24
Future of Retail — Omnichannel
issue 07
“As we enter a new era of blending online and offline insights, a much richer understanding of customer demand becomes possible.”
DATA SETS DRIVING PROFITABILITY What has changed about attitudes to shopping today is that consumers crave a seamless and compelling customer experience across all channels. And this is where traffic analytics, fused with other data sets, can become so powerful. As mentioned earlier, combined data
sets can make it easier for retailers to plan inventory in line with predicted demand. Retailers preparing for peak seasonal events can factor in demographic, and historic cross-channel sales and traffic patterns to amplify the opportunity. With these insights, marketing, merchandise ranges and stock availability can be primed to maximise conversions of local, high-value shopper groups. Staff scheduling can be optimised too.
By planning staff schedules around traffic trend data, demographic and weather data, retailers are mobilising teams for when the weather will bring in more visitors and therefore opportunities to sell. Likewise, store teams know they will be better prepared to tackle other projects on days where predicted weather will reduce foot traffic. Local demographics, working alongside traffic data can help with seasonal inventory management, product selection, loss prevention, stock control, returns management and logistics. ‘Power hours’ – when sales peak in stores
– can be identified and meticulously planned for. So, if Saturday 3pm to 4pm is a fashion retailer’s power hour, that retailer can begin to scope out which are the most popular, or high value items local shopper groups should be channelled towards with layout and promotions. A predictive model for inventory management can then be built, based on these confirmed demand patterns.
Looking ahead, RFID tags, particularly in
the clothing sector, will contribute another highly valuable data set. Retailers will learn which items are tried on but abandoned at the fitting room, for instance, and make decisions on replenishment across all channels, based on the movement of tagged items around the store. Face recognition technology is coming too. There’s every likelihood that retailers will use this technology to better understand who is in their store, and their sentiment while there. When a new product range has landed, will frowns or smiles be picked up by cameras, for example? Could offline returns be reduced if these in-store learnings are acted upon?
INSIGHT IS EVERYTHING As we enter a new era of blending online and offline insights, a much richer understanding of customer demand becomes possible. Traffic data insights, working alongside demographic data, weather data, web traffic data, POS and staffing data, will make this possible. Retailers making a success of this tend
to be those with top-level commitment to turning data insights into actions that can be fed down across the organisation. This might take the form of store-level ‘action points’ delivered from a centralised analytics team, that can be easily implemented, and scaled if necessary. By ensuring data insight is top of mind at head office, and that the process of putting it to use is democratised, with results and learnings shared and celebrated, business wins are more likely to come through. In other words, an analytics-driven strategy
must be embedded fully before it can do its job of helping retailers optimise their store investments, win the shopper, and drive sales. But it will be well worth the trouble. As Goethe famously said, there is nothing so terrible as activity without insight.
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