iStock_000023659928_SmallYou thought you were doing everything right.  You found and gathered data, invested in tools, got budget, and maybe even hired a data scientist or at least an internal analyst.  But you find yourself running into roadblocks that you didn’t anticipate when you championed bringing data analytics into your marketing department.

Trust me, you are not alone. Gartner Research’s recent report “Predicts 2015 – Big Data Challenges Move From Technology to the Organization” predicted that through 2017, 60% of big data projects will fail to go beyond piloting and experimentation, and will be abandoned.

In over twenty years of marketing analytics consulting, I’ve seen my share of these data-driven marketing projects (Big Data and otherwise) go awry.  Sometimes changing corporate or budget priorities derail a project mid-stream. Other times they just painfully limp along.  Worst of all are the projects that fail to get off the ground at all.

In this first article of a three part series, I will focus on the most common of those project-failing reasons – the human factor.

It’s those pesky people!  What you imagine to be the hard part of an analytics project – the analytics – turns out to be the easy part.  Aligning the marketing team with the analytics team is essential but often difficult.  Without it your project will move 2 steps forward and 3 steps back over and over again.  Eventually, both groups retreat to easily defined work and the opportunities to use analytics as a significant business driver are lost.

Not surprisingly, interpersonal problems tend to arise when highly accomplished professionals in very divergent specialties work closely together, each with their own language, priorities and expectations.

Here are three reasons that the human element can derail marketing analytics projects, and what you can do about it.

1. VAGUE BUSINESS QUESTIONS

A business question is the driving force in any marketing analytics project.  When the business question is too vague or not present at all, the project is doomed from the start.   A poor definition by marketing of their key business question can easily lead to misunderstandings in the analytics team.  Those misunderstandings can lead to the analytics team needlessly burning a lot of calories in the wrong direction and not having useable, actionable results at the end.

Alternate Approach: 

Assure success by gaining stakeholder alignment on a measureable, deadline-driven, clear business question.

This process begins by getting ALL possible business questions out on the table, from leaders in any department participating in the project.  Then, work together to agree on THE big critical question, possibly with a few tangential “what if” business questions.

Asking and documenting answers for questions like the following will help keep all project participants focused in the same direction:

      • What does success look like?
      • How does this project align with priorities of the project sponsor?
      • How will this data drive business once the project is complete?
      • What business deadlines drive this project?

An example of a vague key business question is “What are the characteristics of our best customers?”.   A much more actionable, clear question would be “Which of our best customers are most likely to leave and which offer will likely get them to purchase again during the holiday season?”.

 2. ELUSIVE TEAMWORK

This is probably the most common and “worse case” area where a marketing analytics project falls apart.  Some analysts march to their own drummer.  They spend excess time trying to arrive at an answer that is 100% accurate, get caught up in interesting, but insignificant-to-the-business insights, are uncomfortable with approximate results that make more business sense, and don’t respect “imprecise marketers willing to settle for inferior answers.”  Another issue is that marketing and analysts often speak different languages.  This leads to misunderstandings and ‘analytically perfect’ results that no one in marketing can understand or implement.

Without teamwork, the analytics team tends to “work in a vacuum,” moving from an agreed-on assignment to a weeks- or-months-later answer that doesn’t match the business team’s expectations.

Marketers cause their share of teamwork problems, too.  They can have a condescending air toward analysts, change their minds about projects in midstream, expand scope, be unavailable or unwelcoming for questions or generally make the analyst’s job more difficult than it needs to be.

Alternate Approach:

If possible, marketing and analytics should office next to each other.  This physical closeness helps to facilitate a closer working arrangement. The approach that works is not a number of big review sessions where lots of work can be showcased, but a constantly iterative process, where project approach can be tuned based on findings as they emerge.  Daily or bi-weekly informal review sessions can reduce the number of missteps and improve the speed to market for results.

3. LACK OF COMMON GOALS/METRICS

A compounding factor that drives inefficiency between marketing and analytics is a difference in metrics, particularly goals that drive compensation.  Marketing goals should be focused on key business metrics, such as traffic, acquisition, cross-sell and retention.  Analytics metrics can be more operational and educational – complete X number of analyses, produce X number of reports accurately and on-time and learn a new modeling technique.

The gap between the two types of goals means that marketing is pushing hard for analysis that can drive action during the year, and analytics is more concerned with production and accuracy.

Now, accuracy is always important – don’t get me wrong.  But no analysis is 100% accurate and decisions must be made between additional analysis and time to market.

Alternate Approach: 

By mirroring metrics across marketing and analytics, you will clearly change behavior.  Analytics will understand the impact of getting the right answer in a timely fashion in order to hit metrics that will impact everyone’s paychecks.  Both teams can meet and have an orderly discussion about analytic techniques, their benefits and time/resource costs, and make project decisions together.

Remember, change compensation and you change behavior.

While every business project has rough spots, marketing analytics projects experience more than their share of difficulties. In upcoming articles I will discuss how technical and organizational issues also can obstruct progress and success on these exciting and challenging projects.

In the meantime, try some of the solutions mentioned here to give your marketing analytics project the best chance for success.  And let me know how it works for you.