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Actionable insights from data: what they are & how to get them

In a world where the average data-driven business grows 30% more than the competition, it’s pretty clear that data is an essential piece of the marketing puzzle.

But here’s the thing: Data isn’t enough.

Being data-driven means more than just having data. It means using that data to take action. To identify your best customers. To keep people from churning. To provider better customer service. To upsell and cross-sell.

Which is why the conversation is shifting from data itself to actionable insights.

If the term doesn’t mean much to you yet, here’s what it is and why it matters.

What are actionable insights?

Actionable insights are exactly what they sound like: Insightsyou glean from customer data and that you can take real action on.

Data that doesn’t give you a deeper understanding of your customer’s needs and behaviors isn’t an insight. And an insight without a clear path forward isn’t actionable.

What makes data actionable?

So, what turns regular old customer data into actionable insights? The answer is in how that data is analyzed and presented.

For example, a list of customers who live in Wyoming is data. But is it an actionable insight? Does it tell you anything about what those customers want or need or how they behave? Does it give you a clear path forward?

No. It’s just data. Just a list. And it can be useful—sure—for sending a mailer about a Wyoming-specific event or advertising a Wyoming-specific special offer. But, in and of itself, that data doesn’t give you insights or move you toward action.

Now, imagine that same data came to you with another layer of information. Imagine you had a list of customers in Wyoming and you also knew that customers in Wyoming were 30% more likely to buy work boots than any other set of customers.

That information gives you an insight into customer behavior and a clear way forward. Suddenly, it’s clear that you should be advertising work boots to this specific audience.

This is the difference between data and actionable insights.

Data is foundational. We need it in order to glean insights. But, in and of itself, it isn’t always an insight and it isn’t always actionable.

The value of actionable insights

With the example above, it’s pretty clear that actionable insights add value to static data.

In our example above, a list of Wyoming customers won’t get you nearly as close to your sales goals as information about what those customers are interested in buying.

The good news is that the benefits don’t stop there. There are so many different facets of customer behavior and needs that actionable insights can help us interpret.

Actionable insights can help you understand:

  • What products customers want

  • What messages resonate with them

  • How and where they want to hear from your brand

  • What topics interest them

  • How their interests and behavior change over time

  • What content is most likely to move them along their customer journey, keep them from churning, or encourage a purchase or subscription

And based on insights like those, you can make educated decisions about how to move forward with your marketing. You can advertise work boots to people who buy work boots. You can send newsletters on Saturdays instead of Fridays for people who open them on Saturdays instead of Fridays. You can stop advertising baby gear to people who’ve stopped buying baby gear.

The more insights you have, the more you can cater to customer preferences. Which is a recipe for success.

Where do actionable insights come from?

Okay. So you get it: customer insights are a big deal. They make our marketing smarter and more successful.

But if you don’t already have those insights, where can you get them? How can you take the piles of data your company is probably already collecting and turn them into something actionable?

The answer starts with data science, which is, at its core, the action of turning data into actionable insights.

As we explain in our guide to the basics of data science:

“A data scientist typically [turns data into insights] by identifying a goal (for example: we want to understand where our highest lifetime value customers are located), creating a model to sort the data based on that goal using mathematical algorithms and technical systems, and then interpreting the data that model surfaces to tell a story (for example: clients in Omaha have a 60% chance of becoming high-lifetime-value customers).”

A quicker path to actionable insights

Now, if that sounds like a lot of work, that’s because it is. Data analysis, modeling, and interpretation takes time.

And the truth is that marketers don’t always have the luxury of time.

We need to know what Customer X wants today. We need to understand customer trends moment-by-moment. We don’t want to wait a week for an insight and end up losing people to our competitors in the meantime.

Which is where technology comes in.

To get actionable insights driven by data science in real-time, we need systems with built-in data science and built-in machine learning intelligence. Systems programmed by data scientists to instantly interpret our data and give us the information we need to move forward.

Actionable insights for your business

So, here’s some good news: actionable insights are what we at Lytics are best at.

We call our platform a CDP, but it’s not just a data storage facility (like so many others who use that term). It’s a smart machine that collects and connects your data and turns it into actionable insights.

actionable insights

If that sounds intriguing, we’d love to show you how it works. Contact us for a demo today.



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