Explore

Thoughts on (App PMF & Creation)

Maximise:

Output Metric

Customer Lifetime Value

# of transactions

Retention

DAU/MAU

D1, D3, D7, D30 Retention

(using)

Input Metrics

Time Spent on App

PDP Page Conversion (% of clicks on PDP / DAU)

Immediate Priority is to:

finding which sub-component of Time Spent on App correlates strongest with Retention & Transactions:

by sub-section: is it time spent on Home Feed, Profile Feed, Wishlist section, etc.?

by content type:

by format: live, short video, memes, etc.

by source: supplier videos, AI videos, standalone creator videos, YouTube scraped videos

by theme: storytelling video, product demo video, etc.

by UX experiences:

size of PDP, color, layout, etc.

can a re-designed wish-list section correlate well with our output metrics?

by growth loops:

notifications & gamified loops on:

re-targeting

wish-listed items

affinity:

category (you’re looking at Home Decor only)

gender (you’re looking at Men’s Apparel only)

sub-category (you’re looking at traditional women’s wear only)

etc.

Track 1: experiments on smaller optimisations

small, incremental changes

Track 2: re-imagining the core experience with changes in value prop

Track 3: re-examine the assumptions we have taken in Track 1 and Track 2

how do we fit in subjective feedback?

run experiments on a clearer, newly acquired user cohort

Things to do: (non-prioritised)

Hand-curation of Feed

In rule-based logic, put product-tagged content above non-product tagged

A/B experiments on Feed

DS & Personalization-related work

Consolidated Feed

Affinity Targeting

Wishlist Flywheel

Wishlist becoming something more than a standalone feature - but a core value prop of app

Wishlist as a way to know more than about the user, as a way for the user to showcase their taste, as a way for trending products to emerge

This has other benefits:

provides unique differentiation in user’s mind,

helps us target user better,

activates social growth loops,

wish-list and repeated targeting on it gradually wears down the barrier to purchase

Growth & Retention Loops

Share a post

Affiliate Model

Retention Loops - wishlist updates

Notifications Tab & In-App Notifications (use MoEngage built)

Modelling a particular product (Sensetime SDK etc)

Urgency/Persuasion Elements on PDP

Stand-alone PDP

Wishlist Tab or Section?

Price Drop on wishlisted products/posts

Keep everything organized in one place and open up rabbithole of further products

Widget Types that break the feed monotony

Bot: "Show me a quirky look" that leads to an LLM flow

Productizing the content formats that work

Automation of non-negotiable Ops work like Product Tagging

Streaming Infra

Rating + best look

Enabling some constructs (like affiliate product tagging) to enable US iOS app

L2 page for when you tap onto a video

Ability to tag multiple products

Some notes on how we’ll work:

Extreme Speed & Iteration Rate (especially for Track 1)

This pod will move very fast and break many things.

It will make many MVPs, release fast, and scrap many MVPs too.

Find new ways to prototype fast (especially for Track 2)

It will also try to release no-code variants:

We have figured a way to embed analytics onto Framer (a design prototyping tool).

This allows us to release hard-coded MVPs with no Engg effort.

We can release a Framer Web Page that showcases a brand-new experience

Run Facebook Ads to get 100 (some statistically significant number) users on the page

Assess feed depth, time spent, and PDP visits, on the page

Very manual version of the vision → figuring PMF signs → then automate/scale

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Analytics

We will also study all correlations separately.(example: we expect that there might be content types that correlate strongly with Transactions but moderately with Retention - or vice versa).

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