Why is gaining meaningful insights from data still so hard?

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Mar 17, 2021
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MarketingCharts staff

Through a special arrangement, presented here for discussion is a summary of articles from MarketingCharts, which provides up-to-the-minute data and research to marketers.

Half of the marketing, information and marketing tech professionals surveyed in the UK and U.S. for a report from Merkle state that their organization’s data is not organized for easy consumption, making it the most common technical barrier to deriving meaningful insights.

Other barriers include limited storage, cited by 39 percent; slow data analytics processes, 38 percent; the inability to understand what data is most important to decision-makers, 38 percent; data integration hurdles, 38 percent; and data being stored in disparate systems, 35 percent.

Forty-one percent of respondents say they do not have a single customer profile, even though 89 percent agree that creating a consolidated customer profile is very or extremely important. The inability to capture a single customer view also comes despite 81 percent of U.S. respondents reporting they have a CRM and two-thirds having a customer data platform.

What’s standing in the way? For one thing, technology spend doesn’t seem to be a limiting factor. Some 38 percent of U.S. respondents report allocating 21-25 percent of their marketing technology spend to identity-based solutions, while 27 percent allocate 16-20 percent.

Instead, it’s more likely to be a lack of expertise and skills. Data and analytics is not only currently a valued skillset but is expected to remain so in the future. Nonetheless, close to half (46 percent) of U.S. respondents have run into a lack of data and analytics expertise within their organization when trying to implement a data and analytics solution.

Additionally, many have encountered limitations in gaining consensus among stakeholders (46 percent) or a lack of an agile implementation partner to support changing business and time to market requirements (44 percent).

Finally, although IT is said to no longer be a detractor to marketing, the Merkle report suggests it is still more likely to be in control — finding that IT (56 percent) is more likely than marketing (34 percent) to allocate more than 20 percent on martech spend to identity-based solutions.

DISCUSSION QUESTIONS: What do you see as the biggest barriers to using customer data effectively and creating a single customer view? Is the primary challenge resources, competencies, organizational, shared vision or something else?

Please practice The RetailWire Golden Rule when submitting your comments.
Braintrust
"Using data is only as good as the questions that you are seeking to answer."
"First, let me say that insights without predictive value are empty calories. You must have an eye towards prediction or activation for an insight to really have meaning."
"Competencies are the biggest barrier. This includes the will to get things done, ability to overcome legacy methods of doing things, and lack of accountability."

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45 Comments on "Why is gaining meaningful insights from data still so hard?"


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David Naumann
BrainTrust

The greatest challenge for many brands in achieving a comprehensive, single view of the customer is disparate data that isn’t connected in real-time. Data silos for omnichannel retailers has been an ongoing barrier to attain a 360 degree view of customer data. Using a consistent customer identification methodology across all channels is key to recognizing individual customers. Ideally, retailers should adopt a unified commerce platform to keep all data on the same platform for one version of the truth and easy access to data. This would alleviate the top challenge noted in the Merkle report – organizational data is not organized for easy consumption.

Joel Goldstein
BrainTrust

Using data is only as good as the questions that you are seeking to answer. If you’re looking to learn the gender or age range of those purchasing from your store, data can be your best friend. However if you’re trying to build a psychological profile when deciding which colors to use it is a much more challenging prospect as the data may not be easily correlated.

Jeff Sward
BrainTrust

Great way to put it. Data easily answers the question of “What is the best seller?” Easy question … easy answer. The not so easy question is “WHY is that item a best seller?” Style, fabric, color trim…? Movie star posted it on Instagram last week? And even if you know the WHY, then what is the shelf life of the data? A week? A season? Do I re-order, or try to be smarter next time…?

Joel Goldstein
BrainTrust

Thank you Jeff.

Christine Russo
BrainTrust

This is NUTS! Data is such a critical component of future success and access to both forward looking sentiment and rearview history is easier and more affordable than ever. Perhaps this is a factor of an old-guard management point of view. But then change must come, and quickly. Subscription models to data or simply pay for play outfits like Piplsay or Prosper Insights make access to the information easy.

NAVJIT BHASIN
Guest

Christine, I totally agree! Lack of internal data scientists should not stop anyone from gleaning customer insights. In order for data to solve problems, it needs to be unified into a single version of the truth, distilled to the most meaningful insights, and provide corrective actions. Decision intelligence is going to be the the next wave of retail transformation.

Dr. Stephen Needel
BrainTrust

Two thoughts. First, the assumption that a single customer view exists may be a flawed concept. Your business may appeal to multiple customer cohorts – think Walmart, which is both historically downscale yet upscale chic. Second, what keeps businesses from using data effectively is usually competence, and that’s only getting worse as crap AI and poor modeling skills invade marketing.

Cathy Hotka
BrainTrust

Participants in the VP IT Council meeting repeatedly referred to inadequate data use as an ongoing issue. Despite access to multiple data analysis systems, many retailers just don’t adequately benefit from the data they collect, in part because of an absence of vision. 2021 may be the year that we begin to turn the corner on this.

NAVJIT BHASIN
Guest

Cathy – we have been hearing of retailers calling themselves “data driven” for a long time now. But to remain competitive and ahead of the pack, they will be forced to make it happen soon.

Cathy Hotka
BrainTrust

This is the year!

Ken Morris
BrainTrust

I believe the primary barrier is organization and infrastructure. We have marketing folks in charge of technology which they are not trained to do and we have silos of data controlled by IT and in turn by finance who control the budget. We need data normalization. We need to rid ourselves of these islands of customer data and create a holistic plan to brings these separate data lakes under one umbrella and fund the initiative appropriately. The retail world runs on hard dollar savings and what we need here is infrastructure which has soft savings at best. Retailers need to organize technology under technologists, invest in the technology to obtain the 360 degree view of the customer and invest in data scientists under the control of the CMO.

Gary Sankary
BrainTrust

Ken, well said. They also need to empower their teams teams with tools that can use this data to improve execution.

Michael Terpkosh
BrainTrust

To start, in many retail organizations there are multiple sources of data that don’t work well together. Loyalty data, POS data, and syndicated data, to name a few. Each of these sources of data may be stored in different locations and not stitched together to create a holistic view of the retailer’s business or the shopper. When an organization can get to the point of bringing all the data together, the skills of the retailer’s merchandising and marketing teams become critical. Plus, there are competing views of how to execute against any insights. There needs to be retailer vision bringing the data, associates and analytical insights together. Only then can you get to efficient and effective strategies and tactics to execute at retail.

Suresh Chaganti
BrainTrust

Based on what I have seen, the true barrier is the lack of belief in what data-driven decision-making can do. But that is perpetuated by lack of skills in the organization that bridge data and business.

There are plenty of tools in the marketplace. The costs have come down significantly. There is no dearth of data either – tons of first-party data, huge volumes of syndicated and macro data.

But the premium is still on human resources who can make sense of it, and leadership who encourages that.

Gary Sankary
BrainTrust

I would suggest that while there are lots of data analytics tools out there, we still have a gap in the automation and execution tools that inform the tools that front-line workers are using to make their daily decisions. That’s where I see the bottleneck.

Mohamed Amer
BrainTrust

It’s not one thing but a confluence of reasons that also vary by a retailer’s data maturity. Having to choose the biggest hurdle, I suggest that data silos are the common challenge that is, in part, a reflection of the retailer’s organization and the changing priorities over time.

Venky Ramesh
BrainTrust

Last year I interviewed several CPG executives as part of the Capgemini Research Institute survey on Data Powered Enterprises. We found that while everyone understood the importance of data and analytics to the success of their business, less than 40 percent of organizations used data-driven insights to drive business value and innovation. One key reason for that we found was business executives do not trust the data they receive. 62 percent of technology executives believed the business trusted their data while only 20 percent of business executives agreed. The two key reasons for that lack of trust were – quality of data and lack of alignment to business strategy. The complete report can be accessed here.

Gene Detroyer
BrainTrust

That is interesting … “lack of alignment to business strategy.” Does that mean the data is suggesting the business strategy is wrong and the executives don’t like the indications? The data should suggest the direction of the strategy.