Started by analysing existing user behaviour data (e.g. Heat map, visitor recording, traffic flow) collected via Visual Web Optimiser and Google Analytics, I identified key landing page (homepage) and drop off page (pricing tool).
To understand what users were looking for and why they dropped off, I have planned and organised one-to-one usability tests.
Users were asked to explore a full range of scenarios, from browsing to submit an enquiry. During the session I recorded the actions of the user and their verbal response. It was painfully apparent that the pricing tool was asking for sensitive information (estimated revenue) which users were very reluctant to give away. Since they would not give away that information, they could not see the pricing. Without knowing how much they'd need to pay, they were reluctant to send an enquiry (i.e. to become a qualified marketing lead).
Interviews were conducted to understand how they would make a buying decision, context of using such service, and the pain point of using their current service providers.
The quantitative data from web analysis gave me insights of what user did.
The qualitative data from usability tests and user interview gave me insights of why user did it.
Triangulating the two gave me a good idea of the context, and I created prototypes to help user find out about the pricing info and what services was covered. The aim is to provide transparency of the pricing structure, as it was essential for users to know what to expect before they enquire. The prototype was improved iteratively after 2 rounds of testing with users. Completion rate of becoming a qualified marketing lead on the last prototype was higher than the original product.
Interview results informed the creation of value propositions and persona. These artefacts informed my split tests on the live site on different value propositions. It also informed my colleagues' activites on various marketing channels, e.g. intent of using the product has informed what keywords to target for in pay-per-click marketing and search engine optimisation, and the demographics has informed segmentation on Linkedin advertising.