ThoughtSpot AI Powered Analytics Enterprise Edition

What do you like best about the product?

What I like most about ThoughtSpot is how accessible it makes data for business users. Its interface is intuitive, and users can explore data, build Answers and use Liveboards with relatively little help from the Data Team.
Liveboards and Answers also usually load quickly, which makes them pleasant to use day to day. From a Data Team perspective, I appreciate being able to identify Liveboards with performance issues in TS Liveboard and investigate where improvements are needed.
ThoughtSpot also works with our Snowflake environment, and its REST API gives us flexibility to automate administrative tasks. For example, I used it to grant edit access to multiple Liveboards and Answers in bulk.

We’ve used ThoughtSpot as our BI platform for about three years, after moving from Tableau and Holistics. I appreciate how frequently the product evolves, with monthly releases bringing new features and improvements. Spotter has improved a lot over time, and the ability to create agents gives us more options for helping users ask questions in natural language.

I also appreciate our relationship with ThoughtSpot’s Customer Success team. The different CSMs we’ve worked with have been very responsive when we’ve needed help with urgent support issues.

What do you dislike about the product?

One area I’d like to see improved is Spotter. When we first started using it, it sometimes misunderstood questions or returned incorrect insights, which made it difficult to build trust and encourage adoption. It has improved since then, especially with the ability to create agents, but usage remains limited at Navan. Many people find ChatGPT more convenient because they can use it as a single place for a wider range of questions, including questions about data through Snowflake Semantic Views. We’re also not yet sure what advantages Spotter offers over using Snowflake Semantic Views in ChatGPT for our use cases.
I was also disappointed that Spotter became a paid feature in August. I think AI analytics is a major reason companies consider ThoughtSpot, so charging separately for Spotter makes its value harder to justify.
I’d like Spotter to help users discover existing content before creating a new Answer. If a question is already answered by a Liveboard or Answer, it could suggest a link to it or, if the content isn’t shared with the user, show the author’s name so they can request access.

TS Support team can also be slow to investigate bugs or provide a workaround. I don’t find the AI support chat particularly helpful, and I’d prefer the option to open a support case directly. That said, the CSMs we’ve worked with have been very responsive when we’ve needed help with urgent issues.

Managing copies of Liveboards can also be challenging. When users copy a Liveboard, their copy doesn’t receive updates or fixes made to the original, which can lead to discrepancies or outdated insights. I’d like an option on each Liveboard to prevent users from copying it. I could create a new Product Idea on the ThoughtSpot Community page, but my ideas are rarely considered.

Finally, I’d like the Security logs available through the API to be more complete. For example, they don’t always provide the UUID of a Liveboard or Answer that was created or modified. The logs also don’t clearly distinguish between an attempted edit and a completed update: a user clicking “Edit” without saving generates the same type of log as someone who actually changes the Liveboard. More detailed logs would help us identify what changed and who made the change, which would be valuable for compliance and audit purposes.

What problems is the product solving and how is that benefiting you?

ThoughtSpot helps us make data accessible to teams across Navan and reduces their reliance on the Data Team for every question or report. Business users can explore existing Liveboards, filter data, create their own Answers and share insights with stakeholders. This helps them get answers more quickly and allows the Data Team to focus on more complex requests.

It also helps teams monitor performance and make decisions. For example, Sales and Customer Success teams use Liveboards to track business metrics, identify opportunities and prepare customer business reviews. Other teams use ThoughtSpot for recurring reporting, such as tracking hiring and attrition or analyzing financial performance.

Another benefit is reducing manual reporting. Instead of repeatedly gathering data and updating spreadsheets, teams can use Liveboards and automate some recurring reports. In our user survey, several respondents said ThoughtSpot saved them time and helped them work more independently, although the experience varied depending on their use case and familiarity with the tool.

What do you like best about the product?

Its intuitive interface, AI-powered insights, and ability to make complex data easier to understand and explore.
It saves time, simplifies data analysis, and helps users make informed decisions without requiring advanced technical skills.

What do you dislike about the product?

Some features can have a learning curve, and advanced customizations may require technical knowledge. Performance can also depend on data quality and setup.

What problems is the product solving and how is that benefiting you?

ThoughtSpot helps simplify data analysis, reduce time spent searching for insights, and make better-informed decisions. It makes complex data more accessible and helps identify trends and potential issues faster.

What do you like best about the product?

Analysis is really easy to do using ThoughtSpot. we just type a question into the system and get an answer in a matter of seconds in the form of a chart. The support team are quick to respond and the online knowledgebases are very helpful. The interface is very clean and easy to navigate. The search box means that typing in a question give us a chart straight away meaning anyone without any technical knowledge should find it easy to use for analysis. The Live boards are easy to read and share. It does take some time to learn how to create more complex analysis. Performance is also impacted with very large datasets. It integrates well with major cloud based data warehouses and data platforms so we can easily use live data. This means that our reports are consistent and saves time. However it take some work to set this up and may require some technical knowledge.

What do you dislike about the product?

we requires some technical knowledge to set up. it takes time to correctly set up. The results of the tool rely highly on how well the data has been prepared. The setup of the platform requires some strict and clean data modeling. If the base data isn’t modeled correctly then the search can be an issue. There is a high learning curve at the start for new administrators. it is expensive for smaller businesses or growing start ups looking to implement enterprise features. when we are searching large amount of data then it cause loading delay

What problems is the product solving and how is that benefiting you?

By reducing reliance on analysts and IT we are able to make everyday reporting much faster. users quickly search for answers without having to wait for manual reporting processes. Non-technical users often struggle to get valuable insights from data as they don’t have knowledge of SQL or complex data modelling language.it gives permission to users to ask questions in natural language By giving non-technical business users instant and unrestricted access to accurate insights it is better aligned as a team, work collaboratively across departments and make data driven decisions every day. removing reporting delays are more efficient when interacting with enterprise data that provides us an impressive ROI.

What do you like best about the product?

I like ThoughtSpot’s search-based querying. I can ask questions about our sales and marketing data in plain language and get a chart in seconds without knowing SQL or how the tables are joined. Ad hoc questions that used to take a day or two now take a few minutes, and managers can answer many of their own questions instead of filing dashboard requests with the data team. SpotIQ has also caught a couple of regional sales dips we hadn’t noticed in our dashboards. Connecting Snowflake was quick, and once the data modeling was done, rolling ThoughtSpot out to business users was smooth and required very little training.

What do you dislike about the product?

Getting ThoughtSpot search working well took real upfront effort from our data team. We had to clean up table joins and rename columns, and it took a few weeks before search returned accurate results. The search can also struggle with ambiguous phrasing, like confusing “last quarter” with “this quarter,” so I need to sanity-check results before sharing them with leadership.

What problems is the product solving and how is that benefiting you?

ThoughtSpot cuts ad hoc data questions from a 1–2 day wait to a few minutes of searching and reduces the backlog of dashboard requests, so managers can answer questions like weekly sales by region without filing a ticket.

What do you like best about the product?

It has a Google-like interface as it eliminates the frustration of relying on a data analyst to change a filter, add a dimension, or answer a question. It also supports direct queries as it connects natively in real-time to platforms like Amazon Redshift or Google BigQuery without moving or copying data.

What do you dislike about the product?

The rigorous preparatory work as it has an extreme dependency on the semantic layer for the search bar to understand natural language questions. Engineers must prepare and tag all data. Its graphical flexibility and dashboard interface are limited as it has very little aesthetic customization and lacks advanced visualizations.

What problems is the product solving and how is that benefiting you?

The bottleneck in the data team as any business user can write their query in natural language and get a visual response in seconds. Also, the rigidity of static dashboards as it can change dimensions, cross variables, and perform impromptu queries in real-time, although nothing too specific. Its AI engine simultaneously analyzes millions of combinations in the background and shows key factors, solving the slowness of other systems by providing the data.

What do you like best about the product?

I really like how all the data is in one place, and how easy it is to create graphs. I also really like the feature that lets you share the graphs you create.

What do you dislike about the product?

It’s not necessarily ThoughtSpot’s fault, but sometimes there are datasets that aren’t in the system yet, and you have to create them yourself or request that they be created.

What problems is the product solving and how is that benefiting you?

The way the data is presented to us is very beneficial. Since we have to make decisions on a daily basis, this helps us a lot.

What do you like best about the product?

We like that non-technical users can get answers in seconds by asking questions through search and Spotter. Spotter has cut ad-hoc data requests to our team by more than half, so we can focus on product features. The Visual Embed SDK is well designed, supports React, and gives us events and host-app actions for deep integration. The Developer Playground and code samples made embedding a Liveboard quick, and we shipped customer-facing analytics in weeks instead of spending months building a custom UI. TML in Git lets us review changes through pull requests and deploy them automatically, with fewer production mistakes. We also like that the REST API v2 is clean, row-level security handles tenant isolation, and live queries on Snowflake keep data fresh without extracts or ETL jobs to maintain. Connecting Snowflake and creating our first models took a couple of days, so the initial setup was fairly easy.

What do you dislike about the product?

Search and Spotter work well only when the data model is clean, so I spend real effort on modeling, synonyms, and indexing before users get good results. Complex calculations and formulas are harder than in SQL. Live queries on large tables can increase Snowflake costs if I don’t tune them. Liveboard visual customization is limited compared to traditional BI tools, and pricing is high for a growing team. Getting clean models, synonyms, row-level security, and SSO right for production also took a few weeks.

What problems is the product solving and how is that benefiting you?

ThoughtSpot cuts our team’s ad-hoc report requests because users search data themselves instead of asking us to write SQL or build dashboards. Embedding saves us from building an analytics UI; row-level security handles tenant isolation, and TML in Git lets us review and promote changes between dev and prod like normal code.

What do you like best about the product?

I use ThoughtSpot to explore data and find useful information easily. It’s simple to use and helps me understand things without much difficulty. I use search to find information and check reports, and the charts and tables make information easier to understand and compare. Search saves me time because I don’t have to check everything manually. I find ThoughtSpot useful for my regular work and prefer it when I need to explore data quickly.

What do you dislike about the product?

Sometimes I find it difficult to understand Liveboards and customize charts. The filters and search suggestions are not always clear, and I think the interface could be more beginner-friendly, with better explanations for some features. The initial setup wasn’t very difficult, but it took some time to understand the settings and connect everything properly. Our team is still getting used to ThoughtSpot.

What problems is the product solving and how is that benefiting you?

ThoughtSpot helps me find data quickly without going through lots of information manually, and makes it easier for me to understand and analyze data.

What do you like best about the product?

Semantic Layer Tools provided by ThoughtSpot have been an absolute match between our raw marketing data and executing campaigns every day. They allow us to get standardized definitions of metrics such as blended CAC for all our ads channels. Therefore, I am able to ask complex questions and get precise answers regarding the channel profitability.

What do you dislike about the product?

It takes time to train junior media buyers to ask questions correctly, as sometimes if they use the wrong terms, ThoughtSpot may produce inappropriate charts.

What problems is the product solving and how is that benefiting you?

It used to be really difficult for us to deal with fragmented data from several different ad networks. Thanks to ThoughtSpot, I can immediately see which ad creatives bring the most subscriptions to Monad.

What do you like best about the product?

I like that ThoughtSpot gives me immediate answers about the data without relying on a team of analysts; it's like a search engine connected to my company's database. It helps me make real-time decisions and quickly obtain real data. It removes the entry barrier to data and turns interaction with corporate information into a smooth conversation, allowing me to explore it more deeply easily. It also reduces simple reports and the waiting time for personalized answers, making it possible for anyone to query the information. The most valuable thing for me is that it makes data analysis more dynamic and everyday. Compared to Tellius, ThoughtSpot has what it takes for enterprise scale, and its engine offers very smooth interaction. The connection to data sources is fast, and with a good team, modeling work is not a problem.

What do you dislike about the product?

Although almost everything is perfect for me, the initial setup can become complex if I don't have a rigorous data model. The prices seem somewhat high to me, and ThoughtSpot relies heavily on the quality of data sources.

What problems is the product solving and how is that benefiting you?

With ThoughtSpot, I reduce the number of simple reports so analysts can focus on big problems; I eliminate the wait for personalized answers and reduce the complexity of platforms so anyone can query the data.