Item: Sigma Computing
Rating: 7
Author: Randall Hidajat

Use Cases and Deployment Scope

I'm using Sigma Computing primarily to capture and track all KPIs related to customer service. In addition to that, our organization is using Sigma to track all KPIs across multiple different systems. Sigma allows our business users to be able to create, view, and manipulate data how they feel like it is needed.

Pros and Cons

Ability for a data analyst to upload a specific CSV to join on.
Scheduling reports over slack/email/etc
Create hidden tabs/charts to use as an intermediary table
Create charts based off of any table, csv, other table, etc.

Unable to search for a specific chart in a workbook
No clear area to test or put one-off questions
Search overall is really hard to use

Return on Investment

Reduced 60% of the time it takes to build out reporting on a daily basis
Decreased contacts per order by displaying more customer information embedded into various systems
Reduce member cancellations by 70%

Self-Service Analytics

Sigma allows us to use all our data sources together which has been impossible before. Allowing our customer service operations to be able to access the data on a regular basis along with removing the need for manual agent reporting has been a game-changer. In a high paced environment of customer phone calls, actively pushing out reporting to Slack on an hourly basis allows us to be more agile. Using the tool also has encouraged business users to learn how to build their own charts especially without the SQL learning curve.

Ad Hoc Analytics

Because there is still a learning curve, there are not that many people in our organization that can utilize Sigma to build out their own reporting. We still have many different blockers regarding ad hoc analyses or why something happened in order to make decisions.

We are currently only at a point where we can at a high level determine success or not. We are not able to currently dive a little deeper to understand where those opportunities are.

Alternatives Considered

Looker, Tableau CRM, Microsoft Power BI, Sisense, Trevor.io and Metabase

I'd rate Sigma to be extremely similar to Sisense except it looks not as nice. I would say that as a tool, Sigma is more user-friendly than Tableau, Power BI, Trevor, and Metabase.

I do feel that Looker is far more powerful and looks great, but I also recognize that Looker does have a steeper learning curve.

Key Insights

Do you think Sigma Computing delivers good value for the price?

Not sure

Are you happy with Sigma Computing's feature set?

Yes

Did Sigma Computing live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of Sigma Computing go as expected?

I wasn't involved with the implementation phase

Would you buy Sigma Computing again?

Yes

Other Software Used

Kustomer, Jira Software

Likelihood to Recommend

As long as you have data experience, Sigma Computing is a pretty straight forward tool. The ability to embed charts, workbooks, and different assets publicly is very useful especially when needing to send something over to a user. This is a better and cleaner way than to just send over a screenshot of a chart.

Sigma Computing is hard to use however when you are building so many different charts and workbooks, it is impossible to search for a chart that exists inside a workbook. In addition to that, when needing to answer a one-off question, the only option to create is to create a workbook or a new dataset. This means that the best way to test or find a one-off question is to create a workbook called "sandbox", or something temporarily which is not so clean.

Great tool with some weird kinks

Overall Satisfaction with Sigma Computing