Part of's value proposition has always been to use data to help sales organizations sell better.

However, there are other personas involved in go-to-market motions.

Shortly after joining, one of our project managers and I were given a directive: to build something for marketers


We started the project with five user interviews with four of our customers. Because we were starting from a blank slate, we spoke to a range of seniorities, functions, and company sizes in order to understand what each individual's workflow is like, what information they need in order to execute, and how they fit into the broader picture, not only within sales but also within the overall go-to-market motion.

We also spent a few days shadowing our internal marketing team for further insight into some of these workflows and processes, but we used this as reference since our own company doesn't fit within our ICP.

We identified three main pain-points common across all of the people that we interviewed:

  • Leads weren't being followed-up on post-campaign.
  • Marketers don't know whether or not the campaign is effective.
  • Marketing often struggles to link their activities to deals being generated or influenced.

These pain-points were a significant part of the day-to-day for Marketing Operations Managers, as well as marketers in Field Marketing, and Demand Generation, so we focused on users in these roles and excluded Product Marketing. Because Marketing carries a significant amount of go-to-market budget, being able to track the efficacy of a marketing campaign for deal generation and progression and receiving credit for successful sales opportunities is key since this is the metric that marketers are measured against.

We also gained a better sense of how the data generated and analyzed at the individual contributor level funnel up to decision-making at the executive level: the pain-points were the same, but the scale was broader while the focus was more forwards-looking.

We determined that we should focus on creating something that both sales and marketing can use to be aligned.


In addition to user interviews and internal shadowing, I also went through reports generated by our internal marketing operations and sales operations managers to get a sense for how the two different organizations slice, dice, and use our data. We also had walkthroughs of some of the reports that our customers generate and use as additional reference. The goal was to find what the commonalities of these reports are so that we had a solid basis for what "alignment" between the two organizations could mean.

The product manager and I also had a second round of customer interviews where we also spoke with sales operations and SDR managers in addition to following up with some of the marketers we had spoken with previously. I had created some sketches based on the overlapping data from the different reports to help address the marketing pain points that we had identified, and we not only further looked into the dynamic between sales and marketing but also gathered some feedback on our concept during these interviews.

During this process, we were asked to work with engineering to create an early proof-of-concept that could be demonstrated at an upcoming conference. During that second round of customer interviews, we were able to divide the data pertaining to marketing campaigns into a "good to know" bucket and a "what is actionable" bucket, and we used everything we had collected and synthesized so far to create the proof-of-concept:

  • Campaign members have a lifecycle that's based on their interactions with the corporation, so we used these as a top-level filter in the form of tabs.
  • Campaign members are typically assigned to a sales rep (either an AE, SDR, or BDR depending on the company and how they split their different sales functions), so this information lets sales managers and marketers know who is lagging in reaching out to campaign members.
  • Campaign members also have their campaign status that, in conjunction to where they are in the lifecycle, determines what the the expected approach is.

This proof-of-concept was shown at the SiriusDecisions 2018 conference, where we were able to collect feedback from hundreds of conference attendees.

The feedback we gathered was incredibly valuable, not only in validating the concept but also in helping us narrow our focus to individual contributors in field marketing and demand generation.


I continued to iterate on the design for Campaign 360 by working closely with our marketing to further flesh out what the stages of a customer's lifecycle is and to help work everything into different user journeys.

  • A Field Marketer or a Demand Generation Manager can view a campaign that they have created or completed, see at a glance the number of campaign members that had different levels of engagement (none, single-directional, bi-directional, etc.), which members fall into each category, and which reps need to be following up with the marketing-generated leads and contacts. When selecting a campaign member, the marketer can see in more detail what the nature of the completed and upcoming activities with that member are.
  • A Sales Manager can come into the interface and look up their reps to see if their respective leads are being followed up on and which reps are lagging in their SLAs.

Our product manager, as well as our customer success team, worked with a couple of customers to conduct further validation of this offering as well as begin to enable customer roll-outs.


Up until it was discontinued in mid-2020 due to a pivot towards a focus on front-line sales managers, Campaign 360 consistently had the highest engagement rate out of all the modules in's web app since its release in February 2019, as well as a 100% retention rate for the first 13 months. However, it only had 6 weekly active users by the time it reached EOL (it had seven at the onset).

Feedback from users has included one customer stating that their global demand center has begun to rely on Campaign 360 to inform their decision-making.


There were a couple of lessons learned that were applied towards streamlining and improving later projects:

  • Design and Engineering actually had started working on the product almost simultaneously. The back-end architecture was considered locked and finalized while research was still being conducted, which resulted in limitations on what data could be represented.
  • As evidenced by the low amount of weekly active users, most customers opted to continue to use their own dashboards due to the lack of flexibility in data to be displayed. Later efforts in addressing marketing use cases were focused on providing marketers the data they needed through APIs rather than through a UI.
  • A large chunk of the research was oriented around determining what persona to focus on. As the product manager and I were both new to the field in which operates, we might not have been able to avoid this, but we now had a sense for how questions and jobs to be done generally apply across seniorities. This doesn't necessarily translate to functions and verticals, however.
  • In the whirlwind of trying to research, design, and ship, I didn't take a step back to make sure we were organizing and processing our notes effectively; in later projects, I pushed for conducting debrief sessions and creating documents and affinity diagrams as much as possible so that we could have more reliable recall of findings.