If you’re a marketer, you want to show how you’ve helped move the needle for your business. You want to know what’s working, not just what’s happening, and that you’re spending money in the right places and on the right things. You want to see the impact of all your marketing activities, and in terms anyone in the business can understand: Revenue.
Attribution reporting is a massively complex problem space. Most marketers make do by exporting data from many different systems, throwing them into a spreadsheet, and trying to make connections between cause and effect.
My team at HubSpot built a new reporting tool recently that lets you measure exactly how much money your marketing drives for your business. No exporting data, no complicated setup. Just clear attribution reporting, which means you know which marketing efforts are delivering the most value for you.
Making attribution reporting this easy for marketers was an incredibly difficult project to tackle. Maybe your team is working on something hairy and complicated, too. Here’s what we learned about clarifying our goals, sharing our vision, learning as a unit, and looking past the technology to deliver real value, fast.
Clarify your goals
Discovery work doesn’t always result in a clear product direction. The more research we did, the deeper we went into a spiral of possibilities. It wasn’t long before we were inundated by all the different use cases we could potentially solve for. We tried to catalog every single different use case, but the variations were endless.
Every user, it seemed, had a slightly different question they were trying to answer. How are my campaigns bringing in revenue? What about my channels, are they bringing in revenue too? Which types of content are offering the most bang for the buck? From a single piece of content, to campaigns, and then up to channels, our users wanted to see how it all delivered revenue. Most people called that kind of solution “multi-touch attribution.” But most people were also sort of unclear about how it might work.
The reality is that most marketers can’t spend their time studying attribution models. What they want is a tool that does that modeling for them, and to know they can rely on the accuracy of what they see. They want the data that will help them make good decisions. They want to know they’re making decisions they can feel confident about.
Tons of articles online talk about attribution models and how you might measure your marketing with them. But not one of them addresses the realities of sales and marketing misalignments, data fragmentation, and undefined business processes.
If we had just focused on building a tool that offered a wide variety of attribution models to users, we would have missed out on solving the core user need. It doesn’t have to be complicated to find out how marketing is driving real business results. It’s not about offering and explaining a vast array of mathematical models, it’s about helping our users make good, data-driven decisions.
Share your vision
That became our vision: To help marketers make good, data-driven decisions. But we knew we wouldn’t be able to do it alone. You can’t deliver an experience that spans across products without the support of the different teams that build them. A clear vision and strategy helps define and shape the mental model of your people across the organization. Showing others how you see the problem and how you’ll wrangle it from a design lens helps you all go beyond the interface and focus instead on what the interface is trying to achieve.
To make it easier for everyone to visualize, we developed a simple framework that broke down the system into three parts: Connect, Credit, and Measure. We knew marketers wanted to track their buyer’s journey from beginning to end. And for the most meaningful touchpoints, marketers want to clearly show which content buyers interacted with and how much credit is deserved for closing the deal in the end. Our framework of Connect-Credit-Measure helped us understand and explain how all these things worked together as parts of a unified whole.
Learn as a unit
Designing data products comes with its own unique set of challenges. One significant hurdle is using fake data in your prototypes and mockups. In a word: Don’t. Getting the data right is just as important as the interface. Testing prototypes with fake data and content is like taste testing a new flavor of soda by just licking the can.
Building prototypes with real data meant letting go of the usual ways of operating. We found that we had to learn to work more closely together, and to get creative about how we understood our various roles. To get the data right early on, it meant we started by building an excel spreadsheet with realistic data with no front end at all. Now design shifted to be more focused on learning how people could use their data, rather than rushing to make the right interface. And our engineers used that context to get a working prototype up and running, without feeling like design held the keys to all the answers.
As a designer used to pulling together mockups first, that felt unusual. But it turned out to be far more powerful when design relinquished the role of needing to be right, in favor of being productively wrong as soon as possible. The product vision and design strategy set the foundation, and everyone on the team felt empowered to start delivering value however they could.
We pictured the team tied together with a giant elastic band. No one was waiting on anyone else, so everyone was moving in the same direction together. And when one person makes progress, it pulls the whole team along.
We made sure to get the entire team on feedback calls with customers. Just like how a basketball team reviews game footage together, you need your engineering team listening in on calls, asking questions, and debriefing afterward. Our backend and frontend engineers were in every call seeing how customers interacted with our prototypes. It made a tremendous difference in our progress. Everyone on the team benefits from seeing how the customer thinks about and experiences the core problem. We moved faster, found what didn’t work earlier, and stayed better aligned when we stayed focused on learning as a unit.
Look past the tech
The tools we build should help people feel more capable in achieving their goals. Tools should exist to make the tool-user awesome, not to glorify the tool (or worse, the tool-builder). Technology is only a means to an end.
The most critical part of our strategy was to not focus directly on building a set of attribution models. We saw many products in this space were too technology-centric, leaving users with the burden of having to interpret the output. The experience we aimed to create was one where users’ questions were in the forefront, not the models. Where users felt they could literally see the questions that the tool could answer for them. The core of our intention was centered on the user first, and the technology was deployed in service of their needs.
If we were building a tool for full-time data scientists, we might have built something else. But it wouldn’t have solved for everyday marketers. It would instead have focused on the fancy models — the tech — as the means to that end. I think Dyson vacuum cleaners involve a lot of cool technology with hundreds of unique patents. But they didn’t create amazing technology as an end in itself — they created it so that my job of cleaning floors becomes incredibly easy to accomplish without my needing to achieve any new technical skills.
It’s not about the tech, it’s about what you can do with it. It’s about delivering the core, not just delivering more.
Easy and powerful is the future
In every product shipped, there are a few critical things that end up making the most impact with customers. It’s easy to get bogged down in all the possible things we might build. It’s easy to come up with all the “more” we can add. But staying focused on the core user needs will keep us from straying into building something that misses the mark. We couldn’t have found this core if we hadn’t focused on clarifying our goals, sharing our vision, learning as a unit, and looking beyond the technology.
Last month, HubSpot unveiled our new revenue attribution reporting. We’re pretty proud of what we delivered. We’re helping marketers demonstrate the real business impact of the work that they do. It’s easy to use, and powerful, too. And that helps businesses everywhere grow better.
This article originally appeared on Medium.