Personalization of

Bell wanted to increase the direct personalization of the experience on their website. Based on their datas and the multiplicity of user flows, I created a data model system that helped to determine the different situations, user profiles and consumption profiles to therefore create all the possible user stories and design the most personalized messages.

Building a process

The first challenge was how to review, iterate and communicate user stories for the developers to implement. My proposition planned to identify different areas of the site that are independent enough to be taken as personalization silos, or features. Then for each we would thoroughly review the website data both behavioral and to build user profiles. We needed to identify who were we designing for and what could we help them with.

Schema of process: User profile, user flow, mapping and designing

Identifying all the options

Based on the general path, we started to identify touch points, steps and opportunity to build personalized stories.

Example of the search feature

I started with identifying all the possible flows based on the data collected on the site for which the user has a specific motivation, a different entry point and profile to identify what could we leverage and when.

Common Case of user flow for a search feature

Building User stories motivating the company

The User stories were then broken down by Design Principles:

  • Anticipation : Knowing data and previous history (behaviour), we can anticipate user’s needs.
  • Hints : Contextual hints addressing the user directly regarding user’s account will help them make the best of the website.
  • Unification : Presenting the answers to the queries on a single page will help cross sells, support and guide the user into better formulation of their query.
  • Interactions : With call to actions in the search results and personalized keywords, we help the user formulate their needs more efficiently.

Build automation of the personalization

Data model for automation of personalization

Once all the site was mapped, I built a Data Model that helped automating the user stories and how the impact each other in every section of the site.

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