Business solution provider Activity Stream has unveiled its new artificial intelligence (AI) and deep learning sales prediction model to support its entertainment industry partners.

The technology, which will pilot in early 2020, takes data from a number of different venues and uses deep learning and AI tech to predict sales in a “far more nuanced way than current approaches focusing on regression.”

Activity Stream, which handles almost 100 million tickets per year, claims that the model will allow for its entertainment industry partners to understand sales in a non-linear way, as it will be capable of progressively improving as it is fed more information both on a general scale, but also for a specific partner.

In total it will be capable of associating around 150 different dimensions in order to create a prediction. Under testing, the prototype for the model has a rate of accuracy of over 95 per cent at present, Activity Stream claims.

Helgi Helgason, chief technology officer at Activity Stream, said: “In general, Activity Stream is able to gather all of this because of our unique access to a massive amount of data. This means that we are able to approach sales predictions in a wider sense, not just being reliant on data from one venue or organisation. Coupled with our ability to work with deep learning, this creates a perfect situation for us to deliver quality predictions to our customers.

“Our model works with over 150 input variables and produces a predicted sales curve by leveraging the learned relationships of the inputs. In the end, our customers see accurate estimates for total sales and how sales are likely to unfold over each part of the sales period.

“Specifically, the types of data that our sales prediction model will consider are things like how customers are interacting with the product (purchases and more), customer demographics, product attributes, and location-related factors.”