Tea Kettle

This is the final post in a series that addresses the different approaches organizations are taking to implement a Marketing Intelligence solution, a software system that takes raw marketing data from various sources and transforms it into valuable insights. You can read the other posts — part 1, part 2, and part 3. In this post, I will talk about a new type of solution that is now available in the market — vertically-integrated, off-the-shelf Marketing Intelligence platforms that deliver much of the capabilities marketers need right out-of-the-box.

The emergence of vertically-integrated Marketing Intelligence platforms should not be a surprise. When you look at other vertically-integrated, analytics-oriented solutions that are available in the market — like Splunk for IT log data or Hyperion (now owned by Oracle) for financial data — they were developed for specific problem areas as a need became pronounced and it didn’t make sense for a business to build their own solution internally to address the need.

Marketing organizations are currently in that situation. As I talk to many of them 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 to measure, report, and optimize their marketing performance. 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 omni-channel campaigns based on the latest data.
  • Have the foundation for an enterprise-wide, standardized marketing measurement system with increased accountability for performance.
  • Increase transparency and collaboration in their interactions with their agency partners.


While having the capabilities described above are valuable, it is not an easy decision to dedicate the resources necessary to build a Marketing Intelligence solution, particularly since it is a high bar to meet the requirements of today’s marketer:


  • Simple – A solution needs to be easy for marketers (i.e., non-technical users) to use so they don’t have to rely on technical resources on a day-to-day basis.
  • Agile – A solution needs to be easy to implement and as importantly, easy to change, as the needs of the business evolve; again, ideally, without a reliance on technical resources.
  • Powerful – A solution needs to give marketers analysis capabilities that are both complete and deep. Complete meaning that it can provide marketers with all of the information — creative assets and their associated performance data — they need to make decisions. And deep in terms of giving marketers the ability to start with high level metrics and drill all the way down to the performance of individual assets.
  • Cost effective – A solution cannot require a lot of resources (time and money) for implementation and usage. Marketers (and IT resources) need to be able to focus their time on value-added efforts.


Addressing the above requirements is particularly challenging when you take into account the different sets of functionality a Marketing Intelligence solution needs in order to transform marketing data into valuable insights:


  • Data collection and storage – This involves collecting heterogeneous, granular data from a variety of sources on a regular basis and storing it in a scalable storage mechanism. It is important to collect as much data as possible directly from each source. Storing detailed data (e.g., data about each individual marketing asset) — and not just aggregated data — provides the most flexibility to address the broadest range of marketing analytics needs. In order to do this, intimate knowledge of the APIs of each of the marketing services is required, as well as the technical know-how to make sure that the storage mechanism delivers scalable high performance.
  • Data enrichment – This involves ensuring data quality (e.g., hole-filling, back-dating) and normalization (e.g., date format consistency) across the different data sets of the various marketing services. In order to do this, a deep understanding of the nuances of each data source is necessary.
  • Organization and contextualization – This involves organizing the data within the context of a dynamic, omni-channel marketing data model. Such a data model takes into account elements like: dimensions (e.g., product, region, time, etc.), relationships between disparate sets of data, and compound metrics (i.e., formula metrics that combine metrics from various sources). It is also important for the data model to be flexible so it can be adapted as the needs of the business evolve — without involving precious and time-consuming IT or vendor resources.
  • Reporting and visualization – This involves delivering an easy-to-use interface that offers templates of commonly-used dashboards, visualizations, metrics, but also gives marketers the ability to define their own when necessary.
  • Discovery and insights – This involves providing search-like capabilities so marketers can explore all of the stored marketing assets and metrics, and applying data science to the data in order to provide users with insights in an automated fashion, so they don’t have to analyze all of the data at a detailed level themselves.


It goes without saying that taking on an internal project to build a Marketing Intelligence solution would meet the definition of “boiling the ocean” — it is an impossible task to undertake. And even trying to use a generic BI technology stack — whether it is a modern, cloud-based BI platform or a traditional, on-premise platform — it doesn’t really help, for the reasons I outlined in an earlier post.

Fortunately, there are now vertically-integrated, off-the-shelf Marketing Intelligence platforms available in the market that have much of the capabilities outlined above right out-of-the-box. They deliver the following intrinsic benefits:


  • Rapid implementation: With an off-the-shelf Marketing Intelligence platform, a solution can be implemented in days or weeks versus the many months or years required by traditional and cloud-based BI systems.
  • Successful rollout and marketer adoption: Off-the-shelf Marketing Intelligence platforms deliver the simplicity and ease of use required by non-technical business users.
  • True agility: Off-the-shelf Marketing Intelligence platforms allow non-technical marketers to make adjustments that address their continuously changing needs — without involving IT or vendor resources.
  • Superior economics: Ultimately, off-the-shelf Marketing Intelligence platforms provide significantly better total cost of ownership vs an IT-implemented, on-premise BI system or cloud-based BI solution.  


Simply put — better, cheaper and faster 🙂

Yes, we at Origami Logic provide such a solution but there are other vendors who are also trying to address the same market need. I encourage you to take a look at these type of solutions before investing a lot of resources in trying to build such a solution internally. You will save yourself a lot of time and money, and you won’t need to buy a huge pot to boil the ocean.

Next-Gen Marketing Measurement