OpenDNA uses artificial intelligence to deliver ‘true’ personalisation
Australian-listed artificial intelligence company OpenDNA envisions a future where consumers have relevant and personalised online experiences through greater control over their data. It is a future where advertising, marketing, and recommendations are powered by smarter machines.
At the moment, consumers are exposed to more advertising than ever before thanks to being always-connected; we’ve gone from being exposed to 500 ads a day back in the 1970s to as many as 5,000 a day today, according to some estimates.
However, targeted ads are often based on wrong assumptions that are drawn from people’s online movements, according to founder and CEO of OpenDNA Jay Shah.
This is the basis of why OpenDNAexists.
Founded in 2013, OpenDNA’s AI and machine learning system sits at the backend of mobile and web-based applications, analysing a customer’s interactions in real-time and automatically creating detailed psychographic user profiles.
This then enables businesses to automatically deliver more relevant and personalised customer experiences, which means greater engagement, retention, and ROI in marketing, according to OpenDNA.
The company said the benefit for consumers is that they have visibility over their data and can control their online experiences, with OpenDNA claiming consumers have “complete control and transparency” over their data; they can edit their interests and influence their personalised experiences in real-time.
There were two defining experiences that inspired the creation of OpenDNA: On one occasion, Shah had to dig up a valuable link that was buried in page 18 of Google’s search results.
“That’s when I realised there was something wrong here … Why is it on page 18? Apparently the keywords that I typed in were ones that [the owner of the blog] had not optimised for, or he just launched the blog a week earlier … and had not done any search engine optimisation,” Shah said.
“When we search for something, we’re only getting stuff that’s being sent to us by Google based on the fact that those websites have done the right search engine optimisation, not necessarily what’s relevant to us.”
On another occasion, Shah — who has founded, sold, and invested in multiple companies over the last 17 years — found himself being stalked by ads for airline tickets he had already purchased.
“When I bought an airline ticket on one major airline from London to San Francisco, a few days later they were saying ‘Hey Jay, here are some great fares to San Francisco’. The weird thing is I actually bought it on their website. So they still didn’t know that their own systems weren’t talking to each other,” Shah said.
In 2013, Shah started discussing his vision for a system that “truly understood the user” with data scientists and professors from the University of London, from which he graduated.
“They said, ‘Jay, what you’re talking about is the next evolution of the web: The artificial intelligence web, or to be more precise, the internet of me’,” Shah recalled.
The data scientists were sceptical of the feasibility of Shah’s vision given the way large datasets are analysed and the way machine learning algorithms are built.
Large datasets are usually broken down into segments and analysed for patterns before predictive models can be built. Through this process, assumptions are made about groups of individuals — based on, for example, their social media profiles and online movements — that share similar characteristics.
“All of a sudden, we’re the same person being fed the same information. You and I might share a number of interests but that doesn’t mean we’re going to eat the same food, go to the same places, go buy the same products,” Shah said.
He then started investigating the psychology of decision-making, and discovered that there are eight key factors that influence people’s consumption behaviour: Interests, values, connections, time of day, location, weather, financial status, and health.
