01 February 2022

What Is Experiential Retail and How Is Computer Vision Technology Fuelling It?

Experiential retail is on the rise and computer vision technology is fuelling it.

Over the past few years there has been a shift in the way brick and mortar stores operate. Traditionally, the purpose of the retail store was solely to transact goods but the priority has changed over the years with an extra focus now placed on the customer and in creating engaging in-store experiences. In constant competition with online retailers, where technology has streamlined the shopper journey, brick-and-mortar stores must also leverage smart technologies in order to create an in-premise shopping experience that can’t be matched online. Transforming stores into what Deloitte describes as, ‘experience bazaars.’

What is Experiential Retail?

Experiential retail is the creation of immersive and memorable experiences in your physical retail store such as in supermarkets, convenience stores, shopping malls, etc. Experiential retail usually evokes high levels of satisfaction, enjoyment, and positivity in the customer which in turn drives long-term loyalty to the store and increases revenue. Some of the success factors associated with achieving excellent in-store customer experiences include; 

  1. Personalization 
  2. Convenience   
  3. Product Relevancy
  4. Streamlined Customer Journey

Where Does Computer Vision Technology Come Into Play?

There are several smart technologies that can be adopted to increase customer engagement and experience in retail. However, audience analytics technology, powered by computer vision, seems to be leading the way. The innovative technology can be implemented into a stores media network by adding cameras to digital displays, signage, and kiosks and can optimize customer experience throughout the entire path to purchase journey. Let’s take a look at how! 

Success Factor No:

1. Personalization Through Targeted Advertising

Customers like to feel special and appreciated and one method of achieving this is by providing a touch of personalization to their in-store experience. By retrofitting existing in-store signage with audience analysis technology content that is hyper-personalized can be delivered to each visitor in real-time. The process works by adding a camera to each screen within a businesses retail media network. The screens can be placed anywhere, from the entrance, aisle end-caps, or at the POS and each of them can have the technology running simultaneously. When a person is detected in front of a screen, they are analyzed in real-time and pre-defined content will play according to their demographic group. This type of personalization can make customers aware of new products that suit their preferences, help them with their decision making in-store and ensure they have an optimized experience. 

According to a study by Deloitte, ‘75% of customers expect brands to personalize and contextualize interactions and by using audience analytics technology brands, suppliers and in-house marketers who showcase content in-store can all meet these customer expectations. 

2. Convenience Using Optimized Self-Service Checkouts

Self-service checkouts are known for their ability to speed up sales and checkout times in-store. They make shopping convenient for the consumer and offer a nice alternative for people who are not looking to engage with staff at the register. Through AI analysis, added value and additional speed can be brought to self-service kiosks by way of; 

  • Verifying customers’ age for the purchase of restricted goods such as tobacco and alcohol. Reducing the need for manual checks by staff. (Only people who flag as underage will require manual ID checks)
  • Adjusting the screen layout and appearance of the kiosk in real-time to suit the needs of the demographic present. An example of this can be as simple as adjusting the text size and buttons for people above 70 years old. Often older customers can experience difficulty when finishing their purchases at self-service kiosks, therefore implementing small changes like this can have a big impact in helping to get them through the checkout process in a timely and efficient manner and avoiding cart abandonment.


(If you wish to implement this technology into your self-service kiosks, you can check out our DeepSight audience analytics technology in combination with Raydiant’s dashboard which includes a content editing feature)

3. Product Relevancy Utilizing Historical Data Analytics

Keeping up-to-date with your customer’s needs is what will set you apart from the competition. To do that it is important to first establish what their preferences are and then show relevant product offerings to them at the right points within the store. To get to know your main customer groups and understand their purchase behavior it is important to aggregate and analyze the following:  

  1. Ad Viewing Data – This data can be collected using anonymous face and body detection using cameras located on digital screens. Metrics such as impressions, no. of viewers, and viewing times per age group/gender can provide a better understanding of what products received the most interest and by which groups. This data can be collected and analyzed across various campaigns and used to improve and source future product offerings. 
  2. Point of Sales/Transactional Data – By placing cameras at self-service checkouts demographic data can be captured and merged with point of sales data displayed on a dashboard. The benefit of doing this is to see which persona groups are buying certain products and their average transactional values. By having access to this information you can target future customers more easily and offer products that should pique their interest.  

4. Streamlined Customer Journey with AI Activated Messaging

More than ever it is important to make customers feel safe in-store. One way to ensure this is by having a clear strategy on how you are going to implement covid-19 safety policies and then communicate this to your customers. By adding audience analytics technology powered by computer vision to your in-store signage you can keep customers up-to-date on the latest in-store safety policies and provide real-time insights into occupancy levels, displaying ‘enter’ or ‘wait’ messaging and reminders to wear face masks at the entrance and throughout the store. This works through the process of face mask detection and people counting technology and having these technologies in place streamlines the customer journey as customers are aware of exactly when it is safe to enter and are left assured that their safety is a priority. 

Measuring Customer Experiences with Mood Detection

Taking steps to create positive in-store experiences is great, but how do you know that your efforts are working? AI audience analytics technology can be utilized to help you create memorable experiences but it can also be used to measure the effectiveness of them, through the use of mood detection technology. It is a well known fact that happy customers are returning customers therefore measuring happiness can be a great indicator of how customers are experiencing your business. Using cameras at various touchpoints in-store, you can analyze customer mood along their journey and capture their reactions to scenarios such as staff engagements at the tills or marketing messaging on digital screens. 

Sightcorps Audience analytics technology is a non-intrusive and privacy-respecting software that helps retailers to achieve customer success through all of the techniques listed above. If you wish to try the software for your retail use case you can do so, for free, for two weeks. 

By Danielle McCann

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About the Author

Sightcorp is the anonymous audience analytics intelligence specialist for Digital Signage, DOOH, Out of Home Media, and In-Store Analytics. Making lightweight AI edge software solutions that bridge the gap between the online and real world. Providing anonymous in-store analytics to Retailers and powering the DOOH ecosystem with ad performance metrics for advertisers, real-time audience reach for media network owners, and an industry-recognized impression-based currency for programmatic advertising.