A complete guide: Customer analytics
Overview
Customer Analytics is TagFly's customer intelligence dashboard built on top of your server-side tracking data. It transforms raw event tracking into actionable insights about who your customers are, how they engage with your store, and how much value they bring.
This feature helps you answer business questions that ad platform reports can't:
- "Which customers are about to churn — and how do I bring them back?"
- "Who are my real VIPs, and where did they come from?"
- "Why did this specific shopper bounce after viewing a product 5 times?"
- "Which segments should I export to Meta or Google Ads to find more customers like them?"
By combining store-wide trends, behavioral segmentation, and individual customer journeys in one dashboard, Customer Analytics lets you move from generic "all visitors" reporting to high-precision targeting and retention.
What you will learn
In this article, we will explore the following sections:
Filter settings
The filter bar at the top of the dashboard applies consistently across every widget, chart, and table on this page. Set these once, and the entire view re-calibrates around your selection.
Field | Definition | Business meaning |
|---|---|---|
Date range | The reporting period for all data shown | Lets you compare seasonal periods (e.g., last 30 days vs. last 90 days) and isolate campaign windows |
Timezone | Your store's configured timezone | Ensures activity timestamps reflect when actions actually happened in your business hours — critical for correlating with ad campaign schedules |
Customer filter | Either All customers or a specific saved segment | Lets you analyze the activity report through the lens of a single segment (e.g., "How active are my VIPs this month?") |
Activity report
Why this matters?
Before you can act on individual customers, you need to know whether your store's overall traffic and engagement health is improving or declining. The Activity Report gives you the macro view: are people coming back? Are they staying longer? Is your customer base actually growing?
This is where you spot trends before they show up in revenue — a sustained drop in returning users, for example, is an early warning sign of retention issues weeks before MRR reflects it.
Metrics
Metric | Chart type | Definition | Business meaning |
Total Users | Line chart | The total number of unique users who visited your store in the selected period. | Measures the size of your top-of-funnel. A flat or declining trend here means your acquisition channels are stalling — even if conversion is steady. |
Total Sessions | Line chart | The total number of visits (sessions) to your store. | Measures depth of engagement. A session is a visit; a single user can have many sessions. Watch this against Total Users to detect repeat visit patterns. |
Avg. Sessions per User | Line chart | Total Sessions ÷ Total Users for the period. | Tells you how "sticky" your store is. A rising ratio means customers are returning more frequently — a leading indicator of loyalty. A flat ratio with rising users means you're acquiring but not retaining. |
Customer segment
Why segmentation matters
Treating every customer the same is the #1 reason marketing budgets get wasted. A first-time visitor who abandoned cart yesterday needs a different message than a 5-time buyer from 6 months ago.
Customer Segment lets you build behavioral groups based on real on-site activity — then use those groups for targeting, retargeting, lookalike modeling, and lifecycle email flows. This is the bridge between "I have data" and "I have customers I can actually act on."
Segment list table
The segment list shows every segment you've created, with at-a-glance health and scale indicators.
Column | Definition | Business meaning |
|---|---|---|
Segment name | The label you assigned when creating the segment | Lets you instantly identify the behavioral group |
Size | The number of customers currently matching this segment | Shows the actual scale of the audience. A segment of 12 people isn't worth a campaign; a segment of 1,200 is. |
% of customers | The number of customers currently matching this segment | Helps you understand how common this behavior is. If 40% of customers are "cart abandoners," that's a product/checkout problem — not a retargeting problem. |
Last activity | The most recent timestamp the segment data was refreshed or its rules were modified | Confirms the segment is based on fresh data, not stale criteria from months ago |
Status | Sync status — Updated or Syncing | Tells you whether the data is current or in the middle of refreshing |
Actions (⋯) | Action menu | Lets you Edit, Duplicate, or Delete the segment |
How to Create a New Segment
Follow these steps to build a targeted customer list:
- Navigate to the Customer Analytics dashboard and click the Create Segment button.
- Segment Name: Give your segment a descriptive name (up to 150 characters).
- Match Conditions: Select how filters are applied:
- ALL: Customers must meet every condition listed.
- ANY: Customers only need to meet at least one condition.
- Define Rules: Select an attribute from the dropdown, choose an operator, and set the value.
- Click Save to generate your segment.
Understanding Segmentation Conditions
The power of a segment depends on which attributes you combine. Here's what each one unlocks:
Attribute | Definition | Business Meaning |
|---|---|---|
Events | Filters customers based on specific actions they performed (e.g., Add to cart, Purchase, Search, Checkout started). | Lets you identify intent signals before purchase. Detect customers showing high purchase intent but dropping off at specific funnel stages — the foundation of every effective retargeting campaign. |
Number of orders | Total count of completed orders per customer. | Distinguishes loyal repeat buyers from one-time shoppers. Essential for designing loyalty programs, VIP tiers, and post-purchase win-back automations. |
Total spend | The total cumulative revenue from a customer. | Identifies your highest-LTV customers — the ones who deserve premium experiences, exclusive offers, and dedicated retention investment. |
Average order value | The average amount spent per transaction. | Segments customers by spending power. High-AOV customers are upsell candidates; low-AOV customers may respond better to bundles and BOGO offers. |
Days since last order | Number of days since the customer's most recent purchase. | The single most important metric for win-back campaigns. Detects at-risk and lapsed customers before they fully churn — when re-engagement is still cheap. |
Last touch source / URL | The final source/link the user clicked before visiting. | Reveals which channels bring high-quality, high-LTV customers — not just high traffic. Use this to reallocate ad spend toward channels that convert, away from channels that just drive impressions. |
Country | The geographical location of the customer. | Powers localized marketing — region-based promotions, holiday timing, shipping cost optimization, and language-specific creative. |
Size | The number of customers matching all defined conditions in your segment. | Shows the real-world scale of the segment. Use this to prioritize: focus campaigns on segments large enough to move the business, not on micro-cohorts that won't impact revenue. |
Segment Details: Understanding Your Data
Once you've created a segment, click into it to open the Segment Detail View — a deep dive into the behavior and value of that specific group. This is where you confirm whether your targeting is working and where to double down.
Data visualization
Metric | Definition | How to use it |
|---|---|---|
Total Orders | The cumulative number of purchases made by customers in this segment. | Shows the absolute volume this segment generates. Compare against segment size to gauge purchase frequency. |
Average Order Value (AOV) | The average transaction value within this segment. | Reveals whether this group spends more or less per order than your store average. High-AOV segments are prime targets for premium product launches. |
Avg. Revenue per Customer (ARPC) | The total revenue generated by the segment, divided by the number of customers in it. | The most important number for paid acquisition. ARPC tells you what an average customer in this segment is worth — your Customer Acquisition Cost (CAC) ceiling should be a fraction of this. |
Conversion Rate Breakdown | A funnel visualization showing the transition from Visit site → Begin checkout → Purchase. | Identifies exactly where this segment drops off. If your "cart abandoners" show 80% reach checkout but only 5% complete, the issue is checkout (shipping cost, payment options) — not interest. |
Customer profile (within a segment)
Each customer in the segment appears as a row with these attributes:
- Segment name: The identity of the shopper (e.g., Address, Email, Phone number). Clicking the name allows you to view their individual customer journey from first click to final purchase.
- Number of orders: The frequency of purchase
- Average order value: How much the customer typically spends per visit. Use this to identify "Big Spenders" versus "Frequent Small Buyers."
- Last orders (Days): The number of days since their last transaction.
- Last Touch Source: The specific platform (Google, Facebook, Email, etc.) that drove the customer's most recent visit.
- Last Touch Medium: The marketing channel type (CPC, Organic, Newsletter). This tells you if they are returning via paid ads or free organic traffic.
- Last touch URL: The exact landing page the user arrived at. This helps you identify which specific products or blog posts are closing the sale.
Export your customer segments
Choose the export format based on where the data is going next:
Format | Best for |
|---|---|
CSV for Excel / Numbers / spreadsheets | Manual analytic, custom reporting, or sharing internally. Opens cleanly in Excel and Google Sheets. |
Plain CSV file | Standard text format for importing into databases, BI tools, or developer workflows. |
Format for platform compatibility | Direct upload to Facebook Ads Manager, Google Ads, TikTok Ads. Columns are pre-formatted for instant audience matching. |
Strategic Use Cases
Customer Analytics is most powerful when segments feed directly into action. Here are battle-tested playbooks:
- Build Lookalike Audiences (LAL): Export your "VIP Buyers" segment and upload it to Facebook Ads. Use it as a seed list to find new potential customers who share similar traits with your best shoppers.
- Hyper-Targeted Email Flows: Import specific segments (like "High Spend - No Purchase in 30 Days") into Klaviyo to trigger exclusive win-back discounts.
- Custom Retargeting: Use the phone numbers and emails to create "Custom Audiences" on TikTok or Pinterest to remind recent visitors about the products they viewed.
- Diagnose Conversion Problems by Segment: Open the Segment Detail View for any segment and check the Conversion Rate Breakdown funnel. If specific segments drop off at Begin checkout far more than your store average, you have a checkout problem affecting that group — likely shipping fees, payment options, or trust signals.
Customer journey
Why this matters
Aggregate data tells you what is happening across thousands of customers. The Individual Journey view tells you why a single shopper did what they did — invaluable for debugging conversion issues, understanding consideration cycles, and supporting high-value customers.
Summary Metrics
The cards at the top give you an instant snapshot of the customer's lifecycle and value:
Metric | Definition | Business meaning |
|---|---|---|
First visited | Time elapsed since the customer's very first recorded session in your store. | Tells you how long this person has been in your funnel. Useful for distinguishing fresh leads from long-considering shoppers. |
Last visited | How recently the customer interacted with your store. | A core engagement freshness indicator — recent activity means the customer is still warm. |
Total money spent | The customer's lifetime revenue (LTV). | The single most important number for prioritizing customer-by-customer outreach and retention investment. |
Profile & Attribution
Field | Definition |
|---|---|
Customer Profile | Contact info — Name, Email, Phone, Address. |
Last touch attribution | The final source/medium that drove the customer's most recent session — your most reliable indicator of which channel re-engages this person. |
Engagement on Store
This section toggles between two views: a summarized aggregation of actions and a chronological timeline.
- Events Tab (Action Summary)
Aggregates all historical actions taken by this user.
Column | Definition | Business meaning |
|---|---|---|
Events | The action type (e.g., Product viewed, Purchased, Searched). | Identifies which behaviors this customer demonstrates most. |
# of times | Total frequency of that action. | Highlights repeat behaviors — e.g., a customer who viewed the same product 12 times shows clear high intent. |
First time / Last time | Timestamps of the first and most recent occurrence. | Reveals the consideration window — a multi-month gap between first view and purchase tells you this customer needs nurture, not pressure. |
- Customer Journey Tab (Chronological Timeline)
A linear, timestamped record of every action the user took, grouped by date.
- Timestamped logs: Every event is recorded with precise time.
- Session continuity: See how a user interacts across multiple days — the length of their consideration cycle is plainly visible.
- Event filtering: Use the All events dropdown to isolate high-intent actions (e.g., show only Purchased and Checkout started).
Event Data Reference
When you expand any event in the timeline, TagFly reveals the exact metadata captured for that action — full transparency into what was tracked and when.
Event Type | Data Fields Displayed | What this tells you |
|---|---|---|
Visited site | Source/Medium, URL, Referrer | Identifies the traffic source, the landing page (with UTMs), and the referring site that sent the user. The starting point of every journey. |
Product viewed | Item, URL | The specific product the user looked at, with a direct link to the Shopify product page. |
Collection viewed | Collection title, Collection ID | Which product category the user is browsing — useful for understanding interest themes. |
Searched | Search term | The exact keywords typed into your store's search bar. Pure gold for product naming, SEO, and merchandising decisions. |
Product added to cart | Item Name - Variant, Price, Quantity | The specific variant (size/color), unit price, and quantity. Identifies preferred variants. |
Cart viewed | Total price, Total quantity, View details | Current cart value at the moment they opened it. Use View details for the full item list. |
Checkout started | Total price, Total quantity, View details | The potential order value at checkout entry — a key high-intent moment. Drop-offs here are your most expensive lost customers. |
Purchased | Shopify order ID, Total order, Total quantity, View details | The official Shopify Order ID, total revenue, and final purchased quantity. |
FAQs
Q: How far back can I see customer data?
A: Customer Analytics retains up to 90 days of activity. For longer-term analytics, export your segments regularly to your data warehouse, BI tool, or spreadsheet.
Q: How often is the data updated?
A: Activity data refreshes regularly throughout the day. Segment sizes and rules update automatically — the Last activity and Status columns in the segment list confirm freshness.
Q: Why isn't my segment data updating? I just created/edited it but the numbers haven't changed.
A: Segment calculations need time to sync after a segment is created or modified. Check the Status column in the segment list:
- Syncing — TagFly is still processing your customer data against the new rules. Wait a few moments before reviewing results.
- Updated — The data is fully refreshed and ready to analyze.
If the badge stays on Syncing for an unusually long period, refresh the page or contact support.
Q: Can I edit a segment after creating it?
A: Yes. Click the ⋯ action menu next to any segment and choose Edit. Changes recalculate the segment immediately (the Status badge will switch to Syncing during the recalculation).
Q: How many segments can I create? A: Segment limits depend on your plan:
- Basic plan — Up to 5 custom segments.
- Growth plan — Up to 10 custom segments.
In addition, every store comes with a default "All customers" segment pre-built by TagFly. This segment includes your entire customer base and serves as a baseline benchmark — use it to compare conversion rates, AOV, and ARPC against any custom segment you create. The default segment doesn't count toward your plan limit.
If you've hit your segment limit, you can delete unused segments or upgrade to Growth for more capacity.
Q: What's the difference between Last touch source and Last touch URL?
A: Source tells you the platform (e.g., Google, Facebook). URL tells you the exact landing page they arrived at. Source informs channel strategy; URL informs on-page conversion optimization.
Q: Can I use Customer Analytics if I'm on the Free plan?
A: Customer Analytics is available on Basic and Growth plans. Upgrade from your TagFly settings to unlock it.
Q: My segment shows 0 customers — what went wrong?
A: Most often this means your conditions are too restrictive (especially when using ALL match logic with many rules). Try switching to ANY, or remove conditions one at a time to find the bottleneck.
Q: How do I use exported segments in Facebook or Google Ads?
A: Choose "Format for platform compatibility" during export, then upload the file as a Custom Audience in the destination ad platform. Match rates are typically 60–80% depending on email overlap with the platform's user base.
Need Help?
If you run into any issues or want help designing a segmentation strategy for your store, reach out to the TagFly support team via the in-app chat — we're happy to walk through it with you.
Updated on: 05/05/2026
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