Lattice Engines . Predictive Lead Scoring . 2015

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While at Lattice, I led the effort to define and design the first customer-facing version of our Lead Scoring product. When I started, there was already a demo with obvious usability issues. I made the case, using feedback from internal users and customers, to re-think the design and the scope of the project so the UX would:

  • Demo well to marketers
  • Demonstrate value-add and credibility of predictive analytics
  • Show leading-edge visualization(s)
  • Provide useful customer data insights (if possible)

I worked closely with the Product Manager, with lots of input from internal and external customers to define the requirements and scope of the project and iterate on design concepts. I also managed an external Visual Design Consultant and CSS + HTML implementation specialist to take the designs from wireframes to a final, implemented UI.

The resulting design focused on helping Marketing Professionals evaluate the scoring model based on, for the most part, whether or not the score distribution and the attributes that are showing up as predictive (e.g. if a Lead is from the Financial Industry, they are 5x more likely to convert) make sense to them.

The product launch was successful and helped Lattice win a number of deals. There are currently 50 active customers, and the application is used both by the Lattice Engagement Managers, who work with Marketing groups to build and evaluate the model, as well as the Marketers (typically a Director of Demand Generation or Marketing Ops professional).