👀 In this ecommerce podcast, we’re talking about building brand authority in AI search.

A few months ago James Gurd went to a Thrive event run by NOVOS, where Katie Mishner (SEO Team Director) and Jess Higgins (Digital PR Team Director) gave a practical talk on earning authority. We wanted to explore the topic in more depth, so we invited Katie and Daniel Cartland (Delivery Director) to join us on Inside Commerce.

Three reasons to listen:

1️⃣ It’s practical; there are ideas you can test straight away, such as running a simple query fan out prompt if you’re short on time and budget.

2️⃣ It questions the “good for everyone” product description. Dan explains why being clear about who a product is (and isn’t) for helps you match the longer, more detailed queries people now type into LLMs.

3️⃣ It gives a useful view of where citations come from. Katie shares an example from a travel client where the most cited source wasn’t Time Out, but an individual’s train blog.

Key discussion points;

- What authority means for an ecommerce brand, and where E-E-A-T fits in. It’s a rating framework, not a ranking factor.

- Why links carry less weight on their own, and why sentiment (how you’re mentioned) matters more.

- The pillars NOVOS use to measure authority: where you show up, relevance, where links point, cadence and longevity, and sentiment.

- Why product pages are a sensible starting point for AI search, without writing off category pages.

- How to reverse engineer what customers are looking for, starting with personas and then using query fan out and social listening.

Dan makes a key point about the risk of waiting:

“It almost turns SEO from a performance channel into a brand channel.”

He expects adoption to be gradual, so there won’t be an obvious moment to act. Brands that don’t start thinking about it early risk being left behind.

We also discuss why smaller, leaner brands may have an advantage here. There are also plenty of examples from Nike, Adidas, Nobody’s Child and Fourth Glade.

If you run or advise an ecommerce site, we think you’ll find it worth a listen.

Chapters:

• [00:30] - Introduction to the topic and guest backgrounds
• [03:50] - What authority means for ecommerce brands
• [05:55] - E-E-A-T explained: a rating framework, not a ranking facto
• [08:10] - How AI search changes authority: mentions and sentimen
• [13:30] - The pillars for measuring authorit
• [18:55] - Product-led digital PR for specific, long-tail querie
• [23:00] - Reverse engineering where to show up: niche citation
• [25:30] - From PLPs to PDPs: building useful conten
• [30:40] - Five reverse engineering method
• [39:45] - Why reviews and relevance matter for credibilit
• [41:30] - The risk of waiting on AI searc
• [45:20] - Why smaller brands can move faste
• [46:35] - Finding your niche: Nobody's Child and Fourth Glade

How The Sports Edit competes as a multi-brand retailer: SEO, content strategy & experimentation.

In this episode, James chats with Sarah Davis, ecommerce manager at The Sports Edit, a multi-brand sportswear retailer.

They’re in an interesting position. In search, they’re up against their own parent company Marks & Spencer (which they can never beat for domain authority), the D2C sites of the brands they sell and third party marketplaces. And they run experimentation without a dedicated CRO team.

Here are three reasons why you should listen:

Competing in search against bigger domains.

Sarah explains how they focus on where they’re different: exclusive brands, stronger ranges such as running, and specialist comparison content. That thinking also shapes how they’re approaching GEO and visibility in LLMs.

How to run experimentation without a big team or budget.

A small team scaled up testing after changing their tech stack. Sarah makes the point that testing matters more, not less, when dev budget is tight. She also explains where test ideas come from and how they’re prioritised.

Being honest about tech choices.

Why they moved from Optimizely (which they used via M&S) to Visually, plus the AI-native PIM and AI tools they’re watching. She’s open about what’s still unsolved, like keeping content up to date.

Key discussion points:

The multi-brand role. Be the expert source and the one-stop shop for advice and a curated range. Stay on top of price. Make post-purchase service seamless.

The content problem. Shoe models update every year, so comparison content needs regular upkeep. Sarah’s candid that they’re good at launch content but haven’t cracked maintenance yet. AI is one area they’re exploring to help.

Organic strategy. Working with SEO agency Novos, they focus on unique brands, range strengths like running, and product and brand comparisons. Sarah’s team also runs sport strategy across M&S.

How the two sites split. The Sports Edit is the performance channel (top-end running shoes and high-performance apparel), while M&S is more commercial. Higher-priced products need richer content, so video, FAQs and page layout all matter more.

Personas and content. An expert advice blog pillar, long-tail comparison content (Nike vs. Puma, for example), and FAQs, which started on PLPs with PDPs next. Running is the first focus area.

First-party data. Sarah sees this as largely untapped. They capture preferences at newsletter signup, and surveyed customers before relaunching the loyalty programme earlier this year.

How experimentation works. It sits with Sarah and covers merchandising blends, recommendations and A/B tests. Ideas are proven in the testing tool first, then handed to dev to build properly.

Why Visually rather than Optimizely. It’s Shopify native, tests can be built in minutes using its AI generator, and the Contentsquare integration makes deeper analysis easier.

Where test ideas come from. GA and Contentsquare data, other retailers, D2C sites, Visually’s inspiration library and insight shared with M&S. The PDP gets most attention because that’s where PMax, Google Shopping and paid social traffic lands, and it’s increasingly important for LLMs.

Tech on the radar. Emfas, an AI-native PIM they’ve used for just over a year to scale content and work more efficiently, and Alhena, an AI tool they’ve seen in demos, for AI-generated FAQs and virtual try-on.

Chapters:(2:05) Sarah's background and The Sports Edit(3:30) The multi-brand role versus D2C brand sites(7:20) Keeping expert content current as products change(10:00) Performance versus commercial channel positioning(17:20) Personas, comparison content and FAQs for LLM-era discovery(22:00) First-party data and loyalty programme insight(27:10) Experimentation without a dedicated CRO team(33:20) How test ideas are sourced and prioritised(37:40) Learning from failed tests and the next stage of segmentation(41:45) Tech that impressed: AI-native PIM and Alhena

Agents Without the Hype: Where AI Fits in Your Ecommerce Team
with Henrik Hoffman, Co-founder & CMO, DEMA

“AI agents help brands plan and execute faster. Represent uses returns data to understand a product drop’s profitability in days—not weeks.”

You keep hearing that you need to “use AI agents.” What you rarely hear is where they go in your team, which work they should take on, and how they make your people better at their jobs instead of just busier. Henrik joins Paul and James to answer those questions, using real retailer examples.

Tl;dr: three reasons to listen:

1. See where agents fit in your team, and where your people still matter. You’ll get a practical picture of how ecommerce teams are being restructured. Some work moves to automations, workflows and agents. Other work still needs human judgement, and that’s where your team’s time and talent should go.
2. Get a rollout model you can actually copy. Hear how brands spread agents across the business by appointing an internal go-to expert who trains everyone else. You’ll also hear how they get buy-in for a change that is as much a shift in mindset as a line in the budget.
3. Hear how agents work in day-to-day operations. For example, Represent has embedded agents into its returns process and other teams have built DEMA into their weekly planning. Learn how they keep humans in charge and set a regular rhythm, so agents support the team’s priorities instead of working against them.

Also in this episode:

• Why the edge has moved from how you do things to how fast you get to an answer and act on it
• How to avoid choice paralysis and AI slop when you can suddenly do almost anything
• How this shift is changing DEMA’s product roadmap

Chapters:

[00:30] Why faster e-commerce decisions are becoming the edge

[03:15] Turning reporting into action, not just slides

[07:05] Avoiding AI slop and organisational rabbit holes

[09:05] Agents as colleagues and the risk of misalignment

[12:45] Bubble Room using separate agents for brand and performance

[19:40] Applying AI to current processes first

[23:25] Why teams want out of manual, repetitive work

[26:10] Starting with small wins and saving 15 minutes a day

[30:30] Competitor monitoring for peak trading periods

[31:35] Represent and real-time returns modelling

[35:20] Using historical data to validate models and assumptions

[37:20] Black Friday planning lessons from Baby Shop Group

[40:30] DEMA’s roadmap: measurement, agents, and business alignment

[46:30] Using agents to model impact before changing targets