With inadequate data management practices, many retailers are having trouble meeting their marketing objectives, finds new research. Although these martech leaders put acquiring new customers and improving customer experience at the top of their list of goals, they’re not actually able to spend enough time working directly to reach them. To combat this problem, first and foremost, they need to get more from their martech stack.
A newly released study from Forrester Consulting, “Align Technology, Data, And Your Organization To Deliver Customer Value,” commissioned by Bluecore, is based on the results of a survey conducted with 307 martech decision-makers at retailers in the U.S. and Europe. When ranking their three top marketing priorities for 2020, 45% of these decision-makers said that winning new customers is one of their three most important business objectives, followed by customer experience (39%). However, only 21% and 20% said they are actually effective at hitting these goals, respectively.
Additionally, the study focused particularly on the importance of both personalization and omnichannel experiences, with omnichannel involving “the coordination of traditional channels (marketing, selling, fulfillment) and supporting systems to create a seamless and consistent customer experience from discovery to purchase.” However, according to the survey results, 12% said they are “very effective” at providing “personalized experiences” for customers, and 30% said they are “very effective” at “driving seamless and consistent omnichannel experiences” for customers.
So, where are they going wrong? The research points to a “two-sided issue” facing retail marketers: They have so much data, but there’s so much they need to do in order to make sense of it. As the study puts it, although they are “awash in rich sources of data and insight,” they still must “clean, process, align, share and turn all this data into actionable insights.”
In turn, data management, according to Forrester, has turned out to be a “major sticking point” for retail marketers, with only 13% of the respondents saying they are “very confident in their organizations’ data hygiene and reconciliation capabilities” and only 16% believing they “excel at data aggregation.”
In the end, retail marketers are stuck: “It’s impossible to effectively deliver relevant, personalized experiences where and when customers need them if they can’t understand what their customers’ engagement and shopping behaviors are saying,” the study explains.
Getting more from martech
Forrester, noting that deficiencies in marketing technology “often tie back to problems with data management,” says that even though managing customer data has always been challenging for marketers, the problem is only compounding as “data sources proliferate and complexity grows exponentially.” In turn, retail marketers simply need more from their martech stack, the study suggests.
In fact, when asked how well their current martech supports their key marketing objectives, only 35% and 25% of the survey respondents said it improves their top objectives of improving the customer experience and winning new customers, respectively.
Clearly, that just won’t cut it. To address this problem, the study points to the challenge retailers have with organizational silos. When retailers need to manage data across all different segments – e.g., customer, sales and product engagement – tasks are often delegated to IT resources, who end up with too much on their plate. In the end, “ultimate accountability for data management” ends up being too fragmented, says Forrester.
Instead, they need to tear down silos, bringing their data into one place. In the end, marketers have visibility into what’s happening and a way to collaborate and share successes across the organization (new customers, anyone?).
Time after time
Furthermore, the study points to another issue: time, or rather, lack thereof.
The survey, polling 178 IT martech decision-makers from retail enterprises, asked how much time they or their team spends each week on “building data integrations and cleaning tasks for marketing.” Forty-two percent said 5-10 hours, 23% said 10-20 hours, 21% said under 5 hours, 13% said more than 20 hours and 1% didn’t know.
Almost two-thirds of the respondents – whose resources are often “spread too thin to help marketers operate in real time” – spend only 10 hours at most each week on these “critical enablement tasks,” thus “creating a bottleneck on data insights required to power relevant customer experiences.” In the end, this lack of effective data management ties back to the original problem: that retailers cannot fulfill their top marking priorities.
On a similar note, retail marketers in the study found they are spending far too much time waiting for tasks to be completed. A whopping 78% of respondents said they have to wait several days (42%) to a week (33%) for their campaign or audience data requests to be completed after submission. On the other hand, only 10% said near-real-time to a few hours.
“Needless to say, this isn’t a situation that supports real-time customer value,” says Forrester.
Instead, retail marketing leaders’ technology must be able to filter their data so that they can better visualize all of the information and make sense of it. Someone still has to perform an analysis of the data, of course, but if it has already been translated into analytics that allow marketers to see better see actionable insights right off the bat, they can start to make use of the analytics in real time.
In turn, having real-time analytics can lead to better personalization, for example – one of retail marketers’ top priorities. Personalized marketing is most effective when it incorporates detailed data on exactly where prospects are in the buyer’s journey in real time, allowing marketers to act quickly in response to a new touchpoint. When they have the ability to see a prospect is actively looking for a product they’re able to provide, they can push out the right content for them at the right time, leading to (hopefully) a new customer win.
The data usage doesn’t end with personalization insights and improved timing; in fact, it should feed all the way through to planning and strategy efforts, informing product marketers, demand gen leaders, and customer advocacy and operations so that proper segmentation can be established, enabling plans to be balanced according to a set of relevant achievable goals. This is where Hive9 can help! Contact us with more questions or request a demo anytime.