Transforming the Grocery Industry with Customer Analytics

Customer analytics technology helps grocers make critical business decisions faster, more strategically, and backed by real-time data. It places the grocers who use it ahead of the competition, empowering them to spot customer trends, patterns, and purchasing behaviors before anyone else. Retailers often face the challenge of not being able to collect reliable customer data easily or quickly enough to implement any impactful changes before new trends emerge, but real-time, AI-powered customer analytics data solves that.

Customer Analytics: Traditional vs. AI-powered

Traditionally, grocery retailers would have to manually collect in-store consumer data through the processes of observation, conducting surveys, and various other laborious tasks. These outdated research methods were prone to human error and required a lot of put-through to execute; from collection, to collation, to interpretation. This lag in data analysis meant that grocers could never gain insights truly reflective of the moment, placing them on the back foot.

The introduction of AI-powered analytics technology and its real-time data collection capabilities has transformed the grocery industry as we know it by bringing actionable insights to retailers in a matter of seconds, and making accurate, digestible, and easy-to-obtain customer data a possibility.

No Compromise On Customer Privacy

What often comes to mind when people think of in-store customer analytics is customer privacy. Luckily, Raydiant’s AI-powered technology is a non-intrusive and completely privacy-compliant tool that only extracts raw data and never identifies people. The technology analyzes customers in-store using discreet IP cameras built-in to digital signage, or by using existing cameras in operation at store entrances. As the raw data is collected in real-time, there is no need to store any footage.

Impactful Analytics for Grocers

By identifying who their target customers are, what products they like the best, and where they spend the most time in-store, combined with determining the value of these customers, grocers can hone in on where opportunities for extra sales lie and identify areas of improvement. Analytics data facilitates supermarkets and grocery stores to price their items right, place their products more strategically on the shelf, and create high-quality in-store experiences that match customers’ preferences and expectations.

Let’s take a look at what you can measure using AI Analytics:

1. Foot traffic

Measuring foot traffic into your grocery store is beneficial to understand your daily, weekly, and monthly visitor count. This allows retailers to establish peak store times, better allocate staff, and measure store performance across all locations. This data can also be compared with POS data to determine sales conversion rates and identify areas of improvement. For example, a high influx of visitors with no spike in sales reasonably means that there’s a problem in the customer journey.

2. Customer Dwell

When customers linger in an area, it usually means that something has caught their attention. Defining areas in-store where customers tend to gather and stop regularly identifies advantageous spots to place digital marketing campaigns, promotional products, and any goods you want to bring maximum exposure to.

3. Satisfaction

Customer satisfaction can be measured using mood analysis. This is carried out using facial expression analysis to differentiate between neutral and positive expressions. If your customers are signaling high positivity scores, your business is going in the right direction. Get a feel for what customers really think about your grocery store with real-time, honest feedback.

4. Product Engagement

By identifying the products customers interact with the most, grocers can better forecast customer product demand leading to higher customer satisfaction and less overstock. Retailers can also understand what products are popular and source similar goods to offer variety.

5. Customer Profiles

Defining who your loyal and target customers are is imperative to building a successful business strategy. AI analytics measures customer age and gender in order for grocers to profile customers and place them into persona groups. Product promotions and digital marketing can then be tailored to target and engage these groups more effectively.

Beyond Analytics

Real-time analytics is used for purposes beyond solely measuring customer behaviors in-store — it can also facilitate the customer journey. When combined with self-service kiosks, the technology can analyze customers purchasing age-restricted goods and determine if the individual is at the legally-required age to make the purchase. If the person is old enough, the sale goes ahead and at a much quicker rate than if a staff member had to manually check IDs. If the person is underage, they are flagged to staff for further review. Overall, it’s a solution that offers convenience to both customers and employees.

Discover how to shape your retail strategy using AI customer analytics and accelerate your businesses success by booking a demo with us.