Research Deep Dive: Solving the Attribution Problem in Team Selling
How can we measure and reward who contributed to the sale?
Let’s imagine a large account just renewed their $1M contract for $1.2M (20% growth). In this scenario, we usually recognize and celebrate the efforts of the field sales rep (e.g., account executive) for this achievement. The outside rep is typically the face of the deal, after all. She is the one travelling out to the customer, networking across the account, and running demos. So, why shouldn’t she get the credit?
But let’s take a deeper look.
In large accounts like these, it’s unlikely that the field rep was the only one who supported this sales growth, much less the renewal.
For example, who handled the technical questions to get past procurement? Who solidified the internal processes (e.g., delivery timelines, inventory availability) to align with the customer’s needs? Who flagged customer service requests during the previous year to get ahead of installation issues? These were most likely handled by an inside sales rep (e.g., SDR, technical sales, customer success).
But if that’s the case, how do you attribute the contributions of each rep to the deal?
This is a common challenge facing sales organizations because you cannot manage what you cannot measure. Most CRM dashboards and performance management systems are unable to tell us how each rep contributed to the deal. So leaders have to make assumptions and guidelines to try to reward efforts for collaboration.
A common approach is to develop team-based performance metrics (e.g., total sales generated from a customer) to reward reps. But this approach cannot distinguish the real contributors who supported the account from free riders who are simply assigned to the account. As a result, you get perceptions of unfairness, or worse, you demotivate your top performers.
Another common approach is to use activity-based metrics. These focus on tracking rep activity rather than outcomes. But these can quickly incentivize reps to prioritize quantity over quality and ultimately backfire.
This leads us to a core research question: How do we fairly and accurately measure individual and collaborative contributions when multiple sales reps support the same customer?
In this research deep dive, I’m highlighting a recent paper (Shi, Sridhar, and Grewal 2025)1 published to help with this exact issue. I chose this paper for two reasons:
This is a problem I hear about all the time. Comp designers. Frontline leaders. Salespeople on a team. They all feel like there’s not an easy or fair way to attribute credit to a sale when multiple people support a customer.
This paper appears in a non-marketing journal. Sales research most often appears in marketing journals. BUT, the nature of sales research often blends with operational, financial, management, and other internal firm issues. So, it can easily be a better fit in journals like POMS here (Production and Ops Mgmt) than in a marketing journal. That said, if you’re not attuned to looking for updates on this issue or are regularly checking this journal, it’s easy to miss.
The Paper in Brief
In Shi, Sridhar, and Grewal’s (2025) paper (Value-Partitioning of Sales Contribution in Business Markets), they specifically focus on a selling firm that uses an inside rep (IR) to collaborate with an outside rep (OR) to support customer accounts. These specialized two-person groups are common across a lot of selling contexts, so it’s a useful context to study.
Importantly, here, there are no set assignments for these pairs across customer accounts. Some OR-IR pairs serve multiple customers, one IR may support multiple ORs, or one OR may be supported by multiple IRs. This key variation allows them the opportunity to leverage a clever analysis strategy to uncover how each particular OR or IR contributes to the sale.
There are many great aspects to the paper, but I highlight three key points that stood out to me as impactful ideas:
Introduce the idea of value-partitioning from three contribution buckets:
Outside reps (ORs)
Inside reps (IRs)
The synergistic contribution stemming from both reps (BRs)
This third “synergy” bucket is a really nice inclusion in their strategy to estimate rep contributions to the sale because we know reps do not work in isolation to support customers. Collaboration is necessary, and some duos may work better or worse together. Previous research has shown that certain factors create barriers for sales teams to function well together. Some sales teams perform poorly because they conflict over the tasks or harbor relational issues2. Matching the wrong salespeople together has also been shown to worsen team performance3
This focus by the authors allows them to quantify how the collaboration between particular sales team members contributes to sales performance.
Measure the value contributed by salespeople using unobservable effects
One of the biggest challenges in the past for measuring salesperson contribution is that these efforts are hard to observe or measure. This is the heart of the attribution problem and why so many firms simply incentivize on a team outcome.
To get around this challenge, the authors use a value-partitioning approach and a clever application of Empirical Bayes estimation to break down customer-level sales into the distinct contributions of outside reps, inside reps, and their synergy. Using this approach, they transform typical CRM data from a sales organization (e.g., customer sales records, salesperson assignments) into practically useful measurements of salesperson contributions to the sale.
While covering this analysis approach is beyond the scope of this write-up, the key takeaway here is that the authors can measure these “hidden” contributions from all three sources while not being biased by reps who only support a few or many customers (e.g., extreme cases where a rep gets a large sale but only has few customers).
Use the value contributed by salespeople to predict future sales
Building on their analysis, they apply their measures of rep contributions to predict expected future sales. Using data for customer sales in the following year, they estimate how much additional sales one could expect from reps who contribute more than others.
The results of the predictive model suggest that all three contributions matter a lot. In fact, rep contributions predict sales in the following ways:
For 1 standard deviation above average (think reps in the top 30%):
OR increases customer sales by 17.8%
IR increases customer sales by 11.6%
Synergy between OR-IR increases customer sales by 14.3%
It’s important to note multiple aspects here. First, all three buckets of rep contribution are predictive of sales increases. Second, the magnitude of the increases between OR and IR is much closer together than we typically incentivize in practice. Third, the collaborative aspects of the OR-IR combination are impactful for sales.
These measures were not only shown to be impactful but were also better predictors of future sales than traditional joint sales metrics (e.g., total sales from a customer account).
How to Use These Insights
1. Build Smarter Sales Metrics
While implementing the approach to measure rep contribution may be more complex than the context in this study, this study should be a motivator for sales leaders to move beyond traditional means of measuring joint efforts to support customer accounts. Instead of measures like total sales, the paper highlights the predictive value of individual and dyadic value-added scores. As an added benefit, measuring these components will allow for fairer performance reviews, compensation, and promotion decisions.
2. Optimize Rep Assignments
Reassign customers based on rep + synergy value, not just load balancing. The results paint a clear picture that the collaborative nature of team selling has a major impact on contributing to sales. Sales teams that collaborate better offer more value to contribute to the account. As a result, sales leaders must think strategically about how to assign reps in specialized function teams. While workload is certainly a consideration, other aspects like complementary product knowledge, collaborative experience, and customer industry experience should be considered for matching in teams.
3. Evaluate Sales Force Interventions
The measurement of rep value to customer accounts also offers many new avenues to tease out the effects of changes to the sales force. Sales leaders could measure changes to rep contribution before and after a new sales technology is introduced in the field. The same could be done with a change to an incentive. In sum, the introduction of rep contributions offers an array of pre-post comparison options that can clarify ROI of new interventions.
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Closing Thoughts
Modern B2B sales is no longer a solo sport. Deals are won or lost through the coordinated effort of multiple salespeople who are often in different functions and locations. So, if this is how it’s done, then the next goal for top-performing sales leaders isn’t just driving performance… It’s understanding who’s contributing, how, and when.
With smarter data and tools like value-partitioning, we can move beyond gut feel and surface metrics to recognize real impact, reward fairly, and improve strategically. This research shows it’s possible to quantify collaboration, without reducing it to team metrics or call logs.
Shi, H., Sridhar, S., & Grewal, R. (2025). Value-Partitioning of Sales Contribution in Business Markets. Production and Operations Management, 10591478251340433.
Auh, S., Spyropoulou, S., Menguc, B., & Uslu, A. (2014). When and how does sales team conflict affect sales team performance?. Journal of the Academy of Marketing Science, 42, 658-679.
Garrett, J., & Gopalakrishna, S. (2019). Sales team formation: The right team member helps performance. Industrial Marketing Management, 77, 13-22.