How does Aidaptive predict the intent and affinities of anonymous visitors?
How does Aidaptive predict the intent and affinities of anonymous visitors?
How does Aidaptive work?
- Aidaptive consumes and leverages all available data about customers, products, inventory, transactions, promotions, pricing, marketing touches, digital engagement, etc. to feed a predictive AI platform. Initially, Aidaptive consumes all available historical data and then leverages an ongoing feed of real-time data to continue enriching the dataset.
- The initial data ingestion allows Aidaptive to train machine learning models to predict shopper behavior and make predictions.
- These predictions are made available in real-time via API and/or javascript in order to enable a brand to serve unique content and experiences to each individual shopper.
- The ongoing feedback loop enables Aidaptive to continuously tune models to continue improving precision and accuracy, based on specific performance objectives.
What about anonymous shoppers?
- Aidaptive builds a near infinite spectrum of personas based on a business’s past customers.
- When an anonymous shopper hits a brand’s website, the (limited) data available about that shopper (browser information, user agent, IP address, time/day, landing page, referring URL, etc.), enables Aidaptive to identify how similar that shopper to that spectrum of personas. This enables Aidaptive to predict the most likely intent and affinities of that particular shopper, even with limited data. Importantly, as that anonymous shopper continues to engage with the site and respond (or not respond) to the predicted content, her/his profile is enriched with additional signals that allow the predictions to continue being refined and honed.