A Brief Look Back in Time

I’m old enough to remember a world before Salesforce, when sales data resided in the IT department and every new report required a custom-built project.

The evolution of cloud-based, user-friendly CRM applications moved data out of IT and closer to the stakeholders, putting sales analytics at the fingertips of sales executives, and enabling reports to be conceived and built on the fly. This next generation CRM transformed how sales teams were managed and ushered in a new level of predictability to sales forecasting.

Back to the Future

Fast forward and today a similar evolution is under way in marketing. SaaS-based solutions like Keen’s are putting a brand’s full knowledge estate at the fingertips of brand marketers. These are the folks who feel the pain when marketing programs fail to demonstrate measurable financial results.

Marketing data traditionally has been the domain of insights and analytics teams, who negotiate and facilitate high-ticket consulting engagements for marketing mix and attribution providers. In addition to being one step removed from the decision (and pain), the cumbersome process of gathering and parsing data to deliver bulky reports does not meet the needs of today’s brand-side stakeholders.

In the old “farm breakfast analogy,” analytics, like the chicken, involved, but the brand team, like the pig, is “committed.” According to 3M’s Head of Global Insights & Analytics for Consumer Brands, Dawn Cunningham:

“I think getting data into the hands of decision makers is one of the most critical “modern marketing” priorities.”

Owning Your Destiny

Given the pace and complexity of today’s marketing landscape, brand marketers desire greater agency over the decisions that will determine the future of their brands (and often their careers). The power of today’s forward-looking marketing decision-support solutions includes:

  1. While they measure past performance, their focus and value derive from the ability to guide strategic decision making to optimize future outcomes.
  2. The platform uses a company’s own data, as well as a robust base of marketing elasticity estimates, enabling marketers to do blue-sky scenario planning and uncover opportunities in channels where it has limited to no prior experience.
  3. The system learns with the user, so once an annual plan is created, and as new data is added, machine learning helps the marketer apply that new knowledge to recast their plan and outcomes in real-time as the program and market unfold.

“Keen’s data models really helped us understand, where does our marketing drive profitability and sales.”

Andy Judd,

CMO, Yasso Greek Frozen Yogurt

Redefining Roles By Value

What happens then to the massive investments many companies have in internal centers of excellence for analytics and insights?

Rather than becoming obsolete, this new paradigm frees analytics experts to move upstream, pivoting away from tactical measurement and granularity, and the methodological differences between past and new techniques. The future analytics and insights professional will focus on helping to drive outcomes and value portfolio-wide by supporting continuous optimization and decision making. According to John Rehfeld, Associate Director Insights and Planning with Post:

“Predictive analytics have allowed us to make decisions faster, pivot away from poor decisions more quickly and accelerate good decisions.”