SMM Insights

As the CEO of Origami Logic, I have the privilege of spending a great deal of my time talking with marketers in global brands who are trying to use data to get the most out of their efforts. The conversations are fascinating and they always get me thinking about where the industry is going and what we should be doing to help marketing organizations solve their problems. I decided to start blogging to pass on some of my thoughts. I am kicking things off with the first post of a multi-part series that addresses the pain points marketing organizations are grappling with when it comes to their use of data and the different approaches they are taking to overcome those issues. I hope you enjoy the content. If you have any feedback, please feel free to add a comment at the end of the post or send me a tweet at @kahanop.

There is no doubt that digital marketing has transformed marketing. Marketers now have more ways than ever to connect with their target audiences. However, the promise of digital marketing has always been much more than that. Digital marketing was also supposed to trigger a new era of data-driven decision making, as marketers gain access to a wealth of data from the different digital services they use to execute activities.

While there is no doubt that marketers are making some data-driven decisions, it is clear from my conversations with marketing executives that most organizations are not getting everything they want from their data. For example:

  • Making in-flight decisions to optimize cross-channel campaigns is still not possible. Most decisions are made after the campaign is completed and are dependent on post-mortem reports that are often inaccurate.
  • Modeling brand equity and the consumer consideration journey is still based on expensive and time consuming panel survey-based reports, rather than taking advantage of the wealth of digital data readily available.
  • Having an enterprise-wide, standard measurement system that enables accountability, learning and efficiencies across channels, campaigns, brands, products, agencies and regions is not implemented. Most organizations still employ a “system” where each brand or market has their own measurement approach that makes them look good and makes it impossible to benchmark performance and set top-down goals across the organization.

While most marketing executives I talk to are still not where they want to be, it is clear that many understand the value of data and they want to develop the expertise and processes their organization needs to derive more value out of all of their marketing data and become an agile, “data smart” marketing organization . At Origami Logic, we call this discipline of taking raw marketing data and transforming it into insights “marketing intelligence.”

In my discussions with marketing organizations about their marketing intelligence efforts, I have found that the biggest challenge they face is bringing together all of the fragmented, diverse data from the various services they use. They not only want all of their data together in one place; they want it brought together in an automated way where the data is updated, harmonized and organized continuously in a way that makes it instantly accessible to marketers to drive decisions. With a centralized hub of marketing data that is up-to-date and of high quality, and with the right reporting, visualization and exploration tools, marketing organizations can:

  • Have a single source of truth that can be used to make timely decisions and discover actionable insights.
  • Have a one-stop shop to understand the performance of their marketing activities that span channels, campaigns, brands, products and regions.
  • Make in-flight optimization decisions on cross-channel campaigns based on the latest data.
  • Have the foundation for an enterprise-wide, standardized marketing measurement system.
  • Increase transparency and collaboration in their interactions with their agency partners.

But developing such a marketing data hub is very difficult because:

  • There is so much volume and diversity of data from the different marketing channels and systems, where each system represents data in a different manner.
  • New data is being added at a fast pace and metrics related to the data need to be updated often. The best example of this is social media messages and the metrics associated with them.
  • The form and nature of the underlying data continuously changes as the marketing platforms keep evolving at a rapid pace. For example, the nature of ads data on Facebook, Twitter or DoubleClick continuously changes as new ad types are introduced.
  • Global organizations have many instances of the various marketing channels (e.g., hundreds of websites, Facebook pages, DoubleClick accounts, etc.), making it difficult to organize their assets in a meaningful way.
  • Marketers need to make decisions that span both the left (quantitative) and right (creative) sides of the brain and as such, they need both highly structured performance data and highly unstructured marketing asset/creative data at their fingertips.
  • The questions marketers ask of their data and the way the want to organize it, so it aligns with their changing business realities, constantly change.

To tackle the challenge of creating a centralized marketing data hub, I see organizations taking one of three different approaches:

  1. Use spreadsheets – Most organizations typically start by consolidating data into spreadsheets. This approach, however, is time consulting and error prone, it doesn’t support timely decision making, and it simply doesn’t scale.
  2. Use generic business intelligence tools – After realizing the limitations of using spreadsheets, some organizations try to build their own marketing intelligence solution by creating a data warehouse and using generic BI or visualization tools that are already used within the company.
  3. Use an enterprise data hub – I have started to see some companies try to build their own marketing intelligence solution within the context of a broader corporate technology initiative, where a Hadoop-based enterprise data hub is being implemented for all company data.

By using marketing intelligence solutions that transform marketing data into valuable insights, marketers will be able to make more data-driven decisions, increase their agility and competitiveness, and ultimately increase the business impact and efficiency of their marketing spend. Building such a solution, however, is not trivial since it is so difficult to consolidate all of the diverse data used in marketing in an automated and high quality manner, while maintaining the agility in adjusting to constantly changing reporting and measurement needs. As a result, the effectiveness of such a solution is impacted by the approach an organization takes to implement it.

In the next two posts of this multi-part series, I will expand on the last two approaches mentioned above — the generic BI tools approach and the enterprise data hub approach. I will then conclude the series with an overview of 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.

Next-Gen Marketing Measurement