Duplicate Management
Senior Product Designer
2025
PROBLEM
Duplicates eroded trust in the platform
Affinity is a CRM that helps investors uncover opportunities within their relationship network. Since its insights are only as reliable as its underlying data, data quality is fundamental to the platform's value proposition. However, since data is automatically imported from sources like email, calendars, and CSVs, duplicate records often emerge, which can erode trust in the insights customers rely on.
At the time, Affinity was focused on a company-wide initiative called Nail the Basics, prioritizing core product quality over new features. Reducing duplicate records became a key initiative after customers consistently identified data quality as one of their biggest pain points.
Although Affinity already offered a Duplicate Manager at the time, users rated it just 1.6 out of 5 for usefulness, and more than 100+ customers had requested improvements. The biggest issue was trust. Without enough context to understand why records were being flagged as duplicates, users lacked confidence in the recommendations and hesitated to merge.
Instead, most users manually navigated to profile pages to gather the details they needed before merging duplicates, which made an already repetitive process even more time-consuming.
Hypothesis
Could greater visibility lead to increased confidence?
Our goal was to add more transparency and give users the context they needed to feel confident committing merges. We hypothesized that giving users greater visibility into record details and control over merge outcomes would increase their confidence in completing merges.
To measure success, we wanted to increase adoption through higher merge rates with the expectation that it would reduce duplicates in the system and improve overall data quality.
Explorations
Every trade-off was evaluated against our goal of building trust
Before designing anything, I established a set of principles to act as a decision-making framework to ensure every trade-off stayed aligned with the experience we were looking to create.
I explored a range of design concepts focused on giving users control over the underlying data. These included two primary patterns: an accordion layout optimized for speed and efficiency, and a full-page layout designed to support deeper evaluation.
One of the most requested features from customers was the ability to undo a merge, which helped give them more confidence to commit without worrying about making mistakes. Unfortunately, the engineering complexity of supporting this feature made it out of scope for this release.
As a workaround, I introduced a live preview of the merged record in the full-page layout, which helped compensate for the lack of an undo feature by making the outcome transparent before users committed to a merge.
I connected with customers and walked them through each concept to gather feedback. When comparing the two patterns, the accordion layout was perceived as more efficient and allowed users to quickly scan details without needing to navigate elsewhere, while the full-page layout was more comprehensive — the live preview was received well and validated our assumption that giving users visibility into the merge outcome helped build more trust.
We ultimately moved forward with the full-page layout because it prioritized trust over speed, which was an essential factor in giving users the confidence they needed to merge records.
We refined the design based on feedback, which included things like placing fields adjacent to one another to make record comparison faster and easier.
Usability Testing
Addressing friction points identified in testing
After multiple rounds of iteration, we conducted usability testing to validate the end-to-end experience. While participants completed the core tasks with little difficulty, the sessions uncovered a few friction points.
I partnered with my PM and engineers to prioritize high-impact issues that were feasible within our launch timeline.
For customers with a lot of custom fields, the detail page became visually dense and made it harder for them to quickly identify the information that mattered most.
To address this, I identified the a set of core fields users consistently relied on when evaluating records and made them the default view. This reduced unnecessary information and helped users focus on the details that mattered most.
To support different workflows, I added the ability to show or hide rows, which gave users flexibility over which fields they wanted displayed.
Although the new experience was optimal for building trust, users told us the workflow could better support speed. To address this, we introduced an easy way to cycle through duplicate sets while staying within the detail view, which allowed for users to move faster without losing context.
Final Designs
Designing for trust at every step
While users expressed a need to see the underlying record data, they also found significant value in seeing broader signals like match reasons and confidence scores, which provided far more context than the previous experience up front.
In the main list view, our goal was to surface the most relevant signals so they could quickly assess any potential duplicates and take action if they felt confident enough to do so.
For deeper evaluation, the detail view presented all fields side by side, which made it easy to compare records and choose which values to carry into the merged result. A real-time profile preview showed the final outcome as users made selections, which helped them understand exactly what would happen before committing a merge.
As trust increased, users could shift to bulk merging for greater efficiency. While most preferred to carefully review each merge, a segment of power users had no time to inspect and wanted to act immediately. Supporting both behaviors was essential for us to meet different user needs.
We didn't want to just optimize for the happy path. Through technical review sessions, engineers raised some concerns about the latency involved in bulk merging records. I accounted for this by designing different loading states that kept users informed about what was happening while a merge was in progress.
I carried that same principle of transparency throughout the experience by clearly communicating system status and providing recovery paths if something went wrong.
Impact
More merges. Cleaner data.
Within three months after launch, we saw a 530% increase in company merges and a 200% increase in people merges, which exceeded our adoption goals. Within six months, duplicates also decreased by 55%, which demonstrated significant improvements in data quality.
After launch, we received positive feedback from our Big 10 customers, one of our most important customer segments by revenue.
Takeaways
Preserving trust-building moments through constraints
This project served as a reminder that good design is often about making trade-offs without losing sight of the core problem. Earlier on, we aligned on the fact that our goal was not to build the most feature-rich tool, but it was to increase users' trust in the merge process, which gave us a clear principle for making decisions throughout the project.
There were moments when I had to scale back parts of the design due to technical constraints, but through that, I tried staying focused on preserving elements of the design that were directly tied to building user confidence. Keeping that principle in mind made it easier to prioritize what mattered most and let go of ideas that weren't as essential to achieving that goal.