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Senior Product Marketing Manager at Arena, by PTC
I started this project at Arena, by PTC, as a product marketing specialist. Arena helps companies bring products to market faster while reducing errors, rework, and wasted spend. The work served a B2B buying group that typically included engineers and other product-development stakeholders; the people who felt the operational cost of disconnected or error-prone product work most directly, as well as the people who influenced the purchase decision.
At the time, Arena had no formal customer interview program. I noticed that we were making important assumptions about why we won or lost deals without consistently hearing those reasons directly from customers. I wanted to test whether the sales team’s view matched the customer’s view, identify product gaps we might not understand, and find opportunities to improve win rate. The absence of a repeatable feedback process was the signal that created the opening: before trying to change our messaging or sales motion, I believed we needed to listen to customers directly.
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Senior Product Marketing Manager at Arena, by PTC
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Arena’s broader objective was to improve its understanding of why deals were won or lost and use that insight to support a stronger win rate. My objective was narrower and operational: I owned the entire effort to create a repeatable customer interview program from scratch, covering both wins and losses.
I had to identify the right customer contacts, determine which internal tools were available, define the interview questions, write the outreach emails and timing, and create a process for sharing what we learned. The main constraints were access to tools and dependence on the sales team for customer relationships and buy-in. I had to continually work around other people’s schedules and reassure sales that the interviews were not intended to evaluate or undermine them—or put a deal at risk.
We defined success as completing 15 interviews per quarter, split across wins and losses, and holding a meeting every two months to present the findings. We also monitored “win-backs”: deals we interviewed after a loss and later won back. Improving win rate was the strategic aim, but it was not set as a standalone KPI.
I started by building a business case for a formal customer interview program and securing buy-in from the sales leaders. I positioned the work as a way to improve the sales motion—not evaluate individual sellers—and explained that the interviews would not put active deals at risk. That trust was essential because the program depended on sales access to customers and prospects.
We chose to send interview invitations for every deal rather than rely only on Salesforce data. Our reasoning was twofold: Salesforce information was not always complete or accurate, and prospects and customers were more likely to be candid with an outside interviewer than with the salesperson involved in the deal. I segmented the incentive by ARR, offering larger gift cards for higher-value opportunities, and established a process for targeting both wins and losses. As the program developed, I added a Salesforce button that allowed sales to opt specific opportunities out when necessary.
The first interviews surfaced two important patterns: UI/UX was a major reason we lost, while trials were associated with more wins. I shared those findings with the product and solution consulting teams. Product used the feedback to modernize the homepage, while solution consultants began pushing trials more deliberately in the sales process.
Over time, I also identified a structural problem in the operating model: relying on internal tools and other teams to make changes made it difficult to move quickly, iterate, or run A/B tests. Excel and Smartsheet were not giving me the analysis I needed to identify trends efficiently, which became an important input into the next stage of the program.
I started with the tools we already had, then changed the stack as the interview program grew.
AI was not part of the original program because it was not available in the tools at the time. Clozd now includes AI, but I have not treated it as a substitute for judgment: the value still comes from asking the right questions, interpreting the feedback, and connecting it to decisions. If I were building the program again, I would choose an integrated platform earlier rather than stitching together tools and depending on other teams.
Since launching the program in 2022, I have completed more than 215 customer and prospect interviews, consistently meeting the target of 15 interviews per quarter across wins and losses and presenting findings every two months. The interviews also contributed to $175,000 in win-back revenue: opportunities we interviewed after losing and later won back. I treat that as influenced revenue rather than claiming sole attribution.
The program changed decisions beyond the numbers. Customer feedback showed that UI/UX was a major loss driver, which led the product team to modernize the homepage and prompted the AI team to work on product improvements. Feedback also showed that trials were associated with more wins, so solution consultants began using trials more deliberately and we continued working with sales on value selling.
This year, from January onward, our email cadences have averaged a 64.8% open rate and a 9.2% participation rate. The most significant lesson learned is that a repeatable listening process adds value only when its insights influence product and sales decisions, not when the interviews remain merely as a research archive.
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