How marketers can improve their use of data by keeping things simple

Rather, it’s about using tools that are readily available, and adapting campaigns so that they use data, skills and processes in the right way to meet clearly-defined objectives.

With data in particular, marketers can feel overwhelmed by the amount that is available, and at a loss as to how to make the best use of it. However, a new whitepaper produced by Econsultancy and TAP London, ‘Three Steps to Investing in Better Marketing’, argues that it isn’t always necessary to rely on massive databases to make sense of data.

Instead, as Thomas Fordham, Co-Founder of TAP London, points out, it’s about keeping it simple. “The key is to simplify data by organising it around small, segmented customer bases. Rather than have an entire database, it’s far more useful to have refined, targeted segments that can be further refined by, for example, people who are responsive to emails in the afternoon, and those who are better targeted in the evening.”

Here are three practical tips from the whitepaper on how marketers can keep their work with data simple and focused. For even more tips on getting the most out of martech, organising your teams and adapting your processes, download the full whitepaper.

1. Focus on customer need

Giffgaff, the contract-free mobile telecom provider, worked with TAP London to improve its strategy for onboarding new customers. In the first month of a subscription, the company tries to ensure that its customers (referred to as ‘members’) feel properly welcomed and are aware of all the services available to them – enough that they will renew their package at the end of the month.

Giffgaff felt that this process needed to be snappier and more data-led. Richard Fullerton, CRM Lead at giffgaff, reflects that, “We were trying to get a lot of information over in long, dense emails that weren’t targeted. We were assuming that people knew a lot about our service and that they would give us more attention than they may have.”

The solution? Giffgaff cut down each email to a single core message. Where possible, they also targeted the email at members who needed the information more than others.

2. Send the right message at the right time

Giffgaff also drastically cut back on the number of emails that it was sending to its members, using the available data to determine which message was right for which customer segments at each part of their journey.

“A good example is if they haven’t been using [their] data, we message them to see if they are aware they can be using data with us and, if they are having problems, point them to where they can check their settings and look for help,” says Fullerton. “It’s the same if someone hasn’t been making any calls or accessed their voice mail. We send out the relevant information to help them.”

While these details about customers were always available to the giffgaff team, it wasn’t until they started to examine how they could match email content to the needs of customer segments that the marketing team truly made full use of their data to provide a more personalised service.

3. Use a targeted approach

Another brand that has worked with TAP London to improve its use of data is Petplan, the specialised pet insurer, part of Allianz Insurance. Previously, Petplan was taking a “scatter-gun”, one-size-fits-all approach to its data and communications, without tailoring its messaging.

By taking its CRM in-house and getting it to work alongside the company’s business intelligence platform, Petplan was able to use the data it had on pets’ specific breeds and ages to send out relevant content and advice to customers.

“If a customer has made a claim, we can also tailor our communications to advise them on their next steps, knowing what we do about their pet,” says Peter Honeywood, CRM Performance Manager at Allianz Insurance.

The company moved from scatter-gun to sniper with its approach to data, and found that this targeted strategy performed considerably better than the generic communication sent out in the past, which didn’t take advantage of the data that the company already had at its fingertips.