As a Product leader, you might often be faced with three very hard objectives: addressing your customer needs in a prioritized way, rallying teams behind your plan and demonstrating high impact to your entire company.
Unfortunately, there is no magic formula here. Building philosophies largely depend on the organization itself, the people that run it and the stakeholders they interact with.
Through this series of articles, I’ll walk you through how we do things at Everoad, and the results this philosophy has yielded. Our tale will touch upon insights, planning, cadence and more-than-you-could-think-of hacky stuff.
Part one. We generate insights. All the time.
A former boss of mine used to yell constantly ‘Data & Anecdotes, Ben. Data & Anecdotes’. He couldn’t have been more right. Insights are crucial for what we do. Our industry, the Freight industry is a complex one, ruled by specific mechanisms, behaviors and filled with a broad range of stakeholders. None of the 25 people constituting the Tech team comes from a road transportation background. As such, generating relevant and impactful insights is essential for us. So here’s how we collect them.
Data analysis. In our three-year lifespan, we have managed to build a powerful data warehouse containing hundred millions rows of data, leveraged thousands of times per day by our teams. This helps us derive precious data points to determine which features are working well and where we could focus more. As an example, using data, we were able to isolate operational frictions with one of our business lines that were resolved and resulted in significant margin improvements.
User behaviors. To truly understand how our users interact with our interfaces and help improve the experiences we provide them, our team relies on Fullstory. This allows us to navigate each of the 50+ experiences we have built and explore them in a very granular way. Our Freight Search engine for carriers was built on insights derived from this tool. The next step for us here is to integrate quantitative data points identified by Fullstory into our data warehouse to help further automate user research.
Feature requests. With only four Product managers, our quest for insights can’t be as comprehensive as we’d like. This is why we look to each employee of our 120-people startup as an extension of ourselves. Encouraging them to provide us with feature requests feeds us with more ideas while including them in our Product strategy. Using cool automation between Gsheets & Slack, we collaborate in a very transparent way, thus increasing trust between the Tech Org and the rest of the company.
Customer anecdotes. On the less statistically representative side of things, there are customer meetings. We know they only provide a partial and single view, but they are powerful tools to engage with our audience, hear their pains and discuss strategic opportunities (caveat: run away from doing bespoke things). Several discussions with one large Enterprise customer of ours have oriented our team to build a Facility feature to ease load requests but also provide metrics and insights on facility operations.
‘OK — so you’ve got tons of ideas? Cool… But how do you know which one to tackle?’. Good WWTBAM product-edition question. Generating insights at such a scale can only be helpful if you are able to store and index them in a super-structured way.
Enters our backlog.
Our backlog isn’t just another icebox (or that closet in which you throw things hoping they’ll never make it out of the room again). It is the antechamber for our roadmap. The playground of User Research, if you will. This is where we take the time to reflect and think about the different ideas we could work on, at some point in time.
Every item surfaced using the levers mentioned above ends up on our backlog. We have organized it around Programs (conceptual territories designed to foster fast-paced focused innovation, but that’s a story for later) in which we place insights as soon as they are identified. These Programs are generally managed by one dedicated PM (we have one for Shippers, one for Carriers, one for Marketplace and so on) together with their business counterpart. Our Product Manager in charge of Shippers will, for instance, partner with our Head of Sales.
Through t-shirt sizing, the team evaluates each opportunity in terms of complexity (how difficult is it to design & build such a feature?), opportunity (what will the impact of building such a feature be?) and urgency (what could go wrong if we weren’t to deliver this in the coming weeks?). This allows us to rank priorities and know exactly in what order to will tackle topics, distinguishing between ‘roadmap items’ (projects being currently worked on), ‘next in line’ (projects we will tackle next) and ‘brooding’ (projects we don’t have milestones for, yet, but where we start doing research).
In short, our insight generation philosophy largely relies on the three following pillars.
- User obsession is not a value. It is a daily routine.
Caring about users means leveraging both data and anecdotes to master their needs and ensure you prioritize projects that truly move the needles. - Processed workflows are designed to support your scale.
Doing so at scale requires clear ownership, detailed processes and adequate tooling that will stand the test of time, but most importantly, of growth. - Transparency is the key to highly efficient organizations.
To foster trust, increase cross-functional work and collect precious feedback, we believe that transparency is the key to high-value creation.
This principled approach to insights generation has helped us remain user-obsessed while allowing us to avoid the usual traps of fast-growing startups (siloization, misalignments, etc.). But most importantly, it constitutes healthy foundations for planning exercises which we will cover in part deux: We plan together. And commit.
Until then, shout out if you have any questions or want to chat about our approach. We’d be more than happy to address any of your questions!
