Google tried to get ahead of web cookies in 2020, announcing that its Chrome browser would stop supporting them in 2022. That was pushed back to 2023, but the end of web cookies is near, and for experts in recommendation – the customization point – it’s fine.
Innovators are cracking the code on using artificial intelligence (AI) to read purchase intent from a few telling data points, converting browsers into buyers simply by finding out what they’re thinking.
Alexandre Robicquet, co-founder and CEO of the aptly named recommendation engine Crossing Minds, told Karen Webster of PYMNTS that in a quest for conversions, operators have long relied on search engine optimization (SEO) strategy. old fashioned: “What can I get out of this kind of outlaw cookie world that used to exist for me to start figuring out who this person is?”
The problem is that this grouping of look-alikes into cohorts is “usually extremely damaging because it makes you feel like you’re not special,” Robicquet said.
“It makes you feel like you’re having the same experience as 33,000 other people,” he continued. “There’s usually a ton of things that make these experiences feel like, ‘It’s not about me, it’s about who you think I am. “”
It’s a shortcut from the days of Web 2.0, and now we’re at the dawn of Web3. As Robicquet said, knowing a person’s recent browsing and purchase history is more useful than knowing their age and location. He added that these improved data points significantly improve the outcome of recommendation platforms as a service.
He painted a hypothetical situation where a store, online or offline, welcomes a new customer – then a genie appears offering two types of information about that stranger to make a sale.
“I can tell you where they live, their age range, their gender, things about the person, [or] I can tell you the first three pieces they look at and the one they have at home,” Robicquet continued.
It doesn’t take an expert to understand that what consumers buy and own is more telling.
“Anyone would pay for this information, and yet 99% of the Fortune 500 have been brainwashed into thinking you need to have a ton of information about your users to understand who they are,” he said. “The answer is no; it’s not true.
“Instead of focusing on acquiring so much intrusive data about where you live and who you are and everything, why don’t you focus on the first three clicks of what they’re looking at and what they’re looking at. You end up with a ton of implicit, completely anonymized comments that give you an idea of what this person is here for.
AI-powered recommendations do away with the old-school idea of giving websites data just for the sake of using it, transforming digital engagement.
“People thought if they gave you [a free online service], the only way you can pay them back is to give your data or something they can sell,” he said. ” It’s revolting. It’s 2022. You shouldn’t have to pay with your personal information, you shouldn’t have to pay with your time and attention.
See also: Google Analytics violates privacy law
A step beyond research
Digging into how the AI makes these insightful leaps without a website cookie, Robicquet said the creeps of searches blindly following us are missing the point.
“Recommendation is a step further than research,” he said. “That’s what I can show you without you having to type in what you’re looking for.”
The way Crossing Minds does it, a new user arrives on the site or in the store, and the platform serves the best matches based on the behavior tracked by the AI. This can happen on an e-commerce site or with a seller in a store accessing recommendations.
“That’s the concept,” he said. “Send us the live interactions, and we’ll send you back the 10, 20, 64 things you should probably present or display to your users.”
Webster pointed out that the same consumer can behave very differently depending on the type of items and vendors they are looking for, which is a key weakness of cookies. Describing contextual trading, where “session-based” recommendations shine best, Robicquet said the current state of recommendations needs an upgrade – badly.
“There’s a caveat that most services do this – in fact, I thought it was revolting to some extent, where people tell you, ‘We’re providing recommendations for brand-new users’ or ‘We provide recommendations without cookies, “” but they really don’t, he said.
There has been “a realization around the importance of online personalization,” Robicquet continued. “Most companies that provide recommendations never use the words ‘personalized recommendation’ again. Showing you the most popular, showing you the newest, showing you the same as others is still considered a recommendation, but too many companies fall into the trap of assuming these are personalized.
Calling for a new lexicon around personalization for the Web3 era, he added that the point of platforms like Crossing Minds is to proactively use real-time signals, not demographic data.
“Start cherishing your first-party data,” he said. “By definition, the first part is yours. This is what happened on your website. Cherish a click, enjoy a scroll. All of these things are absolutely essential. After that, the idea is that if you start sending us that data…and if you start sending us your catalog of items and what makes each of those items unique – what’s the image, what’s the material, what’s the story behind it – then we can start building models that learn from those models.
Read more: German publishers oppose Google’s plan to end third-party cookies
Do the Tech Cha-Cha
Taking recommendation engines to the next level with AI has implications beyond what to buy. Estimated that 3 billion hours are lost each year due to the paradox of choosing what to watch on TV, smarter recommendations could end many nightly feuds.
“You absolutely know you want to watch a movie, [but] the average time for a user to choose a movie on Netflix is 19 minutes,” Robicquet said. It gets longer by adding partners and friends, and a real-time recommendation engine could save a lot of relationships with streaming alone.
Conceding that he thought cookie-free commerce would be more advanced two years into the pandemic, Robicquet said it was there and needed some realignment of perception to take hold.
Comparing technology and politics to a cha-cha – two steps forward, one step back – he said: “I think in three years people will start to realize that there are alternatives to what has been offered to them so far, both on the base solution for business and on the experience side. People are going to start asking for more when it comes to personalization and digitization in e-commerce.”
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