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Transcription
All interviews were transcribed and summarized for the analysis phases. Today this is automated. 10 years ago, this was mostly by hand :)
The Interviews
1
Semi-Structure Interview Guide
An interview guide was created in advance of the user interviews. To create the interview guide, Product, Sales Engineering, Marketing and Design were consulted.
A semi-structured protocol was used to ensure some amount of consistency among the topics covered during the sessions.
2
Conducting Interviews
I conducted user interviews in person when possible. We visited most users at their sites in Chicago, NYC, and the San Francisco areas. Interviews were conducted with one Product Manager, and often our Sales representative.
Note, not all users consulted were current users; churned users were also included in the interviews.
The Analysis
A modified Grounded Theory approach was taken for the analysis. Each excerpt was categoried into one or more minor and major themes.
The meeting post-it tool, Stormboard— more common in the mid 2010s :), was used in the analysis to organize all excerpts into larger themes for deeper analysis.
98 pages of notes were organized into the larger findings.
An example of an excerpt taken from an interviewee and represented within the analysis tool.
Key themes
A strong parallel was found between the user’s essential tasks and how they deemed themselves successful. Our clients needed measurable, action results. They needed to be regarded as thought leaders. Influencing company decisions was key to their success, as was storytelling*.
More detailed customer use cases, personas, and implications were also shared. An idealized, high level user journey was also shared to address how Quid could overcome some common pitfalls with adoption. Later, we mapped user metrics to evaluate what part of the journey users operated within.
*Note, a deep dive of the results were done for the company, but will not be shared online.
Personas
Analysis: Again, borrowing from techniques of Grounded Theory, Axial coding was used to identify clusters to understand defining characteristics among users in similar roles.
Differentiating factors included:
Turnaround time
Repeatability of workflow
Company type
precision needed for analysis
subject matter expertise on the research topic
Four resulting personas were generated across the consulting, innovation, corporate marketing, and advertising spaces. These personas, particularly “Rosa” and “Stephanie” were used across Design, Product, and Engineering.