News Feed

Situation

The Promontory connects Emerging Manager Funds (EMFs) with Limited Partners (LPs). After a private beta with 120 EMFs and 15 LPs, we noticed a major issue: only 3 out of 135 users posted on the news feed, earning it the nickname “dead disco” internally. Although we initially considered refining the existing news feed to boost engagement, user feedback and data suggested it wasn’t giving the real-time intel both groups craved.

“It doesn't look like a very lively community,” said one EMF.

Task

We needed to keep users on The Promontory (vs. pivoting to external networks) by giving them immediate value. Our goal was to “flatten the universe” by surfacing the critical answers that EMFs and LPs typically hunted for across multiple platforms (LinkedIn, AngelList, Pitchbook, etc.).

This critical questions included:

1. Who’s currently investing in new funds?

2. Which funds are trending—and why?

3. How many new AI funds launched this year?

Action

User Research & Persona Validation

To validate our assumptions, I interviewed 10 users (5 EMFs and 5 LPs) to understand their pain points. After learning why they felt the news feed added little value, I aligned with the PM on new KPIs for the new feed.

Cross-Functional Alignment

I presented my findings to the PM and engineers. We debated whether to update the existing feed or build a new data-centric experience. After weighing a hybrid approach (data + conversation) against user needs, we pivoted to a full data dashboard based on solid research findings.

Design & Iteration

After designing some dashboard concepts, I collaborated closely with engineers to ensure real-time data display was feasible. Our biggest challenge up until this point was building robust backend processes to pull, verify, and update fund data continuously. Some of our data points were more formulaic than others, and gathering fund data from EMFs and LPs was no easy task.

Implementation & Testing

Through several rounds of usability testing, I was able to hone in on an experience that gave users just enough data to keep them on the platform. With an understanding of the final UI layout, we ran A/B test comparing the new dashboard to the original news feed with a control group. The test confirmed that the dashboard directly boosted engagement metrics.

I held daily syncs with engineers to hand off the final designs, reviewing design updates in Figma to triple-check our data architecture. The final design was then QA'd by our entire team before shipping the production version.

“The new layout is exactly what I need—it tells me which funds are hot right now,” said one LP during a feedback session.

Result

The results were pretty staggering.

• Day-14 Retention jumped from 20% to 35%—users who found relevant info returned more frequently, rather than bouncing to LinkedIn or AngelList.

• Average Weekly Sessions per user increased from 1.8 to 3.1 visits.

• Connections Made (direct EMF-LP conversations on-platform) soared from roughly 10/week to 25/week—an overall 150% jump in the first month of the new design.

• Self-Reported “Meaningful Conversations” (leading to at least one follow-up meeting) doubled, from 10% of users to 20%. This KPI is much more indirect when relating it to the dashboard updates.

“This is exactly what I was hoping to find. Now I can see which AI funds are hot right now," an LP told us post-launch.

We did notice that while the dashboard boosted immediate engagement, some users missed the social aspect of the original feed. We plan to experiment with reintroducing selective community features in future iterations.

This pivot from a conversation-driven feed to a data-driven dashboard provided users with the critical insights they needed, improving engagement metrics significantly. Our ongoing plan includes testing hybrid features to balance real-time data with community interaction.