1. Report automation. People connect their marketing data sources and get automated reports on key metrics
2. Anomaly detection. We generate alerts when we see unusual patterns that affect your key business metrics
3. Natural language insights: we uncover interesting patterns and correlations in your data and provide recommendations on how you can improve/optimize your campaigns
> We started as a freemium product and built a unique business data set. We used this dataset to launch NBI.AI - a Generative BI platform that can be connected to virtually any structured data source
We don't use customers' data (eg data from your data sources) for training purposes. What we use is meta-data like objectives, behavioral data, preferences and feedback loop (was it helpful y/n) to personalize the insights.
Not a customer nor have I used the app, but I think one use case you're hitting is the following:
I'm an ad management agency that does google ads for 200x ecommerce companies. Every month I have my marketing specialist create a powerpoint presentation with graphs of their performance + a narrative about it (ROAS was up 23.5% but this was mostly due to on-brand search). Instead of my marketing analyst creating this presentation, I just generate it with nbi.ai.
But let me describe the most popular use cases:
1. Report automation. People connect their marketing data sources and get automated reports on key metrics 2. Anomaly detection. We generate alerts when we see unusual patterns that affect your key business metrics 3. Natural language insights: we uncover interesting patterns and correlations in your data and provide recommendations on how you can improve/optimize your campaigns