Case Study


Designing a new product experience

RavenPack is a Series B big data text analytics provider that operates out of the US and Europe. Data scientists already love what the company has to offer.  When RavenPack approached us, it was to help them redesign their search platform to target a new market of users including asset managers, business consultants and venture capitalists. RavenPack wanted to do it right - understand their jobs-to-be-done before investing in any development work.

Using a combination of qualitative research and user testing, we created two outcome-focused user personas onto which we mapped attributes, desires, needs, and product expectations based on the jobs-to-be-done framework. Our designers then worked with RavenPack to develop a high-fidelity platform prototype in Figma that became the baseline for agile product development.

What We Did
  • Primary user research (survey, focus group, interview)
  • User testing
  • User journey mapping
  • User profiling
  • Product design


User personas based on jobs-to-be-done, pains and feature expectations.


Feature requests prioritized for the product roadmap.


Reduction in development time because of research-driven roadmap.


Value propositions uncovered for the product vision.

“An eye-opening experience! We hired Poocho to help us re-think our new platform experience as we expand into new end-markets. We got a better understanding of our customers and a clearer path towards strategizing new product features... Watching video highlights of our clients using our concepts and listening to their audio testimonials beats doing a survey hands down."
Armando Gonzalez
Founder & CEO, RavenPack
3 big takeaways

Matching stakeholder and user expectations

To equip ourselves with the right information before we spoke to RavenPack’s users, we interviewed and did a focus group with the company’s customer-facing staff first. We used these insights to design persona prototypes and mind maps of their possible journey touchpoints using the RavenPack product. We also analyzed customer support tickets and sales materials to build further context around pain points and anxieties of this audience. 

This combination of data sources made us confident about the questions we would ask during user research. At the end of our study, we were able to compare user-desired outcomes to stakeholder-assumed outcomes. Those outcomes that were ranked as important and common across both sets of insights went into the final product roadmap. This exercise built stakeholder buy-in that was essential to the success of the project.


Goal-based personas

Quickly into the journey mapping exercise, we realized that we were dealing with two different use-cases for RavenPack’s platform. These use-cases were driven by very different underlying motivations between the two groups. One group more closely reflected the audience RavenPack was already targeting but the second group sought different end goals from the platform. To deeply understand this discovery, we dug into those features/workflows/journey milestones where the two groups felt stuck, anxious or frustrated. We then unpacked why they were stuck and what would help them resolve these pain points. 

We used these insights to create two personas, each anchored around one key value proposition. We also included usage traits, industry profiles and jobs-to-be-done for each persona, giving the company a holistic view of the needs and target segments of the two groups for strategic innovation.


Collaborative product prototyping

RavenPack wanted to adopt lean product development. As the external research and design partner for this cycle, our task was to uncover the jobs-to-be-done, desired outcomes and feature priorities as part of a larger product roadmap. To put our findings to the test we worked closely with RavenPack’s product lead to design a high fidelity Figma prototype that incorporated a new journey workflow for our audience. We then tested this prototype with the same users who had participated in the primary research sessions. 

This approach was revelatory and efficient. We already understood user pains and gains and were quickly able to discern why some features/experiences worked or didn’t work in the user testing sessions. There was already an established level of rapport with this group that made the conversations more honest. Finally, we believe this method instilled a level of customer appreciation as users felt their feedback had real impact when they interacted with the new interface design.

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