Backstory Cracks Customer Value Code with Lightning-Fast Tiering Analysis
Backstory, a company in the tech industry, recently implemented an account tiering analysis that helped them identify their most valuable customers. The project, which was led by Haya Kamola, took only three to four days to complete, down from the usual five teams and one quarter of time it used to take.
The goal of the project was to define what made a customer 'golden' and then measure all accounts against that definition. The team started by getting input from account teams and senior leadership on what characteristics made certain customers stand out. They landed on several key factors, including treating Backstory as a core part of their tech stack, planning five years ahead with the platform at the center, and wanting to inform the roadmap.
Kamola explained that most of the signals that mattered didn't exist yet, so they built them as part of the analysis. They created an AI maturity score, which assessed a customer's culture, investment level, technology stack, talent, and willingness to engage on hard problems. They also developed a signal for tech stack mix, which was previously done manually but is now automated.
The team used four connectors to pull data from various sources, including Amplitude, Atlassian, Jira, Salesforce, and Slack. This reduced the time it took to collect data from several weeks to just three days. The analysis runs as a defined sequence in Claude, using Cowork, and takes around 20 minutes to complete.
After four iterations of refining the signals, the team landed on four scoring buckets: growth potential, AI maturity, engagement level, and account health. They found that customers who requested features at a high volume were actually more likely to be high adopters. The output was four tiers of customer value, with Tier A being the most valuable and Tier D being the least.
The company plans to rerun the analysis quarterly to track movement between tiers and refresh their understanding of customer value.