Birst in eLearning Sales and Ops
March 23, 2018
Birst in eLearning Sales and Ops
Score 8 out of 10
Vetted Review
Verified User
Overall Satisfaction with Birst
We use Birst internally to analyze sales and marketing data to improve our marketing efforts (ROI on digital marketing spend) and to provide insights to our eLearning operations team.
Our marketing team analyzes time series of marketing spend vs the revenue received attributable to that spend and adjusts digital campaigns to optimize ROI.
The operations team extract student engagement data from our LMS and identifies students at risk of not completing their coursework in a timely fashion so that they can engage with them to identify issues and assist.
Our marketing team analyzes time series of marketing spend vs the revenue received attributable to that spend and adjusts digital campaigns to optimize ROI.
The operations team extract student engagement data from our LMS and identifies students at risk of not completing their coursework in a timely fashion so that they can engage with them to identify issues and assist.
- Birst is an platform that provides connectors to some of the applications we use, but also allows us to bring in data from disparate systems to perform ETL and integrate all of the data for analyses. It makes no assumptions about your data, which is good for us, as we have a lot of customizations to many of our systems.
- Birst is making inroads towards a more modern UI.
- The Birst product uses it's own query language (BQL) which we feel has been implemented in different ways in different parts of the product.
- This makes learning the entire product more difficult than it ought to be.
- The Birst idea of grains and hierarchies is hard to get a foothold on. I don't think I completely get it yet.
Birst was better than Domo for our needs because we could get in and tinker with it. Our impression of Domo was that it had a lot of connectors and ready to go reports, but it made too many assumptions about applications we use. We customize too much to use a "ready to go" solution like that.
When we looked at Tableau, we liked its visualization capabilities, but it wasn't going to help us do the extractions, ETL, and warehousing of data. It may have come some distance since then.
When we looked at Tableau, we liked its visualization capabilities, but it wasn't going to help us do the extractions, ETL, and warehousing of data. It may have come some distance since then.