Service and Support
ThoughtSpot customer service and support are generally appreciated for responsiveness and expertise. Technical support is usually quick and helpful, but some users find it lacks proactivity and a robust knowledge base. Support ratings vary, with several users rating it between six and eight out of ten, while some experience delays and insufficient assistance. A dedicated customer success contact and online ticket submissions with a prompt response time add value.
Deployment
Users found ThoughtSpot's initial setup to be generally straightforward, often highlighting strong customer support. While some mention cloud setups being easier, others focus on seamless integration with databases. Teams for implementation are small, ranging from three to five people. Timeframes vary, with one instance taking only about an hour. Notably, ThoughtSpot's drag-and-drop feature and compatibility ease data integration despite occasional challenges, such as initial complexity with features like TML and security rules.
Scalability
ThoughtSpot is deemed scalable, particularly when integrated with Snowflake, allowing automatic scaling. Users report managing large user bases, though complexities arise in roles and security. Some find governance challenging with multiple dashboards. Negotiating contracts wisely influences scalability. It accommodates thousands of users without significant issues yet lacks advanced features compared to competitors like Tableau. Most rate its scalability eight out of ten, indicating satisfaction but noting potential for adding new features.
Stability
ThoughtSpot operates with high stability, efficiently managing large datasets and surpassing many other BI tools in speed. Users report minimal downtimes or crashes, with smooth upgrades. Some incidents persist, like prolonged indexing after changes and issues with resizing columns. They find the feature set mature and dependable, though occasionally encountering enhancements needed for integration, primarily between DBT and ThoughtSpot. Resource-consuming workarounds for missing features have occasionally led to performance reductions.