Retail Inventory Challenges? Solve Them with Behavioral and Interest Data

Over the last two years, retail has done well as a sector, growing an estimated 6.7% in 2020, “well above the five-year average of 4.4%.”, according to the National Retail Federation (NRF).  In June the NRF raised their forecast for 2021 to $4.44 trillion, which is a 10.5% to 12.5% growth.

Nevertheless, challenges remain, including customer acquisition and loyalty. A single out-of-stock experience can send a third of a brand’s customers to competitors’ cash registers. Consumers are also going multichannel. While 96% of Americans are using online shopping, they’re spending 65% of their total shopping budget in traditional brick-and-mortar locations. Fortunately, online behavioral data and interest scores are effective digital marketing tools that brands can use to optimize campaigns and meet these challenges.

What Is Online Behavioral and Interest Data? 

Online behavioral data is real-time data that is based on online content consumption and engagement, such as site visits, link clicks, and articles shared. Interest scores measure a consumer’s level of engagement and interest compared to the general population.

Interest Scores measure a consumer's level of engagement compared to the general population

This data is deterministic, and thus predictive. The full picture of consumer identity includes behavior, which changes over time as people’s interests and needs fluctuate. Marketers must consider real-time behavioral data as a criteria when evaluating data providers to ultimately deliver high-quality business results.

Let’s Look at Two Scenarios

A major clothing retailer has an inventory problem

The retailer does not have popular products available and in the sizes customers want—negative online reviews are piling up. It needs to predict and forecast customer purchase intent so that inventory is restocked to meet demand proactively.

Fortunately, the clothing retailer has access to daily zip level data showing which zip codes are advertising 30% off coupon promotions. ShareThis can create and provide the retailer with daily Category Interest Scores, representing a consumer’s interest in things like athletic apparel or footwear. ShareThis can also create and provide Brand Affinity Interest Scores—measuring a customer’s interest in the international clothing retailer itself—for those same zip codes. 

With all of these data points, ShareThis can calculate a derived purchase intent score for each zip code. By following it day-by-day, the international clothing retailer can use this purchase intent score as a predictive variable to anticipate when demand may spike, and therefore optimize supply and delivery schedules to get ahead of inventory demands.

You can more easily anticipate inventory demands by analyzing online interest and engagement

A home decor brand has an email personalization challenge 

The brand wants to personalize its campaign emails to improve performance and optimize its diverse customer base—ranging from designers and wedding planners to happy couples and homemakers of all sizes. They’ve designed four email campaigns focused on these signature areas to address trending preferences. 

The home decor brand provides ShareThis with a long list of customers. ShareThis analyzes each customer against a list of home furnishings and design categories that align with the brand’s objectives and assigns a Category Interest Score to each customer based on topic consumption and frequency of engagement. 

The brand then places each customer in the appropriate email campaign. It can also analyze the data to identify emerging trends in fabric design, furnishing material preferences, and color preferences to inform product development.

You can personalize campaign messaging based on behavioral data such as online engagement with products

Using behavioral and interest data to optimize thorny inventory challenges and email personalization can be an effective strategy, and only two examples in a range of applications for this type of data. And the range and depth will continue to grow as technology helps marketers unlock treasure troves of consumer behaviors, interests, and intent.

Retail is growing by as much as 12.5% in this last year alone. Challenges are as well, especially around customer acquisition and loyalty, but real-time consumer interest data can help. Combining this type of data with proprietary 1st party data can yield predictable next steps and solutions that deliver astronomical business results.

About ShareThis

ShareThis has unlocked the power of global digital behavior by synthesizing social share, interest, and intent data since 2007. Powered by consumer behavior on over three million global domains, ShareThis observes real-time actions from real people on real digital destinations.

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