Revenue teams face mounting pressure to deliver consistent results, yet many organizations struggle with establishing proper accountability frameworks. Creating effective accountability structures requires balancing aggressive targets with achievable goals while maintaining team morale. Beth Thorson brings unique insights to this challenge, having designed compensation structures and managed revenue teams across logistics and SaaS companies. Her experience spans both sides of the equation as a former seller who later created quotas and compensation packages for revenue producers.
Building Accountability Through Experience
Beth’s qualifications stem from hands-on experience across multiple industries and roles. “What makes me uniquely qualified is I have worked for organizations in both the logistics and supply chain space and in SaaS,” she explains. “In those organizations a big part of my role was to find compensation structures that both incentivized growth and attracted top level talent.” Her background includes being a seller herself, which provides crucial perspective on what motivates revenue teams. She has created compensation packages across SMB, mid-market, and global enterprise functions at three separate organizations.
Her experience during COVID at Flexport highlighted the importance of adapting accountability measures to market conditions. “When you looked at effort versus payout during that time, they didn’t line up because we did not adjust our program,” she notes. The logistics industry saw margins jump from $100-150 per container to $5,000, creating outsized compensation that wasn’t tied to seller effort. “If you’re going to pivot on your sales program, do it quickly, with intent, and with clear explanations,” she advises.
The Persistent Challenge of Revenue Accountability
Data quality presents one of the biggest obstacles to effective accountability. “One of the things that makes accountability difficult is the quality of data that people are putting in the CRM,” Beth explains. “When you manage large sales teams, you’re dependent on that data to have the sales stage right, to have the forecasting right, to understand where people are getting stalled.” Without accurate data, revenue leaders cannot provide the training and coaching that teams need to improve performance. Experience levels also complicate accountability structures. Senior sellers often receive different treatment, which can backfire. “You may hire someone with 20 or 30 years of experience and they get maybe a longer rope to be successful,” she observes. “But what you find is they may pull the trigger on one relationship or two.” The risk is that experienced sellers become account managers who “sit on an account and they just collect in perpetuity” without generating new business.
Three Actions for Embedding Positive Accountability
Beth emphasizes creating accountability without fear-based environments. Here are her 3 suggestions:
- Transparency and Motivation – “Make sure those goals are achievable, celebrate those successes and make the data public,” she states. “Don’t hide the information, share it. It’s not that you want to shame people, you want to motivate them.”
- Using Data for Coaching – “Use that data to coach versus embarrass or shame,” she explains. “You lean into the three great things that they’re doing and coach them on doing more or just give them the experience and mentorship that they need and you get such better results.” This approach recognizes that salespeople are “the artists in the sale” who don’t naturally lean toward detailed administrative work.
- Individualized Approaches – “Any effective manager allows people to authentically be themselves and meet them where they are,” she says. “That takes more work from a revenue leader, but it has a stronger outcome.”
AI is about to change everything about sales accountability. Beth sees tools like Gong and Otter evolving beyond simple call recording. “Something that AI is moving towards and will continue to advance is actualizing what stage the deal is really at based on those conversations,” she explains. This fixes a huge problem. Right now, deal staging is subjective and often manipulated. “A seller may be behind on business at a certain stage, so they move something into that stage, but what they’re doing is just setting themselves up for failure.” AI could analyze actual conversations and buying signals to determine real deal progression. The best part? Nobody loses their job. “It actually makes sellers happier,” Beth notes. “It benefits both sellers and operational teams because the divide between information goes away.” Instead of manual CRM updates, AI handles the administrative work while giving leadership better data for decision-making.
Connect with Beth Thorson on LinkedIn to explore smarter, human-first revenue accountability systems.
