need a swimwear specialist, not a generalist
• The $50K tech pack lesson, and hiring a head of product with nearly 30 years in swimwear (including the 2000 Olympics swimsuits)
• The $100K mistake: gifting all their stock to Thread Together when the sizing came up small
• Magic sizing: 49% of their waitlist wore a different size top and bottom, so they built one-pieces with mixed sizing
• Long torso styles, and designing for a size 12 to 16 instead of scaling up from a size small
• Using Refundid checkout insurance to let customers try at home
• Custom fabrics vs cash flow: simplifying to shorten lead times and the cash conversion cycle
• Stock planning with no historical data, air freight, and a seven-month lead time on a sold-out style
• Black Friday: last year's tiered 10–60% discounts, and why this year they're focusing on newness and gift with purchase instead
• Swimwear's short selling window (September to December), and why March makes more sense for a sale
• Being "ridiculously honest" with customers about strategy changes
• The embarrassment tax: why your fails outperform your highlight reel on social
• Shooting product on real customers with a $4,000 camera instead of professional models
• Staying close to customer feedback as the team grows
• Mentors and inspiration: Shelley Sullivan (MCoBeauty) and Emma Grede
• Long-form content, brand voice, and being the "chief reminding officer"
• What's next: a ready-to-wear capsule, the US market, and becoming the most recommended swimsuit brand

What if your customers were your cheapest media channel? Ryan Martin talks with Mike Haywood, Co-founder of BrandPay, about "customer media". BrandPay rewards everyday customers, not influencers, with store credit when they post about brands they already love.

Mike explains how a $1-per-like experiment at his AirBnB retreat grew into a world-first build with Meta.

He also covers why AI search runs almost entirely on third-party content, and how brands like LSKD now get a new piece of customer content every 33 minutes. On average, the cost per click comes in at about half that of paid media.

Mike explains how the idea started. During COVID he ran a hinterland retreat and paid guests $1 per like in wine-cellar credit for posting content. Six months later it was named best holiday home in Australia and featured in Vogue.

He also talks about building a world-first integration with Meta, and the psychology that makes customers post (time and effort, not likes). He shares hard numbers on cost per click, spend-back rates and category performance.

• Why BrandPay separates customer media from UGC and creator content
• How a $1-per-like guest experiment led to a Vogue feature and a new startup
• Building with Meta: a world-first API use case and the challenge of fraud prevention
• Why fixed rewards beat per-like rewards: everyday users think in time and effort, not engagement
• How the BrandPay wallet works: store credit in Apple Wallet, worth half its value at other brands, with the other half returned to the rewarding brand
• #ad disclosure, and why customer content doesn't feel like selling
• AI search and third-party content: Google lowered its follower threshold for showing third-party content in search from 300k to 35k to 10k
• The review flow: 48-hour auto-approval for reels (24 hours for stories), and 98% approval rates
• Pricing: a 25% fee on top of rewards, with no SaaS or setup fees
• Attribution: first-degree clicks at about 50% of paid media cost per click, plus the "BrandPay halo effect" measured via Triple Whale
• Why brands with real community (Facebook groups, Klaviyo lists) win first
• 85% of rewards are spent back with the brand, on average within about 5 days
• Which categories perform best: fashion, beauty, skincare, nutrition, pet food, sunnies and furniture
• First-mover advantage and the "infinite half-life" of third-party content
• Product launches: building customer media groups by postcode
• Beyond e-commerce: distributor brands, service businesses, and TikTok coming soon