23.03.18

Signagelive founder on intelligent signage

Analytics on a crowd in the street

Tim Kridel asks Jason Cremins, founder and CEO of digital signage software provider Signagelive how AI can be applied in the sector.

TK: For retailers and other businesses that use digital signage, one longstanding challenging is quantifying the reach and effectiveness of both the screens (e.g., locations) and the content on them. How does AI enable them to get deeper, actionable insights that wouldn’t be possible without AI? 

JC: We are seeing a growing number of retailers either adding or looking to add audience measurement technologies to serve two functions. The first is to collect viewer data that can be analysed against the proof of play (media logs) and proof of display (device status data) that we collect and report within our platform. Adding proof of view completes the dataset, allowing them to [apply] POS sales data and other internal and external metrics (e.g., weather) to provide a deep insight into the impact of their digital signage network and content strategy.
 
The second use case is using the data gathered (as per above) to dynamical shape and schedule the media playing on the digital signage displays. In this scenario, the scheduled content is adjusted at the point of playback to optimise the content shown based on the insights gathered.

TK: This press release mentions that you have some case studies in the works. What are some across-the-board lessons learned so far? For example, what have you and/or your partners learned about what makes for compelling content, or ideal signage locations or other things? Any old rules/strategies/best practices that no longer appear to make sense?

JC: The key to success continues to be to keep the content fresh, relevant and engaging. Data-driven content combined with dynamic scheduling based on audience insights are set to replace pre-scheduled and published playlists of media that are based on historical general demographic and day-part data.

TK: AI keeps getting more sophisticated because of advances in processing power, algorithms, etc. Regarding your answer to question 1, what additional types of analytics might be possible in, say, five or 10 years?

JC: From our perspective, we are excited to see how the image and video analysis AI technologies will further enhance how content is optimised for individuals and groups of customers.