The credo of Dr Gregory House – and we agree. People do lie and often not knowingly.
Let’s say for example, you ardently believe Fairy Liquid is the best washing up liquid of all time.
However, let’s suppose new evidence arose that proves it is more expensive, weaker and contains more harmful chemicals than other alternatives.
When trying a competitor liquid you might find it cheaper (the change in your pocket tells you so), but your hands are no softer, your plates are no cleaner, it doesn’t smell any sweeter…
Your love of Fairy – and your belief that it is the superior washing up liquid – is creating a confirmation bias in your findings when using the competitor brand.
Confirmation bias is the tendency to search for, interpret or remember information in a way that confirms our beliefs or hypotheses. And we all do it. Whether it’s washing up liquid or political views, we rationalise situations according to our beliefs.
What has this got to do with data? As John Merakovsky at Experian explains, confirmation bias is “the reason you should always balance your decisions about how you serve your customers based on both what they say, and what they do.” And that, “whilst you must listen to your customers to better serve their needs today, don’t count on their views and opinions as your source of innovation.”
In other words, all talk and no data makes for a limited view and bad decision making.
Big data should solve all our problems then, right? Not necessarily. We love this cartoon from Tom Fishburne:
“We have to be careful with what data we choose to listen to…Big data doesn’t inherently lead to greater insight. Marketers have greater access to data than ever before. But finding the signal in all of that noise is the hard part,” he shares in the accompanying blog post.
Accommodating confirmation bias is part of that problem, along with data quality – how much of our data is relevant, current and accurate? And what about data literacy? Who is teaching us how to read data?
The Media Octopus takes the ‘test and adjust’ approach to balancing customer ‘say and do’ differences as demonstrated in our customer acquisition infographic. Follow the customer journey and you’ll see we recommend action based not only on the statistical evidence of digital interaction but the conversational feedback and sentiment consumers pass between themselves and to the brand.
Split testing and changes to the cycle allow us to optimise customer acquisition based not only on what consumers say, but also what they do. The approach allows us to accommodate consumer biases and identify the data that leads to the best results.
If you’d like to know more about how The Media Octopus can help you to acquire more customers for your business get in touch with us today.