Is it possible to have too much of a good thing? In the case of the overwhelming amount of data available to today's marketers, the answer may be yes.
The volume of Big Data is expanding at a dizzying pace. By 2020, 1.7 megabytes of new information will be created every second for every person on the planet, according to IDC research. Meanwhile, companies are struggling to bridge the ever-widening data talent gap. The 2015 MIT Sloan Management Review, for example, found that 40% of all companies were unable to find and retain the talent they need to manage their tremendous stockpiles of data.
Marketers are increasingly dependent on data from a growing number of sources. These include first-party customer data that a company owns either through its internal databases, a proprietary distribution channel or that it purchases from a source like a Nielsen or IRI. It also includes digital device/usage profile data; performance data such as online advertising engagement and conversion rates across media channels; third-party data spanning household demographics and purchases; and a host of social listening data, including conversation volumes, sentiment, themes and influencers.
All of these data sources play a vital role in marketing. Nevertheless, many companies increasingly worry that they have an oversupply of data and an undersupply of people who know how to manage it or shape it into actionable strategies. Herein lies an opportunity to create a new role, one that I call "Data
The Data Navigator will be able to track and coordinate data across disparate departments, synthesize all the information and translate it into marketing strategies that drive sales. He or she can also help the company know which outside data is worth investing in—and which is not. These are key steps that will enable marketers to begin to dig out from the constantly growing supply of data.
Different Industries, Different Challenges
Across different industries, access to data and the ability to leverage customer information for marketing purposes varies widely. In pharmaceuticals and banking, for example, privacy regulations prevent the development of closed-loop attribution systems. This means a drug firm or a financial company cannot, for example, link the acquisition of a new customer to the previous exposure of that customer to digital display ads.
Consumer packaged goods companies face a different set of challenges. Unlike, say, an online clothing retailer or electronics firm where purchases are made directly through the company's website, CPG firms sell primarily through brick-and-mortar retailers and do not own data related to the actual sale; it belongs to the retailer. This inhibits a brand's ability to optimize its marketing across different channels against the most important key performance indicator: sales.
To make up for these data gaps, a company can overlay its database with third-party data that includes customers' lifestyle behaviors and digital browsing histories. Broadly speaking, there are three scenarios that would justify spending significantly on data collection:
- The company is new to the category and needs to quickly get a handle on consumer needs and purchasing patterns.
- The actions taken based on the data will generate efficiencies in media spending and improve conversion rates through enhanced optimization techniques.
- The organization needs quantitative support to break through gridlock for proposed marketing investments—for example, in developing a new product line or entry into a new consumer segment.
Enter the Data Navigator
Today, most organizations take a fragmented or siloed approach to interpreting data. Typically, a company's market research team, customer analytics team, customer care team and digital team are each responsible for tracking different KPIs, which results in the independent development of insights and can lead to conflicting results. At best, these teams may engage with each other three times a year.
Going forward, there is an opportunity to merge these four groups within a single, broader team responsible for optimizing the customer experience—or, less drastically, to form a cross-functional team that would meet monthly to compare insights and develop cross-channel views on overall customer behavior.
The role of Data Navigator is key in the reorganization of new data realities. The Data Navigator must be fluent in data from all kinds of sources, and fully understand the data and insights work already being done at the company. This person should also remain current in the field of new data solutions and be familiar with various data vendors. As leader of the organization's broader learning agenda, the Data Navigator will deliver insights and proposed solutions to help teams work toward the common goal of building a great customer experience.
In this unifying role, the Data Navigator will make a strong contribution to helping organizations better understand their customers and, by extension, how to deliver a truly distinctive customer experience. It's the clearest way to extract the most value from that ever-growing supply of data.
About the Author
Jennifer leads Catapult's Strategy and Insights team, where she develops marketing strategies for clients, oversees delivery of client solutions and spearheads the transformation of insights into big ideas. Prior to Catapult, Jennifer honed her skills as a marketing consultant at McKinsey & Co. and Monitor Group. She also headed strategy and analytics at Ryan Partnership and