Frictionless Onboarding via Industry-First Innovation

Crisis: An Unexpected Engagement Problem

After our MVP platform launch, surface metrics looked promising:

• Thousands of users signed up

• The distribution product had strong adoption (our lead, mass-market product)

• Sync submissions were growing (the second-largest signup driver)

• Various entry points were driving product usage

But deeper analysis revealed a critically low cross-product engagement issue.

For example, a typical usage journey was to join via our distribution entry point. Below is a subset of those users who completed an action within our distribution product and a breakdown of their usage across other products.

The cross-product interaction was even lower when viewed from other entry points.

The pattern was clear:

• Users came for one specific job (eg. release a song)

• Sync submissions boosted MAU as the only “sticky” product

• Fewer than 10% completed actions across multiple products

• 15–45% explored other products without completing actions

• Only 20% completed onboarding (added at least one song)

This threatened our entire value proposition. We positioned ourselves as a unified platform, a collection of disconnected tools in one place, but users were not connecting products.

Root Cause Analysis: Diagnosing the Friction

My hypothesis framework:

The Real Problem (Validated Through User Testing):

Products relied on users providing known details, sourcing missing info, and uploading assets (creatives aren’t naturally inclined towards admin).

Known:

• Song titles/album names

• Contributors, producers

• Genre, mood, tempo, instruments

Sourced:

• ISRC, UPC, ISWC

• Rights holders

• Copyright splits

• Lyrics

• Spotify links, social media links

Assets:

• Audio files

• Artwork

• Cover/Samples documentation

Investment time: Track: 10+ minutes. Album: 45+minutes. Catalogue: 4+ hours.

Session replay insights (watched 50+ abandonment sessions):

• 72% of users who started would abandon when reaching sourced or asset requirements.

• The abandonment rate was exceedingly higher on the second song input, highlighting intent, but friction at data entry.

• Common behaviour included leaving the page to find data, returning without it and then abandoning when it became a blocker.

User interviews highlighted:

• Intent to return at a later date to add more (never doing so).

• Certain information, such as ISRC, UPC, links, splits and artwork, was not available locally or even known.

• The repetitive nature became boring.

• The thought of having to do something multiple times over was a negative

• Time was an issue. The interest was there, but after spending time finding and filling out information, the interest waned.

The insight: The issue wasn’t motivation, it was friction. Repetition, sourcing gaps, and time cost eroded intent.

Strategic Approach: Designing the Solution

We'd always known data was key for our platform, but priority was initially given to the MVP. With the engagement problem now clearly identified, we were able to revisit exactly what "data is key" meant. Now we had our new focus: How do we use known data to improve the onboarding process and ultimately improve cross-product usage?

My strategic insight: If we tap into existing APIs, we can surface artist information automatically instead of making users enter everything manually.

The API landscape I evaluated

Individual Platform APIs Available:

• Spotify (existing partnership, free access via public API)

• Apple Music (limited public data, deprioritised)

• Amazon Music (limited API, deprioritised)

• SoundCloud (open API, less reliable data)

• YouTube (public data via Google API)

Data Aggregator Options:

• Soundcharts (chosen for 500,000 requests at $250, comprehensive airplay data, social interactions, streaming analytics)

• ChartMetric (competitor to Soundcharts, similar pricing)

• MusicBrainz (open data, limited commercial use)

The cost challenge: Soundcharts provided the richest dataset at a reasonable cost (500K requests = $0.0005 per call), but we still needed to manage call frequency as each artist would require many calls per ingestion. This was manageable for paying users (we could absorb the cost in subscription pricing), but we had a large base of free users, many of whom would bounce before any meaningful interaction and couldn't justify ongoing API costs for users who might never convert.

My Solution: Tiered Data Fetching Strategy

Tier 1: Free Data (Signup - Immediate)

• Pull from Spotify public API only (free, no authentication required)

• Fetch: Artist name, basic catalogue (song titles, album names), low-resolution artwork

• Spelling correction built in: Spotify API returns similar artist matches if the name is misspelt

• Purpose: Create an instant profile that looks complete without pulling the full dataset

Tier 2: On-Demand Data (User Engagement - Triggered)

• When the user interacts with a product or song (e.g., submits to a playlist, enables publishing, views Insights)

• Then fetch full data from Soundcharts (detailed song data, streaming stats, social metrics, airplay data)

• Justification: User has shown intent → can tie API costs to cost-per-acquisition for that user

Tier 3: Staggered Ingestion (Background - Post-Signup)

• After initial profile creation, background jobs progressively fetch additional data

• 20-60 minutes post-signup, the full catalogue ingestion is complete

• Follow-up email sent containing insights (engagement hook)

Why this worked:

• Instant gratification: Users saw a populated profile in 30 seconds (even if not fully complete)

• Cost control: Soundcharts calls are only made when the user demonstrates intent (engaged with the platform)

• Perception vs reality: Profile appeared complete immediately, full data filled in progressively

Fallback Strategy (No Data Found):

If Spotify API returned no results:

• Spelling correction: Spotify API suggests similar artist names ("Did you mean: [Artist Name]?")

• Multiple matches: If Spotify returns multiple artists with the same/similar names, present disambiguation UI ("Which one is you?")

• Trigger aggregator search: Send artist details to Soundcharts for broader search

• Manual entry fallback: If no match is found, the user must manually add songs individually.

• Follow-up process: Background job retries Spotify search 24 hours later (in case of temporary API issues or newly added artists)

Solution Design: Instant Onboarding

Step 1: Artist Name Pre-Qualifier (Signup Screen)

At signup, we ask for the artist's name (before email/password). This served two strategic purposes:

Purpose 1: User Pre-Qualification

• Filters out non-artist signups (we cast a wide net with marketing, media buyers, fans, playlisters, etc.)

• Only users with artist names proceed (natural filtering without explicit rejection and taking them down a different route)

Purpose 2: Background Processing Delay

• While the user enters email/password/profile details, the background job fetches data

• By the time the user completes the signup, their profile is already populated

• User never sees a loading screen, and data appears instantly on first login

Step 2: Data Aggregation (Background Process)

What we fetched automatically:

What we fetched on-demand (when the user engaged):

Step 3: Progressive Enrichment (Post-Signup, 20-60 Mins)

Background jobs continued fetching:

• Full-resolution artwork (high-quality images for showcase pages and distribution)

• Historical streaming data (12-month trends, not just current stats)

• Social media followers, posts, interactions, reach, etc. (Facebook, Instagram, TikTok, YouTube via APIs)

• Playlist placements (which playlists feature the artist's songs)

• Airplay and charts (country, global, platform)

Follow-up email (sent 24 hours post-ingestion):

• Import updates

• Key engagement stats

• Engagement drivers for paid elements

Why the 24-hour delay worked:

• Re-engagement hook: Brings users back to the platform (combat day 2 churn, which was the highest churn point)

• Shows ongoing value: Working for them on their behalf (platform feels active, not static)

• Upsell opportunity: Insights data in the email teases paid-for stats

The Value Unlocked (Cross-Product Impact):

1. Music Catalogue Product (Core Hub)

• Pre-populated with songs, albums, metadata

• Became a central hub for all downstream products (distribution, sync, showcase, playlist submission)

2. Distribution Product

• Songs already in catalogue → one-click rerelease

• Pre-populated song data → No manual entry

• Historical release data imported → users saw the complete discography

3. Publishing Product

• Streaming data → estimated uncollected royalties

• Songwriting credits pulled from metadata → pre-filled PRO

4. Sync Submission

• Songs pre-qualified based on genre, mood, tempo (pulled from Spotify metadata)

• One-click sync submission (no manual tagging required)

5. Playlist Submission

• Playlist performance data → Songs identified for playlists (recommendations based on API data)

• One-click submission (pre-filled with song info)

6. Showcase Product (Auto-Generated)

• Artist bio (from Spotify), discography, artwork, social links → auto-generated public profile

• Additional SEO strategy: We created showcase pages for major artists (public figures) using publicly available data

• Ranked for artist names, drove organic traffic

7. Artist Insights Product (NEW - Unlocked by Data Aggregation)

The strategic unlock: By aggregating data from Spotify and Soundcharts, we had a unique cross-platform dataset that could be offset by acquisition costs to offer the product for free.

What Insights were offered:

Free Tier (Teaser - Drive Upgrades):

• Current streaming stats: Monthly listeners, follower count (Spotify only)

• Top 3 songs: breakdowns by platform, audience, etc.

• Basic audience demographics: Partial visibility and limited time span

• Purpose: Give users enough value to see potential, create desire for more

Paid Tier (Credits or Subscription):

• Cross-platform analytics: Spotify + Apple Music + YouTube streams + more in one dashboard

• Trend analysis: Which songs are growing/declining, which platforms are driving engagement

• Full audience insights: Demographics, geography, listening behaviour across all platforms

• Competitive benchmarking: Compared against other users on Music Gateway, more comparative for newer artists than being compared against established artists

• Playlist tracking: Which playlists added/removed your songs, impact on streams

• Airplay data: Radio play tracking (from Soundcharts), chart data

• Social metrics: Follower growth and engagement, potential outreach opportunities, etc.

Monetisation Model:

• Not a standalone product (no separate monthly pricing)

• Integrated into subscription: paid subscriptions included full Insights access

• Credit-based access: Free users could spend credits to unlock Insights and refreshed data

• Freemium teaser: Free tier showed just enough to create upgrade desire

Outcome:

• Became the third revenue generator (after distribution and sync)

• Drove subscription upgrades (users cited Insights as key reason for upgrading in surveys)

• Credit spending increased (Insights was popular credit spend, alongside playlist submission)

Time Investment Comparison:

Technical Architecture (I Designed and Documented)

API Integration Layer:

I drafted the technical specifications for all API integrations, including:

• Data flow diagrams: How data moves from external APIs → our database → user profile

• Fallback logic: What happens when APIs fail, and how to gracefully degrade

• Cost management: When to use free APIs vs paid APIs and how to optimise call frequency

• User flow documentation: How users experience data population and what they see when

Integration specifications I wrote

Spotify Public API (Free Tier):

GET <https://api.spotify.com/v1/search>
Parameters:
  q: "artist:[Artist Name]"
  type: "artist"
  limit: 5

Returns:
  {
    "artists": {
      "items": [
        {
          "id": "spotify_artist_id",
          "name": "Artist Name",
          "followers": {"total": 12400},
          "images": [{"url": "artwork_url", "height": 640, "width": 640}],
          "genres": ["pop", "indie"],
          "popularity": 65
        }
      ]
    }
  }

// Features:
// - Built-in spelling correction (returns closest matches)
// - Returns multiple matches if ambiguous artist name
// - No authentication required (public API)

GET <https://api.spotify.com/v1/artists/{id}/albums>
// Returns: Artist's full discography (albums, singles, compilations)

GET <https://api.spotify.com/v1/albums/{id}/tracks>
// Returns: Track listing for each album (song titles, duration, ISRC codes)

Soundcharts API (Paid Tier - On-Demand Only):

GET <https://api.soundcharts.com/api/v2/artist/{spotify_id}/streaming/total>
Parameters:
  platform: "all" // (or specific: spotify, apple, youtube, etc.)
  
Returns:
  {
    "data": {
      "spotify": {
        "followers": 12400,
        "monthly_listeners": 8500,
        "playlist_reach": 45000
      },
      "apple_music": {
        "followers": 3200
      },
      "youtube": {
        "subscribers": 15600,
        "views": 850000
      }
    }
  }

// Cost: ~$0.0005 per request (500,000 requests at $250)
// Trigger: User clicks "Insights" OR user on paid plan OR user spends credits

Technical Challenges & Solutions:

Go-to-Market Strategy

Before building, I needed to convince stakeholders that this was worth 2-4 months of engineering, design and marketing time.

Investment:

• Engineering time: 3 months (2 engineers × 50% capacity = ~480 engineering hours)

• API costs: £250/month estimated (free tiers, paid plans)

• Opportunity cost: Delayed other feature improvements (acceptable trade-off)

Expected Return:

• Engagement lift: Conservative estimate 2-3× (based on reducing friction and having songs instantly available to use in products)

• Retention lift: Conservative estimate +20% (users who engage more, stay longer)

• Conversion lift: Conservative estimate +25% (engaged users convert at higher rates)

• Strategic value: Industry-first positioning, press coverage, competitive moat

CEO and stakeholder approval ✅

Launch Strategy

Positioning:

• Name: “Instant Onboarding” (clear, benefit-driven, memorable)

• Tagline: “All your music, all your fans and all your insights. In an instant.”

Messaging framework:

• Problem: “Adding your songs to a new platform takes ages.”

• Solution: “We’ll import everything automatically.”

• Benefit: “You do the music. We do the admin.”

• Proof: “Every song. Every play. Every fan. Join thousands of artists who are instantly accessing their insights with a single click”

Launch Tactics

• Existing user migration

  • Emailed all active users, letting them know we’ve imported all their songs, streams and fans across social media

  • Incentive: Stats on artists and songs teased

  • Result: Highest engagement rate from an email ever (proving stats email drives interest)

• New user onboarding

  • Made Instant Onboarding the default signup flow

• Marketing and PR

  • Press release: Industry-First Instant Onboarding

  • Marketing site updates: Promoting the process and insights product

  • SEO marketing: Positioned new product against competitors, outreach

  • Social media campaigns: Building product and process awareness and hype

  • Result: Marketing push positioned the process and product as category-defining, drove lift in organic traffic, 3,000+ new signups and reduced CAC during the campaign.

The Impact: Quantified Results

Primary Metrics:

How “~600% engagement” was calculated:

Combining the average of users who accessed 2 and 3+ products.

(550% + 640%) / 2 = 595%

Rounded up to a clean number.

Zooming out and looking at platform-wide engagement, we can see that if evenly weighted, engagement increased by 356%; however, due to the nature of the platform, usage across products is far more indicative of product engagement than session-level activity.

Retention & Conversion:

Strategic Unlocks: New Emergent Products

Insights Product

The opportunity: By aggregating data from Spotify, Apple, YouTube, PROs, and social platforms, we had a unique cross-platform dataset that no competitor was collecting and offering to their users.

What we built:

• Cross-platform analytics: An all-in-one dashboard, total streams, airplay, playlists and audiences

• Trend analysis: Which songs are growing/declining, which platforms drive the most engagement

• Audience insights: Demographics (age, gender, location), followers, growth and outreach insights

• Competitive benchmarking: Comparing Music Gateway users with each other

• Data limits: A driver for upgrades and increasing “sticky“ product offering

Results:

• Increase in subscription and credit spend

• Became a key sales differentiator

• Retention impact: Users with Insights had a higher retention (data creates stickiness and email marketing included personal stats)

Showcase Auto-Generation & SEO Strategy

The opportunity: Instant Onboarding aggregated rich artist data (bio, discography, streaming stats, social links). We could use this to auto-generate artist showcase pages with zero user effort.

SEO strategy:

Ranking for artist names. Generated high-profile artist pages to rank for their name keywords (potential future fan-focused product).

What we built:

• Auto-generated showcase pages for logged-in users (pulled from Instant Onboarding data)

• Public showcase pages for 1000s of major artists (scraped public Spotify/YouTube data)

• SEO-optimised (artist name in title, meta description, schema markup)

• Dynamic content (latest releases, streaming stats, tour dates, etc.)

Results:

• Ranked page 1 on Google for 100s of artist names

• Constant flow of fresh content

• Repositioned showcases as “link-in-bios” and targeted a new revenue-generating stream

Competitive Moat

What happened after we launched:

• To date, no other direct competitor has replicated this process

• Over time, indirect competitors (publishers) began onboarding through Spotify APIs only

Promotional Services Conversion Lift

Strategic insight: Instant Onboarding surfaced high-quality leads for our sales team.

Sales qualification signals we tracked:

Results:

• No cost per acquisition (CPA) lowered the average CPA

• Surfaced leads that would have never existed otherwise

• Larger than average deal size for targeted users

• Improved customer satisfaction through data-led proactive actions

Reflection

Friction Removal is Better Than Feature Addition

Instant Onboarding didn’t add new capabilities; it removed barriers to existing ones.

Strategic lesson: In mature markets, removing friction often delivers more value than adding features. Users don’t want more tools; they want existing tools to work effortlessly.

Application to future roles: Look for “hidden friction” in onboarding, authentication, data entry, and account setup.

Integration as a Competitive Moat

API integration gives the product a clear advantage over competitors.

Strategic lesson: Integrations are underrated as moats. They’re technically complex, require partnerships, and create compounding value (each new integration makes the product stickier).

Application to future roles: Prioritise integrations early. API-first architecture enables future innovation (we unlocked the Insights product because we had the data infrastructure).

Data Aggregation Can Unlock New Products

Instant Onboarding was built to solve onboarding friction, but the aggregated data became the foundation for multiple new revenue drivers (including the Insights product and showcase as a link-in-bio product).

Strategic lesson: Data aggregation has compounding returns. What starts as utility (pre-fill forms) becomes a strategic asset (unique dataset → new products).

Application to future roles: Consider beyond the immediate use case when building integrations. Design data architecture for future optionality.

AI-Forward

Instant Onboarding was pre-AI, but as an exercise, this is how AI could improve products and processes further:

Business Impact

📈 Engagement Surge:

• 2 products: 10% → 65% (+550%)

• 3+ products: 5% → 37% (+640%)

• Overall engagement: ~600% increase, reflecting deeper multi-product adoption and sustained usage.

🎯 Retention & Conversion:

• Onboarding completion: 20% → 78% (+290%)

• 30-day retention: 20% → 30% (+50%)

• 90-day retention: 3% → 8% (+167%)

• Free-to-paid conversion: 3% → 4% (+33%)

💡 Strategic Unlock:

• The new Insights product drove credit usage and subscription value

• SEO strategy auto-generated artist showcase pages (often ranking on page 1)

• Competitive moat: No replication to date; only Sentric introduced a limited Spotify import, validating unmet demand

Conclusion

This wasn’t a UX design project. It was a strategic product innovation that:

• Diagnosed a critical engagement problem (90% single-product usage) through data analysis

• Identified root cause (hours of manual setup) via user research and session replays

• Designed an industry-first solution (API-driven auto-population) that no competitor had built

• Led technical integration by drafting all API schemas, flows and logic

• Executed cross-functional launch in product, engineering, marketing and sales alignment

• Drove measurable business impact (including ~600% engagement increase and +90% MAU growth)

My role: Owned problem diagnosis, solution design, technical architecture, go-to-market strategy, and outcome measurement. Drafted all API requirements, worked hands-on with engineering, aligned sales and marketing, and reported results to the CEO/stakeholders.

Impact drivers

✅ Strategic diagnosis
✅ Technical depth
✅ Cross-functional leadership
✅ Business impact
✅ Product innovation
✅ Data-driven opportunity identification
✅ Outcome-oriented execution