Customer experience management is about using CX data to impact what happens next—and there’s no better way to do that than using predictive analytics to operate in real time.
With so many feedback channels, it’s easy to see how that haystack of data can lead to major issues flying under the radar. SMG’s AI-powered text analytics leverages industry-specific machine learning models—fed by billions of customer comments—to predict whether each piece of unstructured data indicates a “needle” issue that warrants your immediate attention.
Food safety detection is one very impactful example of this. There are few things that can damage a brand’s image more than foodborne illness. That’s why we made this our first priority and developed a model that detects when illness-related comments or phrases are referenced in unstructured feedback.
The food safety model is trained to detect when a customer comments that they or someone they know got physically sick from food during a visit. It uses a proprietary algorithm that excludes tangential ideas—such as excessively short comments or fear of sickness—to reduce false positives and provide more accurate results.
Once a potential food safety incident is detected, SMG’s case management solution triggers a real-time alert so the brand can assess the incident and respond quickly.
This kind of streamlined process in a tech platform is the best way for brands to stay informed, respond quickly, and mitigate operational risk effectively. And as we’ve discussed in previous blogs, timing is everything when it comes to resolving customer issues—particularly those that involve their health. With 1 in 3 customers saying they’ll leave a brand they love after one bad experience, you need to act fast when trouble hits.
To learn more about how our AI advancements are helping organizations surface more actionable insights, download the white paper: 3 ways data science is reshaping how brands approach CX data.