The burdens on today's CMOs are increasing: theyre taking on larger roles and budgets while needing insight into an increasingly complex customer journey. Leah Pope, CMO, Datorama discusses how brands can leverage AI in 2017 to fuel success

As CMOs today, were operating with more responsibility than ever. Now we must simultaneously understand our customers, keep up with their every move across channels in an increasingly complex customer journey, and take on bigger budgets while adapting to a bigger seat at the executive table, as sales and service will soon roll up into our department. In many respects this has thrust marketers into becoming not only data-literate but also data-fluent practitioners.

This means we must be capable of defining the KPIs. We need to ensure that all marketing metrics, be they social, brand health, or email, align with and support our overarching business goals.

Ultimately, we are responsible for understanding how to move marketing performance and business impact in a predictable manner. Considering this is based on something that, traditionally, has been unpredictable, its a tall task. So, how do you turn a practice more akin to trial and error into a repeatable, scientific process as you attempt to tease out marketing-related insights?

If we want to make our performance predictable, it stands to reason that the insight generation process that moves the marketing needle needs to become more predictable as well.

Which brings us to a new topic that should be on every CMOs radar in 2017: How can marketers leverage emerging technology e.g., artificial intelligence (AI), more specifically, machine learning to create predictable intelligent insights that will serve as guidance to make an impact on business- and marketing-related KPIs?

In the last few years, AI and marketing-based analytic data models have made it possible to do things that marketers have talked about for decades. This conversation has converted into reality now thanks to cheap computing power, consumers that are more connected than ever, and advances in AI.

In fact, according to Gartners 2016 Priority Matrix for Digital Marketing and Advertising Hype Cycle, Predictive Analytics have a very high benefit for marketers, and an anticipated mainstream adoption of 2-5 years.

That means we can drive better marketing performance and understand ROI properly for the first time.

Today machine learning can be applied to automatically connect all of your marketing data across channels, systems and partners into a single source of truth to measure your departmental performance across all of your data. Heres the best part: They can adjust at a moments notice to take in the data from a new market, a new product launch or a new presence on Snapchat, or your latest programmatic video experiments.

Compared to the days of cumbersome, error-prone Excel sheets and constant data warehouse projects, this is a welcome paradigm shift. Its actually made the terrifying task of connecting, organizing and collecting marketing data, dare I say, easy.

So whats next for AI? Heres a pretty big hint: intelligent insights. Intelligent insights is another application of AI that works on behalf of marketers to elevate information that supports better decision making.

This introduces a new way to collaborate with your marketing technology. You provide an agenda composed of the KPIs you want to watch on an ongoing basis, and off goes your assistant into your data. Now, millions of data points get analyzed on a continual basis to tell you whats driving KPI performance, in a prioritized order of impact.

You might want to keep an eye on channel or campaign Marketing ROI, campaign engagement or conversion Rate, or campaign CPM or CTR.

Rather than rely on a labor-intensive, manual effort thats sure to miss critical findings in your ever-increasing data, imagine a marketing world where your KPI performance could be better understood via intelligent insights that help you learn whats working and what is not. That way you know exactly which campaigns are the root drivers of your marketing ROI and which campaigns are pulling it down. And, you can get granular, for example: The specific targeting method responsible for the great campaign engagement rate your team just engineered lets keep doing that. While this is merely one idea, there is a sea of opportunity for todays marketer thats provided via this technological advancement.

As a CMO always on the lookout for new ways of measuring performance and improving our marketing initiatives, I cant wait for whats next.

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2017 CMO Focus: What's Next from AI? Intelligent Insights - MarTech Advisor