There’s a lot of chatter in the retail space about the threat of online sales to traditional brick-and-mortar stores. Perhaps that talk should be about the huge, missed opportunity walking out of stores every day: the browsers who could be buyers, and about whom most retailers have little or no information.
Concern about online sales has evolved with good reason. Since 2000, the growth of e-Commerce has far outstripped that of other retail channels, with an average annual increase of 20%, according to Deloitte’s The Next Evolution: Store 3.0 report. Indeed, the seemingly endless analytics available about online shoppers is an advantage to retailers.
However, despite its impressive growth, online sales still comprises a small fraction of total retail sales. According to Forrester Research’s Mobile Commerce Forecast: 2011 to 2016, total e-Commerce sales will grow from 7% in 2011 to close to 9% percent by 2016. So, with brick-and-mortar’s 93% of sales, and similar percentage of cost, the retail store remains a critical focus. The challenge is how to make traditional stores relevant to the new breed of omni-channel shoppers. One clear possibility is to take a page from the online manual and get to know as much as possible about in-store customers, and not just those who are buying.
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Insights about every shopper who walks in the door will enable brick-and-mortar retailers to better serve their customers and capitalize on a big, missed opportunity — the up to 80% of browsers who walk out the door every day without buying a thing.
Most of the analysis that’s done today is based on POS data. If 80% of the people that come into the store don’t make a purchase, they are absent from the analysis that retailers use to feed decision-making.
It seems shortsighted to plan retail operations around the 20% who buy and completely ignore the lost opportunity of the 80% who are doing goodness-knows- what inside the store. Yet it is completely understandable, given retail management’s limited information about these non-buyers. Strategy must be based on intelligence and information. Other than door counters used at a small percentage of retail outlets, there has, historically, been very little intelligence or insights available about browsers in-store.
Regardless of retailer type or the direction in which management wants to take its stores, it is clear that increased information and analysis of what shoppers are doing once they are in-store will be critical in both developing and executing a competitive strategy for the new reality of retail.
In-Store Insights Helps Target Browsers, Not Just Buyers
Fortunately, increased customer information has been made possible by technology advances. Gathering, quantifying and analyzing visual customer intelligence gained from in-store video cameras provides the closest thing to online analytics that retail management has available.
With the latest solutions, store management can go beyond traditional people counting and quantify customer behavior inside their stores. Management can see where shoppers stop and spend time, what areas of the store get the most traffic and which ones the least. Traffic to, and engagement with, promotional displays can be measured and analyzed and, most importantly, acted upon.
So how can a retailer use all this information to turn browsers into buyers? There are lots of ways.
Service Drives Conversions ― Match Staffing And Traffic Levels
In many types of retail outlets, service drives conversion; in the new world of cross-channel and connected customers, it is likely that service will play an even more important role across the board. But with increased staffing comes significant cost, and management faces the challenge of balancing cost with sales. Increased in-store customer intelligence can help.
Staff schedules often are based on transaction volume, but this information does not account for the highly variable nature of conversion rates by hour of the day and day of the week at both store and department levels.
For example, in one retail outlet, a 40% to 50% drop in conversions was recorded in the early afternoon; store operations was able to trace that drop to staff members leaving the sales floor to manage inventory in the stock room. This type of in-store insight allows management to see a problem clearly then react to it.
In another store, visual customer intelligence showed that employees were twice as busy on weekends, serving double the number of customers. Knowledge of this significant imbalance in staffing between weekdays and weekends allowed store operations to adjust staffing levels to match traffic.
Stores using accurate staff-to-customer ratios over hours and days to plan staffing levels have seen a 1 to 2% reduction in total staff costs and have reduced staffing on some schedules by up to 20% ― without an impact on conversions. Alternatively, stores that have increased staffing based on accurate data have seen increased conversions.
An accurate customer to employee ratio, based on actual opportunity, not just sales, helps find the optimum balance between operating costs and sales.
Measure Marketing Effectiveness
In Forrester Research’s 2009 Global Marketing Technology Survey, two of the top four challenges with marketing programs were measuring results and creating customer insights to drive decision-making.
Without in-store customer insights, marketing campaigns and in-store promotions are merely hopeful: the retailer runs the ads and hopes that shoppers come to the store. If it all works, that’s great, but if retailers do not see increased sales of the product promoted, they may never know why.
With a view of how many customers entered the promotional zone and engaged with the product, combined with sales for that product, marketing professionals can see the actual impact of their campaigns. They also will have the ability to troubleshoot.
Quantifying what’s going on in-store allows the marketing team to see the impact of its campaigns, in real time, and make small tweaks that turn browsers into buyers.
Merchandising ― Know Where Your Browsers Go
Retail merchandisers love the ability to know where customers go and with what they engage. Imagine the power of witnessing a 300% difference in browsers between the busiest and next busiest branded promotion area, and what that means in terms of the relative value of that space.
Visual customer intelligence puts power into the hands of the merchandising team that it’s never before experienced.
For example, one customer was concerned when a heavily promoted product was not selling as well as expected. Analysis of in-store traffic flow and engagement data revealed that the product was located in a promotional zone where only 4% of shoppers ever ventured. The product was moved to an area that recorded high traffic regularly, with a subsequent sales uplift for that product of 35% over other stores in the chain. Once the adjustment was proven, other stores also could solve the problem of browsers who weren’t buying because they couldn’t find the product.
Knowing your browsers ― how many there are and where, when and with what they engage ― provides brick-and-mortar retailers a powerful arsenal in the battle for buyers.
Kevin Blackmore, Consumer Insights and GM of Europe for LightHaus, helps LightHaus retail clients improve their business profitability and their customers’ overall store experience. Blackmore brings 20 years of experience in retail, technology, consumer and marketing insights and analytics to his role at LightHaus. Previously Blackmore was responsible for Customer Insight Strategy and Analytics at Best Buy, one of the world’s largest consumer electronics and customer-centric retailers.
