fromthegut

Thank you, this is a great list!

It looks like we forgot to update the mobile version of the website when we crossed 3000. Thanks for letting us know!

The Snowflake comparison doesn't really make sense here because of different ACVs and businesses models.

Black Mirror. S3 E3

Yes, we plan to add Shopify, Klaviyo and many more integrations soon!

This is so accurate, it feels as if our actual customer wrote it :)

We helped many agencies to automate reporting the way you described: https://www.narrative.bi/solutions/agencies

We do a lot of pre-processing and post-processing with iterative generations and a voting system to ensure accuracy.

AI is mostly used for natural language generation.

For insight-generation, we built our own algorithm (ML-based).

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.

Hey @vood, thanks for the feedback!

We actually improved our drill-downs recently. Check it out: https://www.narrative.bi/product-updates/purchase-insights-g...

It's totally OK to use Narrative BI in a no-UI way via email or slack, but our web UI provides more advanced insights so you may want to check it from time to time. Simply click on an insight in your email and you'll be redirected to a more detailed view.

Good luck then!

You can learn more about our solutions here https://www.narrative.bi/solutions

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

Your interpretation is accurate! The self service connectors we build are mostly marketing/ sales data sources, so the narratives we generate are focused on growth insights and recommendations.

Feel free to try: would love to hear your feedback!

Thanks for the feedback!

Historically, we've been focused on growth use cases (marketing, sales, PLG). "Data narratives" is how we call our natural language written insights (AI generated). So it might sound like a corporate jargon but actually describes our value proposition. Will think how to make it more clear. Thanks!

Hi HN, Yury and Michael are here to answer your questions.

2 years ago, we launched Narrative BI to make data analytics available for everyone. Since then we helped 2,500+ teams get insights from their marketing data.

Our backstory is here: https://news.ycombinator.com/item?id=33627953

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 (unlike our previous version designed for specific data connectors).