Which data capabilities are still out of reach for marketers?

Photo: Getty Images/gorodenkoff
Aug 18, 2022

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.

Fewer than four in 10 marketing leaders are extremely (12 percent) or very (26 percent) confident in their data, analytics and insights systems, according to a study from the CMO Council and GfK. The report outlines the data capabilities that remain “out of reach” for marketers.

Based on a survey of more than 300 marketing leaders across industries and geographies, the report reveals that the data capability most out of reach for marketers is real-time availability of insights, cited by 42 percent of respondents. Real-time marketing is dependent on rapidly accessible data and actionable insights, which many marketers are lacking. To wit, even among the top data marketing performers in the study (dubbed “top performers”), fewer than half described the amount of time it takes to move from data gathering to actionable insights as fast or immediate. Worse still, just seven percent of “bottom performers” could say the same.

Furthermore, only around one in four top performers had real-time access to all relevant points of customer insight and data from across the entire organization as well as external partners and third parties.

Perhaps not surprisingly, when top performers were asked which data capabilities they are improving over the next 12 months, a leading 67 percent said real-time availability of insights.

Other data capabilities top performers are seeking to improve include the extraction of data signals across channels (64 percent), data-driven CX (56 percent) and predictive analytics (50 percent). Predictive analytics was also singled out as “out of reach” by four in 10 respondents.

Meanwhile, with access to data being a key differentiator between top and bottom performers — and one of the hallmarks of being a data-driven organization — the report reveals the main barriers to data access. The leading response overall was insufficient tools/technology, as indicated by almost three-quarters (73 percent) of respondents. The second-biggest obstacle was the lack of data management processes, as noted by six in 10 respondents, with other significant challenges including data control lying elsewhere in the organization and data not being real-time (each at 41 percent of respondents).

DISCUSSION QUESTIONS: What’s causing the lag between data gathering and generating actionable insights? Which technologies or processes offer the most promise to elevate data-driven marketing?

Please practice The RetailWire Golden Rule when submitting your comments.
"Simplification is underrated."
"Rarely do I see execution systems that are able to consume the results of the analytics team’s recommendations."
"Two keys come to mind that are likely root causes of the lag between data gathering and insights — Data Governance & Focus."

Join the Discussion!

12 Comments on "Which data capabilities are still out of reach for marketers?"

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Mark Ryski

It’s curious how these challenges have persisted for many years, if not decades – despite the fact that there’s more data and tools available to marketers than ever before. Extracting insight from data that connects to business outcomes is just simply hard to do. This is exacerbated by a couple of years where the trends in the data appear utterly anomalous because of store closures and other pandemic-related tumult. Ultimately, marketers need to focus on the critical few metrics that inform decisions and reduce or eliminate the many other metrics that provide only nominal insight. Simplification is underrated.

Ken Morris

For retailers, “real-time availability of insights” translates to “tell me now what I’m doing right and wrong.” Unfortunately, garbage-in/garbage-out is par for the course. The real fix is to wire in-store activity to pick up and relay meaningful signals to retailers immediately, just like online does already.

Silos of data that end up getting batched and cobbled together at the end of the day? This is the problem for omni-channel retailers. POS is almost always an on-premise solution that doesn’t update until a day after the sale. A day late and sometimes a dollar short. Real-time like Amazon is where they must be. 

Dr. Stephen Needel

There is an assumption that data contains actionable insights. More often than not, that is not true. Data might be good for monitoring the “current” state of a business and the right data combined with the right analyst may be able to answer a marketing questions in a way that’s useful. The lag is caused by high expectations with no good reason to hold those expectations.

Melissa Minkow

Data is different from insights in that insights require interpretation of data, so there will always be at least a slight lag between gathering data and deriving actionable insights from it. However building smart data visualization tools as part of the data strategy is key to allowing teams to quickly understand the story the data tell. With regards to accessing data, we see this often as a massive struggle for retailers, as a lot of data is collected without an entry point into seeing said data and using it. In most cases of this happening, additional technology will have to be added to the system in order to allow for data access. Until retailers get that access layer built out, some data will inevitably be trapped in a way where they can’t use it.

Dion Kenney
5 months 20 days ago

There are at least two factors impacting how actionable marketers’ data is, both of which suffer from inertial resistance to change: good tools that are both powerful and user-friendly, and the learning curve inherent in building a sublimated understanding of what the data says. The lack of tools is particularly surprising. Despite the remarkable improvements in technology, all of the fundamental components – databases, analytic algorithms, bandwidth, user interfaces, etc. – have been around for ages.

But perhaps more glaring is marketers’ failure to intuitively understand the meaning and nuance of the data at the same unconscious and intuitive level that a jazz musician understands music. It is becoming an increasingly complex world, and if you can’t improvise you should think twice about climbing on the bandstand!

David Spear
Becoming a data-driven company doesn’t start with some small skunk project led by an entry-level data scientist. It starts at the top with a strategic decision made by the C-suite, namely, the CEO, who realizes no matter the industry in which they operate, data is one of the most precious assets within the enterprise and everything they do must flow from insights uncovered by the enterprise. Top to bottom, everyone needs to maintain a data mindset, and a culture that oozes data, data, data. Data strategy and workable architecture with a company’s tech stack become critical to enabling insights, whether batch or more real-time. This is where another C-suite exec, the chief data/analytics officer, plays a key role in developing the right strategy so data pipelines can deliver the data at the right time, right place, and to the right person/group. A key challenge that nearly all companies face is the ability to integrate many sources of disparate data held in silos across the company. Another challenge is the the type of analytics platform (tools/technologies)… Read more »
Jenn McMillen

While the optimal state for data is 100 percent real-time and actionable, companies need to get comfortable with the idea that 80 percent is OK, and it’s never going to be 100 percent perfect. If you wait that long, the opportunity to leverage it is likely long gone. Patience may be a virtue but not in the actionable insights arena.

Gary Sankary

This gap between insights and action is prevalent across retail, not just in marketing. I believe that one of the main issues at play is a disconnect between the analytics teams, their tools and information products, and the execution teams. Specifically, the systems and applications they use to implement their strategies. Rarely do I see execution systems that are able to consume the results of the analytics team’s recommendations. Often acting on those results requires manual intervention, which at scale, never really happens.

Retail IT professionals should spend more time integrating disparate tools and data that analysts and the folks in the positions that are “doing the work” are using to execute their jobs. It would also be helpful if the analytics teams did a little less chasing of shiny new analysis and worked to get more ROI out of their existing suite of applications.

That would give the execution teams a bit of stability to build and implement strategies around their recommendations.

Joan Treistman

You have to know what will give you actionable insights and use the software or create it to give you data you can then interpret to deliver insights. I agree with Stephen that numbers aren’t insights. It takes interpretation of the data within the framework of needed information and marketing goals to deliver insights. For a long time, I’ve thought that many marketers are keen on the idea of having a dashboard at their fingertips, a dashboard that will produce whatever they need when they need it. The article suggests that’s what they are still looking for.

Di Di Chan

The technology is here already. Data gathering isn’t the issue. Generating actionable insights takes a while because it involves operational changes, and most retailers don’t have enough bandwidth to change quickly.
It typically takes about five to ten years to incorporate new technologies into everyday retail business practice.

Brian Cluster
Two keys come to mind that are likely root causes of the lag between data gathering and insights — Data Governance & Focus. Retail has changed in the last few years as more e-commerce, emerging digital channels, social media, and RMN data are now joining the traditional in-store set of data for marketers. Data Governance is key here as this data needs to be brought into the organization, understood, classified, attributed, and finally delivered in a process-driven way to the BI tools for analysis/dashboarding. Marketers not only need to be data-driven but also data-enabled. Agreements need to be made about different data sets between departments regarding the current use and plan to make the data more accurate, trustworthy, and valuable. Marketers need to focus on their top use cases and work across the organization to increase the speed, quality of insights, and ROI of the work that they do. A unified data model may help ensure that everyone is on the same page: referring to the same hierarchies, locations, and channels and talking about customers… Read more »
Oliver Guy

The biggest cause of lag has to be the technology — there are so many examples you can see where organisations are attempting to collect data, but getting it to the decision makers in time to make specific choices simply takes too long. It typically ends up as part of a retrospective report.

Change management too, however, plays a part in terms of individuals like merchandisers may want to control things themselves and do not necessarily trust the insight the data might provide.

"Simplification is underrated."
"Rarely do I see execution systems that are able to consume the results of the analytics team’s recommendations."
"Two keys come to mind that are likely root causes of the lag between data gathering and insights — Data Governance & Focus."

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