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SIGMA: IDEAL CUSTOMER PROFILES 

Challenge

Sigma s mainly sold to data and more technical teams. But it sought to expand its market to include non-technical (business) users. Which departments or roles would it get the most traction? 

Solution

Find out what qualities correlated to higher Sigma usage for existing business users. Then find out what data use cases were valuable and important for us to demonstrate that Sigma could solve for them. ​

Outcome

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:

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

  • ID which departments and roles had those qualities

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

  • Determine what their biggest blockers were to executing those (valuable and common) analysis current'y

To do this I did a series of studies:

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

  • Surveys (100) of existing business users to understand a) most important use cases b) biggest pain points wihtout Sigma c) what obstacles they faced in doing these analyses in Sigma (qual/quant)

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

  • Surveys with external non-Sigma users (50-100) 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 when they got stuck.

From:

  • Analysis of behavioral data captured in Sigma

  • Surveys (100) of existing business users 

  • Interviews (50+) with existing users

Sigma-ICPs-same2.jpg

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 tools. These are the use cases we identified:

  • Ops Directors managing logistics

  • Marketers optimizing campaign spend

  • PMs tracking product performance

We then ran these by non-Sigma users in the relevant departments.

From: ​

  • The aforementioned surveys of existing business users

  • The aforementioned interviews (50+) with existing business users

  • Surveys (50+) with non-Sigma users who need to get insights from their data as part of their jobs

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. 

Sigma_Onboarding.jpg

Their pain points included:. 

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

  • How to organize their data for the kinds of analysis 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 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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