In the first couple posts of our new Executive Insights Series, I initially introduced the notion of Marketing Intelligence solutions and how organizations are trying to build them in order to get valuable insights out of their marketing data. I then talked about how some organizations are trying to use the generic Business Intelligence technology stack to build such solutions and how generic BI is not a good match with today’s marketing data. For this post, I am going to discuss another approach I am starting to see organizations explore to implement a Marketing Intelligence solution – the enterprise data hub.
The most common approach for storing data needed for analytical purposes is the use of data warehouses (or data marts) based on relational database technology. Recently, thanks to the emergence of new big data storage and processing technology — Hadoop and NoSQL databases — organizations are starting to experiment with a new data storage architecture where, in concept, they will take all of their data, enterprise-wide, and store it centrally in what is being called an “enterprise data hub” or a “data lake.” The breakthroughs in cost, scale and flexibility of modern big data infrastructure enable this approach for the first time. By putting all of their enterprise data (across marketing, sales, finance, product, operations, etc.) in one place, enterprises aspire to draw broader, deeper insights to better drive their business, as they plan to use generic BI and visualization tools on top of the enterprise data hub to provide functional dashboards, reports and scorecards.
As I talk to global brands about their marketing intelligence needs, I’m learning about CMOs who are trying to figure out how their marketing organization should participate in such initiatives, which are typically led by the CIO or CDO (Chief Data Officer). Ultimately, they want to know whether they will get what they need to support the agile, data-driven marketing organization they are aspiring to lead.
I feel that the concept of an enterprise data hub is fantastic but certain key considerations need to be taken into account in the context of marketing intelligence…
Having all data in one place is not enough
While the premise of putting together all of the enterprise data into one enterprise data hub is a breakthrough, it is not nearly enough. The challenge in deriving insights from data has a lot more to do with understanding the various types of data and how they are related, rather than getting the data into a “single” storage platform. So to have IT resources be responsible for understanding the detailed nuances of data from each functional area is a monumental task in itself. But then, to have to also understand the relationships among all of the cross-functional data is like boiling the ocean.
To make this easier to understand, think of the following analogy…If you took the list of raw ingredients of the best dishes in the world’s top ten restaurants and put them together in a huge pot, nothing much will come out of it without the individual chefs each applying their own unique preparation process to the ingredients.
Today’s marketing data ecosystem is very complex
Having to understand the intricacies of data, as mentioned above, is particularly acute in the context of modern marketing. Today’s marketing data is extremely diverse, highly fragmented, and is continuously changing in form and nature as new marketing systems and advertising vehicles emerge. A typical enterprise marketing organization may have as few as hundreds to as many as tens of thousands of concurrent data feeds across their web, social, mobile, display, search, email and offline marketing channels. So it’s not only highly challenging to reliably collect the data but it is also difficult to harmonize it across the different channels and organize it into the appropriate business context. This requires deep, marketing-specific domain specialization.
Today’s marketers need to be nimble
Enterprise data hubs are typically managed by IT resources. Those resources will be under tremendous pressure to meet the needs of the different functional areas that have data in the enterprise data hub. Ultimately, today’s marketers need to be able to make decisions and take action in an agile manner. They can’t be constrained by broader organizational initiatives and systems.
Marketing intelligence hub + enterprise data hub can be a win-win
I feel that there is an approach that can balance the needs of the broader organization and the requirements of marketing — have the marketing organization manage a “marketing intelligence hub” and have IT be responsible for the enterprise data hub. The marketing intelligence hub can collect, refine and store the granular, fast-changing data that marketers need in order to make decisions in a timely manner, while the enterprise data hub can define the common business taxonomy and contain aggregated data from the different functional areas. Relevant data can then flow bi-directionally between the two hubs since marketers need data from other functional areas (sales data, for example) in order to understand the business impact of their activities.
This balanced approach lets marketing have the control and flexibility they need to manage their data and make decisions based on the insights they see, while giving IT the ability to bring together corporate-wide data for cross-functional decision making. This approach can also be a good proxy for how CMOs and CIOs can work together. CMOs can own the marketing intelligence hub and CIOs can own the enterprise data hub.
In my next post for this series, I am going to address a final approach organizations can take to implement a Marketing Intelligence solution – use a marketing intelligence platform. This is a new type of solution that is now available; vertically-integrated solutions that deliver much of the capabilities marketers need right out of the box.