A Chat with James Taylor, Founder and CEO at Personalisation Company: Particular Audience

Meet the company bringing Amazon-style hyper-personalisation to every other retailer.

Tell us about Particular Audience

Particular Audience is an AI-native retail media and personalisation company. The platform (DiscoveryOS) tackles the ‘endless aisle’ challenge by creating a unique storefront for every shopper – matching each visitor with the products they’re most likely to buy, at the moment they’re most likely to buy them.

How did you come up with the idea for the company?

I was running Asia-Pacific for a Google-backed personalisation startup, which recently sold to Publicis Group, and it was there that it occurred to me that legacy approaches to personalisation were super-manual and failed to drive improvements to the customer experiences.

As I started researching how Amazon succeeded in creating a different website for every customer, given their 300 million users and 300 million items, something clicked. Machine learning recommendation systems were foundational in enabling everything we now take for granted on the internet, from Facebook and Amazon to Netflix and Spotify, yet the majority of retailers were massively behind the curve, some still are.

We launched with what has now become the market-leading personalisation platform, powered by AI and machine learning. A year into operations, we noticed ‘Sponsored’ labels appearing across product listings on Amazon, and we were inspired. The amount of margin in selling a click is 4-10x the margin in shipping physical products, so we got to work in enabling this adtech functionality within our retail software-as-a-service.

Tell us about your core product or service

Retail Media is the topic du jour in most retail boardrooms today. The problem facing the market, however, is that nearly all software solutions in the market are strictly and simply advertising technology.

Retail media is about retail which provides real-time context of high intent consumers in transactable environments. This is immensely valuable to brands, and it is in stark contrast to ads on a news website, for example.

Most retailers face what we call a ‘multi-objective problem’ set. They may have suppliers wanting to fund promotional activity, yes, but they also have overstocks, private label items to push, spoiling and slow-moving inventory to shift, buyer-led trade agreements to honour, and visual merchandising imperatives to consider.

99% of retailers today face fragmentation both in their org chart, and especially in their technology vendors – one for search, one for personalisation, one for merchandising, one for pricing, one for retail media, etc.

Particular Audience brings this all under one decision engine, where different teams can collaborate within one unified customer experience technology. It might seem obvious, but retail is only now waking up to this. Our vertical integration of retail media with our own advanced AI-powered search and recommendation capabilities is what drastically improves ad performance vs siloed platforms. It is unique and it is immensely powerful for maturing retail media networks that face tradeoffs in ad density.

What most excites you about the retail media industry?

We are still so early in its development. Only a tiny minority of retailers, albeit some of the largest, have launched retail media networks so far, and massive agency budgets are only just opening up to retail media.

Retail media teams, often with advertising backgrounds, are quickly learning about the nuances of retail and are on the same journey that e-commerce and conversion rate optimisation teams have been on for the last decade or so. This knowledge curve is unlocking tremendous value once legacy technology is replaced.

What has been the biggest challenge you’ve had to overcome along the way?

I think it’s really hard to run a startup without spending 110% of your waking hours thinking and acting on the problem space you have chosen to build for, and to approach it all with first-principles thinking.

Everyone has an opinion, often informed by anecdotal experience in adjacent and therefore distinct situations. Talk is cheap. I would say my biggest challenge has been maintaining laser-focused conviction throughout the marathon. There are always bumps in the road, and you get pulled in all sorts of directions by the market, cheap advice and shiny-object syndrome.

What is your number-one piece of advice to aspiring entrepreneurs?

Resilience is what separates winners and losers. Market-leading enterprise software platforms aren’t built overnight; no startup is born enterprise-ready. Success is a product of years of client feedback and feature requests to refine a defensible compound value proposition. The trick is staying alive. Be conservative with money but take measured risks. Learn to price risk.

What can we hope to see from Particular Audience in the future?

AI-as-a-channel is an exciting opportunity we are working with a select few retailers on using what I think is the most exciting technology in the market right now: Model Context Protocol. A big question is, what happens to sponsored listings in retail media when consumers use AI assistants to shop on their behalf? Our answer is that retail media needs to be further integrated with organic discovery on websites to succeed here, and Particular Audience is uniquely positioned to make it happen for retailers.