3 Ways Retailers Can Use In-Store Analytics
Omni-shoppers account for 40% of retail purchases (comScore).
Today a retailer’s ability to compete is becoming increasingly tied to creating value from data. Not just online, but in-store as well—where over 92% of all retail sales are still taking place (U.S. Census Bureau).
Emerging in-store analytics solutions seem to offer answers. But, more “unactionable” data mounds is the last thing you need. Can in-store analytics easily offer insight rather than additional headache? And, how would you even apply these insights?
In my last article we discussed the pros and cons of available in-store analytics solutions. Here, I’ll focus on in-store video analytics, what metrics are available and applications for retailers.
First, let’s talk about metrics.
Here is a sample of key metrics that you can now get with in-store video analytics…
- Visits: # of shopper visits to a store / department / category / area over a given period
- Demographic Counts: Shopper age and gender statistics
- Path Analysis / Heat Maps: Shopper traffic and dwell patterns throughout store
- Attention Time: How long shoppers look at a specific brand / merchandising / promotion
- Dwell Time: How long shoppers spend within a specific department / category / area
- Visits to Stops: Counts & conversion statistics of shoppers walking by the department / category / merchandising versus shoppers walking by that then stop
Okay, more data. Now what?
Here are 3 ways you can apply these metrics to support both your marketing & operations…
- Understand Shoppers’ Path to Purchase
- Improve Category / Department / Merchandising Performance
- Segment Most Valuable Shoppers
With shopper traffic data and heat maps in hand, you can optimize staffing allocation and inventory management in different store categories / departments by month, day or even hour to improve your customer experience and sales. You’ll also be able to easily identify and remedy things like long wait times, low-traffic or congested areas to optimize sales per square foot. And, metrics such as average visit duration compared against sales data can be a good indicator of overall experience measurement and help compare performance across store locations / regions.
By understanding how shoppers navigate your store(s), what attracts their attention and where they spend their time, you’ll be able to optimize store footprints, SKU rationalization, product placement and cost per shelf. Additionally, you’ll be able to start comparing performance across your stores beyond just sales. For example, you’ll be able to see which products / categories / departments / merchandising are converting traffic at high, low and average rates across your store locations, and address it accordingly. Check out: How Retailers Find ROI with In-Store Analytics, for more on in-store analytics and conversion.
We’ve all seen the infamous Gartner stat: 80 percent of your future profits will come from just 20 percent of your existing customers. And, now thanks to demographic and new vs. returning visitor metrics, you can more easily identify high-value shoppers and analyze the behavior and needs that drive individual shoppers. As a result you’ll be able to drive more personalized experiences and targeted offers in-store to help drive sell-through.
Are you ready to start exploring how in-store analytics could help your company?
If so, then I recommend checking out: In-Store Analytics: 3 Things You Need to Know,
where I breakdown the pros and cons of current in-store analytics solutions.
Image Copyright: Bigstock/BostoX