The Mercanto artificial intelligence platform is incredibly easy to use, operating in the exact drag-and-drop way you’d want it to.
Once the delivery has been made, Mercanto monitors what the consumer does with that communication, learning what they did and didn’t engage with and adjusting future experiences accordingly. With every interaction, the artificial intelligence platform learns how to serve the customer better.
Real-time personalization is not just about who likes what, it’s about who likes what, in what format, at this very moment.
The first leg of the stool – product tagging – is based on a particular AI technology called Natural Language Processing (NLP). NLP automatically extracts ‘tokens’ from products based on the product descriptions. These could include single or multi-word tokens such as ‘party shirt’, ‘slim fit jeans’, ‘Tommy Hilfiger’, ‘work to evening’ – there can be millions of tokens extracted across a retailer’s entire product catalog. The goal is to look beyond the standard product data to understand the product’s most important features and attributes.
As consumers interact with products, these interactions are married with each product’s tokens to construct a ‘taste profile’ for each consumer. This the second leg of the three-legged stool. The taste profile is a collection of everything a consumer interacts with – online, in-store, and in-app – broken down into a collection of ranked tokens. Taste profiles are the foundation of personalization: they aid retailers in recommending new products as they’re added to the catalog. And if a consumer happens to like the most quirky and unusual product in your catalog, something that only 20 people in your database would dig, you can find those 20 people and connect the dots between the product and the consumers. At the end of the day, it’s about understanding each consumer’s personal tastes, and making recommendations accordingly.
3. Algorithms bring it all together
The connection between data from the retailer’s product catalog and each consumer’s personal taste profile is the third and final leg of the stool. We take all of these tokens and the user behavior data and then we use sophisticated Deep Neural Network algorithms to figure out what’s most important and what we should weigh. It’s all about the data. On one side, we build a model of the retailer’s products, and on the other side, we have a taste profile for each consumer. We continuously take these two things, do a little magic filtering, and rank products to match products to each consumer’s taste profile, while also incorporating new and popular products, together with an element of diversity.
Integrate with ease
Mercanto completes comprehensive integrations in just a few weeks. Since we integrate directly with your existing web analytics platform and product feed, you’ll soon be up and running with tangible results.Read more
Harness untapped data
Why should marketers care about a system that uses Deep Neural Networks to process consumer interests and product data in milliseconds? Because it (finally!) enables them to serve the right message to the right person at the right time. Marketers gain complete control, eliminate organizational bottlenecks, and drive more impact.Read more
Launch at scale
Individualized content is key to unlocking ROI across digital channels, yet most marketers fall short due to organizational barriers, data silos and technological shortcomings. Mercanto’s artificial intelligence platform empowers marketers to launch 100% individualized campaigns in less than 10 minutes.Read more
[Playbook] Welcome To The AI Revolution
Marketing is in the midst of an AI revolution that challenges the fundamentals of the traditional marketing playbook. At stake is the opportunity to drive breakthrough marketing results, based on a genuine 1:1 dialog with each individual consumer. In this playbook, we share practical advice and best practice when it comes to applying AI in your marketing.