About 2.0
From static, impersonal and ineffective content to a rotating content engine built for relevancy and backed by data.
What’s the project? A feature, similar to Instagram’s Notes, helps users quickly share availability or lightweight expression with their friends and family using a text + emoji format.
Problem
WhatsApp's About feature was buried 2-3 taps deep in Settings, defaulted to a stale "Hey there, I’m using WhatsApp" and had no visibility where conversations actually happen.
Low awareness + adoption
Low feature comprehension
No aggregate surface for users to see + reply to Abouts
No content strategy to educate new users, re-engage existing ones, & keep the feature feeling novel and in the moment
Solution + My Role
Make it easier to create an About and more useful in the moments that drive conversations.
We introduced a lightweight emoji + text format with duration and surfaced About as a thought bubble in 1:1 chat.
My Role:
Helped define user problem and design solutions
Built a tailored user-journey content strategy aimed at educating and bringing awareness to new users and reengaging existing ones.
Led e2e content experiment
Helped shape product & GTM positioning + naming
Collaborated on UXR planning
Established scalable logging
Impact
+.17% Sends per Daily Active User & .5% group send per DAU
Exceeded adoption goals by 45% and retention by 50%
100% user positive sentiment
How my judgement & strategy shaped the feature
Solving awareness and adoption with content
Content strategy & product positioning
Entry point ghost text was a primary lever for awareness, education, and adoption. Content had a direct line to the feature's growth goals.
Constraints/Challenges:
UXR showed that users lacked awareness and feature comprehension
Users felt insecure or unsure of what to post for their About
Needed clear distinction from WhatsApp’s other feature, ‘Status’
Status is a visual, broadcast, creation-heavy tool.
About 2.0 was text-first, low-lift, surfaced intimately in a 1:1 as a thought bubble, not a feed post
My solution - a content strategy based on 4 principles
Simple and actionable — instantly convey this is an availability tool
In-the-moment relevance — prompts that inspire posting right now
Zero creation anxiety — lightweight, not performative
Spark conversation — inputs that invite a reply
I crafted a voice, tone and terminology framework with explicit guardrails to reinforce our availability/lightweight expression strategy and differentiate from Status’ richer, full creation experience.
For example:
DO NOT USE “Create” or “Share” — too tied to heavy-creation
DO NOT USE “Update” — owned by Status in the home tab
From static and impersonal to a dynamic content engine
I led content experimentation partnering with DS, Eng, and Marketing, to validate what resonated with users.
Problem
Low awareness, engagement, and comprehension. UXR revealed a range of use cases for About from availability to lightweight expression — the content needed to speak to all of them.
My goal
Build an adaptive content engine that personalizes ghost text entry point based on behavior signals, moving the approach from static to dynamic and perpetually novel. The content needed to create a feeling of freshness, drive in-the-moment posting, reduce anxiety, and educate new users —all tied directly to moving top-line metrics:
Group Creation DAU
Send Session @ 14 (retention)
Leading XFN collaboration:
I led XFN collaboration with DS and Eng to create a 4-arm prod experiment testing four thematic approaches.
Expression
User-journey (new users vs existing users)
In-the-moment (time of day, DOW, seasonal)
Varying mediums (emojis + music)
To induce freshness aligned with the strategy, a user would see a new prompt every time they opened the app.
Results:
We saw impressive results. Key takeaways were that highly personalized/relevant and in-the-moment prompts resonated most.
Group Creation DAU
+7% = Expression
+5.64% = in-the-moment
+16% = Emoji (iOS)
+5% - 16% = seasonal
Marketing integration:
Seeing the impact the prompts could have on creation, our strategy shifted to include our marketing activations. I partnered with PMM to create prompts for World Cup 2026.
Presets
After
Before
A universal approach aligned with product goals
The preset redesign was a deliberate content framework — not a copy refresh — built to reinforce the feature's framing and educate users on how to use it.
Rooted in availability, scaled to expression — Presets span from hard availability ("Free to chat," "Slow to respond") to lightweight expression ("Traveling," "Hanging with friends") to keep the feature coherent and show its full range.
Novelty was core to the strategy: low-performing presets rotated out, seasonal and holiday presets rotated in for relevancy.
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.
The range of explorations show a methodical approach to final content. Using a scale for tone and use case to find the right balance aligned with user need and product goals.
Universal
Personality + flaire
Rigid availability
Full expression
Curation over comprehensiveness
The initial preset list mirrored the original About 1.0 approach — long, exhaustive, covering every scenario. I advocated to cut it down significantly.
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.
A short, well-chosen set of presets does more: it signals "this is easy," establishes the feature's range without overwhelming it, and makes each option feel considered rather than exhaustive.
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.