Turning exploratory research into internal tools.

After six months of delivering reporting tools, I initiated an exploratory research track with the Director of Product Management to understand how teams used our existing data in Tableau and Salesforce. The research led to the design and development of two internal tools:

Feature Usage Baseline helped teams prepare feature recommendations using peer adoption and associated outcomes.

Book of Business Analysis helped Account Executives narrow hundreds of customers to the few worth investigating.

I led the research, synthesis, design, testing, and refinement of the two tools.

Stakeholder: DocuSign
Skills: Product DiscoveryHypothesis-Driven DesignUser Experience
Year: 2023-24
Role: Senior Product Designer

Initiating research:

I shortlisted 65 account executives based on their performance within the company, location, and experience. Six agreed to one-on-one interviews, and four joined an exploratory workshop.

A parallel interview track with product teams also provided context on the friction between product data and sales data.

Video interview with an account executive — One-on-one interviews with Account Executives.

Discovery workshop session — Discovery workshop with Account Executives.

Designing Feature Usage Baseline:

I explored one idea in two ways: compare a customer’s performance with similar customers, or compare which features those peers used and adopted.

Each interpretation was turned into a design and tested with a focus group of account executives.

Two peer-comparison concepts — One hypothesis, explored through two concepts. Undated project artifact.

Discovering the extremes in user interpretation:

Although the data was intended for internal use, the performance comparison fell flat because sellers imagined sharing it with customers and worried that poor results would make DocuSign appear to be a poor partner.

The feature comparison resonated because sellers could use it to show customers what their peers had purchased, how those peers were performing, and which features might help them.

The deeper insight was that users valued comparison data when it could support a conversation, strengthen a recommendation, or help make a sale, rather than when it remained private analysis.

Illustration of user frustration — Illustration depicting the frustration users shared after seeing designs based on the different hypotheses.

I combined which features similar customers used with the outcomes associated with those features. The result was evidence for preparing a recommendation.

Controls for defining similar customers — Controls for defining ‘similar’ customers.

Customer-value feature groups with redacted notes — Features grouped by customer value. All note text is permanently redacted in the public asset.

Feature adoption and associated outcomes — Feature adoption beside associated completion-time and send-velocity outcomes.

The complete Feature Usage Baseline dashboard brought account criteria, feature adoption, and associated outcomes into one view.

Designing Book of Business Analysis:

Although many metrics were available to internal teams, Account Owners had to update internal documents with their BDRs twice a week to organize the data, prioritize customers, and spot anomalies.

This process was especially time-consuming for Mid-Market and Virtual Account Executives, who managed between 200 and 3,000 customers.

Needle-in-a-haystack prioritization illustration — Illustration: a needle-in-a-haystack prioritization problem.

While each Account Executive had a unique approach to sorting data, an iterative synthesis helped me create a six-bucket model, with every customer in an AE’s book fitting into only one bucket.

I started by designing workflows to identify these six customer types. This was later simplified into a set of filters that acted as a custom control center, helping to spot patterns among customers.

Six proposed account groups and controls — Six proposed groups and the controls used to explore them.

Account patterns interface — Examples of the account patterns the tool helped sellers investigate.

The complete Book of Business Analysis dashboard combined account patterns, thresholds, and filters in one view.

Impact:

#01 - Feature Usage Baselines became a standard reference tool while building customer presentations and QBRs.

A quarterly survey showed that approximately seven in ten Account Executives consistently used screenshots from the Feature Usage Baselines in their slides while evaluating upsell and renewal plans with customers.

#02 - Book of Business Analysis transformed customer strategy for Account and GTM teams.

The simple ability to split an entire book of business based on an MRR threshold, while also inspecting it along multiple dimensions, allowed Account Executives to iterate faster on their personal MRR thresholds.

Those thresholds also showed DocuSign how sellers across regions, markets, and quarters judged account value, turning individual instinct into information the company could compare and learn from.

Multiple teams also reported a noticeable reduction in weekly account sorting activities.

Research synthesis shared with product leadership — The broader research synthesis shared with the Director of Product Management used artifacts and insights from the discovery workshop. It included research across sales, marketing, product, and customer success and was later presented to Chief Information Officer Shanti Iyer.

What I learned:

Reliable delivery created permission to challenge the roadmap.

Despite wanting to innovate, my first few months involved building designs that worked within set constraints, enabled development, removed blockers, and reduced ambiguity.

Once trust was built, it was easier to make a case for exploratory research, which led to deeper and more ambitious problem setting.