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In an interview with Shane Williams for the Platform Diaries Podcast, James Taylor discusses the death of third party cookies, how to personalize customer experiences without violating personal information (PI) and the power of contextual advertising.
Three key takeaways from the podcast include:
- Contextual advertising will be king in a third party cookieless world
- Product data, rather than customer data, is the way to achieve effective personalisation
- The future of eCommerce will be led by recommendations - and we can fit the brief.
In the podcast, CEO and Founder James Taylor speaks to the rising demand from consumers for privacy. With Google and Apple announcing their intention to phase out support for third party cookies by 2023 and massive regulatory changes on data privacy in Europe and countries such as Canada, advertisers need new strategies to engage with consumers online. Spending on ads, targeting/retargeting ads and measuring cross site performance is made much harder without third party cookies.
James said, “Contextual advertising (focused on click stream and product data) will persist in a world with no third party cookies.”
James and Shane discuss Amazon’s ‘pay to play’ model: sponsored products and Retail Media.
James emphasizes that the rise of Retail Media, as an example of contextual advertising, is paramount in terms of timing with the fast approaching death of third party cookies.
“Retail Media is a huge magnetism for advertising dollars, retailers will earn money from their front end and advertisers will be able to pay to promote items to in-market consumers.”
Retail Media platforms like Particular Audience that use first party, 100% anonymous item data to achieve contextual advertising are powerful in the time of the privacy conscious consumer, as, in James words “data that is never stored can’t be leaked or violated”.
Then James discusses the importance of product data to achieve effective personalization
Shane asks about common mistakes in the eCommerce space.
James said, “There’s an assumption that you personalize around the customer. This is counter intuitive and ineffective; greetings based on your name or content about the weather in your location have nothing to do with what a consumer wants."
"They’d [Consumers would] rather login and see items they want right away…. This can be achieved with item data, which is a much more robust data set than customer data.”
James notes that personalization is just good prediction, and item data can help you make better predictions based on in-moment intent. ECommerce Managers think they need segments and cohorts based on customer data, but “...if you group customers by tenuous attributes, like middle aged men in Sydney you lose effectiveness of personalization.”
To demonstrate this, James highlights the success of businesses that don’t need to know about demographics to show you content you like or will engage with, chief among these being Spotify and Netflix. He emphasizes that Netlifx doesn't try to make predictions based on your age, location or name, instead it uses information about what you’ve recently watched to predict what you want to see next. Likewise, on Spotify the songs you’ve recently listened to are a better indicator of what you want to hear based on your changing context.
To finish, the future of eCommerce is recommendations, not search
Netflixication of personalization in eCommerce, a.k.a the rise of effective personalization, is at the heart of the Particular Audience platform and James’ mission as a Founder. As the conversation wraps up, James predicts that search as we know it will be made redundant by intuitive, personalized recommendations.
James said “You need relevance and scale to win in eCommerce. The accepted wisdom is that for every 10% increase in product catalog you have a 12% increase in revenue, you get more traffic from google shopping. But with these endless pages of items, many won’t ever be seen, which creates a ceiling on profit.”
James emphasizes that by using wisdom of the crowd algorithms, natural language processing and computer vision, Particular Audience can rerank an entire product list based on customer intent and interests, scaling catalogs, appealing to more niches and ensuring more relevant experiences for each individual.
This speaks to a greater vision of a semantic web with an intuitive understanding of what customers want, in which recommendations are so good that search becomes redundant.