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Sigma has mainly been sold to data orgs and more technical teams within orgs. But it sought to serve non-technical (business) users. Which departments or roles should the company target? 


Identify the qualities that correlated to higher Sigma usage. Then identify the use cases most valuable to those who fit that profile. Finally, demonstrate how we solve those cases for them. ​


We IDed several depts and use cases.

  • Ops Directors managing logistics

  • Marketers optimizing campaign spend

  • PMs tracking product performance

Structure of the research

What I needed to know/do:

  • Identify what qualities of existing business users correlate to greater engagement with and success with Sigma

  • Identify which departments and roles had those qualities

  • Define what use cases were both valuable and common for people in those departments and roles

  • Determine what their biggest blockers were to executing those (valuable and common) use cases

So I did the following:

  • Analyze behavioral data of existing business users to define departments and roles that tended to have most success

  • Surveys (100+) of existing business users to understand a) most important use cases b) biggest pain points without Sigma c) what obstacles they faced in doing these analyses in Sigma 

  • Interviews (50+) with existing business users to flesh out and fully answer for points a, b, c above 

  • Surveys with external non-Sigma users (100+) who mapped as similar to our business user profiles to check whether use cases existing users cared about were also high value for prospective users who we would be selling to 

These business user traits correlated to more Sigma usage ​

Intermediate to advanced Excel skills and basic SQL knowledge mapped to greater Sigma usage. However, expertise in Excel mapped to some struggles in Sigma. Also correlated to Sigma usage were certain departments and roles, e.g. Directors of Operations and PMs. They tended to have a better understand of how data works in broader terms and/or had a mindset to figure out tasks in Sigma if/when they got stuck.


  • Analysis of behavioral data captured in Sigma

  • Surveys of existing business users 

  • Interviews with existing users


Identify departments and roles, then use cases 


Once we identified top departments and roles we identified what use cases were important to people in those departments. Then we looked for overlap with use cases that users struggled to address with other data tools. These are the use cases we identified:

  • Ops Directors managing logistics and supply chain

  • Marketers optimizing campaign spend

  • PMs tracking product performance

We then did a survey of non-Sigma users in the relevant departments to verify their use of data analytics and the value of the use cases we identified.

Determine existing users pain points in Sigma 

To sell to business users in the future we also needed to know where current business users struggled in Sigma, especially in the onboarding process.


We captured these in the surveys and interviews mentioned above. And I highlighted them in the diagram here. 


Their pain points included:. 

  • How data worked differently in a database vs spreadsheet (column vs cell-based data)

  • How to organize their data for the kinds of analyses they needed

  • Finding the right data

  • ​Initial creation of visualizations

This info was also gathered in the methods already mentioned, surveys and interviews. We then took one area of focus -- marketers doing campaign spend attribution analysis--to create a compelling experience for marketers around why Sigma would work for them. See Sigma: Selling to Marketers.

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