Designed a personalized feature report card to drive upgrades through AI powered workflow

Designed a personalized feature report card to drive upgrades through AI powered workflow

Claude Design

NotebookLM

Pendo Guides

80%

Users requested a report card through Pendo

28%

Upgraded to a plan after trial

0%

Engineering effort required

BACKGROUND

Teachable is a SaaS platform where creators build and sell online courses where trial-to-paid conversion was a key growth metric.

DURATION

4 Weeks

MY ROLE

AI native product designer

TEAM

Matthew Malia - Senior Product Manager

Sarah Driscol - Product Design Manager

Thais Toma - Research partner

HOW IT STARTED

Despite a stable and growing subscriber base, upgrade rates remained consistently under 1% of total subscribers per month.

The team had assumptions about why. None of them were validated. I ran the research to find out.

AI x RESEARCH

I built an AI research pipeline that simplified hours of reading 15 interview transcripts, the risk of missing patterns and synthesis that can take weeks if done manually.

Not to replace research judgment, but to make it faster and wider.

AI x RESEARCH

I built an AI research pipeline that simplified hours of reading 15 interview transcripts, the risk of missing patterns and synthesis that can take weeks if done manually.

Not to replace research judgment, but to make it faster and wider.

(01)

Record + Transcribe

With 15 sessions captured verbatim, no pattern could slip through the cracks.

(01)

Record + Transcribe

With 15 sessions captured verbatim, no pattern could slip through the cracks.

(02)

Synthesize patterns using NotebookLM

One theme kept surfacing: users didn't know what their plan included.

(02)

Synthesize patterns using NotebookLM

One theme kept surfacing: users didn't know what their plan included.

(03)

Auto-clip Highlight Reel using Descript

Seeing users say it out loud made the invisible value problem impossible to dismiss.

(03)

Auto-clip Highlight Reel using Descript

Seeing users say it out loud made the invisible value problem impossible to dismiss.

(04)

Opportunity board using claude

I fed in interview themes to generate opportunity statements, then scored each against effort and impact criteria.

PRIMARY PAIN POINT

Across these interviews, we identified a consistent feature discovery and value communication gap across the Teachable experience

The upgrade blocker wasn't price. It was invisible value.

“Maybe that's a feature that I missed. I didn't realize that we could remove the, the teachable branding.”

Creator 1

Avatar image 1
Avatar image 2
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“I wasn't aware of all the features that I'm missing now with the growth plan.”

Creator 2

Avatar image 1
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PRIMARY GOAL

How might we communicate feature value and drive upgrades without engineering resources or building new product surfaces?

BRAINSTORMING AND DECISION MAKING WITH PM

I worked with the PM to map opportunities against effort vs. impact based on engineering capacity

Feature Report Card

A personalised breakdown of which features a creator has used, missed, and locked behind their plan — delivered via email.

Quick wins

Big bet

AI-feature recommendations

A contextual engine that surfaces the right feature to the right creator at the right moment based on their school type, goal, and usage behaviour.

Onboarding checklist V2

A step-by-step guide that walks new creators through the features most relevant to their goals.

Won't do

Nice to have

Pricing page redesign

Restructure the plans page to make feature differences between tiers clearer and easier to compare.

SOLUTION

I used Claude to generate divergent layout directions for a personalised feature usage report card that makes the value gap impossible to ignore.

From a list of ideas this proved to be high impact low effort idea

DIRECTION 1

Spotify Wrapped style

Name-forward layout makes it feel personal, not generic

Social proof and ROI framing adds credibility

More celebratory and engaging for creators

Less scalable in product — better suited for marketing emails

Action items are hidden and hard to differentiate

Doesn't explain why they should upgrade

DIRECTION 2

Creator journey map

Shows visual progression

Unique concept for driving upgrades

Requires learning how to read the map

Too abstract for a billing context

Nudge is not visible enough to drive action

Not scalable across product and emails

DIRECTION 3

Feature grid with suggestion

Works across product and email surfaces

Shows usage data and social proof in context

No clear categorisation — colors and shapes don't communicate meaning

Less motivating tone, feels less personal

No feature description — creators don't know why each feature matters

WHAT WE DELIVERED VIA EMAIL

My figma design cherry-picked personalization + celebration from Direction 1, progress visualization from Direction 2, scalable card structure from Direction 3 with added human thinking

THE CLIMAX

Due to limited engineering resources, instead of building the full in-product system, I utilized Pendo, Braze and Sigma to solve this at low cost.

Sigma dashboard

Pulling feature usage data and identifying who to target

Used Sigma to query creator feature usage data — identifying which trial creators had low feature activation and which features were sitting unused. This became the targeting logic for the experiment.

Pendo nudge in product

Triggering the request in-app

Configured an in-app guide in Pendo to show trial creators on days 7–10: "Request your report card." No engineering required — targeted, timed, and launched directly in Pendo.

Pendo nudge in product

Triggering the request in-app

Configured an in-app guide in Pendo to show trial creators on days 7–10: "Request your report card." No engineering required — targeted, timed, and launched directly in Pendo.

Braze email

Delivering the personalised widget report

Collaborated with marketing team to build the designed widget as an email template in Braze with dynamic variables for each creator's feature data with a direct action link on every gap and a clear upgrade CTA.

IMPACT

Strong user response gave me the data to advocate successfully for the feature and was added to Q2 roadmap for engineering investment

80%

Users requested a report card through Pendo

28%

Upgraded to a plan after trial

0%

Engineering effort required

CHALLENGES

Some challenges and learnings that helped shape my understanding of using AI and working within constraints

AI hallucinations

The AI occasionally generated insights or quotes that weren't directly supported by the interview transcripts, or combined details from multiple interviews in misleading ways.

Limited engineering capacity

Limited engineering pushed me to explore and use no-code tools (Pendo + Braze) to validate the feature report card concept

AI x RESEARCH

I built an AI research pipeline that simplified hours of reading 15 interview transcripts, the risk of missing patterns that span multiple sessions, and synthesis that can take weeks if done manually.

Not to replace research judgment, but to make it faster and wider.

(01)

Record + Transcribe

With 15 sessions captured verbatim, no pattern could slip through the cracks.

(02)

Synthesize patterns using NotebookLM

One theme kept surfacing: users didn't know what their plan included.

(03)

Auto-clip Highlight Reel using Descript

Seeing users say it out loud made the invisible value problem impossible to dismiss.

(04)

Opportunity board using claude

I fed in interview themes to generate opportunity statements, then scored each against effort and impact criteria.