It’s a hyper-competitive world for retailers as well as their CPG manufacturing partners. By collaborating better and aligning their goals around shopper needs, the two trading partners can better tap the potential of big data and predictive analytics.
Delivering a meaningful and differentiated shopping experience is a complex journey, not simply a destination. Luckily, it’s a journey that retailers don’t have to travel alone.
It’s challenging to incorporate the shopper into every aspect of the decision-making process around price, promotion, assortment and personalized marketing, particularly when you consider the intense pressure retailers experience in a margin-squeezed, hyper-competitive marketplace. But there’s great asset that can be leveraged by enhancing collaboration with trading partners – an opportunity that retailers need to take advantage of.
In fact, through primary research focused on customer-centricity, Precima found that only 29% of CPG manufacturers say they think retailers use shopper data frequently. Clearly, there is plenty of potential for retailers and suppliers to capitalize better on the full promise of big data to build a more shopper-centric approach.
As I outlined in a chapter of “The Little Book of Big Data,” by the Shopper Technology Institute, rather than viewing big data as one more hurdle to be managed, as many in the industry do, it should be embraced as a valuable asset to understand individual customer needs more completely. When the data is captured and analyzed in a timely and consistent manner, it helps retailers drive a shopper-centric strategy; provide personalized, omnichannel communications; and inform their price, promotion and assortment decisions with shopper insights. When retailers take a shopper-centric collaboration approach with suppliers, it magnifies the benefits by aligning each supplier’s resources with the needs of the specific consumers that shop with the individual retailer.
Armed with the right data – including shopper analytics, marketing analytics and merchandising analytics – retailers can make better decisions. Those choices include when and what to promote, where to make investments to disproportionately improve price perception, how best to allocate finite macro and micro space, which items can safely be taken out of the mix without affecting sales of other items, the smartest way to use coupons and special offers, and many more.
Smart use of data also provides retailers and manufacturers with critical insight into the potential value of each individual shopper by category and enables them to work together to capture a greater share of spend.
Too often, retailers and CPG manufacturers invest in big data initiatives but then fail to leverage the efforts across their respective organizations to make better shopper-centric decisions. It’s critical that the insights are made available to decision-makers, in the context of their individual roles, so they can be turned into actions that drive top-line and bottom-line growth. For the retailer, this approach should embrace the merchandising, marketing and store operations teams to make better category, shopper marketing and store planning and investment decisions. For the manufacturer, this approach should be leveraged across sales, marketing and consumer teams to make better trade, consumer and brand marketing decisions.
Employing predictive analytics puts relevant insights into the hands of those decision-makers to inform their choices in a timely fashion. Going a step further, leveraging prescriptive analytics provides decision-makers with actionable recommendations that translate insights into actions that will capture increased value.
One of the many ways retailers and manufacturing partners can work together to deliver on the potential of big data is by better evaluating the promotions they design together. Big data allows the two parties to identify which promotions are performing well, which can be improved and which should be terminated. In this manner, they’re able to gather the right items to promote, the best discounts to offer and the most appropriate allocation of merchandising support. At Precima, we have found this can lead to dramatic performance improvements, with our clients seeing increases of 3% to 6% for promoted sales and 5% to 10% for promoted gross profits.
An area of increasing importance is personalized marketing. Too often retailers and manufacturers are pursuing their own approaches to personalized marketing, resulting in inefficiencies and suboptimal results. Retail and CPG manufacturers can tap the power of collaboration and data to deliver improved response rates, incremental sales and greater scale to the mutual benefit of shoppers, retailers and manufacturers.
There’s intense pressure on retailers and manufacturers these days. With limited resources, seemingly unlimited competition and ever-evolving consumer needs, they must make tough decisions about which areas of the business make the most sense for investment to connect best with their most loyal shoppers. After all, one reality of retailing has not changed: The retailers that best satisfy the needs of shoppers will win.
Big data and predictive analytics, when done right, give retailers and manufacturers power unlike any they’ve known before to understand the needs of shoppers and then determine actions to satisfy those needs better than the competition. When they prioritize better collaboration, retailers and CPG manufacturers together can execute a best-in-class shopper-centric strategy that most effectively leverages their collective investments across the value chain.
Better yet, becoming shopper-centric and delivering on the full promise of big data won’t take years to happen. Retailers, when asked, predicted it would take four years to reach that goal, but our recent experience shows it takes less than a year to start implementing strategy and tactics and seeing results.