In two WARC Best Practice papers, Crawford Hollingworth and Liz Barker, of The Behavioural Architects, explain how to use behavioural science to build more effective everyday communications and detail the seven concepts that are key to achieving this.
Behavioural science embraces the cognitive biases and nuances of human behaviour, they note, so simply by looking at a brand’s communications through a behavioural science lens can help understand, for example, how cognitively easy a letter is to understand, absorb and act upon.
This process can also highlight how a communication may or may not affect the sense of urgency to act or how sensitive it is to the specific context in which it will be received and read.
“Everyday communications can be optimised to drive desired behavioural outcomes by improving clarity, salience and impact,” they state.
A four-step process starts with clearly defining the action marketers want their customers to take and identifying any potential behavioural barriers.
Then it is necessary to understand where and when communications will be received, read and acted upon, since comms may need to be adapted for different audiences and contexts.
The next stage is to audit the communications through a behavioural science lens. The second paper addresses the most relevant and effective concepts here, including: Choice Architecture, Salience, Anchoring, Framing, Chunking, Cognitive Ease and Social Norms.
Finally, test and learn. “Whilst it can be tempting to roll out changes in communications assuming that they will be effective, it’s best to trial and test using a control group initially,” Hollingworth and Barker advise.
“Whilst behavioural science can provide a guide to what to do and change, tiny subtle differences in versions of comms could make all the difference,” they say.
And repeated iterations need not be a major imposition given that everyday communications are fairly easy and low cost to test. Further, many organisations have access to a large database of customers, so getting a large enough sample size to ensure tests are sufficiently rigorous is rarely a problem.
Sourced from WARC