Data Waste Is Putting Retail Loyalty at Risk — Here’s Why
Retail marketers are grappling with plenty of challenges in 2023. Data waste isn’t one of them. For most marketers, data wastage is at the bottom of the list in terms of global importance, far below issues like evolving privacy regulations and the looming death of third-party cookies. Treasure Data’s Zack Wenthe thinks that’s a mistake.
According to Wenthe, data wastage — the efficient or ineffective use of data — has become a common blight among brands in all industries, and especially those in the retail, automotive, CPG, and entertainment spaces.
“Data wastage comes in a variety of forms from data sources such as customer service, sales, or operations departments,” Wenthe says. “[It] is usually the result of a collection of unnecessary data, withholding relevant data from the right team, or failure to analyze or action on the data that has been collected.”
While it’s not always easy to identify data wastage, Wenthe says time spent managing customer data collections is often the main culprit. According to Gartner, data inefficiencies can end up costing organizations an average of $12.9 million per year — a huge chunk of change for just about any company to lose.
“This issue is important for any brand where their data remains disjointed and unable to interact with one another,” Wenthe says.
Given the influx of data coming through new channels and departments, including customer service, sales, and operations, it’s no surprise to hear that retail brands right now are struggling. Despite widespread growth in data maturity, Wenthe says the constant influx means retail marketers often feel ill-equipped to get the most out of their data in a timely manner.
Even worse, since c-suite executives may not realize certain data sources exist, data wastage can be hard to diagnose.
“In most cases, retail marketers can easily recognize data duplication, but it’s the more subtle cases — for instance, when a data set is used for a particular purpose and then the underlying data is discarded or no access to tools to extract any usable intelligence are available — where data wastage becomes a ghastly time, resource, and financial suck,” Wenthe says.
Loyalty Is at Risk
Not only is data wastage among retail marketers putting customer loyalty at risk, but Wenthe says it’s also the cause of low marketing return on investment, as well as decreased revenue and business insights that can be useful to other parts of the enterprise.
“As an example, post-COVID shopping behaviors are similar to those seen at the height of the pandemic, as consumers still enjoy online shopping — but they’re also returning to physical store locations,” Wenthe says. “Retailers now need to connect shoppers’ experiences across digital and physical channels so they can easily engage buyers throughout their entire path-to-purchase.”
Retailers can’t afford to leave any customer data on the table — unused or wasted — and they need to be better about understanding their customers in order to increase acquisition, improve customer retention and loyalty, boost customer lifetime value, and reduce marketing costs.
“When retailers don’t have access to actionable data insights, they risk operating at a severe disadvantage in the marketplace,” Wenthe says.
Wenthe encourages enterprises to develop best practices in data management that allow for a constant audit of data workflows so they can identify data wastage. This can begin with setting rules for data collection to ensure that only relevant data is gathered and filtered. Consistent monitoring of data usage is also helpful in sourcing underused data.
“Measuring time management of data maintenance can also inform brands of inefficiency hidden within their data,” Wenthe says. “It’s a clear red flag if a marketing manager is spending more than 10 hours each week in customer data management.”
Sophisticated data governance tools are available to allow marketing, customer support, sales, and IT teams to access and analyze the same data in real-time. Adopting these tools should help curb data wastage, while establishing data governance policies and protocols, such as data hygiene checks and data origin tracking.
“It is easy for a business to just accept data inefficiencies as part of the process, but these inefficiencies truly have a negative impact on their bottom line and future potential,” Wenthe says. “Businesses now need to begin addressing this type of loss, and once they do, they will start to uncover more opportunities with their data and business models.”