Making Sense of Marketing Clouds

By Nielsen Data InSites Archives
Cover image for  article: Making Sense of Marketing Clouds

The marketing world has never been more complex. Consumers are generating more data than marketers can handle as they watch, buy and interact across physical touch points and digital screens. Advertisers have the opportunity to market more effectively than ever before, but in trying to make sense of all this data, they are faced with a dizzying array of "point solutions" that do little to make managing and employing all of this data any easier.

In the '70s and '80s, it was easier for companies to reach most of their audience on live broadcast TV, whereas consumers now watch TV live, on demand, on DVR and on their computers and mobile devices.  It goes without saying that effectively reaching a large consumer audience today requires a comprehensive multi-channel marketing strategy.

Marketers must also factor in changing consumer expectations when it comes to advertising.  Finding messages that resonate has become a far more byzantine task.  Adding to these challenges, there is increased pressure from the executive suite to quantify the return-on-investment (ROI) for advertising. With over 69 percent of Fortune 1000 companies unable to quantify the long-term impact of their marketing spend (and 63 percent unable to quantify short term impact[1]) we've got a bit of a problem on our hands to say the least.

Enter the Marketing Cloud

Arriving at the confluence of all of these trends was the marketing cloud. Filled with functionality, promising clarity and promoting simplicity, the first wave of integrated marketing offerings was heavy on firepower, but light on real results. The number of apps (email, CRM, DMP, etc.) included in the marketing cloud rapidly took precedence over how they worked together and what true value they could bring. Additionally, like any engine, these marketing stacks were only as good as the fuel powering them.  In many cases, marketers were running turbo-powered V-8s on lawnmower fuel, and the results showed. Marketers remained confused and unimpressed by the new tech on the block.

Data Quality Makes its Mark

As marketing clouds proliferate, it has become increasingly clear that the old adage "garbage in, garbage out" not only applies to the challenge marketers face in gaining the critical insights needed to accelerate the power of their newly acquired toolsets, but also in their ability to improve marketing ROI. The difference between a successful marketing cloud implementation and a less than stellar one is the quality of the data. It all starts with the precision of the insights available about consumers and what is driving their behavior. Holes or gaps in this data result in faulty conclusions.

The way many marketing stacks respond to the data challenges we face is to "go big." Unfortunately, "bigger" on its own is rarely better.  All big data has bias and coverage gaps. If marketers really want to have confidence in the consumer information they receive, they need to ask how their audience models are being built and if those models are being calibrated with a representative set of real people.  This type of "cleansing" exercise helps make all that big data much smarter.

Harnessing the Power of Data Science

The next step is to bring media planning, marketing activation and campaign analytics together in a single workstream. To start, marketers need to be able to conduct complex analyses on a wide range of consumer and media information, including their own first-party data and data from third-party sources.  Next, they need to be able to reach consumers across devices in a consistent and meaningful way, easily evaluate the results and optimize tactics as quickly as possible.

Let's look at a simple example that illustrates how a consumer packaged goods (CPG) company can more effectively spend its marketing dollars to sell more product. CPG brands have always had challenges directly accessing consumer data because retailers, who own the customer relationship, often aggressively guard this asset. The right marketing cloud can help this company by pulling consumer purchase data from multiple third-party sources, mapping it to first-party information from places like the company's CRM, website or mobile app, and enhancing it with other behavioral characteristics gleaned from digital partnerships.

Armed with these data insights and the predictive power of algorithms that get smarter over time, this company can now generate more timely and relevant messages encouraging consumers to switch from another brand, buy more of their own product, or take other actions to drive loyalty. Furthermore, through a continuous cycle of consumer data analysis and device mapping the right marketing cloud can help this brand see users across multiple devices and analyze in real-time what's working and what's not.

Not All Marketing Clouds Have a Silver Lining

If results, not feature lists, are the metric by which marketing clouds are evaluated then data quality and analytics are what will make one stack stand above the rest. Marketers should look for marketing cloud providers that understand how to best apply consumer and media data first, with media planning, cross-channel marketing activation and analytics capabilities a close second.

The right combination of data and marketing technology enables companies to cut through the complexity of big data, achieve a fully-integrated view of their customers and power more efficient, better performing marketing. The wrong system, overburdened by features and running on low octane data, will deliver incomplete results, betraying the promise of an "integrated stack."

[1] Source: "Companies lack quantitative metrics to demonstrate marketing spend impact," Slide 60, CMO Survey Report: Highlights and Insights, CMOSurvey.org, Feb 2016.

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