- Problem
Customers were unsure about how to take action on the insights we were giving them about their business.
- Solution
A dashboarding experience that leveraged our powerful NLP AI to convert metrics into prescriptive action items for their business.
- Result
This upgrade earned the highest NPS score of the entire product ecosystem at 59 points.
- Is it still live?
Yes! Though it isn't public due to it being a B2B SaaS product. You can learn more about Reputation Insights and request a demo here.
I went through a series of discussions with the PM to set the objective of the project. In addition to multiple internal exercises to ensure clear vision, we also did a large number of qualitative interviews with customers to better understand their pain points and objectives with the Reputation Score page. Once we were able to understand that, we created a variety of persona types to represent the users interests and preferences across multiple industries, technical abilities, and roles to help us narrow in on what mattered most for the MVP.
It was an integral part of the collaboration and discovery process to create mocks and utilize them in our user research. I went through a series of feedback loops to help us define our product vision for the MVP and for the future of the product both with the PM and with our customers.
Not only was the customer feedback extremely positive, it skyrocketed the product to having the highest NPS score of all the products in the Reputation ecosystem at 59 points.
This score summary not only allows you to easily see your score, but how you compare to the industry benchmark and other companies that are "best in class."
Our proprietary score allows for an easy and intuitive way to understand how your company is doing when it comes to your online reputation by aggregating a variety of factors into one easy to understand Reputation Score.
Our customers asked to have a more clear description of how to improve their online reputation, so that is exactly what we gave them. Recommendations informed by our industry leading machine learning engine allow us to give precise instructions on how our customers can improve their reputation score.
For those who are interested in getting into the nitty-gritty of the score, they are able to take a look at our components. They describe in detail all of the factors that go into the score, how they are defined, and give you a good sense of how you are performing in each area over time.
This project challenged me to figure out how to manage multiple stakeholder opinions while guiding us to a final solution. The PM's opinion of what direction we should take was strongly influenced by each customer call we took, which caused a lot pivots and scope creep.
Though the project did end up taking much longer than expected, it was a great opportunity to educate the product organization on how to digest qualitative feedback and synthesize it into a clear direction. We were able to take this wisdom forward with us, allowing us to have a more streamlined approach with future projects.