How do you build a marketplace?
10 growth ideals with some tactical how-to's
Online marketplaces have revolutionised the economy, from how we book stays (Airbnb) to how we find rides (Uber). Yet, behind their success lies a complex interplay of supply, demand, and data-driven optimisation.This essay distills 10 marketplace growth ideals with simple tactical know how’s and actionable insights that you can start experimenting with on your own.
Spoiler alert. This is going to be a SERIOUSLY long article.
#1: Solve friction first, not liquidity
Marketplaces don’t sell goods—they sell reduced friction. Uber doesn't sell rides; it sells the ease of finding a driver. The true value of a marketplace lies in how effortlessly it connects buyers and sellers, not just in the goods or services exchanged. This is why marketplaces like Uber and Airbnb succeeded where others failed—they prioritised removing transaction friction.
Why it matters
Without addressing friction, user acquisition becomes an uphill battle. Users quickly abandon platforms with complex workflows, limited trust, or unclear pricing. On the other hand, a seamless experience ensures early adopters become advocates, accelerating word-of-mouth growth and reducing churn.
Use cases
UrbanSitter initially solved a simple but critical friction: cashless payments for babysitters. Before UrbanSitter, parents had to scramble for cash at the end of a babysitting session. By enabling credit card payments, UrbanSitter eliminated an awkward pain point, attracting users and laying the groundwork for their marketplace. Once users experienced the convenience, they were more likely to continue using the platform.
Airbnb similarly addressed friction by ensuring secure payments and offering host guarantees, making both guests and hosts feel safe transacting on the platform. This trust-building step was pivotal in its growth.
How to apply?
Identify core frictions
Conduct user interviews and surveys to uncover bottlenecks.
Analyse competitor platforms and user complaints to find common pain points.
Map the user journey to identify drop-off points.
Build a frictionless MVP
Prioritise features that reduce complexity, such as instant booking, transparent pricing, and simplified onboarding.
Ensure mobile-first design for accessibility and convenience.
Iterate based on behaviour
Use heat-maps, session recordings, and user feedback to identify areas where users struggle.
A/B test solutions to validate effectiveness.
Automate where possible
Implement automated notifications, payments, and matching algorithms.
Ensure user profiles are pre-filled where possible, reducing manual input.
Build trust
Include identity verification, user reviews, and secure payment gateways.
Highlight guarantees or insurance to reassure both sides.
#2- Start as a single-sided platform
Most marketplaces fail by trying to build both sides simultaneously. Success often starts with one side, attracting the other later. By focusing on a single side first, you create a foundation of value that naturally pulls the other side in, as the network grows.
Why it matters
Balancing supply and demand from day one stretches resources thin. Without sufficient supply, demand falls flat. Without demand, supply dries up. Building one side first ensures you deliver immediate value while creating organic pull for the other side. It also allows for more focused product development, marketing, and customer support, improving retention and satisfaction.
Use cases
Uber: Uber initially focused solely on attracting luxury black car drivers. To overcome the hesitation of joining a new platform with no riders, they offered guaranteed hourly pay, ensuring drivers earned even when they didn’t get rides. Once enough drivers were onboard, Uber could confidently market the service to riders, knowing there was a reliable supply.
OpenTable: OpenTable started by solving a clear problem for restaurants—managing reservations. They provided software that streamlined booking and reduced no-shows. With enough restaurants on the platform, they could then attract diners by promoting the convenience of finding available tables in real-time.
How to apply?
Choose your anchor side
Decide whether supply or demand faces the bigger initial friction. In most cases, onboarding the supply side is more critical because they need to see value before investing time and resources.
Example: Airbnb prioritised hosts by offering free professional photography and personalised onboarding. Once there were enough listings, guests naturally followed.
Incentivise early adopters
Provide compelling reasons for the first users to join. These can include financial incentives like subsidies, guarantees, or promotional support.
Example: DoorDash offered restaurants reduced commissions and free marketing to get them listed on the platform.
Showcase success
Use testimonials, case studies, and performance metrics from the active side to lure the other side. Early adopters become proof points that the platform delivers value.
Example: Fiverr highlighted top freelancers’ success stories, encouraging more buyers to post projects and more sellers to join the platform.
By anchoring your growth on one side, you create a flywheel effect. Once one side gains traction, the other side follows more organically, reducing the need for heavy investment in simultaneous growth.
#3- Scale liquidity before marketplace mode
Until you achieve scale liquidity—a healthy balance of buyers and sellers—you’re not operating as a true marketplace. Liquidity means that users on both sides of the marketplace can consistently find what they’re looking for with minimal friction. Without this, users churn, and the platform fails to deliver on its core value proposition.
Marketplaces only begin to thrive when supply and demand reach equilibrium. Achieving liquidity isn't about raw numbers but about ensuring the right supply meets the right demand in the right context.
Why it matters
Low liquidity results in a poor user experience. In marketplaces, users expect near-instant fulfilment—whether it’s finding a ride, booking a stay, or hiring a freelancer. If a user searches for a product or service and doesn’t find it quickly, they’re unlikely to return.
For sellers, the lack of buyers means idle inventory, wasted time, and a reluctance to stay active on the platform. This creates a negative feedback loop where both sides disengage. Liquidity is the tipping point where your marketplace shifts from being an idea to a viable business.
In practical terms:
For a ride-sharing app, liquidity means a driver arriving within 5 minutes.
For a freelance marketplace, it means receiving 3–5 qualified proposals within 24 hours.
For a property rental platform, it means finding at least 10 available listings in a city for the desired dates.
Without liquidity, users don’t just churn—they lose trust in the platform.
Use cases
Airbnb’s early success was driven not just by individual homeowners listing spare rooms but by "professional" hosts who managed multiple listings. This ensured there was always available supply, even when guest demand was inconsistent.
For example, in the early days, Airbnb partnered with property managers who had multiple units in major cities. This meant a traveler searching for a stay in New York or San Francisco could always find options, avoiding the frustration of empty search results. Without enough listings, potential guests would have left the platform, assuming it lacked inventory.
Similarly, platforms like Uber seeded their driver supply by offering guaranteed payouts, ensuring that riders wouldn’t face long wait times or unavailable rides.
How to apply?
Set liquidity benchmarks
Define clear metrics that indicate when a market or category has reached critical liquidity. These benchmarks vary by industry but should align with user expectations for fulfilment speed and availability.
Examples include:
E-commerce: 5 sellers per product category.
Real estate: 20 listings per neighborhood.
Ride-sharing: 1 driver within 5 minutes of a user’s location.
Freelance platform: 3 bids per job post within 12 hours.
Benchmarks should be dynamic, adjusting as user demand grows. For example, Airbnb shifted from focusing on “listings per city” to “available listings per search” as user volume increased.
Subsidise participation
To seed supply and demand, consider short-term incentives that reduce friction for early adopters:
Supply-side: Offer free listings, reduced commissions, or guaranteed payouts to encourage providers to join. Uber famously guaranteed earnings for new drivers, while Airbnb offered professional photographers to hosts to improve listing quality.
Demand-side: Provide discounts, rebates, or credits for first-time users. TaskRabbit, for example, ran campaigns offering discounted services to encourage users to post tasks.
The goal is to create enough activity for network effects to take hold. Incentives should taper off as liquidity improves in each market.
Expand strategically
Resist the temptation to scale too quickly. Expanding into new markets without achieving liquidity in existing ones spreads resources thin and compromises user experience.City-by-city: Uber famously launched in one city at a time, ensuring a critical mass of drivers before opening a new location.
Category-by-category: Etsy initially focused on handmade crafts rather than expanding into mass-produced goods.
Only enter new markets once you’ve hit predefined liquidity thresholds in existing ones. This ensures each new expansion builds on a strong foundation rather than stretching the platform too thin.
Checklist for expansion readiness
80% of users find what they’re looking for within the first search.
90% of transactions are fulfilled without manual intervention.
Customer satisfaction scores remain high (e.g., NPS > 50).
Liquidity is the lifeblood of any marketplace. Without it, your platform is just a collection of disconnected users. By setting clear benchmarks, incentivising early participation, and expanding only when existing markets are thriving, you can transform your platform from a hopeful experiment into a self-sustaining ecosystem.
In essence, focus on depth before breadth—saturate one market, build trust, and let network effects drive organic growth.
#4 - Use data to optimise matching
Data-driven matching reduces friction, improves user satisfaction, and drives higher engagement and retention by ensuring users quickly find the right solution.
Why it matters
Reduces friction: Users abandon platforms when they can't find what they need quickly. Poor matches frustrate both sides, leading to churn.
Boosts conversion: Intelligent matching increases the likelihood of successful transactions, whether it’s hiring, purchasing, or booking.
Enhances stickiness: Users are more likely to return to platforms where they consistently find good matches.
Use cases
Upwork employs advanced machine learning algorithms to match freelancers with job postings. These algorithms analyse factors such as job fit, past success, responsiveness, and client preferences. By prioritising freelancers most likely to be hired, Upwork significantly increased hire rates, reduced the hiring cycle, and improved overall platform satisfaction.
Other platforms like Airbnb and Amazon also leverage similar strategies, showing users listings or products based on previous searches, ratings, and preferences, ensuring a personalised experience that increases conversion.
How to apply?
Collect comprehensive data
Track user behaviour, including search queries, clicks, time spent on listings, conversions, and ratings.
Capture context, like user preferences, location, and past interactions, to enrich data profiles.
Ensure data is structured and accessible for real-time analysis.
Implement predictive models
Use historical data to build machine learning models that predict which listings, providers, or solutions will best match user needs.
Train models on key indicators such as user preferences, behaviour patterns, and successful outcomes.
Prioritise matches based on likelihood of conversion, satisfaction scores, and urgency.
Refine continuously
Implement feedback loops to improve algorithms based on real-world outcomes.
Analyse drop-off points to identify where matches fall short.
Use post-interaction ratings, reviews, and follow-up surveys to measure satisfaction.
A/B test new matching strategies and adjust models based on performance metrics.
Ensure transparent matching
Explain why a match was recommended, building user trust in the system.
Allow users to refine preferences and adjust search criteria for more personalised results.
Balance user and business goals
Optimise for user satisfaction while aligning with business objectives, like promoting high-value listings or prioritising engaged providers.
Ensure fair visibility for new listings or providers while maintaining quality standards.
Key metrics to track
Match quality: Percentage of users satisfied with their first recommendation.
Conversion rate: How often matched users complete transactions.
Time to match: How quickly users find what they need.
Retention: Whether users return to the platform after a successful match.
By leveraging data to optimise matching, platforms can create a seamless, personalised user experience, driving growth through higher engagement, satisfaction, and retention.
#5 - Balance supply and demand with dynamic pricing
Dynamic pricing helps balance marketplace liquidity by adjusting prices in real-time based on fluctuations in supply and demand.
Why it matters
Static pricing creates inefficiencies that harm both sides of a marketplace:
Shortages: When prices remain fixed during high-demand periods, available supply quickly runs out. For example, concert tickets at a fixed price sell out instantly, leaving latecomers without options and creating a secondary market with inflated prices.
Excess Supply: When demand is low but prices remain unchanged, providers face unsold inventory, empty bookings, or idle resources. Airlines, for instance, use dynamic pricing to fill seats that would otherwise fly empty.
Dynamic pricing ensures an optimal balance by adjusting prices to reflect real-time conditions, maximising revenue for suppliers while ensuring availability for consumers.
Use cases
Uber’s surge pricing: During peak hours or high-demand events, Uber increases fares to incentivise more drivers to get on the road. This ensures riders can find transportation when they need it most, while drivers benefit from higher earnings. Without surge pricing, there would be a shortage of drivers during busy periods.
Airbnb’s smart pricing: Airbnb offers hosts a Smart Pricing tool that adjusts nightly rates based on factors like demand trends, local events, seasonality, and booking lead times. This helps hosts avoid underpricing during busy times or leaving properties vacant during slow periods.
Without dynamic pricing, both platforms would struggle with imbalances—too much demand and not enough supply during peak times, or too much supply and low occupancy during off-peak periods.
How to apply
Monitor real-time metrics
Track key supply-demand indicators such as inventory availability, booking times, click-to-purchase rates, and user search volume.
Analyse historical patterns alongside live data to identify peak and off-peak trends.
Automate pricing adjustments
Implement algorithms that adjust prices dynamically based on supply-demand gaps, competitor pricing, and consumer behaviour.
Ensure algorithms account for floor and ceiling prices to prevent extreme fluctuations that could harm user trust.
Communicate clearly
Transparently explain why prices are changing, especially during peak periods.
For example, Uber shows users when surge pricing is in effect and provides an option to wait for prices to drop.
Ensure users see value in paying a premium—whether it's guaranteed availability, better service, or exclusivity.
Refine and optimise
Continuously test and refine pricing models using A/B testing to find the balance between maximising revenue and maintaining user satisfaction.
Leverage machine learning to improve accuracy and responsiveness in pricing predictions.
By implementing dynamic pricing, platforms can achieve better liquidity, improve customer satisfaction, and maximise profitability while ensuring suppliers remain engaged and responsive to market needs.
#6- Prioritise trust through rating systems
Trust is the backbone of marketplaces, and well-designed rating systems are critical for fostering user confidence, encouraging repeat usage, and driving higher transaction volumes. Effective rating systems not only provide transparency but also set clear expectations for users on both sides of the marketplace.
Why it matters
Without trust, users hesitate to transact, leading to higher drop-off rates and lower conversion. Transparent reviews and trustworthy badges reduce uncertainty, making users more likely to engage. Positive experiences, reinforced by credible ratings, encourage repeat usage and increase lifetime value.
Key impacts include:
Increased conversion: Users are more likely to transact when they see high ratings and trust signals.
User retention: Reliable ratings lead to consistent positive experiences, driving repeat usage.
Reduced platform moderation: Transparent reviews and trust systems reduce the need for dispute resolution.
Use cases
Airbnb’s Superhost badge: Airbnb introduced the Superhost badge to recognise hosts who consistently provide outstanding experiences. To qualify, hosts must maintain a high response rate, receive at least 4.8 out of 5 stars from guests, and complete a minimum number of bookings without cancellations. This badge not only incentivised hosts to improve their service but also signalled trust to potential guests. Listings with the Superhost badge saw up to a 20% increase in booking rates.
Upwork’s top rated badge: Upwork’s "Top Rated" badge highlights freelancers with strong performance, positive client feedback, and a track record of reliable delivery. According to Upwork, freelancers with this badge experienced a 30% higher hire rate, as clients perceived them as safer, high-quality choices.
Google play store’s "Editor's Choice": Apps labeled as "Editor's Choice" often see increased downloads, as users perceive them as trustworthy and high-performing based on both user and editorial reviews.
How to apply
Design effective labels
Move beyond traditional star ratings, which can be subjective and inflated. Instead, use clear, expectation-based labels. For example:Replace "5 Stars" with labels like "Exceeded Expectations," "Met Expectations," or "Needs Improvement."
Highlight key metrics, such as "On-Time Delivery" or "Responsive Communication."
Use visual cues like colour-coded badges (green for high satisfaction, yellow for mixed feedback) to simplify decision-making.
Normalise ratings
Standardise ratings based on marketplace norms to prevent inflation and provide meaningful comparisonsDynamic adjustments: If most users rate 4.5 stars on average, recalibrate so that 4.5 represents the norm, not perfection.
Contextual ratings: Consider factors like service type, price range, and user demographics when displaying ratings.
Delay early reviews: To prevent new users from being unfairly penalised by one or two reviews, delay the visibility of ratings until a threshold is met
Threshold-based visibility: Show ratings only after 3-5 transactions to ensure balanced feedback.
Private feedback: Allow users to submit private feedback in early stages, giving providers a chance to improve.
Incorporate multi-factor trust signals
Trust should go beyond ratings. Combine multiple signals for a holistic view:Verification badges: Identity or certification badges can reassure users.
Response rates: Highlight how quickly sellers, hosts, or freelancers respond to inquiries.
Repeat customers: Showcase how many users return to the same provider.
Combat review manipulation
Ensure reviews are authentic byVerified transactions: Only allow reviews from completed transactions.
AI-Powered fraud detection: Use algorithms to detect suspicious patterns.
Moderation and reporting: Let users flag fake or abusive reviews.
A well-designed rating system transforms trust from a barrier into a competitive advantage. By setting clear expectations, normalising feedback, and ensuring authenticity, marketplaces can drive higher engagement, satisfaction, and revenue.
#7 - Fight disintermediation with continuous value
Disintermediation occurs when users connect through a platform but then bypass it to transact directly, cutting off the platform’s revenue and weakening its network effects. To prevent this, platforms must provide ongoing value that incentivises users to remain engaged beyond the initial connection.
Many marketplaces struggle with this challenge, as users often find it more convenient and cost-effective to conduct future business outside the platform once trust is established. The key to combating disintermediation lies in creating an ecosystem where the benefits of staying on-platform outweigh the perceived savings of going off-platform.
Why it matters
Disintermediation not only cuts off revenue but also undermines the very network effects that drive platform growth. When users bypass the platform, it loses valuable data, trust-building mechanisms, and opportunities to upsell premium services.
Additionally, disintermediation can lead to inconsistent user experiences, eroding trust in the platform's ecosystem. Users are less likely to return if they perceive the platform as merely a middleman rather than an essential part of their workflow.
By delivering continuous value, platforms can maintain user engagement, reinforce loyalty, and sustain their competitive edge.
Use cases
Several leading platforms have tackled disintermediation by introducing features that make on-platform transactions more secure, convenient, and valuable:
Upwork: Introduced Payment Protection for freelancers and clients. This ensures that freelancers get paid for their work while clients only pay for completed milestones. Without this safeguard, both parties would face increased risk when transacting off-platform.
Airbnb: Provides Host Guarantee Insurance and Guest Insurance, offering protection against property damage and liability. This coverage incentivises users to keep booking through Airbnb rather than arranging future stays directly.
Etsy: Offers Purchase Protection and an Etsy Payments system that ensures buyers receive their goods or get refunds if issues arise. Sellers also benefit from dispute resolution and reduced chargeback risks.
LinkedIn Premium: Encourages continued engagement by offering InMail, profile insights, and learning courses that add value beyond basic networking.
These examples demonstrate how platforms can extend their role beyond matchmaking to become indispensable partners in every transaction.
How to apply
Here’s how platforms can proactively combat disintermediation:
Offer exclusive features
Provide features that users can’t access off-platform, such as:
Insurance: Airbnb’s host guarantee and Upwork’s payment protection ensure safer transactions.
Dispute Resolution: Platforms like Fiverr and Etsy mediate conflicts, ensuring fairness for both sides.
Premium Support: Exclusive customer support for on-platform users increases convenience and satisfaction.
Compliance Tools: For B2B marketplaces, offering tax compliance, invoicing, and cross-border payment solutions can lock users into the platform.
Use tiered fees
Reward long-term users with lower fees to discourage off-platform deals:
Graduated commissions: Upwork reduces its commission from 20% to 5% once a freelancer earns $10,000 from a single client.
Volume discounts: Platforms like Shopify offer lower transaction fees for higher subscription tiers.
Loyalty programs: Airbnb gives Superhosts greater visibility and exclusive perks, encouraging them to stay engaged.
Monitor behaviour
Track user behaviour to identify signs of disintermediation and address root causes:
Repeat transactions: If users repeatedly interact without corresponding transactions, they might be moving off-platform.
Inactivity after matching: If users stop using the platform post-connection, investigate why they disengaged.
Pattern recognition: Use machine learning to identify users likely to bypass the platform and intervene with tailored incentives.
Integrate workflow tools
Make the platform indispensable by integrating into users’ daily workflows:
Communication tools: Slack and Zoom integration for seamless collaboration.
Project management: Platforms like Upwork and Fiverr now offer built-in task tracking.
Payment automation: Automatic invoicing, tax calculations, and escrow services simplify transactions.
Build community and trust
Foster a sense of belonging and mutual benefit:
User ratings & reviews: Trust signals like ratings encourage users to stay within the platform.
Networking opportunities: LinkedIn Premium’s job-matching and course offerings add continuous value.
Exclusive content: Masterclass retains subscribers with regular new courses and celebrity-led content.
Measuring success
Repeat transaction rate: Measure how often users transact with the same partner on-platform.
Churn rate: Monitor user drop-off after initial connections.
Average revenue per user (ARPU): Increased ARPU indicates users find value in staying on-platform.
Net promoter score (NPS): High NPS reflects user satisfaction with platform-exclusive benefits.
Customer lifetime value (CLV): A longer CLV shows users remain engaged over time.
#8 - Experiment relentlessly, but measure what matters
Experiments are essential for innovation and growth, but they can easily lead to micro-optimisation if not aligned with core business goals. Running experiments without a clear understanding of what success looks like can create noise rather than progress. Effective experimentation requires a balance between creativity, speed, and rigorous measurement.
Many companies fall into the trap of chasing vanity metrics—improvements that look impressive but don’t translate into meaningful outcomes. True progress comes when experiments are designed to test assumptions tied to the metrics that truly matter for business success, such as user retention, revenue growth, or customer satisfaction.
Why it matters
Without focused experimentation, you risk wasting resources on changes that don’t drive real impact. It’s easy to get caught up in running endless tests—tweaking button colors, rearranging page layouts, or adjusting copy—without moving the needle on core business outcomes.
By aligning experiments with strategic objectives and measuring what truly matters, you ensure that every test, whether a success or failure, contributes to the organization’s understanding and progress. Moreover, focusing on meaningful metrics prevents the team from celebrating false positives and ensures that wins are sustainable.
Use cases
Airbnb’s introduction of the Superhost badge is a classic example of how focusing on the right metrics can reveal long-term value. Initially, the badge showed no significant impact on bookings—the primary metric the company had hoped to move. If they had solely relied on short-term booking data, they might have scrapped the initiative. However, a deeper analysis revealed a more important outcome: hosts who achieved Superhost status were significantly more likely to remain active on the platform and continue providing high-quality experiences. This improvement in host retention led to a healthier supply side of the marketplace, ultimately benefiting Airbnb’s long-term growth and customer satisfaction. It was a reminder that not all impactful results are immediately visible and that understanding second-order effects can be just as important as direct outcomes.
How to apply
Formulate clear hypotheses
Every experiment should start with a well-defined hypothesis. This means clearly stating what you believe will happen, why you believe it, and how you’ll measure success.Example: If we add a progress bar during the onboarding process, users will be more likely to complete their profile because they will better understand their progress.
Key Metric: Profile completion rate.
Prioritise learning over success
Not every experiment will lead to a win, but every experiment should lead to insight. A failed experiment can reveal flawed assumptions, helping you avoid bigger mistakes down the line.Example: When LinkedIn tested personalised connection suggestions, some experiments showed no increase in connections but revealed users were more likely to return to the platform, enhancing engagement.
Increase velocity
The faster you can run experiments, the more you can learn and iterate. This doesn’t mean cutting corners but rather designing tests that can quickly deliver meaningful insights.Example: Google’s "20% time" allowed employees to rapidly prototype ideas. Gmail and Google Maps were born from this culture of fast, iterative experimentation.
Focus on second-order effects
Sometimes, the primary metric won’t tell the whole story. Look for downstream impacts that reflect long-term success, like user retention, churn reduction, or lifetime value.Example: Spotify’s early experiments with personalised playlists like Discover Weekly didn’t just increase listening time but also improved subscriber retention over months.
Balance exploration and exploitation
Dedicate a portion of your resources to high-risk, high-reward experiments (exploration) while continuing to optimise what’s already working (exploitation).Example: Amazon consistently experiments with new shopping experiences while fine-tuning its existing product pages for conversion optimisation.
Relentless experimentation fuels progress, but only when it’s guided by a clear understanding of what truly matters. Measure impact, not activity, and treat every experiment as a step toward deeper insight and long-term growth.
#9 - Avoid early monetisation mistakes
Premature monetisation can stifle growth, deter user adoption, and encourage disintermediation. If users perceive fees as excessive relative to the value they receive, they will seek ways to bypass the platform, undermining its long-term sustainability.
Why it matters
Monetisation should grow organically alongside user behaviour, rather than imposing constraints. When platforms introduce fees before users experience significant value, it creates friction and reduces retention. By aligning monetisation with user success, platforms can sustain growth while ensuring customers remain engaged and satisfied.
Use cases
Odesk (now Upwork) initially implemented a 10% fee on transactions between freelancers and clients. This model worked well for short-term projects but fell apart when long-term relationships formed. Once users built trust and established ongoing work, they moved their engagements off-platform to avoid continued fees. This highlighted how a rigid pricing structure can inadvertently incentivise disintermediation.
How to apply
Start with value-based pricing
Instead of charging flat fees, monetise the core value you provide. This could be through match fees, subscription access to premium features, or transactional charges tied to successful outcomes.
Example: Marketplaces like Airbnb only charge a service fee once a booking is confirmed, ensuring users see value before paying.
Adapt as you scale
Once the platform achieves liquidity—when supply and demand are balanced—transition to more sustainable monetisation models.
Example: Etsy started with listing fees but introduced transaction-based commissions as sellers found success, ensuring fees scaled with value delivered.
Offer flexible plans
Introduce tiered pricing or membership options tailored to different user segments. This prevents a one-size-fits-all approach that can alienate certain users.
Example: LinkedIn offers free, premium, and recruiter-focused plans, ensuring users pay based on their specific needs and goals.
Monitor user behaviour
Regularly analyse how users interact with the platform. If users start bypassing the system, it’s a sign that pricing may be misaligned with perceived value.
Example: Fiverr introduced Fiverr Business to cater to companies that wanted ongoing freelancer relationships while keeping transactions on the platform.
Prioritise retention over extraction
Focus on keeping users engaged and successful. When users see the platform as essential to their success, they’ll be more willing to accept fees without feeling exploited.
Example: Substack enables writers to monetise newsletters while taking a small cut of subscription revenue, ensuring the platform benefits only when creators succeed.
#10- Build for long-term network effects
Marketplaces and platforms thrive when users derive increasing value as the network grows. The more participants join, the richer the experience, creating a self-reinforcing loop where both supply and demand sides benefit. Successful platforms leverage these dynamics to drive exponential growth while fortifying their competitive edge.
Why it matters
Strong network effects create defensibility by making it harder for competitors to replicate the value proposition. As more users join, the cost of switching to another platform increases, while the platform itself gains organic growth through user-driven referrals and engagement loops. Moreover, the compounding nature of network effects can lead to dominant market positions without proportional increases in acquisition costs.
Use cases
Substack began as a simple newsletter platform but transformed into a discovery engine. Initially, writers attracted their own readers, but as the platform grew, Substack introduced cross-promotion features. Now, readers get recommendations for similar newsletters, allowing writers to gain subscribers through network-driven exposure. This ecosystem creates value not just from the product itself but from the interactions within the platform.
How to apply?
Encourage user connections
Foster connections between users, providers, and content creators to strengthen engagement. Networks grow fastest when users can interact, recommend, and share.
Tactics
Implement referral programs with tiered rewards to incentivize sharing.
Create user groups or community forums where users can discuss, collaborate, or share insights.
Introduce features like “Follow,” “Connect,” or “Favorite” to keep users engaged with each other’s activity.
Example: LinkedIn's "People You May Know" feature significantly increases user connections, enhancing the platform’s value for both job seekers and recruiters.
Invest in discovery tools
Make it easier for users to find relevant content, services, or people. Effective discovery increases engagement and keeps users returning.
Tactics:
Develop recommendation algorithms based on user behavior and preferences.
Highlight trending or popular content to surface valuable listings.
Enable search filters, tags, and categories to streamline the discovery process.
Example: Airbnb’s personalized search suggestions and “Guest Favorites” listings improve booking rates by helping users find the right stay faster.
Reassess continuously
As the network scales, user needs evolve. Regularly assess which features continue to add value and which might need refinement.
Tactics:
Collect user feedback through surveys, NPS scores, and in-app prompts.
Monitor engagement metrics to identify where users drop off.
Launch beta features to test innovations before a full rollout.
Example: YouTube continuously refines its recommendation engine, ensuring users find new videos aligned with their interests as the content library expands.
By embedding these practices into your product strategy, you'll cultivate a thriving ecosystem that not only attracts users but keeps them engaged through the compounding value of network effects. Start small. Solve a real pain point. Scale liquidity. And always, always iterate based on data.
About Me:
I write to learn. More about me here. Follow @ hackrlife on X