NDA
Goal
Understand the user experience of the company’s flagship software among operational users with different roles and levels of experience, in order to map recurring patterns, pain points, and opportunities for improvement. The results will be used to design the new user experience and reposition the software as a market benchmark.
Who did we involve?
We built the sample by selecting 6 clients, one or two per cluster: top brands, small brands, retailers, and demanding clients (who require numerous customizations). For each client, we selected a few people from the shooting, post-production, manager/supervisor, merchandising and e-commerce, and admin teams.
Which activities did we choose?
The research was carried out in three phases, for each of which we used a specific methodology:
1 - Online questionnaire (quantitative approach): offers a general overview of the user experience, useful for identifying recurring patterns and the most widespread pain points. It allows users to be involved quickly while keeping them anonymous (reducing the risk of social bias). The questionnaire was designed based on the ISO 9001 standard, with the addition of a few questions specific to the software under review. 110 respondents from different teams took part, and they highlighted common friction points.
2 - Online focus groups (qualitative approach): we ran 7 sessions in small groups (4-6 people) aimed at exploring in depth how the software is used, with the chance to ask follow-up questions, dynamic interaction, and the identification of unspoken needs. Each workshop (about 3 hours long) followed a five-stage agenda: icebreaker, defining pain points, exploring solutions, focus-group interview, closing and wish list.
3 - Behavior analytics analysis: involves anonymously recording real usage sessions with tools like Hotjar, with the aim of observing users’ actual behavior and comparing it with what they reported. This activity was not completed due to a lack of additional privacy permissions from clients.
What did we discover?
We analyzed the data collected from the survey by building indicators that produced numerical values, which can be used in the coming years to track how they change by repeating the research. The findings from the workshops were clustered and organized by theme. All insights were then analyzed with the help of artificial intelligence, to surface further correlations and build a ranking of importance.
We compiled the results of the analysis (not covered here, as they’re protected by NDA) into a PDF report presented to the company’s board, from which team-specific documents were then extracted. This allowed each department to put together an action plan for implementing the solutions within its remit in the near future.
