Product Strategy Research
Develop Human-Focused, Resilient Product Strategy
When your strategy is overly focused on the product or solution, people get ignored or minimized, feature opportunities get missed, and the strategy becomes brittle over the long term. Instead, Indi and her team use Data Science that Listens to help you develop human-centered product strategy that lasts far beyond your product development life cycle.
Below are a few key ways that Data Science that Listens can help you create strategy that leaves no one out and informs your next decade of product development:
1. Gap Analysis
The difference between approaches and your orgs capabilities
2. Risk mitigation
Verify that solutions are aligned to people
3. Diversification
More closely align design possibilities to the nuances of the different thinking styles
4. Consolidation
Consolidate existing research into one overview
5. Consensus building
Clarify positioning and prioritization
6. Content strategy
Content mapping of a proposed solution
7. Untapped opportunities
Widen knowledge of the possibilities in the problem space
8. Stronger Metrics
Tune your metrics to how well you support a thinking style, per tower in the mental model diagram.
How we build Mental Model Skylines
Each time we conduct a study, it includes 5 participants per behavioral audience segment, focused on a certain purpose. You can start small and aggregate over time. We begin the engagement with a discussion of the research scope to ensure we frame it in a non-solution-focused manner. Then we conduct the research and provide you with weekly updates as the work progresses. We can give you transcripts of the listening sessions about halfway through, and then we deliver the mental model skyline and/or the thinking style segments, depending on what you’re after. We conclude with collaborative working sessions where we discuss insights, actions, and next steps with you and your stakeholders.
Examples of the application of Mental Model Skylines and Thinking Styles →
I have spent a decade in corporate design strategy, and never seen a quicker way to deep insights. In addition, it was well under our expected budget. We had our mental model printed out on 15ft. plotter paper in the room and the impression of the insights was awesome. For the budget the result was quite incredible, so expect it to be done again.
We had our mental model printed out on 15ft. plotter paper in the room and the impression of the insights was awesome. For the budget the result was quite incredible, so expect it to be done again.
I've been able to use the mental model diagram with my team to guide design decisions and areas for further exploration. It's been great having easy to access quotes to show as support, as well.
Mental model diagrams help organizations learn their customers inside and out through rich motivational research that produces fundamental insights you can actually act on.
From our research collaboration with Indi, we were able to identify four major strategic areas to explore to improve our overall consumer journey and business model. Exploring these four areas produced solutions that supported the identified strategic initiatives helped our business better support our consumers and improved our annual sales figures. Not only that, the empathic stories collected enabled us to get all of our internal stakeholders aligned.
Not only that, the empathic stories collected enabled us to get all of our internal stakeholders aligned.
Indi put both rigor and truth into our user research, which makes it impossible to go back to the bad old ways. It is not about how much you know about people, but how much you really know about people, and how do you know you know. We use the alignment diagrams regularly, even though we did them over 8 years ago. They are still fresh and valid. The concept of problem space research is super powerful. I evoke it all the time.
It is not about how much you know about people, but how much you really know about people, and how do you know you know. We use the alignment diagrams regularly, even though we did them over 8 years ago. They are still fresh and valid.
The concept of problem space research is super powerful. I evoke it all the time.
The conversation around automation in our industry needs to change from equipment and technology to people and process. The results of the research changed our way of thinking and focused our automation project team on the people involved in a profoundly clarifying way. Our two Mental Models showed us a clear process for moving forward.
The results of the research changed our way of thinking and focused our automation project team on the people involved in a profoundly clarifying way. Our two Mental Models showed us a clear process for moving forward.
The research, especially the mental model diagram, clarified things. It was like bringing a microscope into focus and finally getting the fine detail that eluded us. We finally have an in-focus perspective of the world according to the users. Up to this point, we could make up problems and think we knew how the users wanted us to behave. Now we have the hard data. It made our work complete.
We gained incredible depth of knowledge, understanding of, and empathy for our audiences through the mental models approach. The project with Indi taught me to approach research and strategy in an entirely new way. Also, walking through the entire project together as a team was so helpful in terms of “getting” the methodology.
Also, walking through the entire project together as a team was so helpful in terms of “getting” the methodology.
I now have a new superpower with which to make sure we are fixing the right thing. Beyond the actual artifacts produced (which are still valuable in 12 years later), the most valuable takeaway was having learned a dynamically relevant process for viewing deeply qualitative data. A tool to think about and describe qualitative data – and its relationship to the tangible world – is no small feat, especially in an engineering space where the prime directive is to "just fix it." Experimentation happens while the engineers are fiddling, so if something seems to work, it’s rarely redone. It’s important to do all we can to have a better idea of what it is we’re actually making. The way in which I could collaborate on the project was one of the most important elements of the experience. I was able to observe and then get my hands in the mix. Without that, it's abstract.
Beyond the actual artifacts produced (which are still valuable in 12 years later), the most valuable takeaway was having learned a dynamically relevant process for viewing deeply qualitative data. A tool to think about and describe qualitative data – and its relationship to the tangible world – is no small feat, especially in an engineering space where the prime directive is to "just fix it." Experimentation happens while the engineers are fiddling, so if something seems to work, it’s rarely redone. It’s important to do all we can to have a better idea of what it is we’re actually making.
The way in which I could collaborate on the project was one of the most important elements of the experience. I was able to observe and then get my hands in the mix. Without that, it's abstract.
The mental model diagram gave us actionable insight into what people in our target market actually DO for consideration, selection & long term support of enterprise level relational database software.
Coaching appointments
You may not be ready for a full fledged coaching. But, if during your work there are questions that come up you can get in touch, by booking an appointment. These are working sessions, where I will help you find out stuff.
