How can analytics help improve the retail customer experience and ultimately drive sales? What additional customer insight can they provide? How can retailers use this information? And where should they start? These are some of the fundamental questions retailers have when considering analytics to optimize their business.
Back to basics
The obvious starting point for most retailers is people counting. It’s straightforward: knowing how many people have visited their store and when. It’s accurate: video-based analytics has come a long way with consistent accuracy of 95% or higher. It’s extremely cost-effective using standardized IP cameras. And it’s intuitive for retailers to cross-reference with other data such as point of sales transactions, promotional campaigns, and even weather reports, to pinpoint the factors driving people in-store.
In fact, visitor traffic is a primary KPI for most fashion and global chain retailers – second only to sales. And it’s vital to measuring sales conversion, evaluating marketing campaigns, assessing store performance, and developing employee incentive programs. Ultimately, it’s a metric that determines whether a store opens or closes.
Adding actionable insight
Counting visitors is just the beginning, and retailers know that there are many factors that can impact – positively or negatively – the in-store visitor experience and overall profitability.
Long queues are just one example of how retailers can lose a sale or a loyal customer, after having successfully enticed them into the store and placed the product in their hands (and research in the UK has pointed to the high cost of this). For this reason more large grocery and home goods stores are abandoning manual monitoring and adopting automated queue analytics that can trigger a silent alarm to retailers to open additional tills or re-direct customers to a shorter check-out line.
While store optimization analytics are a great way to improve retailers’ bottom line, that additional profitability can still be eroded by loss and shrinkage, which, per the Global Retail Theft Barometer 2014-2015, amounts to over $123 billion and on the rise.
Retailers are therefore looking for intelligent technology solutions to prevent and mitigate loss. One example is grocery store chains who supplement their one-way traffic flow systems with direction detection analytics, to alert staff of a visitor exiting from the store entrance rather than the check-out area. Another points to a growing number of round-the-clock open membership clubs and gyms who use tailgating analytics to detect when members bring non-paying friends with them after regular working hours.
By combining a clear retail business goal with video analytic technology and expertise, retailers can improve profitability and maintain a competitive advantage. And in an increasingly competitive retail environment, such insight can be the difference between success and failure.