Getting into consumers’ heads is the most mind-boggling part of merchandising today.
Both brands and retailers continue to ramp up on the technology that will enable them to harness and analyze consumer data with the hope of ensuring the right products are in the right stores when shoppers want them most.
“Companies are realizing that to succeed in today’s highly competitive, omnichannel market, leveraging big data and predictive analytics will not just be necessary, but a requirement,” according to supply chain planning and execution solutions company JDA. “This type of data provides companies with greater insights into their consumers’ preferences and behaviors, enabling companies to provide more localized assortments and better meet their shoppers’ needs.”
The JDA Voice of the Category Manager survey tapped about 100 category and merchandising managers on both the brand and retail side to determine the degree to which they’re able to use customer data to create better product assortments.
The good news is the vast majority of respondents (81 percent) say their companies are at least average or better at piecing together data to generate usable insights.
But when asked to identify areas in which their companies are lagging behind, 70 percent said predictive analytics, which means they’re not able to crunch the numbers to develop sharper pricing and make better decisions.
Almost 60 percent also acknowledged a skills gap when it came to leveraging the geographic and socioeconomic data needed to create targeted promotions and offers.
Respondents also identified recognizing consumer preferences within the data (about 45 percent) and maintaining loyalty programs (about 27 percent) as areas where their peers might have an edge.
The goal for many of those polled is to get to the point at which data is directing their merchandising plans at a store level.
To do so, they’ll need the ability to create a fuller picture of their customers. Sixty-seven percent of the companies are eager to gain more insight around the path to discovery, and 53 percent identified shoppers’ price sensitivity as a behavior they’d want more information on as well.
“The modern shopper has changed the game for both retailers and manufacturers. Getting merchandise assortments right the first time is crucial to shopper satisfaction, as well as profitability,” JDA said. “Effective assortment localization is dependent on a company’s ability to identify the key product attributes or specific characteristics that drive local preferences and demand in each category.”
Nearly 70 percent of those polled said personalization and localization are a top priority for the coming year, and for 37 percent they’ll know they’ve been successful when sales increase. For another 21 percent the measurement of success will be determined by the level of visibility they have into stores and for an equal number of respondents, better inventory levels will tell the tale.
With the ability to customize assortments by stores comes the question of how this affects planograms in each location. While most respondents say that having stores comply with corporate planograms is essential, 47 percent say stores have more leeway today due to localization. In some cases, stores are empowered to make their own decisions, while in others the home office provides multiple options from which store managers can choose.
As localization matures, respondents say further changes to compliance rules are likely. Thirty-eight percent foresee a need for more corporate resources in the next five years, while 28 percent envision companies creating smaller regions that will each have their own customized planograms. Another 27 percent anticipate stores gaining more control in this area.
Looking ahead, the companies represented in the report plan to make strides with new technology to further their ability to use automation to do more with less (53 percent), gain consumer insights (48 percent) and translate assortment decisions into space plans (44 percent).
To achieve these goals, 41 percent report that big data/predicitive analytics tops their investment priorities followed by customer-driven data science at 37 percent and automation at 21 percent.