SIGMA: IDEAL CUSTOMER PROFILES

Challenge

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

Solution

ID the qualities correlated to higher Sigma usage for existing users. Then for potential users who correlated to those, ID the data use cases most valuable to them. Finally, demonstrate how we solve those cases 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 and roles
Determine what their biggest blockers were to executing those (valuable and common) use cases

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 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.

From:

Analysis of behavioral data captured in Sigma
Surveys (100) of existing business users
Interviews (50+) 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
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 (100+) 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.

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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