Website audit
Find out how customers really feel about your website
Highlights:
Quali-quant best practice review
Interviews with audience for insight
Reveal success factors
Expose emotional barriers
I was originally inspired to create this method, by some tech geeks from Singapore. We were part of the digital start-up crew at Ogilvy who were figuring out how to use the internet as a commercial tool some time ago.
Get experts to score you vs the competition
They had a quali-quant audit tool that enabled consistent team review and rating of site features and functions. I picked up on that core idea and built it into a tool that assesses what marketers need to know - if their customers benefit from their website. With a systematic method, your site and your competitors are reviewed and rated. The result is a scorecard with a ranking to understand how your site stands up compared to best practices and competitors.
Talk to people and watch how they really behave
Add to the scorecard research interviews, to understand the feelings of your audience as they go through the site. In addition to seeing where they go, listening to them talk about what they take-away from your communications uncovers successful points and barriers. Dialogue can reveal emotional reactions that can inspire you to make impactful changes.
Financial services category learning
A comprehensive review for a leading Canadian financial services provider uncovered an emotional barrier, which explained high user engagement but low conversion.
Primary research into Gen X and Gen Y content consumption on the product content revealed:
Quickly read the first couple of sections on the homepage
Scroll down the homepage but only scim to look for something eye-catching
Do not to navigate to other pages
Use a configurator to find ‘personalized’ product info
The actionable insight:
Although website visitors were interested in the product, they froze when they received a 'personalized' product recommendation. This led to site abandonment. Visitors had answered all the questions in the tool and, until that point, had not dropped off.
The research revealed that they actually didn’t understand many of the questions and faked their answers. They lacked confidence in their ability to give accurate info about their needs and therefore didn’t believe the personalized recommendation was right for them - and gave up.