We talke to James Taylor of Particular Audience on how merchandising and product list personalization supports the needs of your retail business and this is what he had to say.
First of all, how are you and your family doing in these COVID-19 times?
James Taylor: Thanks for asking Edyta. We’re fortunate here in Sydney. Australia has done well to manage the situation, and life feels relative back to normal. Most of my family is based in London. However, lockdown seems to be a little more persistent for them! I hope you and yours are keeping well too.
Tell us about you, your career, how you founded a Particular Audience.
James Taylor: Originally an investment banker, I moved full time into technology with my first startup back in 2013. I’m now an ex-pat based in Sydney, Australia, having moved here six years ago to launch the Asia Pacific business for London-based Yieldify. In 2017 I decided to set up Particular Audience to build a business centered around AI and machine learning technology opportunities. We provide eCommerce businesses with a no-code AI-powered personalization layer that sits on top of their transactional eCommerce platform. The business took off, and we expanded to Europe with a London office in 2019. A deal closed at the end of November brings our total seed funding to $4.7m, allowing us to double headcount to 40 people and open a Vancouver office to target the North American market, of which I’m incredibly excited. The team we’ve hired there is fantastic.
How does Particular Audience innovate?
James Taylor: We believe that useful innovation comes from a flywheel approach to product development. By that I mean, mutual reinforcement between products offers economies of scale and can also act as a growth multiplier. Early on, we did well at building a core platform with www.particularaudience.com – a product graph of consumer products, and perhaps more importantly, the relationships between those products. It was already solving enormous problems for online retailers, which meant we got to monetize early in our journey. To take this a step further, the technology we had built had huge ramifications in the broader internet, resulting in the launch of our consumer product www.similarinc.com – which is effectively a personal recommendation system at the scale of the entire internet. Add it to Chrome, and it will save you money – I promise.
Sustainable innovation in the data field (and we do believe that software is ultimately commoditized, so data IP is central to success) has led us down a path where everything we do at PA is without the need for personally identifiable information. It doesn’t matter who you are to personalize something for you, which is both necessary and unique in an age of GDPR. It seems like an oxymoron, but this is a vast misconception about effective personalization. It is quite logical. Any given website, even a mega platform that you use every day, still has but a fraction of a percent of your data. Consumers are not commoditized like consumable items, consumer intent is continuously changing, and more shoppers are than items. In this light, how robust does customer-orientated data sound? It’s a rabbit hole. On the flipside, items are commoditized, and we can find 100% of the item interaction data and item metadata online.
There is very little about your attributes that predict what you are likely to want next. Ozzy Osbourne and Prince Charles are both Princes in the same demographic – this is not useful information. The items you’ve engaged with most recently, and in sequence, are a much better indicator of intent. Think about how Spotify Discover works to play you new music that you love, appropriate to the mood. Similarly, all intent prediction and calculation of preferences depend simply on the clicktale exhibited by a hashed and anonymous ID, tied to contextual signals. Longer-term, in say five years, we hope that it will seem archaic to go to a search engine bar, type in a search query, and then filter through multiple tabs to find what you want. Suppose Particular Audience continues to innovate to plan. In that case, we will instead have this personal AI capable of preempting search intent, layering contextually relevant information to users as they browse the web.
How the coronavirus pandemic affects your business, and how are you coping?
James Taylor: We have been fortunate. With the shift of everything online, servicing online retailers has meant that demand for our products is at an all-time high and continues to grow as more retailers look to develop their digital presence. We did have a minority of adversely affected clients – for example, in the costumes and party supplies vertical, so we made sure we supported those guys through a tricky time.
Did you have to make difficult choices, and what are the lessons learned?
James Taylor: Admittedly, when lockdown struck, we were in a state of total uncertainty, venture capital conversations all got put on ice, and prospective clients reacted to their stores shutting down by pausing new commitments. One thing we knew was that we had to keep everyone in the company safely in a job. I and some of the team took pay reductions to ensure we had a runway well into 2021. Fortunately, we were able to pay this all back after just a couple of months when we raised a precautionary round of funding from our investors Carthona Capital. They were incredibly supportive. New business sales continued to flow in as retailers realized they needed to invest online as Covid persisted in helping even further. The lesson learned for me was to look after your team. The support is mutual, and it has created an incredible company culture as we come out of Covid, more vital than ever.
How do you deal with stress and anxiety?
James Taylor: My wife is amazing. She’s learned to read my stress levels and send me down to Bondi for a swim if I need a reset. For more significant issues, I find that sitting down and planning scenarios help best. I like to know what my options are.
Who are your competitors? And how do you plan to stay in the game?
James Taylor: I mentioned that we believe software is ultimately commoditized. As far as I can see, none of our competitors on the B2B front are approaching this problem from a data perspective. So rather than join a race to the bottom on point features, we will continue to build on our flywheel of reinforcing products and maintain a leadership position through data. Data is, after all, what is depended on by AI.
Your final thoughts?
James Taylor: Well done on building Startup.info – looks great! Thank you for reaching out to us. We look forward to keeping in touch.
All the best, and I hope anyone reading this stays safe.
B2B Website: www.particularaudience.com
B2C Website: www.similarinc.com
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