Thanks to clickstream data and other types of digital breadcrumbs, today’s multichannel retailers can learn a lot about their online and mobile customers. But according to a Forrester Research analyst quoted in The New York Times, “well over 90% of sales still happen in physical stores.”
All too often, retailers have an analytic blind spot in brick-and-mortar channels—the very place where behavior intelligence could potentially deliver the greatest value.
In the same way that online data drives decision-making for digital channels, a detailed understanding of what’s going on in physical stores can help managers forecast staffing needs, address customer service issues and evaluate how things like merchandising, promotions and product placement impact sales conversions.
This intelligence not only leads to better and more profitable decisions in individual stores; it can also help retailers measure brick and mortar performance within the context of broader multichannel strategies.
Here’s the challenge: no clicks are generated when a brick-and-mortar shopper steps into a store or stops at a display, and data capture is not simple or straightforward. How do retailers address this?
POS data alone is not enough. Retailers have traditionally used POS transaction data to track in store purchases. But this doesn’t tell the whole story. A shopper who looks and then leaves is a missed opportunity, so knowing how many people didn’t buy is just as important as knowing how many did. This is the conversion rate.
Clickstream data has helped online channels get pretty sophisticated about improving conversions—think about all those times an ad for shoes you viewed on a retail site has followed you around the Web.
In the brick-and-mortar world, calculating conversion depends on knowing how many shoppers have entered a store, so that overall traffic can be measured against the number of in-store transactions. This is where people counting technologies come in.
Placed at the door, devices can be used to anonymously count the number of arrivals and exits, so that retailers can better understand conversion, and ultimately, store performance. It could be, for instance, that a store with a low volume of transactions appears to be performing poorly, when it’s actually doing a great job converting a low volume of shoppers into buyers.
Without traffic data to reveal that high conversion ratio, the retailer may mistakenly punish an excellent store manager and miss addressing the real problem: too few customers entering the store! In such a case, the retailer needs to find ways to drive more consumers to the location to shop. Better data fuels more appropriately targeted performance strategies across all sales channels.
Move beyond the front door
Knowing what customers do after they pass through the front door is also critical. Much like clickstream data is used in ecommerce environments to determine which page layouts, imagery, offers and other site elements improve the customer experience and increase conversions, capturing behavior-related data inside physical stores is incredibly valuable.
This deeper level of behavior intelligence can be used to improve staffing, service and queue management, and even to optimize product placement, signage and merchandising strategies. While clickstream data is easily captured in the digital world, special devices are again required in brick and mortar stores to anonymously track activity beyond the front door as customers shop.
Measuring in-store behavior is more challenging than in other channels, however, so it’s important to understand how to address blind spots and other environmental issues that can impact data capture.
Variables such as bad lighting, big crowds and even temperature fluctuations can impact the accuracy of the data collected in physical spaces. How people shop (in groups, with children, or separately, for instance) can also change a retailer’s understanding of the metrics.
Over- or undercounting shoppers will distort sales conversion figures, and impact the decisions that rely upon this important metric. Overestimating customers’ time in queue can result in too many checkouts being opened, driving up labor costs, while underestimating means customers wait longer and become frustrated.
While no analytics technology is 100% accurate 100% of the time, some solutions are more accurate than others. When evaluating technology, consider whether a data capture solution is able to do things like distinguish between adults and children or between people and non-human objects like shopping carts. Is it able to track specific behaviors or interest (such as people congregating at a specific display)? Measure actual wait times vs. average wait times?
The more the accuracy of your brick and mortar solution is on par with your online analytics, the easier it will be to compare both and better understand retail performance across all channels.
Multichannel retailers can dramatically impact their brick-and-mortar customers’ experiences just as they have improved online shopping, provided they invest in capturing and analyzing in store behavior data. Retailers simply can’t afford to be blind when it comes to their largest sales channel: the store.
Ralph Crabtree is CTO of Brickstream.