This study focused on evaluating two closely related products within the trading experience: Single Forwards and Multi Forwards. While both enable users to book forward contracts, they differ significantly in capability. The Single Forward flow supports one transaction at a time, whereas the Multi Forward flow allows users to book up to 25 forwards within a single session.

Given these differences, we wanted to better understand user behavior across both experiences and determine whether guiding users toward Multi Forwards would improve efficiency and overall usability.

Single vs. Multi Forward Flow

Problem

Research Goals

Although both products were actively used, there was limited visibility into how effectively they supported user workflows. Anecdotally, we observed that some users were repeatedly booking multiple Single Forwards in quick succession—a behavior that could indicate friction or inefficiency in the current experience.

We hypothesized that users making multiple Single Forward bookings would benefit from adopting the Multi Forward flow, which is designed to streamline bulk transactions. However, we needed data to validate whether this shift would meaningfully improve user efficiency and whether either flow contained usability or performance issues.

The study was designed to evaluate both product performance and user behavior over time. Key objectives included:

  • Assess whether encouraging Single Forward users to adopt Multi Forwards would improve their workflow efficiency.

  • Identify usability issues or friction points within either flow.

  • Measure and compare time-to-completion across both experiences.

  • Track completion rates for Single Forward versus Multi Forward bookings.

  • Understand post-transaction behavior and user navigation patterns.

  • Analyze how frequently users complete multiple Single Forward bookings within a short timeframe.

A central focus of the study was understanding repeated Single Forward usage, as this behavior could signal an opportunity to introduce a more efficient alternative.

Methodology

My Role

Key Insights

To capture behavioral data at scale, I partnered with Product Analysts to define a tracking strategy using Heap Analytics and Power BI. Together, we identified the key events and metrics needed to evaluate each objective.

Custom event tracking was implemented in Heap to monitor user interactions across both flows, including session activity, booking completion, and time-on-task. These events were then validated and visualized through dashboards in Power BI, enabling ongoing analysis throughout the study.

Data was collected over a three-month period, allowing us to observe trends over time rather than relying on isolated snapshots. This longitudinal approach provided a more reliable view of user behavior and product performance.

A critical component of the analysis was defining a consistent benchmark for comparison. We established a threshold of three bookings per session for both Single and Multi Forward flows. This allowed us to directly compare efficiency between users completing multiple individual transactions and those using the bulk booking experience.

Additionally, we closely analyzed session-level behavior, particularly the time it took for a single user to complete multiple Single Forward bookings in succession. This metric was key to determining whether Multi Forwards offered a meaningful efficiency advantage.

  • Collaborated with Product Analysts to define tracking strategy and success metrics.

  • Identified key user behaviors and hypotheses to validate through data.

  • Guided the implementation of analytics events within Heap.

  • Analyzed data across multiple dashboards and synthesized insights.

  • Translated quantitative findings into clear, actionable recommendations for stakeholders.

The data revealed a strong behavioral pattern that validated our hypothesis.

  • 32.3% of Single Forward users completed at least three bookings within a single session.

  • Users took an average of 9 minutes and 18 seconds to complete three Single Forward trades.

  • In comparison, users completed three trades using Multi Forwards in an average of 5 minutes and 35 seconds.

This represents a time savings of nearly 4 minutes per session, making users approximately 60% more efficient when using the Multi Forward flow for multiple bookings.

These findings highlight a clear mismatch between user behavior and product usage. A significant portion of users are engaging in workflows that are better suited to the Multi Forward experience, yet continue to use the less efficient Single Forward flow.

The study provided strong, data-backed evidence that Multi Forwards delivers a more efficient experience for users completing multiple transactions. As a result, we recommended increasing visibility and adoption of the Multi Forward product, particularly for users who exhibit repeat booking behavior.

Beyond supporting a strategic product shift, this work also demonstrated the value of leveraging behavioral analytics to uncover hidden inefficiencies in user workflows. By aligning product design more closely with actual user behavior, we can reduce friction, improve task efficiency, and create a more intuitive trading experience.

Outcome