Most marketplace teams can tell you exactly how many transactions happened last week, which categories are trending, and how many new sellers onboarded. Ask them which marketing channel actually delivers buyers who transact repeatedly, or what their true CAC looks like when you separate supply-side from demand-side acquisition, and you'll get spreadsheets from five different dashboards that still don't answer the question.

The metrics that separate growing marketplaces from ones burning cash on both sides of the network aren't the vanity numbers in board decks. They're the liquidity indicators, two-sided unit economics, and network density metrics that show whether your marketplace actually functions when you scale to new categories or cities.

This guide covers the acquisition, transaction, network health, and monetization metrics that mobile-first marketplace platforms track to build sustainable networks instead of subsidising empty transactions.

Why Marketplace Metrics Are Fundamentally Different

Marketplace apps face a measurement challenge that single-sided apps don't: your product only works if both sides of the network work. A new buyer is worthless if there's no inventory. A new seller is worthless if there's no demand. And your attribution must track which marketing channels build balanced, liquid networks versus which ones break your economics.

The difference between vanity metrics and actionable metrics is brutal here:

Vanity metrics hide problems:

• Total registered users (mixing buyers and sellers masks imbalance)

• Gross Merchandise Value without context (high GMV with thin margins means nothing)

• Transaction count (subsidised transactions inflate volume without profitability)

• App installs (most never list or buy anything)

Actionable metrics reveal network health:

• CAC separated by buyer vs seller acquisition

• Liquidity score by category and geography

• Time to first transaction by user type and acquisition source

• Take rate after accounting for incentives and refunds

• Repeat transaction rate by cohort

• Supply-demand balance by market segment

If you're running a mobile-first marketplace across Meta, Google, TikTok, influencer partnerships, and seller referral programmes, your users interact with multiple sides of your platform across different devices. When attribution lives in six different systems, you can't see which channels build healthy networks versus which create imbalanced supply or demand.

The Two-Sided Attribution Problem

A metric is any measurable data point. Total transactions is a metric. New listings is a metric. Search volume is a metric.

A KPI (key performance indicator) is a metric tied to a specific business goal. "Cost per active seller from Meta ads who list 5+ items and generate 3+ sales within 30 days" is a KPI. It tells you whether that channel builds valuable supply.

The best marketplace KPIs answer questions like "Which channel brings sellers who actually transact?" and "Which channel brings buyers who purchase repeatedly?" They ladder up to network liquidity and profitability, not just volume.

Marketplace attribution is uniquely complex because:

• Two-sided acquisition: You're running separate campaigns for buyers and sellers with different messaging, creative, and economics

• Network effects compound: A great seller attracts buyers; active buyers attract more sellers. Attribution must capture this flywheel, not just first touch

• Cross-side influence: Buyers discover you through seller content on social media. Sellers join because they see buyer demand. Traditional attribution models miss this

• Geographic density matters: A marketplace works in Mumbai but fails in Jaipur because density drives liquidity. You can't blend metrics across markets

Tracking KPIs across Meta, Google, TikTok, influencer campaigns, and cross-side referrals requires unified attribution. Without it, you're guessing which campaigns build networks versus which drain budgets.

Supply-Side Metrics: Building Quality Inventory

Supply-side metrics track seller acquisition, activation, inventory quality, and retention. Without healthy supply, demand-side marketing is pointless—buyers find nothing to purchase and churn.

Seller Acquisition Cost (CAC)

Seller CAC is total spend on seller acquisition divided by active sellers acquired. Active sellers have listed inventory and completed at least one successful transaction.

If you spent ₹3 lakhs on seller campaigns and acquired 150 active sellers, your seller CAC is ₹2,000. But if 300 sellers signed up and only 150 became active, your signup-to-active conversion is 50%—revealing onboarding friction.

Track both:

• Signup-level CAC: What you pay per seller registration

• Active seller CAC: What you pay for sellers who actually contribute inventory and transact

The gap between them reveals onboarding effectiveness. If Meta brings signups at ₹400 but only 30% activate while referral sellers activate at 70%, referrals are actually cheaper per active seller (₹571 vs ₹1,333).

Benchmarks by marketplace type:

• Product marketplaces (fashion, electronics): ₹800-2,500 per active seller

• Services marketplaces (home services, tutoring): ₹1,500-4,000 per active seller

• Hyperlocal delivery: ₹500-1,500 per active seller partner

Seller Activation Rate

Activation rate is the percentage of registered sellers who complete their first listing and first successful transaction within 30 days.

Track conversion at every stage:

• Signup-to-profile-completion: 60-75% target

• Profile-to-first-listing: 50-70% target

• First-listing-to-first-sale: 40-60% within 30 days

If 1,000 sellers sign up but only 600 complete profiles, 400 list items, and 200 complete sales, your overall activation rate is 20%. That means 80% of your seller CAC is wasted on users who never contribute to the marketplace.

Inventory Quality and Listing Velocity

Inventory quality determines whether buyers find what they want. Listing velocity measures how quickly sellers add new inventory.

Quality indicators:

• Listing completeness: Photos, descriptions, pricing, availability

• Response rate: How quickly sellers respond to buyer inquiries (target: <2 hours for 80%+ of messages)

• Fulfilment rate: Percentage of accepted orders that sellers actually fulfil (target: 90%+)

• Seller ratings: Average rating from buyers (target: 4.2+ out of 5)

Listing velocity:

• Time to first listing: How many days from signup to first item listed (target: <3 days)

• Listings per seller per month: Active inventory growth (benchmark: 3-10 depending on category)

• Refresh rate: How often sellers update prices, photos, or descriptions

Low-quality sellers create bad buyer experiences that tank retention. Track quality metrics by acquisition channel—if TikTok brings sellers with 2.8 average ratings while Instagram brings 4.4-rated sellers, adjust targeting even if TikTok delivers cheaper signups.

Seller Retention and Churn

Seller retention measures what percentage of sellers remain active over time. Active means continuing to list inventory and fulfil orders.

Key retention windows:

• Month 1: 70-85% for healthy marketplaces

• Month 3: 50-70%

• Month 6: 40-60%

• Month 12: 30-50%

Churn varies by:

• Transaction success: Sellers who sell 5+ items in Month 1 retain at 3-4x the rate

• Earnings: Sellers earning above a threshold (₹5,000-10,000/month) rarely churn

• Category competition: Saturated categories drive seller churn as margins compress

Track churn separately for high-value sellers (top 20% by GMV). Losing high-volume sellers destroys supply faster than onboarding new sellers fixes it.

Demand-Side Metrics: Activating Buyers Who Transact

Demand-side metrics track buyer acquisition, transaction behaviour, purchase frequency, and retention. Buyers are your revenue source, but only if they transact repeatedly.

Buyer Acquisition Cost (CAC)

Buyer CAC is total spend on buyer acquisition divided by buyers who complete at least one successful transaction.

If you spent ₹5 lakhs on buyer campaigns and acquired 2,000 transacting buyers, your buyer CAC is ₹250. But if 8,000 users installed the app and only 2,000 transacted, your install-to-transaction rate is 25%.

Track both:

• Install-level CAC: What you pay per app install

• Transacting buyer CAC: What you pay for buyers who actually purchase

The gap between them reveals conversion funnel efficiency. If Meta drives installs at ₹50 but only 15% transact while Google costs ₹120 but 50% transact, Google delivers cheaper buyers (₹333 vs ₹240 per transacting buyer).

Benchmarks by marketplace type:

• Product marketplaces: ₹200-800 per transacting buyer

• Services marketplaces: ₹400-1,200 per transacting buyer

• Hyperlocal delivery: ₹150-500 per transacting buyer

Time to First Transaction

Time to first transaction measures how many days between app install and first purchase. Shorter windows predict better retention.

Benchmarks:

• Product marketplaces: 2-7 days for healthy cohorts

• Services marketplaces: 3-10 days (higher consideration)

• Hyperlocal delivery: 1-3 days (immediate need)

Users who don't transact within expected windows churn at 70-90% rates. If your typical window is 5 days but a user hits Day 8 without purchasing, churn risk spikes dramatically.

Track time to first transaction by acquisition channel. Channels bringing users who transact faster typically deliver higher LTV because they're attracting ready-to-buy intent.

Purchase Frequency and Basket Size

Purchase frequency measures how many transactions a buyer completes per month. Basket size (average order value) measures spending per transaction.

Purchase frequency benchmarks:

• Product marketplaces: 1.5-3 transactions/month for active buyers

• Services marketplaces: 0.8-1.5 transactions/month

• Hyperlocal delivery: 4-12 transactions/month

Basket size varies by:

• Category (electronics higher than fashion accessories)

• Buyer segment (enterprise buyers have 3-10x larger baskets than consumers)

• Seller pricing strategy (competitive categories compress basket size)

Track both metrics together. A marketplace with ₹500 average basket and 2 transactions/month generates ₹1,000/buyer/month. One with ₹800 basket and 1.5 transactions/month generates ₹1,200/buyer/month. Different unit economics require different growth strategies.

Buyer Retention and Repeat Rate

Buyer retention is the percentage of buyers who make a second purchase (and third, fourth, etc.). Repeat rate is the overall percentage of transactions that come from returning buyers versus first-time buyers.

Retention benchmarks:

• Second purchase within 30 days: 40-60% for healthy marketplaces

• Third purchase within 90 days: 30-45%

• Active at 6 months: 25-40%

Repeat transaction rate: 60-80% of GMV should come from repeat buyers at scale. If first-time buyers dominate transactions, you're running an acquisition treadmill that burns cash.

Track retention by acquisition channel and first-purchase category. Buyers who first purchase in high-frequency categories (groceries, food delivery) retain better than those starting with one-off purchases (furniture, electronics).

Transaction Metrics: GMV, Take Rate, and True Revenue

Transaction metrics show whether your marketplace generates sustainable revenue, not just subsidised volume.

Gross Merchandise Value (GMV)

GMV is the total transaction value flowing through your marketplace before any fees, discounts, or refunds. If buyers spend ₹1 crore this month across all transactions, your GMV is ₹1 crore.

GMV alone is a vanity metric. What matters is:

• GMV growth rate: Month-over-month and year-over-year

• GMV per active user: Total GMV ÷ monthly active transacting users

• Category contribution: Which categories drive GMV (and which ones subsidise)

Track GMV separately for organic (repeat buyers, direct traffic) versus paid (attributed to marketing spend). If 80% of GMV comes from organic but you're spending heavily on acquisition, your marketing might not be driving sustainable growth.

Take Rate and Net Revenue

Take rate is the percentage of GMV that you keep as revenue. If your marketplace processes ₹1 crore in GMV and you charge a 15% commission, your gross revenue is ₹15 lakhs.

But true take rate accounts for:

• Discounts and promotions: First-order coupons, seasonal sales, referral credits

• Refunds and cancellations: Transactions that reverse

• Payment processing fees: 2-3% to payment gateways

• Chargebacks and fraud losses: Disputed transactions

If you charge 15% commission but give 5% in average discounts, lose 2% to refunds, and pay 2% in payment fees, your net take rate is 6%—60% lower than the headline number.

Take rate benchmarks:

• Product marketplaces: 10-20% gross, 6-12% net

• Services marketplaces: 15-25% gross, 10-18% net

• Hyperlocal delivery: 20-30% gross, 12-20% net

Track take rate by category and user segment. High-value categories (electronics, furniture) often have lower take rates due to competition, while niche categories (handmade goods, specialised services) support higher rates.

Transaction Success Rate

Transaction success rate is the percentage of initiated transactions that complete successfully without cancellation, refund, or dispute.

Track failures by stage:

• Payment failures: 5-15% of checkout attempts fail due to payment issues

• Seller cancellations: 5-10% of accepted orders cancelled by sellers (inventory issues, pricing errors)

• Buyer cancellations: 3-8% cancelled by buyers (changed mind, found alternatives)

• Fulfilment failures: 2-5% of orders fail due to delivery or quality issues

If your transaction success rate drops from 85% to 70%, you're losing 15% of GMV to operational issues. This compounds—failed transactions destroy trust, driving both buyer and seller churn.

Network Health Metrics: Liquidity and Balance

Network health metrics reveal whether your marketplace functions as a true network or just processes subsidised transactions.

Liquidity Score

Liquidity measures how quickly supply meets demand. A liquid marketplace means buyers find what they want fast, and sellers' inventory moves quickly.

Liquidity indicators:

• Search-to-transaction rate: Percentage of searches that convert to purchases (target: 8-20% depending on category)

• Time to match: Hours/days between a listing going live and first sale (target: <48 hours for hot categories)

• Inventory turnover: How quickly listings sell (target varies by category: fashion 15-30 days, food delivery <4 hours)

Low liquidity creates death spirals:

• Buyers search but find nothing → churn

• Sellers list but don't sell → stop listing → churn

• Both sides leave, network collapses

Track liquidity separately by category and geography. A marketplace might have strong liquidity in Mumbai electronics but terrible liquidity in Pune home services. Blended metrics hide where the network is broken.

Supply-Demand Balance

Supply-demand balance tracks active sellers versus active buyers in each market segment. Imbalance kills economics:

Oversupply (too many sellers):

• Sellers compete on price, margins compress

• Low sales per seller drive seller churn

• You're overpaying for seller acquisition that dilutes value

Undersupply (too many buyers):

• Buyers can't find inventory, browse without purchasing

• High buyer CAC wasted on users who can't transact

• You're paying to drive demand you can't fulfil

Balanced ratios (vary by vertical):

• Product marketplaces: 1 active seller per 10-30 active buyers

• Services marketplaces: 1 active seller per 5-15 active buyers

• Hyperlocal delivery: 1 active seller per 20-50 active buyers

Track balance by category and geography. Category expansion requires achieving minimum liquidity thresholds before scaling—if you need 50 active sellers and 500 active buyers to create liquidity, don't launch a new category with 10 sellers.

Cross-Side Engagement

Cross-side engagement measures how buyers and sellers interact beyond transactions: messages, favourites, follows, reviews.

Key metrics:

• Message response rate: How quickly sellers respond to buyer inquiries (target: 80%+ within 2 hours)

• Seller follow rate: Percentage of buyers who follow sellers for updates (indicates brand loyalty forming)

• Review completion rate: Percentage of transactions that generate reviews (target: 40-60%)

• Repeat seller-buyer pairs: Transactions where the same buyer returns to the same seller

High cross-side engagement predicts network stickiness. Buyers who message 3+ sellers before purchasing convert at 2-3x the rate. Sellers who respond within 30 minutes close 40-60% more sales.

Unit Economics: CAC, LTV, and Contribution Margin

Unit economics determine whether your marketplace is a business or a subsidy engine burning investor cash.

Customer Lifetime Value (LTV) for Both Sides

Buyer LTV is the total net revenue a buyer generates before churning. Formula: (average basket size × purchase frequency × customer lifespan × take rate) - (acquisition cost + support cost).

If a buyer spends ₹1,000 per order, transacts 2x/month for 18 months (36 transactions), and you capture 12% net take rate, they generate ₹4,320 in revenue. If buyer CAC is ₹300 and support costs ₹200 over their lifetime, buyer LTV is ₹3,820.

Seller LTV is trickier because sellers generate GMV that attracts buyers (network effects), but you only capture revenue via take rate. Formula: (GMV generated × seller lifespan × take rate) - (acquisition cost + support cost).

If a seller generates ₹50,000/month in GMV for 24 months (₹12 lakhs total), and you capture 12% net take rate, they contribute ₹1.44 lakhs in revenue. If seller CAC is ₹2,000 and support costs ₹5,000 over lifetime, seller LTV is ₹1.37 lakhs.

But sellers also create buyer retention and attraction—this network effect is hard to quantify but massively increases seller value. A single high-quality seller might attract 50+ buyers who each generate ₹3,000+ in LTV.

The CAC:LTV Ratio for Marketplaces

Track CAC:LTV separately for both sides:

• Buyer CAC:LTV: Target 1:3 to 1:5

• Seller CAC:LTV: Target 1:4 to 1:8 (higher because seller LTV is harder to measure and network effects amplify value)

If buyer CAC is ₹300 and buyer LTV is ₹3,800, you have a 1:12.6 ratio—extremely healthy. If seller CAC is ₹2,000 and direct seller LTV is ₹1.37 lakhs, you have 1:68—but this doesn't account for the buyers that seller attracts.

Critical nuance: Marketplaces can afford higher CAC on one side if the other side is strong. Uber prioritised driver acquisition even at high CAC because drivers attracted riders. Etsy could spend heavily on seller acquisition because quality sellers drive organic buyer growth.

Contribution Margin Per Transaction

Contribution margin is net revenue per transaction minus variable costs:

• Commission captured: Your take rate

• Payment processing fees: 2-3% to gateways

• Fulfilment costs: Delivery, packaging (if you provide)

• Customer support costs: Disputes, refunds

• Fraud and chargebacks: 1-3% of GMV typically

If average transaction is ₹1,000 with 15% commission (₹150), you pay ₹25 in payment fees, ₹30 in delivery support, and lose ₹15 to refunds/fraud. Contribution margin is ₹80, or 8% of GMV.

Track contribution margin by category and user cohort. High-frequency categories (groceries, food delivery) may have thin margins (4-8%) but high volume. Low-frequency categories (furniture, electronics) may have fat margins (15-25%) but require higher marketing spend to drive transactions.

If contribution margin is negative, you lose money on every transaction. Scaling makes losses worse, not better.

Category and Geographic Expansion Metrics

Expansion metrics show whether you can replicate your core marketplace success in new categories or cities.

Category Penetration and Liquidity

When launching new categories, track:

• Minimum viable liquidity: Seller and buyer thresholds needed for the category to function (typically 30-100 sellers, 300-1,000 buyers depending on niche)

• Time to liquidity: Days from category launch to achieving target search-to-transaction rates

• Cross-category adoption: Percentage of users who transact in 2+ categories (indicates platform stickiness)

If you launch "Home Services" but only achieve 5% of the search-to-transaction rate you see in your core "Electronics" category, the category isn't liquid yet. Continuing to market it wastes budget.

Geographic Density and Network Effects

Geographic expansion requires achieving density thresholds:

• Tier 1 cities (Mumbai, Delhi, Bangalore): Need 5,000-20,000 active users for liquidity depending on category

• Tier 2 cities (Pune, Jaipur, Ahmedabad): Need 2,000-8,000 active users

• Tier 3+ cities: Need 500-2,000 active users

Don't expand geographically until you've saturated core markets. If you have 50,000 users spread across 200 cities, you don't have network effects—you have 200 thin networks where most users can't transact.

Track CAC and LTV by geography. Tier 2 cities may have 40% lower CAC but also 30% lower basket size and 25% lower purchase frequency. Blended metrics hide whether expansion is profitable.

Attribution Challenges for Two-Sided Networks

Attribution connects marketing spend to outcomes on both sides of your marketplace. Without unified tracking, you can't see which channels build balanced networks.

Separating Supply and Demand Attribution

Run separate campaigns with separate tracking for sellers versus buyers:

• Seller campaigns: Different creative, messaging, landing pages, conversion events

• Buyer campaigns: Different targeting, value props, onboarding flows

Tag every campaign with side-specific parameters. If you blend seller and buyer attribution, you can't calculate true CAC for each side or optimise spend allocation.

Use deep links to send sellers to seller onboarding flows and buyers to browse/search experiences. Generic homepage links dilute conversion.

Return on Ad Spend (ROAS) by Side

Buyer ROAS: Revenue generated from buyers acquired via a specific channel divided by spend on that channel.

Seller ROAS: Revenue generated from GMV attributed to sellers acquired via a specific channel (harder to calculate because seller impact is delayed and indirect).

Track both separately. A channel delivering 6x buyer ROAS and 2x seller ROAS might justify pausing seller spend there and reallocating to channels with better seller performance.

For marketplaces, ROAS must account for:

• Delayed contribution: Sellers might take 30-60 days to ramp GMV

• Network effects: Sellers attract buyers organically (channel-agnostic impact)

• Lifetime contribution: One-time CAC generates multi-year revenue

Mobile measurement partners like Linkrunner unify attribution across Meta, Google, TikTok, influencer campaigns, and cross-side referrals. You see which channels drive balanced networks, not just installs, and optimise spend across both sides without reconciling five different dashboards.

Building Your Marketplace Analytics Stack

Most marketplace teams have fragmented data: Firebase for app events, backend databases for transactions, payment processors for revenue, separate tools for seller and buyer funnels. Hours wasted reconciling data that doesn't match.

A unified stack connects:

1. Two-sided attribution: Track seller and buyer acquisition separately by source

2. Transaction analytics: GMV, take rate, basket size, frequency by cohort

3. Network health: Liquidity scores, supply-demand balance, category density

4. Engagement tracking: Search behaviour, messaging, reviews, cross-side interactions

5. Revenue attribution: Connect transactions back to original acquisition source for both buyers and sellers

Linkrunner unifies attribution, deep linking, and engagement analytics so you see CAC, LTV, ROAS, and network health by channel in one dashboard. No more reconciling screenshots from Meta, Google, payment systems, and backend databases. Our platform auto-surfaces campaigns that create imbalanced networks (too much supply, too little demand) and suggests where to reallocate budget for better liquidity.

Request a demo to see how marketplace apps track what matters and scale both sides profitably.

Track What Matters and Build Network Effects That Last

Tracking the right metrics—separated CAC for buyers and sellers, liquidity scores by market, take rate after incentives, repeat transaction rates, contribution margin—lets you build sustainable marketplaces instead of subsidised transaction volumes. Marketplace platforms need unified attribution to see network health across both sides.

Linkrunner connects attribution data across acquisition channels, transaction events, and network behaviour so you can see which campaigns build balanced, liquid networks versus which drain budgets on one-sided growth.

FAQs About Marketplace App Metrics

What are the most important metrics for marketplace apps?

Separated CAC for buyers and sellers, liquidity score by category and geography, take rate after discounts and fees, repeat transaction rate, supply-demand balance, and contribution margin per transaction. Each ties directly to network health and helps you decide where to spend on each side.

How do I track attribution when I'm acquiring both buyers and sellers?

Run separate campaigns with distinct tracking parameters for each side. Use deep links to send sellers to seller onboarding and buyers to browse/search flows. Mobile measurement partners unify attribution so you can calculate true CAC and ROAS for each side without blending metrics.

What is a healthy buyer-to-seller ratio?

Varies by marketplace type. Product marketplaces typically need 10-30 active buyers per active seller. Services marketplaces need 5-15 buyers per seller. Hyperlocal delivery needs 20-50 buyers per seller. Track this by category and geography—ratios that work in electronics might not work in home services.

How often should marketplace apps review their metrics?

Review CAC, transaction success rate, and liquidity scores daily or weekly to catch network health issues early. Review take rate, contribution margin, and supply-demand balance weekly. Review LTV, retention cohorts, and category expansion performance monthly to assess long-term network effects.

Why do some marketing channels bring sellers who don't transact?

Channels optimised for volume (broad targeting, viral campaigns) bring curious users who sign up but don't commit inventory or fulfil orders. Channels optimised for intent (search ads, referral programmes, niche influencers) bring sellers who actually list and transact. Track activation rate by channel to identify quality sources and adjust targeting to attract committed sellers, not tire-kickers.