Growth & Strategy
Personas
Ecommerce
Time to ROI
Medium-term (3-6 months)
Last year, while working on the SEO strategy for a Shopify ecommerce site, I discovered something most marketers completely overlook: collection pages. We had over 200 of them, each getting organic traffic but only serving one purpose - displaying products.
That's when I realized we were leaving money on the table. Every visitor who wasn't ready to buy was simply bouncing. No email capture, no relationship building, nothing. But more importantly, I started noticing something interesting about how our customers were actually sharing our brand with others.
The conventional wisdom says customers share through reviews, social media posts, or word-of-mouth recommendations. While that's true, I discovered there are much more nuanced and powerful ways customers tell others about brands - ways that most businesses never tap into because they're not looking for them.
Here's what you'll learn from my experience:
The 7 hidden ways customers actually share brands (beyond the obvious ones)
How I built 200+ personalized sharing systems that customers used naturally
Why context-specific sharing beats generic "tell your friends" campaigns
The AI workflow system that scales personalized sharing across thousands of touchpoints
How to turn organic sharing behavior into sustainable growth loops
This isn't about building another referral program. It's about understanding and systematizing the natural ways people already share brands, then making those pathways 10x more effective.
Industry Reality
What most businesses think they know about sharing
Most businesses approach customer sharing with the same tired playbook: build a referral program, ask for reviews, hope people post on social media. The industry standard looks something like this:
The Traditional Customer Sharing Checklist:
Set up a "Refer a Friend" program with discounts
Send automated emails asking for reviews
Add social sharing buttons to product pages
Create shareable content and hope it goes viral
Track "word-of-mouth" through surveys and attribution
This approach exists because it's measurable and scalable. Marketing teams love systems they can track, optimize, and report on. There's nothing wrong with these tactics - they work to some degree.
But here's where this conventional wisdom falls short: it's based on how marketers want customers to share, not how customers actually want to share.
The reality is that most customer sharing happens in micro-moments, in specific contexts, through natural conversations that have nothing to do with your formal referral program. Someone browsing vintage leather bags has a completely different sharing context than someone looking at minimalist wallets.
Yet most businesses treat all customers the same - generic "share this" buttons, one-size-fits-all referral programs, and broad social media campaigns that ignore the specific moment and context where sharing actually happens.
What I discovered is that the most powerful sharing happens when you align your systems with the natural, context-specific ways people already want to tell others about what they've found.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
This insight came from working with a Shopify client who had built an impressive catalog - over 1,000 products across 200+ collection pages. Each collection was getting solid organic traffic from SEO, but the conversion rate was bleeding.
The data told a brutal story: visitors were landing on collection pages, browsing a few products, then leaving. The homepage had become irrelevant - people were entering through search, finding collections that matched their specific interests, but then... nothing.
My first instinct was to optimize the collection pages themselves - better layouts, improved filtering, faster load times. Standard e-commerce conversion tactics. But as I dug deeper into user behavior, I noticed something interesting in the analytics.
The pattern that changed everything: Users who spent time on specific collection pages were actually returning to the site multiple times, often through different collection pages. They weren't just browsing randomly - they were exploring related categories, comparing options, building a mental picture of what the brand offered.
But here's what really caught my attention: when I started talking to customers, I discovered they were actively sharing specific collections with friends and family. Not the brand as a whole, not individual products, but specific collection pages that matched what someone they knew was looking for.
Someone browsing "minimalist desk accessories" would bookmark the page and later text the link to a friend who mentioned wanting to redesign their home office. Someone exploring "travel photography gear" would share the collection in a photography Facebook group.
The sharing was happening naturally, but we weren't capturing any of that energy. Every person who discovered us through a friend was starting from scratch - no context, no relationship, no ongoing connection to the brand.
Here's my playbook
What I ended up doing and the results.
Instead of building one generic lead magnet, I decided to create something different: each of our 200+ collection pages would get its own tailored sharing system with a personalized email sequence.
The core insight: Someone browsing vintage leather bags has different interests, problems, and sharing behaviors than someone looking at minimalist wallets. So why would we give them the same generic "10% off your first order" offer?
Here's how I built the system:
Step 1: Context-Specific Lead Magnets
For each collection, I created lead magnets that matched the specific interest. For the "travel photography gear" collection, it was a "Essential Gear Checklist for 10 Most Photographed Cities." For "minimalist desk setup," it was a "Productivity Setup Guide with Space Calculations."
The key was making each lead magnet immediately valuable for that specific interest, not just a discount to buy something.
Step 2: AI-Powered Content Generation
Creating 200+ unique email sequences manually would have taken months. Instead, I built an AI workflow system that:
Analyzed each collection's products and characteristics
Generated contextually relevant lead magnets for each collection
Created personalized email sequences that spoke directly to that specific interest
Integrated everything seamlessly with Shopify's email automation
Step 3: The Natural Sharing Integration
This is where it gets interesting. Instead of asking people to "share with friends," each email sequence included specific, contextual sharing prompts:
For the travel photography sequence: "Know someone planning a trip to Japan? This gear guide might help them avoid the mistakes I made in Tokyo."
For the minimalist desk sequence: "Working with remote teammates who are struggling with home office setup? This might be exactly what they need."
Step 4: The Segmentation Magic
Each person who signed up was automatically segmented based on their specific interest. This meant future campaigns could be laser-targeted. Holiday promotions for travel gear went to people interested in travel photography. Productivity content went to the minimalist desk crowd.
But more importantly, when people shared specific collections, their friends were entering pre-segmented funnels that matched their exact interests.
Micro-Targeting
Each collection page became its own customer acquisition channel with pre-built audience segments for future campaigns.
AI Workflow
Custom automation analyzed product catalogs and generated contextually relevant lead magnets at scale without manual work.
Natural Integration
Sharing prompts matched specific user interests rather than generic "tell your friends" messaging for higher engagement.
Segmentation Engine
Automatic customer categorization based on collection interests created precise targeting for all future marketing efforts.
The results spoke for themselves, but more importantly, they revealed patterns about how customers actually share brands that completely changed my approach to growth.
Immediate Impact:
Email list growth increased dramatically, but these weren't just random subscribers - they were segmented from day one based on their actual interests. Higher engagement rates, better conversion rates, and ultimately more revenue per subscriber.
The Hidden Sharing Patterns:
Through tracking and customer feedback, I discovered seven distinct ways customers were sharing our brand:
Problem-Solution Sharing: "My friend mentioned X problem, this collection might help"
Interest-Based Sharing: "You love minimalist design, check this out"
Event-Triggered Sharing: "Saw your Instagram story about redecorating"
Group Context Sharing: Sharing in relevant Facebook groups or Reddit communities
Gift Research Sharing: "Looking for ideas for [person] who likes [specific thing]"
Expertise Sharing: "I've used these products, here's what I recommend"
Bookmark Sharing: Saving and sharing specific collections for future reference
The system worked because it aligned with these natural sharing behaviors instead of fighting against them.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
This experience taught me that customer sharing isn't about building better referral programs - it's about understanding and systematizing the natural ways people already share, then making those pathways more effective.
Key Lessons Learned:
Context is everything: Generic sharing prompts fail because they ignore the specific situation where sharing naturally happens
Segmentation beats scale: 200 targeted micro-funnels outperformed one "perfect" generic funnel
AI enables personalization at scale: You can create hundreds of unique experiences without a massive team
Sharing behavior reveals customer intent: How people share tells you more about their motivations than what they buy
Value-first sharing lasts longer: People share helpful resources more than promotional content
Organic sharing compounds: When sharing feels natural, it creates sustainable growth loops
Measurement should track behavior, not just conversions: Track sharing patterns, not just referral revenue
What I'd do differently: Start with customer interviews to understand sharing behavior before building any systems. The insights about natural sharing patterns could have come much earlier and saved months of experimentation.
This approach works best for businesses with diverse product catalogs or service offerings where customers have specific, distinct interests rather than one-size-fits-all solutions.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS implementation:
Create feature-specific onboarding sequences for different use cases
Build sharing prompts around specific user workflows and integrations
Segment users by feature usage patterns for targeted campaigns
Track sharing behavior through specific use case scenarios
For your Ecommerce store
For Ecommerce stores:
Develop collection-specific lead magnets matching customer interests
Implement automated segmentation based on browsing behavior
Create contextual sharing prompts for each product category
Build email sequences that acknowledge specific customer interests