Data-driven marketing has become an essential focus for marketers over the past few years, and it’s clear why. Analysing data helps us make informed decisions about where to focus our time, money and efforts when it comes to producing content for different audiences. Making choices based on preference, ignoring the data available, is no longer how marketers should be working. They simply can’t afford to.
Unfortunately, not everyone has caught on to this yet.
A couple of years ago Turtl pitched to a potential client in the financial publishing sector. The spotlight was given to the analytics feature.
With Turtl, the client would receive detailed analytics on the content they create, such as reads, sign-ups and average read times. They’d also be able to identify individual readers and see which chapters they engage with the most. They could use this insight to better target subsets within their audience and evaluate the value (and price) of ad space accordingly.
Curious, the client decided to carry out an A/B test using Turtl and their existing design tool.
Working with the design team, the company published two emails, identical in every way except the content piece that was linked. The email was sent out to a total audience of 1,200 recipients, 600 each. The main objectives were to improve click-through rates and increase engagement.
The team gathered the data, exchanged a few looks and shared the results with us.
Turtl outperformed the competition, HANDS DOWN. And with Turtl’s data to prove readership numbers in more detail, the client would be able to charge more for ad space. Hurray! Go us.
The design team were not on board. They weren’t keen on leaving their current ways of working behind. So what, right? Using Turtl would literally increase revenue opportunities. A no brainer, surely!
Wrong – It was never going to be that simple now, was it?
It turns out the designers were a dominant force in the decision-making process, and they didn’t care about the data. The more senior stakeholder recognised the importance of the data but didn’t want to undermine the team.
The evidence was clear, but in the end, the decision was made based on preference.
This is just one example of how the weighting of decisions undervalues hard results.
Businesses are letting creative teams produce content based on intuition without evaluating whether their work is delivering returns. Until these businesses adapt their mindset, the battle against disposable content will continue.
Curious about what Turtl could do for your data analysis and client engagement? Click here to speak to our team.
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