The Unstructured Data Challenge

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Matthew Keylock, SVP, Media Partnerships at dunnhumby

Within an industry rapidly becoming obsessed with unstructured data, are we losing our focus? Unstructured data, data from customer emails, social media, video, and elsewhere that doesn’t fit into a relational database, has great potential to provide rich and powerful insight. However, in reality, few businesses are in a position to worry about harvesting and activating their unstructured data assets. Many companies are investing significant time and resources to investigate new technologies and the myriad of companies offering unstructured-based insights or targeting solutions. As companies race to solve these challenges, many are skipping an important step.

Before diving into approaches to manage and analyze the volume, variety, velocity and value of unstructured data, businesses need to assess their structured data assets. Data should allow a business to learn more about their customers overtime. Without that foundation and proven success in leveraging structured data, the addition of unstructured data is guaranteed to create more noise rather than clarity. If businesses continue to regulate “The Big Data Challenge” to IT, or think software is the means to a resolution, they will likely continue to face roadblocks to long-term viability and success with that data. They will continue to just chase the next shiny tech object without a view into how to make it accountable to the business

If we look at the landscape, the race to resolve unstructured data shouldn’t come as a surprise for a few reasons.

IT departments chase new technology solutions. The IT department needs to demonstrate that they are ahead of the game and positioned to drive new value for the organization with cutting edge new technologies. It’s not just important to have the latest technology on one’s resume, it’s also about proving leadership and credibility in the organization, the boardroom and to the wider industry at large to sustain a forward-leading reputation.

Marketers in many organizations are still mired in yesterday’s world. Granular execution at the customer-level and the ability to drive more accountability with purchase data is clearly the next phase for marketing but the industry isn’t yet ready for this. Many marketers don’t have the data expertise that is needed and therefore spend most of their focus finding the new great “proxy” for customer needs and attitudes by chasing things like customer sentiment. Proxies can work well for trends and broad-scale activations, but today’s world is personalized. Consumer level data is needed not only for execution but for better strategies and measures. For example, marketing thinking has long cautioned marketers not to run a TV spot at the same time as price discount because prevailing insight showed that they often canceled each other. Thanks to customer-level data, we know now that this isn’t true, that in fact the opposite is true.

Data means nothing without a strategy. It’s not the data that will give you the competitive advantage; it is how you think about that data- unstructured or structured- across your organization and how you use it to drive change. Side-by-side insights from siloed data sources create confusion, inefficiency and ultimately a fragmented consumer experience.  The total data asset, from social to analytics and transactions, should provide a deep and consistent view of each individual customer. Very few businesses are doing this today. In fact, by focusing on unstructured data, many are reinforcing, if not proliferating, data silos and inconsistent decisions and customer experience.

For example, in the behavioral continuum image below, marketers largely remain on the left, while finance and IT focus on the right. Their worlds don’t connect.  It’s not just the objectives that are different but the metrics and the data sources they are using to drive their decisions.  This continuum needs to be connected using granular, customer level behavioral and structured data as the foundation.

Without a connection to a larger customer strategy, sentiment data will only be helpful in informing a macro view of consumer trends. Dangerous too is activating unstructured data in one channel and leveraging shopper data in another. While we organize our businesses and industry in silos, the customer experiences only one brand. Leveraging unstructured data to inform a digital advertising strategy and then shopper data for trade promotions is likely to generate a fragmented experience for the customer.

Admittedly some, such as packaged goods companies, other manufacturers and some retailers, don’t have the consumer dimension in their transaction data to do all of this, but many business do and just aren’t using it right.  Even those that haven’t traditionally had this consumer dimension in their data should be focused on leveraging new digital channels to start to build this individual-level view into their transactions.  Without this personalized understanding of who your customers are, what they buy and how they shop it’s tough to deliver anything with highly personalized relevance that consumers are increasingly expecting. For example, a customer-level understanding can bring a new standard of effectiveness to a brand extension where awareness and trial are the primary objectives. By targeting households that are known purchasers of a category that also value convenience for a new product that offers those benefits, you’re more likely to see a better response across channels. So, with this customer dimension, your social media outreach, display advertising and direct mail are greater than the sum of its parts: executing these together with relevance drives more awareness and trial than a one-off approach.

Taking this one step further into unstructured territory, some marketers are targeting their best customers and giving them the tools to turn loyals into advocates on social media. With a solid foundation, they are able to leverage unstructured data to answer questions like, “Who are those advocates communicating with?” “What’s the impact on sales?” “How were they able to influence their network of friends?” It is that link between structured and unstructured, shopper data and sentiment data, which can push unstructured data into the realm of “semi-structured” data and make both easily actionable.

A data strategy should be created to support and drive your business objectives: how are we leveraging data to better understand our customers, their media habits and our marketing strategy? Is this data and insight tied to every touchpoint on the customer lifecycle? Are our structured data assets positioned to anticipate and articulate your future needs across the business? By following the customer, this evolution will become less of a burden for marketers. It will also allow businesses to consolidate Big Data and give it a clear purpose beyond IT and marketing, for a more customer-centric approach across the organization.

Follow Matthew Keylock (@mattkeylock) and AdExchanger (@adexchanger) on Twitter.

Enjoying this content?

Sign up to be an AdExchanger Member today and get unlimited access to articles like this, plus proprietary data and research, conference discounts, on-demand access to event content, and more!

Join Today!