About 2.0

From static and ineffective content to a data-backed rotating engine

What’s the project? A feature, similar to Instagram’s Notes, helps users quickly share availability or lightweight expression using a text + emoji format.

GTM campaign

We introduced a lightweight emoji + text format with duration and surfaced About as a thought bubble in 1:1 chat.

Content: I created a rotating prompt engine for the entry point content & a universal preset list that spoke to primary use cases.

My Role:

• Helped define user problem and design solutions

• e2e content strategy + experimentation

• Helped shape product & GTM positioning + naming

• Collaborated on UXR planning

• Established scalable logging

Before

• UXR showed that users lacked feature comprehension: “I don’t know what this feature is for?”

• Users felt insecure or unsure of what to post for their About.

• The feature needed clear distinction from WhatsApp’s other feature, ‘Status,’ which is a visual, broadcast, creation-heavy tool.

• Universal — reach 180+ countries which varied significantly on comfortability with ‘expression’

Content was a primary lever in the usage of this feature. It needed to meet:

• User need: feature education, use case (availability-expression), easy to use

• Business need: Feature adoption, make About an everyday posting tool, and ultimately drive conversation.
  

A principled approach to content strategy

I crafted principles rooted in UXR to shape the content to meet user need and ladder to top-line product goals.

Why run an experiment & how I got buy in

Getting buy-in meant speaking each team's language. With engineering, I scoped the test small enough to read as low lift, not extra work.

With PM, I made the case that content was integral to reaching product goals of adoption and retention, and the only way to prove which direction moved those numbers was to test what actually resonated instead of assuming.

Build an adaptive content engine that creates a feeling of freshness, drive in-the-moment posting, reduce anxiety, and educate new users —all tied directly to moving top-line metrics:

• Group Sends per DAU

• Send Session @ 14 (retention)

I led XFN collaboration with DS and Eng to create a 4-arm country test experimenting with 4 thematic approaches. To induce freshness aligned with the strategy, a user would see a new prompt every time they opened the app.

In-the-moment: DOW, Time of Day

Why?

The 2026 product strategy required shifting About from a weekly to a near-daily habit.

Results

My choice to create a rotating content engine successfully drove feature adoption and message sends.

Interestingly, user-journey prompts did not perform well indicating less need to educate through content and more through design.

I chose the top performing prompts from expression, in-the-moment, and emoji/music that gave users a new prompt every time they opened the feature.

Because the strategy drove measurable lifts in adoption and retention, I partnered with PMM to extend it into app-wide marketing moments like World Cup 2026.

Presets

Before

A system, not a copy refresh

I treated presets as a system, not a copy pass. They had to reinforce what About is for while flexing across different use cases — from "I can't talk right now" to "I'm feeling something and want you to ask about it."

The tension I was solving for: How to keep one legible feature that still spans hard availability to lightweight expression, without reading as a grab-bag. The fix was a spectrum, not a list — every preset sits somewhere between "Free to chat" and "Traveling," so the range reads as one idea.

• Universal by design: Situations and feelings that are globally recognizable, evergreen, and age-agnostic. Emoji choices informed by chat usage data.

• Always invite conversation. Shifting from "Busy" → "Slow to respond." "Available" → "Free to chat" opens a door to conversation. "Feeling excited!" prompts "About what?" Every preset gives a contact a reason to reply.

• Educate through example. For new users, presets are the onboarding. They model the right length, tone, and specificity — lowering blank-canvas anxiety while showing what "good" looks like.

Novelty kept it alive. Low-performers rotated out; seasonal presets rotated in — so the feature didn't go stale after week one.

Explorations - A methodical approach to finding the right range, tone and use cases that aligned with user need and product goals

A key decision to cut the list in half

The initial preset list was long, exhaustive and did not align with our new product goals/primary user needs. I cut the list by half.

Why?

• Users were already coming to About 2.0 with NO clear mental model of what the feature was, so presenting them with a wall of options would compound that confusion.

• Posting anxiety was a core barrier to adoption, a long list risks the opposite of its intention — instead of helping users pick something, it paralyzes them.

Outcome:

• Adoption of presets went up by 22% after cutting the list

• UXR showed it helped with user education on how to use the feature

Implemented logging = improved optimization

Previous presets had NO logging. I changed this. I ensured logging was implemented with DS for us to understand the user-value of these and which ones were not resonating with users.