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Marketing Analytics Trends for 2016: Where, How, and Why Marketing Drives Revenue

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In 2016, we'll see an accelerated maturation of marketing analytics, with companies taking increasingly granular looks under the hood at how, where, and why marketing is driving revenue.

Here are the marketing analytics trends to watch in 2016.

1. The use of predictive- and prescriptive-only analytics decline, and explanatory analytics rise

Predictive analytics is an incomplete approach because it only gives you a likely outcome if nothing changes. It doesn't tell you why outcomes are likely, the correlations driving those outcomes, or—perhaps most importantly—how to change those outcomes.

Prescriptive analytics is something of a step beyond predictive analytics in that it tells people not only where they're headed but also the moves they can make to improve the outcome. However, that is still basically a black box approach; most prescriptive platforms don't let people understand why the platform made certain recommendations.

Enter explanatory analytics. Marketers are smart people, and as such they (not computer code) should be asking the analytics questions, driven by their curiosity and intuition. They should then bring in the machine to investigate the correlations that matter.

2. Social media listening platforms get a facelift

In 2016, it will become even more apparent that social listening platforms, by themselves, are unable to correlate to revenue or reveal growth opportunities.

Those platforms will continue to offer slick visualizations of financial performance as add-ons, most without any actual correlation of data. Marketers should be on guard to make sure they look at data correlations, not data coincidences.

3. Agile marketing goes mainstream, collapsing annual budgeting cycles

As comprehensive reporting inches closer to real time, marketers will keep shrinking the amount of time it takes to change course. The days of 3-month tests or trial balloons are waning. Now, marketers will know in a matter of weeks (if not days) whether initiatives are working. There will be fewer excuses to burn money once it's evident campaigns are misguided. Contracts with vendors will shorten in length.

We now have the technology, data, and skillsets to adjust on the fly. CEOs and boardrooms expect that pliability. At the same time, traditional corporate planning cycles still produce annual budget approvals. Though the traditional cycles of plan-execute-measure-adjust continue to converge and collapse, the processes that allocate resources against that cycle remain annual.

4. CMOs tap analytics to get closer to CIOs, CFOs, and CEOs

Explanatory analytics equip CMOs with concise insights into what drives revenue and why.

A 2015 Forester study found that 74% of enterprise architects say they want to be data-driven. Only 29% of those same respondents could say their firms are good at translating analytics into measurable data outcomes. And virtually every organization is thirsty to understand why revenue moves the way it does.

The fact that marketers have traditionally not understood what drives revenue has cost them dearly in terms of internal standing. For example, three out of four CEOs say their CMO "lacks business credibility" because they don't talk about how they drive revenue, according to the Fournaise Group.

Marketers' duties will continue to resemble those of a chief revenue officer as their suggestions begin to provide the most intelligent and actionable insights into how to grow revenue.

5. "Human-in-the-loop" computing will dominate marketing analytics

Increasingly, industry experts are calling for a "human-in-the-loop" approach to data science across multiple disciplines. Marketing is the poster child for why that makes sense.

When you think about it, curiosity is simply an organic algorithm processed in the human brain, the conclusion of which is "this is worth further study." So, the first function of a marketing analytics platform is to trigger the curiosity algorithm in the human, at the right time and place.

Similarly, intuition is just another organic algorithm, the conclusion of which is "this is worth taking action on, even if I can't articulate the rationale completely." And when deciding whether to take action on the insights surfaced, nothing is better than human intuition to make that calculation.

So the second function of a marketing analytics platform is to trigger the intuition algorithm with as much intelligently-correlated data as possible.

In 2016, much of the mystery and magical thinking around marketing analytics will evaporate as intelligent marketing analytics goes mainstream. The real race to watch in 2016 will be which marketers are first to figure out what to expect from and how to work with their marketing analytics platforms.

Marketers need to ask themselves important questions

As the landscape shifts, ask yourself the following questions:

  • What are my biggest blind spots as a marketer?

  • Where do I have the clearest view into how I'm affecting revenue?

  • Where would analytics help deepen my understanding the most?

  • How closely correlated are my marketing analytics to actual KPIs and other revenue metrics?

  • How will my role as the marketing lead within the organization change as advances in analytics technology heighten the expectations of my peers and my CEO?

  • How can I use the latest advances in marketing analytics to strengthen my position as a leader, change agent, and trusted C-suite advisor within my own organization?

These are just some of the exciting questions to consider as we get deeper into 2016.

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Joshua Reynolds is head of Marketing at Quantifind, an on-demand insights platform for brands.

LinkedIn: Joshua Reynolds

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