The three essentials of insight-driven marketing

By now you’ve probably heard quite a bit about data-driven marketing. Insight-driven marketing, though? Maybe not.

That’s likely because the term “data-driven marketing” is often used to talk about both — in fact, it tends to take on several definitions and varying levels of difficulty depending on who you ask.

Essentially, data-driven marketing is based on the application of single data points - for example, tailoring the content of promotional email based on customers’ location.

Insight-driven marketing involves bringing together multiple data points to form a more complete (and less obvious) picture of customers. (We go a bit deeper into the difference between data-driven and insight-driven marketing in this post.)

There’s nothing wrong with data-driven marketing; insight-driven is simply the next step on. So what does an insight-driven approach look like in practice? Here are a few characteristics...

A healthy, usable customer database

Insight-driven marketing relies on having the right data. And to really put that data to use in an effective and relevant way, it needs to be accessible and all in one place. The data you’ll need will vary depending on your business / industry, but will probably include:

• contact information
• demographics (i.e. gender, location)
• purchase history
• interests and preferences
• loyalty programme membership info
• past engagements (with your emails, app, calls to your contact centre, etc.)

Aside from having all the right information in a central place, having a healthy database means data needs to be up to date and accurate.

Typically, a customer's data is considered out of date when they haven’t bought anything or interacted with your brand in several months.

However, when it comes to insight-driven marketing, data can go “out of date” much quicker - sometimes within a few hours. To keep the insight you glean relevant, information about customers’ purchases, behaviour and interactions with your brand needs to come into your database in real (or near-real) time.

If your database is out of date, inaccurate or simply a mess (e.g. full of duplicates), the insight you take from it won’t give you an accurate picture, and any comms you do off the back of it may miss the mark.

So how do you ensure you do have a healthy database with the right information?

You’ll need software that can pull data from many touchpoints into one central location, at a fairly high frequency. But you’ll also need to clean up your database from time to time.

A re-engagement message sent periodically to subscribers that haven’t engaged in a while can show you whether contacts are worth keeping in your database — if they don’t respond after a couple of attempts, delete them. Here’s a playful, but clear example of a re-engagement email from ecommerce retailer, Not On The High Street:

How often you do this will depend on your business / industry, but cleaning out your subscriber list regularly keeps the insights you gather relevant, makes your data more manageable and also helps with message deliverability.

Hyper-personalised content at just the right time

Sending personalised, relevant messages is the main goal of insight-driven marketing, because it’s these types of comms that really engage, creating memorable customer experiences and driving loyalty and value.

This requires insight into who your customers are and what motivates them to choose your brand — which, at scale, is usually best accomplished using customer personas.

Personas can be used to tailor content and messaging for different types of customers, across a range of channels — through email and SMS, when they log in to their account or loyalty member portal, when they use your app, etc.

Knowing where customers are in the lifecycle will also help you create more tailored and effective marketing content.

For example, let’s say a fashion retailer has noticed that many of its customers who are at risk of churn fall into two key personas, called “Loyal Lucy” and “Comfy Chris”. Loyal Lucys are big spenders who shop often and from multiple departments, while Comfy Chrises buy almost exclusively from leisurewear.

Customers in both of these personas will be worth winning back, but each persona will likely need different content to draw them back in:

An insight-driven approach also helps marketers send highly relevant offers and rewards. Automation is required to accomplish this at scale, but by matching offers to different interests, preferences, shopping habits and other things you know about them you can deliver hyper-personalised experiences that customers find truly relevant.

Continuously adapting in real-time

Connected customers can interact with your brand at almost any moment of the day, meaning data about these interactions needs to come into your database almost as soon as it happens. This ensures that the messages driven by this insight are as relevant as possible and helps marketers avoid saying the wrong thing.

Insight-driven marketing uses customer’s behaviour to dictate which messages they should receive.

For example, let’s say a customer who has recently made a purchase calls your customer service line to complain. Because of their recent order, in a few hours they’ll automatically receive an invitation to post a review. But if insight about the outcome of their call and their sentiment towards your brand can be applied to your marketing comms in real-time, you can prevent them from receiving messages that make your brand seem oblivious to their current situation.

Ultimately, an insight-driven approach comes down to having a solid understanding of what insight you'll need and why, and having the systems / technology to enable everything to happen in real-time and at scale.