July 24, 2018


The necessity for CMOs to produce accurate revenue forecasting cannot be overstated. And yet, for most mid-sized companies, this level of reporting remains elusive.

In a recent report on the state of marketing automation, Chirta Ayer, Editor in Chief of Martech Advisor addressed this elephant in the room for CMOs: revenue forecasting as a requirement when many marketing automation tools often don’t have dashboards with dollar signs in their reporting.

Specifically, as Pierre Custeau, Vice President Product for Eloqua and Content Marketing, Oracle Marketing Cloud notes “Most marketing automation analytics today focus on the data the platform generates or has direct control over. For years those metrics have been used as a proxy to a marketing organization’s impact on revenue.”

What marketers need, now more than ever, are solid dollar-based metrics accurately tied to their marketing campaigns.

With this information, they can then gain clarity on their revenue goals and move toward reporting that includes accurate revenue forecasts on their marketing campaigns. Without this, they are stuck in the past:

  • Using metrics that are essentially proxies for revenue, effectively guessing at that actual financial impact their marketing campaign will have on the bottom line
  • Focusing their time mainly on creative campaigns and “soft” metrics that unfortunately don’t give them equal seating at the executive board table.
  • Spending too much time trying to create accurate revenue forecasting but lacking the tools to do so.



Siloed Data Creates Challenges for Revenue Forecasting

One of the main issues in marketing analytics today is that the data is siloed: perhaps more so today than a decade ago. With 7000 or more Martech solutions available, and each mid-sized company using at minimum a half dozen and many using a dozen or more, unifying those data streams in a meaningful way is, for many marketing teams, an insurmountable problem.

Attempting to create reports across these siloes takes time and energy away from the actual work which will drive a positive impact on revenue: the creation and maintenance of marketing campaigns.

And, of course, the probable inaccuracy and irrelevance of these reports drives home the point: marketing teams today need reliable revenue forecasting for their marketing campaigns in order to prove their value to the company. Sadly, this information is not easy to come by.


Confidence in Revenue Forecasts Essential

Siloed data streams from marketing technology solutions is only one reason to mistrust the data in revenue forecasting. Another issue which impacts the statistical confidence in these forecasts lies in the fact that marketing data can be challenging to collect in an accurate and consistent manner.

And it can be difficult to comprehend the transformational nature of the sheer amount of data in our daily lives. Though businesses have used data to drive change for centuries, today’s 2.5 quintillion bytes of data per day ensures job security for data scientists and requires modern companies of all sizes to integrate solid data-driven models into their planning. Indeed, a recent article in Forbes from a Sequoia Capital partner titled CEOs: Model Or Die refers to data modeling as the “new black gold” — this is not hyperbole; it is fact. Smart CMOs will find a way to harness this knowledge and use it to their advantage or be left behind.

To ensure that forecasts are reliable, it’s imperative that data collected be accurate and consistent. That may sound obvious, but consider that in marketing, the data collected comes from many sources — for example:

  • A purchase made on a smart phone may have been initiated in-store days earlier.
  • A client journey may have begun via a blog post, continued through email marketing, and ended with a purchase after seeing a Facebook advertisement.
  • Sales leads may enter your ecosystem via several platforms and either be missed or over-counted

Attempting to wrangle that disparate data into a unified and blended data asset requires either hours and hours of diligent work (that arguably should go toward creating and maintaining campaigns) or a dedicated system for data integration, which is cost-prohibitive for most companies.


What About the Cloud?

It’s true: cloud-based data integration is a good start and the game changer for the future of marketing revenue forecasting.

In short, it’s where every marketing team should be now, and with the cost-barrier effectively gone in the last eighteen-months, marketing teams can begin to harness the power of cloud computing to help with their data integration.

The more complicated task, once the data is integrated in a single, unified, blended source, is the application of machine learning models to your correctly understood problem and then communicating the result via data visualizations that work.


Revenue Forecasting Essentials

Marketing teams, and CMOs in particular, should invest in solutions now that will drive revenue up while reducing costs.

Look for solutions that use technology available today to solve real problems in a way that offers tangible, ROI based benefits. These solutions should include the following factors:

  • Target a specific question, activity or problem. Consistently yield complete, correct, current, and credible results
  • Deliver value immediately, as measured in days to weeks
  • Present new and actionable insights in ways that can be understood swiftly
  • Accelerate revenue growth (and if they also cut costs, that’s nice, too)