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 OpenDNA exists.
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.
"These factors, combined, tell us as human beings what to do on a daily basis, what products to buy, what ads to click on, what to wear, what to eat, everything. So I was looking at how we could map this, and I put a team together in 2014 and we did it," Shah said.
"We built a system that learned my interests ... As time progressed, it would feed me more and more interesting [content from 200 sources] and I was able to discover some new stuff that I would have never searched for before.
"That's the element of discovery coming in that everyone is looking for. It's like serendipity -- you haven't searched for it, but you still found it, and it was interesting for you."
Shah explained that OpenDNA would know, for example, that an individual is enthusiastic about both sports and technology. It would know that the individual is especially interested in golf, prefers Tiger Woods over Phil Mickelson, and wants to purchase a pair of golf shoes. The system would also know that Tiger Woods is endorsed by Nike.
In this hypothetical scenario, when the individual visits a sportswear ecommerce site powered by OpenDNA, the list of recommended products that they would see would include Nike golf shoes with built-in sensors that maps the individual's activity levels.
Shah admitted that the company is initially targeting the adtech, media, and business intelligence markets, though he said OpenDNA's system can also be used in the ecommerce, finance, hardware, and many other markets.
The funding dilemma
The company listed on the Australian Securities Exchange (ASX) late last year after raising AU$8 million in its initial public offering. The company raised venture capital prior to that, but decided going public in Australia was the best option moving forward.
Shah pitched to numerous venture capitalists in Silicon Valley who were largely impressed by OpenDNA, but were demanding that the company tweak the technology to the point that it no longer aligns with the founding team's original vision.
Six months later, when OpenDNA was seeking Series A funding, a few of the investors Shah had spoken to earlier approached him again and presented the same argument, but this time they asked for the focus to be on adtech.
At that point, Shah realised that if he went ahead and accepted money from the investors he had spoken to, the OpenDNA vision would be destroyed.
"They would end up putting someone into the company that really does not appreciate where we're going with this business and what we can actually do with this technology," Shah said.
An OpenDNA shareholder then advised Shah to "go raise money elsewhere".
"He said: 'You're not from the Valley, your entire team is in Cape Town, and it's a unique situation'," Shah recalled.
After reaching out to his investor network, one particular investor suggested that Shah explore a listing on the ASX. Not long after, Shah was in Australia meeting with high net-worth individuals, accounting firms, and lawyers; and on November 9th, OpenDNA was a publicly listed company.
The company has since enhanced its technology; in addition to providing software development kits for iOS and Android, OpenDNA is also building "data connectors" that allow companies to pull psychographic data from OpenDNA and add it to their other systems such as customer relationship management systems, content management systems, or business intelligence systems.
"You can then query the way you want. You can also utilise the recommendations from OpenDNA and then allow your systems to just push those recommendations to the user. Or you can intervene and control what you want the users to watch or see or read or buy," Shah said.
"This is a fundamental step which is now allowing us to interconnect with major providers such as publishers, adtech environments, media and broadcasters, video streaming companies, business intelligence companies, hardware businesses, and so forth.
"We have the ability as a company to interconnect into a lot of these businesses that people perceive to be competitors and provide them with a completely new way of automating building psychographic profiles of their customers."
Shah said many struggle to believe that Google has not created what OpenDNA has.
"When I was going through the IPO process, we had a whole bunch of investors say: 'Isn't this company a competitor?' For example, they would say 'Surely Google's doing this, surely this other company is doing this'," Shah said.
"I've spoken to a whole bunch of these businesses including Google who we were told were doing exactly the same thing. They're not."