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Let’s Make 2020 the Year of Insights and Action

There are big changes looming on the horizon for 2020. They’re predicted on every front. To better adapt to change quickly, we’ll need data. But more than data, we’ll need insights. Insights are what keep us ahead of the curve. In a perfect world, insights will allow us to be proactive, rather than reactive.

So, with economic uncertainty looming on the horizon, smart marketers are shoring up their systems of intelligence, insights, and action for the year ahead.

AI Will Begin to Close the Expectation Gap

The terms “artificial intelligence” and “machine learning” fire up the imagination, conjuring rich imagery: Watson winning “Jeopardy,” Terminators bent on world domination, and a level of intelligence and predictive capability that’s borderline psychic and a little scary.

But when AI hit the advertising world, it first and most commonly took the form of programmatic display ads (lackluster) and … chatbots. The collective let-down was palpable. Cue the trombone wah-wah.

Nothing against chatbots; they have their role when it comes to answering “Frequently Asked Questions.” But pop culture promised us a level of intelligence on-par with Hal in Stanley Kubrick’s “2001: A Space Odyssey.”

Here’s the thing: The folks who think that AI ends at chatbots lack imagination. We have only begun to scratch the surface. Sentiment analysis, lead scoring, anomaly detection, predictive customer care — all of these things would be comparatively time-consuming for a human, while instantaneous for AI.

AI can use modeling to predict when a customer is going to lapse, and proactively launch an email, or display an offer meant to reactivate that customer; something that wouldn’t be feasible on a human-to-human level.

Content generation, too? Sure. The Washington Post’s bot published 500 articles last year. Admittedly, it’s in its infancy. But you have to start somewhere. And we know that Google has been using AI to assemble dynamic ads for Smart Shopping campaigns, coming to market with a new algorithm in 2019 that’s much improved over its lackluster predecessor.

But while AI and machine learning have a lot to offer, these shifts, predictions, and data points still need context and human intelligence to direct the action on a macro level. As per usual, data is easy, insights are (still) hard.

Small and Mid-Sized Businesses Embrace Intelligence Dashboards

With good reason, business intelligence dashboards are all but ubiquitous among enterprise-level businesses. However, with tools like Google Data Studio and Tableau making the cost-of entry manageable for everyone, small and medium-sized businesses should be quick to follow.

Business intelligence dashboards can provide a much-needed 360-degree view of the business, what’s driving the most revenue, and what’s the customer lifetime value for each channel.

This can help inform business decisions; especially where to put marketing budget and invest internal resources.

They also serve as a “single source of truth” for marketers, an absolutely essential key to solving the multichannel attribution problem.

The tricky part with all business intelligence dashboards is turning this new, holistic, 360-degree view into — you guessed it — data insights to figure out how to apply it.

Powerful Behavioral and Psychographic Data Offline

We’ve long had the ability to target ads using behavioral, psychographic, and demographic data on Google and Facebook. And this powerful combination of factors has empowered many a brand to grow dramatically, using the sheer strength of the data.

There’s a reason that this intersection of data is so powerful:

  • Behavioral: You know they’re currently shopping.
  • Psychographic: You know that they are interested in what you are selling.
  • Demographic: You know that they match your customer profile.

However, that powerful intersection of behavioral, psychographic, and demographic data is locked inside their respective platforms — meaning, you can’t export a list of prospects out of it to do anything else with, (e.g., a B2C marketer can’t send them direct mail, and a B2B marketer can’t add them to a CRM).

And marketers who use offline tactics shouldn’t be strangers to the power of overlaying digital data. They’ve seen the lift caused by overlaying email data or browse behavior onto mailing lists.

Thankfully, there are a few co-op databases that have recognized the need and have taken to website tagging to add behavioral data — browsing behaviors across sites — to layer onto their existing database. That’s bringing the insights that were formerly only accessible through their proprietary platforms and making them accessible, making the data more powerful and actionable.

Data Analysts as Problem-Solvers

Storytelling is undergoing such a boom in popularity that everyone seems to be in a rush to characterize themselves as storytellers, and data analysts are no exception. They may be right, because in order for disparate data points to make any kind of sense, they need to be woven together to form a cohesive narrative. But what good analysts do is more prescriptive.

So the data analysts who push past descriptive storytelling — campaign performance and KPIs — and use data to spot potential opportunities, signal weak areas, or map a clear path to business goals are our problem-solvers. And that’s what we need in the coming year.

Using Data to Create a 2020 Vision

We’re going to continue to struggle against a lot of familiar challenges. There are some truths that the marketing community agrees on, in principle, but we can’t seem to put them into practice. They’ve proven to be difficult, partly because of our fast-paced, demanding production timelines. They are:

  • Keep data informing creative, and vice-versa.
  • Get our separate teams regularly communicating in a meaningful and productive way.
  • Solve the multichannel attribution problem; especially when it comes to online and offline data.

So how do we make 2020 the year of insights and action? With small, simple steps: communicating frequently, incorporating AI, and using smart dashboards. Then those problem-solving data analysts can put it all into a greater context, and turn that insight into action.

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