Using Product Discovery to Create a Better Shopping Experience and Drive Growth with Next’s Jay O’Neill (episode 613)
Jay O’Neill was Product Manager of Product Discovery at Next, one of the UK’s most successful high street retailers focused on fashion and homewares. Jay specialises in growth through digital marketing, CRO, and tech stack optimisation. He scaled soak.com from £2 to £80million, drove digital growth at Holland & Barrett, and took Bathroom Mountain from £0 to £40million in 18 months.
In this episode, returning guest Jay shares what he learned from leading Product Discovery at Next, from getting the foundations of product data right to using AI and search insights to uncover new growth opportunities. He also explains how eCommerce teams can make product discovery work harder across SEO, PPC, onsite search and the wider customer journey.
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Dive in:
[03:09] AI in product discovery
[06:16] Dealing with data silos
[10:34] Using AI to analyze search data
[14:42] Improving search and utilizing chatbots
[16:27] Choosing the right chatbot provider
[19:26] Leveraging domain authority for SEO
[23:33] Listen to Jay’s Top Tips!
Treat Product Discovery as a Business-Wide Growth Opportunity
Product discovery is no longer just about onsite search. Jay explains how Next broadened its approach to include recommendations, chatbots, SEO, PPC and other customer touchpoints. The key is to make sure these channels are working from the same product data and insights. This can reduce duplicated work and create a more consistent customer experience. It can also help your product data drive growth across more parts of the business.
Fix Your Product Data Before Investing in More Technology
Better technology cannot compensate for poor product data. Jay has seen retailers struggle with search because their data was incomplete or inconsistent, even when they had sophisticated search tools. At Next, improving product data helped reduce the need for thousands of manual search rules. The lesson is simple: garbage in means garbage out. Before adding another AI tool or chatbot, make sure your product information gives that technology something useful to work with.
Focus on the Product Attributes That Customers Actually Use
You do not need to perfect every possible product attribute at once. Jay recommends identifying the roughly 20% that matter most to customers and getting those right. Search terms, filters and onsite behaviour can show you which attributes shoppers care about. AI can then help analyse large volumes of search data and uncover patterns that would take a human team much longer to find. This gives eCommerce teams a practical way to focus their effort where it can have the biggest impact.
Use Your Product Data to Capture Emerging Demand
Good product data can do much more than improve onsite search. Jay explains how retailers can use product attributes and trends to create new category pages, target long-tail searches and build timely campaigns. The real opportunity comes from moving quickly when a trend starts to appear. If your data shows that a particular colour, style or product attribute is gaining interest, you can build content and campaigns around it before competitors catch up. AI can also help teams spot these trends much faster by analysing large datasets.
Keep Testing, Cleaning and Shopping Your Own Site
Product discovery is not something you set up once and forget. Jay recommends regularly reviewing old search rules because outdated rules can create problems as technology and customer behaviour change. He also stresses the value of simply shopping your own website like a customer and checking what competitors are doing. This hands-on approach can reveal problems that reports may miss, from poor search results to gaps in product information. Make that kind of review part of your regular workflow, and you will spot more opportunities to improve the customer journey and drive growth.
eCommerce Book Top Tip
- The E-Myth Revisited by Michael E. Gerber
eCommerce Traffic Top Tip
- If you’re a founder-led business, build your personal brand on LinkedIn and other social platforms to increase visibility and trust.
Tool Top Tip
- Connect Claude or ChatGPT to your business tools and workflows to automate tasks and bring useful insights together.
Carbon Top Tip
- Track damages and returns regularly to find ways to reduce waste, improve efficiency, and lower your carbon footprint.
Interview links
- Jay on LinkedIn
- Listen to Jay’s first episode on the show where he talks about Building a High-Growth, High-Profit eCommerce Business
Related Episodes
- Michael E Gerber, author of Beyond the eMyth and small business guru talks eCommerce with Chloë (episode 89)
- Top Tips for eCommerce Growth in 2025 (episode 526)
- 5 Big Wins You Get with an AI Shopping Assistant (episode 599)
Without the sponsors the podcast wouldn’t be possible – please do check them out:
When an AI recommends a product to your customer, is it recommending yours? Rithum surveyed over a thousand US and UK shoppers on how they use AI to find, compare, and choose.
One in five shoppers had bought from a brand they’d never heard of because AI recommended it — and only five percent verify what AI tells them by visiting the brand’s own site.
AI is answering these questions already. The data you publish decides what it says.
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