Traffic sources
The Traffic Sources report reveals the complete story of your customer acquisition - tracking merchants from their first interaction with your App Store listing through to becoming a paid subscriber. By connecting pre-install behavior with conversion data, you can identify exactly which channels bring your most valuable customers.
Traffic source data syncs automatically with your App Store listing, giving you a complete picture of your acquisition funnel. More than just visitor analytics, Mantle helps you turn traffic insights into actionable marketing strategies across your entire business.
Understanding your sources
Shopify URL parameters
After you’ve set up analytics for your app listing, Shopify passes additional URL parameters when a merchant clicks on your app listing from the Shopify App Store. These parameters provide detailed information about how merchants found your app, including:
- The language selected by the merchant
- The type of page they came from (home, search, category, etc.)
- The specific section of the page where they found your app
- The exact position of your app within that section
These parameters give you valuable insights into your app’s visibility and discoverability in the Shopify App Store.
For a complete reference of all URL parameters and their possible values, see the official Shopify documentation on tracking listing traffic.
Campaign tracking: In addition to these automatic Shopify parameters, you can add UTM parameters to any external links pointing to your app listing (ads, social media, emails) to track your marketing campaigns in this report.
Traffic dimensions
Each dimension reveals different aspects of your acquisition:
| Source | Description |
|---|---|
| apps.shopify.com | App Store traffic |
| google.com | Search engine traffic |
| facebook.com | Social media traffic |
| yourwebsite.com | Direct site traffic |
| (direct) | Untracked visits where Google Analytics couldn’t detect a specific referrer or UTM tag |
| Source medium | Description |
|---|---|
| organic | Natural search and App Store browsing (e.g., merchants finding you in Shopify search) |
| cpc | Paid advertising clicks (e.g., Google Ads, Facebook Ads) |
| referral | Website link traffic (e.g., blog mentions, partner sites) |
| cpa | Cost-per-action campaigns (e.g., affiliate marketing links) |
| Forums | Community discussions (e.g., Reddit, Shopify Community) |
| Search terms | Description |
|---|---|
| Branded terms | e.g., “your app name” |
| Feature terms | e.g., “inventory management” |
| Problem terms | e.g., “fix out of stock issues” |
| Referrer sites | Description |
|---|---|
| Partner websites | e.g., integration partner blogs |
| Review sites | e.g., merchant review platforms |
| Content platforms | e.g., Medium articles |
| Campaign type | Description |
|---|---|
| Seasonal promotions | e.g., “black_friday_2024” |
| Feature launches | e.g., “new_feature_march” |
| Partner campaigns | e.g., “agency_referral” |
| Surface types | Description |
|---|---|
| Search results pages | App Store search results |
| Category listings | Category-based listings |
| Collection features | Featured collections |
| Surface details | Description |
|---|---|
| ”Top Inventory Apps” | Featured in top apps section |
| ”Staff picks” | Selected by Shopify staff |
| ”Trending in Marketing” | Trending apps section |
Surface inter position: The numbered section on the page where the merchant found your app (e.g., if your app appears in both section 1 and section 2 of the page, you can see which section drove more traffic)
Surface intra position: The position within a section, numbered left to right and top to bottom starting at 1 (e.g., position 1 is top left, position 4 starts the second row)
Understanding (direct) traffic
When you see (direct) as a traffic source, it means Google Analytics couldn’t detect a specific referrer or UTM tag for that visit. The system couldn’t attribute the traffic to a known source like Google, Shopify, Facebook, etc.
This usually happens when visitors:
- Type your app’s URL directly or use a bookmark
- Click a link in an email without tracking parameters
- Come from a private browsing session
- Arrive from a site that strips out referrer information
So, (direct) traffic represents untracked or organic visits where the original source couldn’t be identified.
Performance metrics
| Metric | Description |
|---|---|
| Listing view volumes | How many merchants discover your app through this source |
| Install click rates | The percentage of viewers who click to install from this source |
| Installation completion | How many merchants actually finish the installation process |
| Subscription conversion | The number of installations that turn into paying subscriptions |
| Source-specific LTV | The average lifetime value of customers from each source |
| MRR | Monthly recurring revenue metrics showing active MRR / total MRR generated from each source |
Available funnel events
The Traffic Sources report tracks customer journey events from discovery to revenue. Available events depend on your integrations:
Pre-Install Events
Require Google Analytics 4 with BigQuery integration
| Event | Description |
|---|---|
| App Listing Page View | Customer views your app’s listing page |
| Add App Button Clicked | Customer clicks “Add app” button |
Post-Install Events
Available to all customers
Installation & Setup
| Event | Description |
|---|---|
| Installed | Customer installs your app |
| Reinstalled | Customer reinstalls your app after previously uninstalling |
| Uninstalled | Customer removes your app from their store |
Trial & Conversion
| Event | Description |
|---|---|
| Trial Started | Customer begins free trial (trial apps only) |
| Trial Converted | Trial customer becomes paying subscriber |
Subscription Management
| Event | Description |
|---|---|
| Subscribed | Customer activates a paid subscription |
| Unsubscribed | Customer cancels their subscription |
| Resubscribed | Previously cancelled customer reactivates their subscription |
| Upgraded | Customer moves to a higher-tier plan |
| Downgraded | Customer moves to a lower-tier plan |
| Subscription Frozen | Customer’s subscription is temporarily paused |
| Subscription Unfrozen | Customer’s subscription is reactivated after being frozen |
Revenue Events
| Event | Description |
|---|---|
| One-time Charge | Customer makes a one-time purchase |
| First Transaction | Customer completes their first revenue-generating transaction |
| Charge Abandoned | Customer starts but doesn’t complete a billing process |
Account Management
| Event | Description |
|---|---|
| Customer Account Reactivated | Previously inactive customer becomes active again |
| Customer Account Deactivated | Active customer account becomes inactive |
💡 Pro tip: The order you select events matters for conversion rate calculations. Each step converts from the previous step, so arrange them to reflect your actual customer journey.
Event selection nuances
Adding Events
- Choose from the funnel events dropdown to add events to your chart
- Events automatically appear based on your app configuration (e.g., trial events only show for trial-enabled apps)
- This report requires Google Analytics 4 + BigQuery integration to function - without it, no traffic source data will be available
Event Order Matters
-
Use “Change event order” to reorder events in your funnel
-
Order affects conversion rate calculations (each step converts from the previous step)
-
Pre-install events automatically appear first when available
-
Recommended order for apps with trials:
Installed → Trial Started → Subscribed → Trial Converted- Why: Subscribed = subscription activated (often at install while the trial is still running). Trial Converted = trial ended and rolled into paid. Placing Subscribed after Trial Converted can yield 0 because the subscription usually happens before conversion.
Chart Display
- Events appear as columns on your chart in the order you’ve selected
- You can switch between “Count” and “Conversion rate” views
- Conversion rate shows the percentage converting from one step to the next
- You must have at least one event selected (can’t remove all events)
Traffic categories
Your acquisition channels typically fall into three groups:
App Store organic
| Type | Description |
|---|---|
| Search result placement | e.g., “inventory management” search results |
| Category browsing | e.g., found in “Inventory Management” category |
| Direct listing visits | e.g., merchants typing your app URL directly |
| Collection features | e.g., “Staff Picks” or “Trending Apps” |
External sources
| Type | Description |
|---|---|
| Direct traffic | e.g., merchants typing your website URL |
| Search engines | e.g., Google, Bing search results |
Website referrals:
| Type | Description |
|---|---|
| Blog posts | e.g., tutorials mentioning your app |
| Integration partners | e.g., complementary app websites |
| Review platforms | e.g., third-party app review sites |
| Community forums | e.g., Reddit, Facebook groups |
Campaign traffic
💡 Pro tip: All campaign traffic requires proper UTM parameter setup to be tracked accurately. Without UTM parameters, your paid campaigns may show up as generic traffic sources instead of your specific campaigns.
Marketing initiatives:
| Type | Description |
|---|---|
| Email campaigns | e.g., newsletter promotions |
| Content marketing | e.g., blog post campaigns |
| Seasonal promotions | e.g., holiday specials |
Referral programs:
| Type | Description |
|---|---|
| Partner referrals | e.g., agency recommendations |
| Customer referrals | e.g., word-of-mouth programs3 |
| Integration partnerships | e.g., app integration launches |
Paid advertising:
| Type | Description |
|---|---|
| Search ads | e.g., Google Ads campaigns |
| Social media ads | e.g., Facebook, LinkedIn campaigns |
| Display advertising | e.g., banner ad campaigns |
Making the most of traffic data
Report filters and pivots
The report offers powerful filtering and pivot capabilities:
| Option | Description |
|---|---|
| Time period | Analyze performance over custom date ranges |
| Pivots | Choose from 11 available pivot dimensions to segment your traffic data |
| Funnel events | Track from 22 available funnel events along the customer journey |
The extensive pivot options include Source, Source medium, Search term, Affiliate, Referrer site, Traffic source name, Campaign, Page/Surface type, Surface detail, Surface inter position, and Surface intra position.
The Affiliate pivot is particularly valuable for identifying which affiliate partners drive the most valuable traffic to your app, enabling you to optimize your affiliate relationships based on both conversion metrics and MRR impact.
Performance analysis
The breakdown table provides actionable insights:
- Source-specific conversion rates - see exactly how many visitors from each source become paying customers
- Full funnel progression tracking - watch how visitors from different sources move from discovery to subscription
- Visual trend identification - spot patterns with color-coded bars that make changes easy to spot
- LTV by traffic source - understand which channels bring your highest-value customers, not just the most visitors
- Revenue attribution - use the MRR column to identify which sources generate the most revenue, with both active and total MRR metrics shown as “active MRR / total MRR”
- Multi-dimensional analysis - leverage the extensive pivot options to uncover deeper insights, such as which search terms perform best with specific affiliates
- Individual customer journey details - click through to see the actual customers behind the numbers and explore their complete path
Smart analysis
Common ways teams leverage traffic data:
- Time period analysis: Establish baselines with 30-day windows and track seasonal patterns to identify growth trends
- Source impact: Track platform-specific conversion rates and monitor performance across search engines and social media
- Channel performance: Compare how different traffic types convert - from steady organic growth to campaign-driven spikes
- Search insights: Analyze search terms to understand merchant discovery patterns and identify listing optimization opportunities
- Referral quality: Identify which sites send your best-converting visitors and measure the impact of partnerships
- Revenue impact assessment: Use the MRR metrics to determine which traffic sources contribute most to your revenue
- Affiliate program optimization: Pivot by affiliate to monitor partner performance and better manage your affiliate relationships
- Campaign tracking: Compare marketing initiative effectiveness and optimize spending based on customer lifetime value
- Store presence: Track performance across different App Store sections and understand how listing position affects conversion
These insights help teams identify their most effective acquisition channels and optimize their marketing strategy for both immediate results and long-term growth.
Advanced traffic source optimization
Ready to take your traffic analysis to the next level? Our comprehensive guide on mastering your traffic sources shows you how to move beyond basic reporting to double down on what drives real growth. Learn advanced techniques for LTV analysis, affiliate optimization, and strategic budget allocation.
FAQ
Setup and Data
Why do I need BigQuery integration for this report?
This report connects your Google Analytics 4 traffic data with customer value data from Mantle. BigQuery acts as the bridge that allows us to match traffic sources with actual customer behavior and revenue. Without it, we can't connect the dots between where visitors come from and how much value they bring.
How far back does the data go?
Data availability depends on when you connected your BigQuery integration. Google Cloud/BigQuery doesn't backfill historical data, so we can only access traffic data from the date your GA4 to BigQuery connection was established.
Why might some traffic not show up in this report?
Shopify tracks app listing data through Google Analytics, but this tracking isn't always 100% accurate. Ad blockers, privacy tools, and browser settings can prevent some visitor activity from being recorded. This means you might see fewer visits in this report than actual traffic to your listing.
Understanding Data Differences
Why do my numbers in Google Analytics look different from this report?
Your numbers might look different, and that's okay. While Google Analytics shows every page view, we focus on unique views. If someone views your listing 80 times but only 50 are new visits, we'll show 50 in the Viewed listing count - giving you a clearer picture of your true reach.
Why don't my install numbers match other activity reports?
The traffic source report only shows traffic and installs that originated from your App Store listing page, not from all possible sources. Other reports (like activity reports) may show all installs regardless of where they came from. This focused approach helps you understand specifically how your App Store listing is performing as an acquisition channel.
Why do my numbers look different from the Funnel report?
The Traffic Source and Funnel reports use different data aggregation methods, which can result in different numbers for the same events.
The Traffic Source report shows all visitor activity and focuses on traffic attribution. It includes every visitor who viewed your listing, clicked buttons, or installed your app, regardless of their complete journey. This gives you a comprehensive view of how different traffic sources perform in driving awareness and initial actions.
The Funnel report focuses on installed customers and their complete lifecycle journey. It starts with customers who actually installed your app and traces their path backward and forward through all events. It uses a more complex aggregation that separates users with installations from anonymous visitors.
Think of it this way: Traffic Source helps you optimize your marketing and acquisition channels, while Funnel helps you understand customer lifecycle and conversion patterns. Both views are essential for different business decisions.
Why do I see different numbers when I look at individual events versus the funnel?
Numbers only reflect events that happened within your selected time frame and can be affected by ad or traffic blockers. For example, when viewing the App Store listing → Install funnel, you see merchants who both viewed your listing AND installed within that timeframe.
However, if you look at just the Install event alone, you might see additional installs from merchants whose listing views were blocked by privacy tools or occurred outside your date range - such as a customer who viewed your listing on June 8th (outside your selected report period) but installed on June 15th (within your date range). This makes the standalone install number appear higher than the funnel conversion.
Using the Report
How do the funnel events work in this report?
The funnel events show a cohorted customer journey. For example, if the report shows 1,000 app listing views and 200 installs, this means that 20% of the merchants who viewed your listing continued on to install your app. This true conversion tracking helps you identify exactly where merchants drop off in your acquisition funnel and which traffic sources deliver the best conversion rates through each stage.
How often does the data update?
You can control how often the data updates by going to Settings → Integrations → BigQuery and setting the polling frequency. The more frequently you poll BigQuery, the more up-to-date your data will be, but this may increase your BigQuery costs. That said, BigQuery offers a generous free plan that covers most typical usage.