CASE STUDIES

Global database platform saves >10 business days per month with Frame AI

A global database platform with >6k customers leverages Frame AI to unify their customer voice across disparate channels, normalize and predict satisfaction scores so that they can identify and proactively address gaps in their customer experience. The company supports Enterprise customers in shared Slack channels and uses a combination of Intercom and Salesforce Service Cloud to support the majority of their customers. 

Before working with Frame AI, the company lacked an effective, consistent way to measure customer sentiment. CSAT data was sparse due to low response rates, and inconsistently calibrated, since the scores came from different systems. The Salesforce Service Cloud version of CSAT offered customers a survey on a scale of 1-7, whereas Intercom provided a scale of 3 emojis. In Slack, they had no official means of gathering sentiment data. “We basically had no hope of understanding what was driving sentiment and addressing the drivers appropriately, if we couldn’t even measure sentiment on the same scale,” says the company’s Head of Customer Operations. 

With Frame AI, the company looks directly at its holistic customer voice to pinpoint customer experience drivers. Within weeks, Frame AI unified the company’s three primary customer voice channels, immediately allowing the team to understand Intercom and Slack data with context from Salesforce custom objects, such as customer tenure. Within one month, using existing CSAT data recalibrated by Frame AI, the company could make sense of its current sentiment data.

With a recalibrated CSAT score range, the next step was to predict scores across the non-responsive majority. “Having the scores in a normalized format means we can easily interpret them, and having them applied to every single conversation means we can buy into the trends we see in aggregate. Decisions that used to take weeks and months now take hours and days, and we can see the impact of our data-driven decision-making right away.” 

Frame AI’s predicted scores also offered the company a level of nuance that was far more actionable than traditional CSAT scores. The AI-driven scores provide attribution across discrete aspects of the customer’s experience, such as a product frustration or an especially helpful support experience. “Now that we’re sharing data with this level of coverage and context, instead of anecdotes, cross-functional meetings feel less political and more productive. Also, having the flexibility to tune underlying models based on unique factors to our business was an enormous consideration for us when we decided to pursue an AI-based approach to sentiment. Frame AI’s configurability stood out to me as an early selling point, and it continues to impress me, well past implementation. It’s like having a dedicated data team, laser-focused on the customer voice.”  

The company also relies on Frame AI’s configurability to keep all CX stakeholders aligned. “Having the ability to push scores into our systems of record means we can do something about what the data tells us. We have the Frame scores from every conversation pushed back into our Salesforce instance, which makes reporting a breeze. Success Managers can monitor fluctuations in scores across conversations with their accounts. We also feed reporting into our internal data lake that feeds analysis and prioritization for the entire company. I’d estimate that this saves the company at least 10 business days every single month in terms of productivity.”



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