I like that it’s a very flexible collaboration and analysis tool. It solves a lot of the headaches that come with working alongside other analysts, and it also makes it easier to share those analyses with business stakeholders. On top of that, its LLM integration is solid and pushes the overall user-friendliness even further.

It integrates well with our data warehouse (BigQuery), and is generally quite performant. It's very useful that you can both run SQL and Python for analysis. The support team is very helpful. Review collected by and hosted on G2.com.

I would like it slightly more if it had more features to lock down reports and create truly reusable dashboards. Right now it's more of a scratchpad (which is very useful), but we still use Tableau next to it for our "gold standard" reports as Count can be quite "open" and does not (to my knowledge) allow for the possibility to completely lock down a certain canvas to enable users to use it as a dashboard. Review collected by and hosted on G2.com.

I really value the freedom of working in a canvas that lets us build dashboards, reports, and data applications with almost unlimited capabilities. Review collected by and hosted on G2.com.

There’s a learning curve for non-data engineers, such as business stakeholders. That said, the new AI features are helping reduce that gap. Review collected by and hosted on G2.com.

I have switched to Count for all the analysis I run, so I would say I use it on a daily-basis.

With Count, you can have queries, plots, text, reports, and comments all in the same place. I find this extremely valuable, as it effectively makes everything self-documenting: the queries that support the results, the interpretation, and the reviews that were made all live together. Moreover, we can collaborate in real-time on the same canvas, which is amazing.

I really like that Count allows you to create tiles and reference results, in a way that feels similar to a DAG in dbt. This helps avoid a lot of code duplication and significantly streamlines query creation. Personally, I think this makes a big difference because it allows me to split complex queries into clearly defined components and then combine their results as needed.

When using other tools, I sometimes felt constrained by the lack of flexible filtering, which was often managed at the organization level and pushed me toward hacky solutions. With Count, control cells make it easy to implement the exact filters you need, giving you a lot of freedom and power to build very flexible dashboards.

Finally, I think the Count support team is excellent. They are consistently helpful, whether I’m stuck or just looking for best practices to implement something in the tool. They either provide a solution or take note of the feedback to improve the product. A good example is the recent addition of support for different scales in facet plots, which addressed a limitation I personally encountered. Review collected by and hosted on G2.com.

Regarding areas for improvement, I do have a few ideas.

I think the construction of frames could live in a separate canvas, similar to how Tableau approaches dashboards. This would offer the best of both worlds: plots would remain close to the queries that generate their data, while still allowing the creation of a dedicated dashboard that brings everything together.

There are also some smaller usability issues that can make the interface feel unintuitive at times. For example, when creating custom plots, individual marks cannot be named, which makes it harder to understand what each mark represents. Similarly, when multiple marks are used, it’s not always clear which variable is assigned to the secondary axis.

Some solutions also feel a bit hacky—for instance, adding vertical lines to indicate events by using bar plots, where it’s not always obvious how to control the bar width cleanly.

Overall, these are relatively minor points. They don’t slow me down in my day-to-day work, and I see them more as a wishlist than as real blockers. As with any tool, there is always room for improvement—but Count is already a superb product. Review collected by and hosted on G2.com.

I like how easy it is to pull data from different sources and bring it together into a comprehensive, easy-to-use dashboard.

Also, having the ability to run SQL queries and Python scripts in one place makes things much easier and more flexible whenever we need to process data. Review collected by and hosted on G2.com.

This tool has a bit of a learning curve, and you need to get past that before you can really see its full value. Review collected by and hosted on G2.com.

I really enjoy how flexible and easy to use Count is. The layout is intuitive and there are an ever growing list of helpful features available to use. The output is very slick as well to create reports as it allows for creative visualisations and has a lot of templates to help if you need some inspiration. Review collected by and hosted on G2.com.

Count is still growing so there are very infrequently some issues that pop up, but the customer service team are really great and help is always on hand! It really feels like a company that is on the side of the customer and wants to help grow together, which is really appreciated. Review collected by and hosted on G2.com.

I really love the collaborative aspect of it, and how it helps facilitate storytelling in a smooth, natural way. You can also tell that team are passionate about building the best product to their customers. Delighted to have this as part of my analytical toolbox! Review collected by and hosted on G2.com.

Not many complaints, as somebody who writes SQL in BigQuery/dbt the switch to DuckDB syntax can be a tad annoying. But I appreciate the performance you get from DuckDB so I get their decision Review collected by and hosted on G2.com.

The flexibility and simplicity of having one tool for many purposes means Count is our primary tool within the Data and Analytics team, and it does most jobs so well that it is hard to justify using anything else!

An example project may involve exploring and interrogating data direct in our warehouse, combining it with CSV's to create models and analysis, bringing the stakeholder into the canvas to work collaboratively, sharing ideas and progress, then producing ad-hoc insights and analysis directly from the data on slides the stakeholder can share with the business, and finally creating standard interactive reporting/dashboards that are scheduled to refresh for use by the wider business - which we then monitor with Count Telemetry to make sure they are used. All of this in one tool, no switching between tools, no copy and pasting analysis or visuals into presentations, no keeping separate records of notes/ideas or feedback, it's all in one place.

Since we started using Count we have had great feedback from around the organisation. The speed at which we can work, the almost limitless ability to create visualisations and layouts that make sense, the ease of access and the admin/governance of users have made it a firm favourite across the board.

Added to the tools itself, the support from Count and the community they have built is exceptional and the future roadmap is always clearly driven by the customers and their feedback. Review collected by and hosted on G2.com.

Due to it's virtually unhindered flexibility compared to other tools, it can sometimes be difficult to find out how to do something you know should be obvious (e.g. move a legend) and there is an initial learning curve. However, once you get more familiar with the concept and UI (which doesn't actually take very long) then these things become easily solvable. Review collected by and hosted on G2.com.

Befriends sql, python, and visualizations Review collected by and hosted on G2.com.

Messy codebase, no tracking of changes. Review collected by and hosted on G2.com.

Count has become the first place I go when working with our data, and I usually don't leave. Where context used to be stored across multiple tabs, Miro boards, figma designs, spreadsheets and more, I can now pull everything into one canvas and work alongside it. I don't need to keep it all in my head any more.

Having all of the context in the same place also helps when coming back to something after some time away - there's no need to go searching for requirements, or alternate versions, everything can be dropped into the one place. Review collected by and hosted on G2.com.

Working with large datasets can be a little challenging. There is a tension between breaking out CTE's for visibility and aggregating early for efficiency. Finding the right balance has taken a little while. Review collected by and hosted on G2.com.

I really enjoy the canvas-style approach to BI. It feels much more fresh, speedy, and accessible than tools like Tableau. It's really well-suited for:

- Enabling data teams to co-create insights in real-time

- Allow for rapid, iterative data exploration at the beginning of an analysis

- Visual storytelling, for example for workshops

- Running Python scripts

This makes it very valuable for BI analysts.

As a previous data analyst, now product manager, I use it almost daily.

Customer support is also good and feature improvements have been turned around quite fast. Review collected by and hosted on G2.com.

In contrast to other tools, like Sundial, Count does not work with natural-language queries (at least not reliably) and does not offer "opinionated" intelligence. This limits its usability, especially for more business-oriented roles with limited hands-on analytical skills, like product managers.

There could also be potential to provide more out-of-the-box support for use cases like A/B testing, cohort analysis, churn analysis, genAI APIs, etc. Review collected by and hosted on G2.com.