Displayforce is an artificial intelligence-based platform for displaying personalized advertising content on screens at the point of sale. The Displayforce Box is equipped with cameras and able to analyze the audience instantly.
Facial features are broken down into multiple data points that are compared to a pre-trained model, and the system makes an intelligent decision about the person's gender and age. Depersonalized data is sent to the platform, and the platform selects content that may be of interest to a person in front of the screen. The data is not stored, but for a quick moment of "contact" with the buyer, it even manages to provide the store with statistics on the number of visitors, their age and gender, and what advertising materials were displayed. It also analyzes the number of contacts with a unique audience, the customer dwell-time, and reactions to broadcasted offers. The reaction is determined by how much time the customer has spent close to the screen. Thanks to the platform, the retailer saves on marketing automation (it enables centralized management of all marketing activities at the points of sale by 1 employee). The retailer also receives additional revenues due to increased sales of advertised products, plus experiences the increase of the foot traffic because of the screens located at the entrance.
The Displayforce platform is suitable for any retail chain having more than ten locations and more than 200 visitors per day. "We also have solutions for small stores, but the maximum effect is achieved when the company has a lot of traffic. The solution is suitable for branded and multi-brand retailers, - explains Serge Galeev, CEO and co-founder of Displayforce. The more stores are there in the network and the higher is the retail margin, the more profit our platform can bring to the business. The reason for that is that the increase of conversion to sale of high-margin products (private store brands or expensive commodity items) directly affects the payback rate "
Displayforce has been developing the platform since 2014 when the company decided to focus on business processes within the retail industry related to marketing communications. It was just the time when digital screens start appearing in large shopping malls, where advertisements and other useful information for buyers were displayed. For instance, it was information about promotions and discounts. Displayforce decided that this information should be as client-oriented as possible. "If in online stores you can make personalized offers based on the visit history or the history of previous purchases; if you can count buyers, analyze their customer journey and, depending on this, offer goods or discounts, then why not move this to offline? - says Serge Galeev. - At that time, the concept of Store as Media ("store as a means of communication") was gaining popularity globally: a point of sale should be evaluated not as a sales channel, but as a channel of emotional contact with an audience, and the effectiveness of this channel should be measured using new metrics "
Retailer's content managers generate marketing hypotheses (ideas that impact the result) and select advertising creatives. Then the creatives are published on digital screens installed in a store or shopping center, hypotheses are being tested to keep the most effective ones for a longer period. When selecting advertising concepts, specialists rely on their knowledge about the target audience or put their trust in Displayforce algorithms.
The algorithm recognizes and records about 40 buyers' parameters: which department was visited, how much was the dwell-time in front of the screen, what advertisement grabbed buyer's attention, how changes their facial expressions -- what emotions were displayed. Based on this data, the system builds up a client-oriented strategy: it shows only relevant content. For example, a woman walked into the makeup department and noticed a screen when a lipstick of a certain brand was being advertised. Further, when walking through the store, she will see other lipsticks advertisements; the system will be able to understand which particular offer interested her the most based on her reactions. Then the system would show promotions for the lipstick and continue to measure visitor engagement, making the offer more personalized.