TOWER London was struggling with a low conversion rate in a highly competitive market where it is difficult to differentiate on products due to multiple other retailers also selling them, and the limited control over how to present other brands products.

Therefore, the focus needed to be on WHY TOWER London? Why should customers buy from TOWER London and not another store, and ideally, without overly focusing on price.

I began working with TOWER London in October 2020 and after introducing new research methods, and testing processes began to roll out new A/B tests across the site to improve conversion rates.

In addition, an audit of the website revealed various technical bugs that were then fixed by working with their development agency.

My process starts with research:

1. A full review of Google Analytics to identify where blockages appear in the customer journey
2. Review heatmaps in tools such as Hotjar to see how site visitors are interacting on pages where those blockages occur.
3. Running on-site surveys such as Exit Intent, to discover why customers are abandoning the site
4. Customer interviews, One to One where possible, to get detailed, qualitative insight as to what customers like and don't like about the website, about competitors, and why they buy from the stores they choose to spend their money with.

This feeds into a testing pipeline (and prioritisation process), as well as identifying areas for quick wins, such as bugs on certain browsers that are fixable and don't need testing.

Then we move into an ongoing Testing & Iteration phase.

This involves working alongside designers & developers to design the tests, QA them to ensure they work properly and don't have any unintended negative impact on the website and set the test live.

Once the test has hit statistical significance with a minimum number of site visitors, the test is ended and either rolled out at 100% until the development agency can build the feature, or ended as a Losing test.

While other tests are then being put live, the results are analysed to identify areas for further improvement, or to gain insight into why a test failed.