Marketing Technology Roadmap: Start Here

Apr 06, 2016
Technology has found a new home in the Marketing Department.
And it’s a mess.

MarTech chart

Scott Brinker published the chart above in an effort to express the magnitude of this “new” category; it does not do justice to how confusing and complicated the category is in reality.

The vast majority of these 3,874 MarTech vendors are “point solutions” that do something specific and try to do it very well.

MarTech number count

Within each category and sub-category, the features and functions have commonalities and also differences, many of which are neither obvious nor visible. Most buyers are provisioning for the first time and few have insights into the nuances of how these point solutions deliver value and work with other point solutions in a fully networked value chain.

The issues are many and complex, as well as unique to each company, so I’d like to focus this article on two topics: fresh data and integration.

Fresh data is unique in that you harvest it often from many different places, particularly social media. Like lettuce, the longer you store it the more it wilts. Fresh data is often unstructured data and produced without a data schema that makes it harder to conform and monetize.

The solution to maximizing the value of fresh data involves data integration: how do you structure and share the data across multiple systems, processors, and databases.

From the onset of a project, there are two common points of friction:

  • Business requirements, meaning what you want to automate to create consistent, repeatable value; and
  • Alignment to technology solutions, meaning how do current and new infrastructure and point solutions deliver the value users need.

For success it is critical to have shared knowledge, understanding and communications between the business strategist, subject matter experts, data architects, technology developers, coders and others who touch the systems or processes.

The good news is that you can architect a solution and make the data flow with purpose across the enterprise and certain parts of the marketing department.

Here’s a high level part of our roadmap:

  • Round up the Marketing team and talk about what they do and how it creates value for stakeholders (value streams). This is not about how you do it (process), or who does it (job responsibilities). An example would be “to collect new registrations from the website, attribute them to an inbound source, send them off for cleaning and de-duplication, merge with an existing record if found or create a new identity file, then pass them to a marketing data warehouse and business intelligence database.”
  • When you have your list of value streams, determine the inputs, outputs and sinks (places data flows and/or stays). These are going to indicate points of IT integration.
  • Understand the data; its form, format, and substance. Is it always the same, does it vary over time, is it usable in its native format or must it be converted? For example, free form text like twitter must be semantically analyzed for sentiment and context, then categorized into a particular taxonomy so it can align to other data schema.
  • Conduct an inventory of existing technologies. Do an assessment of quality and value, likes and dislikes. As necessary evaluate alternatives.
  • Create a Marketing IT architecture chart that maps the data flows across existing operational software to visualize integration points and/or missing components. This is similar to creating a “marketing stack” but from an alternative approach of data flow for value streams.


By this point in your road-trip, you’ll have an understanding of strategy, value streams, assets, integration, and data architecture. The next steps are to evaluate options to satisfy requirements.

More on this to come, ask me anything.

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