Peter Szalontay
Datamilk CEO and Founder Peter Szalontay launched his career at Google, where he incorporated AI in ad writing that made — and continues to make — the mega-company billions of dollars.
But that wasn’t the apex of the data aficionado’s career. He ultimately left Google to create his own company, Datamilk. It uses data and AI to create software that improves UX instantly after integration and creates guaranteed significant financial uplift.
DataMilk utilizes attention data, which is first-party data of each of a user’s interaction with an online store, whether swiping, scrolling or lingering on a product. Not only does it address the third-party data going away and users’ privacy concerns that are surely on the rise, but also it is highly effective to create predictive AI-driven online experiences as the AI has the information about where the user is focusing in the moment, and how they react to each item and product they see.
Peter is focusing on financial results. All of DataMilk’s AI-backed UX components are delivering a stable increase in performance like conversion rate and also financial metrics like AOV, revenue and profit, that our customers daily view on their dashboard charts. But also, an important contribution to customers profitability is the quickness of integration. Instead of months of data loading and building and customizing models, DataMilk starts working right away, learning the behavior of your users against your interface and products on its own, without occupying any of your staff.
DataMilk’s Smart Components can predict site users’ steps toward buying without having to sacrifice privacy. This is because the attention data collected from user behaviors on DataMilk client’s sites, where people are usually good with the site’s first-party data. Additionally, it is non-PII as well, so real-time action data, like clicks, scrolls, swipes and lingering are the determining factors. At the same time, attention data is powerful and extremely helpful in making predictions based on what the AI observes in user behaviors, similar to an emphatic sales person in a brick-and-mortar store.
“People and companies are more privacy aware than ever. Countless surveys show high numbers of respondents being concerned about how their personal data is handled,” said Szalontay. “Most of that data shouldn’t even be connected. There’s so much opportunity in anonymous user experiences.”
Recent legislature backs up Szalontay’s statement. Globally, industry leaders — including Apple, Firefox, and Brave — are listening to users’ concerns and have blocked third-party cookies. Google will join them in 2024.
Here are Szalontay’s top six ways to boost e-commerce profit and engagement while protecting users’ digital privacy.
In the age of effortless experiences, navigation and so called burger menus give a great deal of work to the users. While they are used to scanning everything, users have to read through all the category titles. It’s even worse on mobile, navigation is a source of misclicks and churn because of smaller screen sizes, shorter attention spans, and the ‘fat finger’ effect.
Smart navigation and customized content help the user get to the products they want with minimum cognitive effort. Serving as an in-store UI element, or a carousel, smart navigation offers real-time, custom content, which is pulled by AI collections and items that are relevant to the user. This speeds up the discovery of generating products that the specific user may like.
Users are comfortable with frictionless experiences when they are not required to research for a product. Instead, they find the experience more enjoyable when it is for something plain, clear and on the surface.
“We’ve learned to create custom content from customers’ attention signals while interacting with a store: when they swipe without clicking, browse sizes and colors, or linger over a product and scroll back to it,” he said.
As seen on many modern fashion sites, ‘smart FOMO’ provides automatic, real-time tags that can be added to any product. These indicate a limited supply or that the item is selling fast and experiencing a high sales volume.
The benefits of FOMO and social proof, which offer a ‘little push’ to shoppers created in real-time when they are hesitating on making a purchase. Online shopping creates a feeling that you can always go back and buy a product at any moment, so there’s a great temptation to delay purchasing. With consumer procrastination, online retailers lose a lot of sales, and customers suffer too, because they end up unable to get that product, as it is either sold out by the time they return, or they simply can’t return as the store is buried deep in the memory of countless shops the user recently visited. So it is important to convey scarcity and urgency, two factors that are highly effective at overcoming buyer hesitation.
A technique related to ‘smart FOMO,’ smart social proof includes tags that can be added to any product to show the number of recent purchases and views, updated in real-time.
Tags and labels are typically thrown all across the online store and can result in ‘banner blindness’, which will lead to a lack of trust. FOMO tags should be triggered for each particular user separately. What sets DataMilk’s FOMO apart from the competition is that it is based on the shopper’s historical and expressed behaviors, and the AI identifies that in the moment. When the tag appears at just the right moment, or when the user is interested in the product but needs a little motivation, FOMO becomes effective and leads to an increase in sales.
These useful phrases populate a search bar or similar space containing a block of suggested words and terms for searches related to what you’ve viewed. Users can essentially search without typing by merely clicking on a suggested search chip.
These invite customers to go ‘down a rabbit hole’ into a category and explore lots of variations while providing helpful additional context about the items on the page and the catalog.
Sometimes people search pictures and use a specific keyword, typically when they have a product in mind. This is where related search comes in. The AI identifies the intent and suggests related searches based on patterns performed by other users. A block of related searches can appear in the feed after much scrolling and not finding the right product too, which is effective.
The handy section that often populates the bottom of a page contains items similar to what you are shopping for.
They are often placed using widgets inserted into the middle or bottom of the page to show a set of related content to explore. ‘Discover More’ sections create variation and interest on a page and provide a way to navigate to more content without needing to scroll up to the menu.
To learn more about these smart components and what they can do for your e-commerce site, visit https://www.datamilk.ai/smart-components.
About DataMilk
DataMilk is an end-to-end solution for e-commerce UX optimization, from AI and data infrastructure to ready-to-implement optimizations. DataMilk is built on attention data: signals showing every user interaction on your store like click, scroll, view, and more and know exactly where customers are focused in real time delivering the most relevant experiences for the customers — and increasing sales for e-commerce retailers. For more information on how to join and build the next generation of UX, please visit https://www.datamilk.ai/
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