What Google Analytics Can’t Tell You About Profit (And How LayerFive Axis Fixes It)

Ecommerce brands don’t fail from lack of data.

They fail because their analytics don’t tell them what actually makes money.

Google Analytics 4 tracks activity—sessions, pageviews, conversions, funnel drop-offs. But profit comes from something entirely different: context, margin awareness, and attribution truth. You can have perfect traffic reports and still be losing money on every sale.

Here’s the reality: Google Analytics can tell you what happened. LayerFive Axis tells you whether it was worth it.

If you’re an ecommerce brand scaling past $5 million in revenue, this distinction isn’t academic—it’s existential. The difference between revenue reporting and profit intelligence determines whether your next funding round happens or whether you’re explaining to your board why customer acquisition costs are eating your margins alive.

The Core Problem: Google Analytics Was Never Built for Profit

Google Analytics Measures Traffic, Not Business Outcomes

Let’s be clear about what Google Analytics does exceptionally well:

• Sessions and pageviews: GA4 excels at telling you how many people visited your site and what they clicked
• Conversion events: It tracks when someone completes a purchase, signs up, or hits a goal
• Basic funnel analysis: You can see where users drop off between steps
• Engagement metrics: Bounce rates, time on site, pages per session

These are valuable metrics. For content publishers, SaaS companies with simple pricing, or early-stage startups just trying to understand if anyone cares about their product, GA4 provides tremendous value at zero cost.

But here’s what Google Analytics fundamentally cannot do for ecommerce businesses:

• Profit-based decisioning: GA doesn’t know which sales actually made you money after accounting for costs
• Margin-aware attribution: It can’t tell you which marketing channels drive profitable customers vs. discount-chasers who return everything
• CAC vs LTV reality: Customer acquisition cost and lifetime value require data GA simply doesn’t collect
• Contribution margin tracking: The actual profit per transaction after shipping, returns, payment processing, and fulfillment costs

Google Analytics cannot calculate profit because it does not connect revenue events with cost, margin, retention, or full-funnel attribution.

This isn’t a criticism of GA4—it’s an acknowledgment of what the tool was designed to do. Google built Analytics to help advertisers understand website behavior so they’d spend more on Google Ads. It’s a traffic measurement system, not a profit intelligence platform.

GA4 Optimizes for Engagement—Not Contribution Margin

The fundamental architectural difference comes down to this:

Google Analytics rewards clicks and conversions.

Ecommerce profitability runs on:

• Shipping costs that vary by geography and carrier
• Return rates that destroy margin on certain product categories
• Discount leakage where promotional codes get shared beyond intended audiences
• Repeat purchase behavior that determines whether customer acquisition was actually worth it

GA sees a conversion event and records revenue. It doesn’t see that the customer used a 40% discount code you didn’t intend for them, returned two of the three items they bought, and will never purchase again.

In GA4, that looks like success. In your P&L, it’s a loss.

LayerFive Axis sees the profit outcome—not just the conversion.

5 Things Google Analytics Can’t Tell You About Profit

1. Which Customers Are Actually Profitable

Google Analytics segments users into two basic categories:

• New users: People visiting for the first time
• Returning users: People who’ve been to your site before

But ecommerce profitability depends on understanding:

• High-return customers: Shoppers who buy frequently, return items constantly, and drain customer service resources
• Low-margin buyers: Customers who only purchase during deep discount periods
• Repeat purchase value: The difference between one-time buyers and customers with increasing basket sizes over time
• Cohort profitability: Whether customers acquired in Q4 2025 are more or less valuable than those from Q1 2026

The LayerFive Axis Fix:

Axis provides customer-level profit scoring that connects every purchase to:

• Total revenue generated
• Discounts applied
• Returns processed
• Shipping costs incurred
• Customer service interactions
• Predicted lifetime value based on behavioral cohort analysis

You can segment your customer base by actual profitability, not just by whether they’re “new” or “returning.” This fundamentally changes acquisition strategy—you stop optimizing for volume and start optimizing for profit.

When a DTC brand using Axis discovered that their TikTok-acquired customers had a 47% return rate compared to 12% from Google Shopping, they didn’t kill TikTok entirely—they adjusted creative to attract different buyer personas and changed their landing page experience to set proper expectations. Six months later, TikTok return rates dropped to 28% while maintaining acquisition volume.

That’s the difference between traffic analytics and profit intelligence.

2. Which Campaigns Drive Revenue vs Margin

Google Analytics attribution comes in two primary flavors:

• Last-click attribution: Gives all credit to the final touchpoint before conversion
• Data-driven attribution: Uses machine learning to distribute credit across the customer journey

But both models are still fundamentally incomplete for ecommerce profitability because they’re missing:

• Cost of acquisition: GA doesn’t know what you actually spent across channels
• Discount impact: It can’t track how promotional offers affect margin
• Channel overlap: The messy reality where Facebook claims credit, Google claims credit, and email claims credit for the same sale
• Quality of customer acquired: Whether that channel brings one-time bargain hunters or high-LTV repeat buyers

The LayerFive Axis Fix:

Axis delivers profit-adjusted ROAS and margin-weighted attribution by connecting:

1. Ad spend data from Meta, Google, TikTok, Pinterest, and Snapchat
2. Revenue data from Shopify, WooCommerce, or your ecommerce platform
3. Cost data including shipping, fulfillment, payment processing, and returns
4. Customer behavior data showing repeat purchase rates and lifetime value by acquisition source

This creates a complete attribution picture where marketing performance is measured by contribution margin, not just by reported ROAS.

Here’s a real example: An apparel brand saw their Google Shopping campaigns reporting a 3.8 ROAS in GA4. When they connected LayerFive Axis and factored in that Google Shopping customers had 2.3x higher return rates and primarily bought discounted items, the actual profit-adjusted ROAS was 1.4. Still profitable, but nowhere near the performance GA4 suggested.

They shifted 30% of their Google Shopping budget to branded search and organic social, improving overall profitability by 22% while maintaining the same top-line revenue.

3. What Your True CAC Is After Hidden Costs

Customer acquisition cost seems straightforward in Google Analytics: divide ad spend by conversions. But this calculation misses enormous chunks of actual acquisition cost:

GA4 CAC blind spots:

• Post-purchase support: Customer service time and tools for onboarding new buyers
• Shipping costs: Especially for brands offering “free shipping” that’s actually built into pricing
• Return shipping: Processing returns, restocking fees, and destroyed inventory
• Payment processing fees: 2.9% + $0.30 adds up quickly at scale
• Fraud prevention: Chargebacks and fraud screening tools
• Quality assurance: Additional inspection time for first orders from new customers

For many ecommerce brands, these hidden costs add 30-60% to the reported CAC from Google Analytics.

The LayerFive Axis Fix:

Axis connects marketing spend with operational cost layers to calculate real CAC by cohort. It tracks:

• Full-funnel acquisition costs from first touch to conversion
• Operational expenses associated with order fulfillment
• Customer service costs in the first 90 days
• Return rates and associated costs by acquisition channel
• Payment processing and fraud prevention expenses

When a supplement brand implemented Axis, they discovered their Facebook-acquired customers had 40% higher customer service contact rates in the first 30 days compared to email-acquired customers. This wasn’t visible in GA4 but added $14 to the effective CAC for Facebook.

By adjusting their Facebook creative to better set expectations about product benefits and shipping timelines, they reduced early-stage support contacts by 60% and improved unit economics significantly.

4. Where Attribution Breaks in a Multi-Platform World

The modern ecommerce customer journey is magnificently complex:

• Shopify reports one conversion path
• Meta Ads Manager claims credit through its pixel
• Google Ads reports conversions through its tag
• Amazon steals purchase intent without telling you
• TikTok insists its ads drove awareness
• Email shows opens and clicks that led to sales
• Affiliates claim last-click attribution
• Influencer partnerships generate promo code usage

Each platform has its own tracking methodology, attribution window, and conversion definition. None of them talk to each other. And Google Analytics, sitting in the middle, can only track what happens on your website—it has no visibility into:

• Cross-device behavior: The customer who researches on mobile but buys on desktop
• Channel interaction effects: How a Facebook ad creates awareness that leads to a Google search three days later
• Platform-native conversions: Sales that happen directly on Facebook Shops, Instagram Shopping, or TikTok Shop
• Offline touchpoints: Customers who see a digital ad but purchase in-store

The LayerFive Axis Fix:

Axis creates an identity-resolved attribution graph that unifies conversion truth across:

• All digital advertising platforms
• Ecommerce platforms
• Email and SMS marketing systems
• Offline sales data
• Customer service interactions

Through probabilistic and deterministic identity matching, Axis connects customer touchpoints across devices, platforms, and channels to create a single source of attribution truth.

A home goods brand using Axis discovered that their Meta ads weren’t directly driving conversions (as GA4 suggested), but were creating awareness that led to branded Google searches 3-7 days later. By understanding this relationship, they optimized their Meta creative for brand recall rather than direct response, reduced their Meta CPA by 35%, and saw their branded search volume increase by 67%.

That insight was completely invisible in Google Analytics because GA4 couldn’t connect Meta exposure to later branded search behavior.

5. Why Your “Top Products” Might Be Losing Money

Google Analytics happily reports your best-selling products based on transaction volume and revenue. But “best-selling” and “most profitable” are often completely different lists.

What GA reports:

• Products with highest transaction count
• Items generating most revenue
• Popular categories by pageviews

What GA ignores:

• Margin per SKU: Some products have 70% margins, others have 15%
• Return rates: That top-selling item might have a 40% return rate
• Bundling effects: Products that sell alone vs. those that increase basket size
• Customer acquisition bias: Products that attract one-time bargain hunters vs. repeat buyers
• Fulfillment complexity: Items that require special handling or slow-moving inventory

The LayerFive Axis Fix:

Axis provides a product profitability dashboard showing:

• Contribution margin by SKU after all costs
• Return rates and reasons by product
• Average order value impact when products are included
• Customer lifetime value of buyers by product category
• Margin leaks by product line

A fashion brand discovered through Axis that their “hero product”—a jacket that represented 23% of total revenue and ranked #1 in GA4—had a 52% return rate and an average contribution margin of just $8 per sale after accounting for returns, shipping, and payment processing.

Meanwhile, a $35 accessory item that ranked #47 in GA4 had a 4% return rate, 65% margin, and customers who bought it had 3.2x higher repeat purchase rates.

By shifting marketing emphasis from the hero jacket to the accessory—and redesigning the product page to better set expectations for the jacket—they improved overall profitability by 31% while growing top-line revenue by only 8%.

That strategic shift was impossible to make using Google Analytics data alone.

The Hidden Profit Blind Spot: Dashboards Without Context

Most Analytics Tools Show Data Without Meaning

Here’s the uncomfortable truth about most ecommerce analytics setups:

You’re drowning in metrics but starving for insight.

Your team looks at GA4 dashboards showing:

• Conversion rates up 12%
• Revenue up 18%
• Average order value up $6.30
• Customer acquisition costs up 22%

Everyone nods. The numbers look good. You increase ad spend.

Three months later, your CFO asks why cash flow is tightening despite revenue growth. Your margins are compressing but you can’t explain why. The analytics said everything was working.

The problem isn’t the data—it’s the absence of context.

Google Analytics gives you metrics. But ecommerce brands need:

• Decisions: Clear recommendations on where to invest and where to cut
• Forecasts: Predictive models showing what happens if you maintain current trajectory
• Profit clarity: Absolute certainty about which activities generate actual profit

The Axis Philosophy:

Context is the difference between reporting and intelligence.

Raw data tells you what happened. Context tells you why it matters and what to do about it.

When Axis shows you that your Meta ROAS dropped from 4.2 to 3.8, it also shows you:

• Which audience segments drove the decline
• Whether the drop reflects quality issues or market saturation
• How your competitor’s increased spending affected your CPMs
• What your projected CAC payback period looks like at current rates
• Which creative variations are driving profitable vs. unprofitable conversions

That’s not just reporting—it’s actionable intelligence.

Why Ecommerce Brands Outgrow Google Analytics in 2026

GA4 Is a Reporting Layer, Not a Profit Engine

The ecommerce landscape in 2026 demands more sophisticated analytics than what Google Analytics was built to provide.

Modern ecommerce leaders require:

1. Predictive insights: Not just historical reporting but forecasting based on current trends
2. Profit-based attribution: Understanding which channels drive profitable customers, not just conversions
3. Customer intelligence: Deep segmentation based on profitability, lifetime value, and behavioral cohorts
4. Margin visibility: Clear understanding of contribution margin by channel, campaign, product, and customer segment
5. Cross-platform unification: Single source of truth across all marketing and sales channels

Google Analytics stops at: “What happened?”

It tells you historical facts about website traffic and conversions. For free. Which is valuable.

LayerFive Axis answers: “What should we do next?”

It connects your marketing data, ecommerce data, customer data, and financial data to provide profit-based recommendations that drive better decisions.

The brands that will dominate ecommerce in the next five years aren’t the ones with the most data—they’re the ones who can turn data into profitable action fastest.

How LayerFive Axis Fixes Profit Analytics

LayerFive Axis Is Built for Profit-Driven Ecommerce Analytics

LayerFive Axis is not “Google Analytics with extra features.” It’s a fundamentally different approach to ecommerce intelligence, designed from the ground up for brands that need to understand profitability, not just activity.

Axis Core Capabilities:

1. Marketing Attribution + Incrementality: Multi-touch attribution that accounts for channel overlap, diminishing returns, and true incremental impact
2. Customer Data Platform Intelligence: Unified customer profiles connecting behavior across channels, devices, and platforms
3. Profit Forecasting Engine: Predictive models showing expected revenue, margin, and cash flow based on current trends
4. Ecommerce Margin Visibility: Real-time tracking of contribution margin by channel, campaign, product, and customer cohort
5. Unified Source of Truth: Single platform connecting Shopify, advertising platforms, email/SMS, customer service, and financial systems

Axis Feature Breakdown

Axis Profit Attribution Engine

Multi-touch attribution that goes beyond GA4’s data-driven models:

• Accounts for channel interaction effects
• Weights conversions by contribution margin, not just revenue
• Includes assisted conversions across multiple sessions and devices
• Factors in diminishing returns as spend scales

Contribution margin weighting:

• Attribution credit adjusted by actual profitability
• High-margin conversions weighted more heavily than low-margin
• Discount and promotional impact factored into channel performance

Channel overlap resolution:

• Deduplicates conversions claimed by multiple platforms
• Identifies true incrementality vs. credit-stealing
• Shows view-through vs. click-through impact by channel

Axis Customer Intelligence Layer

LTV prediction models:

• Machine learning forecasts of customer lifetime value
• Based on purchase frequency, recency, basket size trends, and product mix
• Segmentation by predicted high-value vs. low-value customers

Cohort-based profitability:

• Compare customer profitability by acquisition date, channel, campaign, or creative
• Track how cohorts evolve over time
• Identify which acquisition sources drive sustainable growth

Retention segmentation:

• Churn risk scoring
• Win-back campaign targeting
• Loyalty program optimization based on profitability

Axis Executive Profit Dashboard

Profit per channel:

• Contribution margin by marketing channel
• True ROAS accounting for all costs
• Blended CAC across acquisition sources

CAC payback period:

• How quickly you recover acquisition costs
• Broken down by channel and customer cohort
• Cash flow impact modeling

Forecasted revenue impact:

• What happens if you increase/decrease spend by channel
• Predicted margin impact of promotional strategies
• Scenario planning for growth investments

Axis Shopify + Ad Platform Integration

Seamless connections to:

• Shopify, WooCommerce, BigCommerce, Custom platforms
• Meta Ads, Google Ads, TikTok Ads, Pinterest Ads, Snapchat Ads
• Klaviyo, Attentive, Postscript for email/SMS
• Gorgias, Zendesk for customer service
• Amazon Seller Central, Walmart Marketplace

One profit truth layer across all platforms:

• Unified conversion tracking
• Deduplicated attribution
• Consistent margin calculations
• Single source of customer identity

Real Example: GA Says “Winning Campaign” — Axis Says “Unprofitable”

The Campaign That Looked Great… Until Profit Was Measured

Let’s look at a real scenario that plays out constantly in ecommerce:

The Setup: A skincare brand launches a new Meta campaign targeting “skincare enthusiasts aged 25-40.” After two weeks, the metrics in Google Analytics and Meta Ads Manager look fantastic:

• Meta ROAS: 4.2
• GA4 conversion rate: 3.8%
• Revenue: $87,000
• Ad spend: $21,000

Leadership celebrates. The marketing team gets congratulated. Budget is increased.

The Reality:

When the brand connects LayerFive Axis and examines the full profit picture, they discover:

• Average discount used: 35% (far higher than other channels at 18%)
• Return rate: 41% (vs. company average of 19%)
• Repeat purchase rate at 60 days: 8% (vs. company average of 34%)
• Customer service contacts per customer: 2.7 (vs. company average of 0.6)

The Axis Analysis:

After accounting for:

• Product costs (40% of retail)
• Shipping and fulfillment ($8.50 per order)
• Returns and restocking (41% of orders × $12 average cost)
• Payment processing (2.9% + $0.30 per transaction)
• Discount impact (35% vs. intended 20%)
• Increased customer service costs

The actual contribution margin per order was negative $4.20.

The campaign that looked like a 4.2 ROAS winner was actually destroying $4.20 in profit on every sale.

The Fix:

Armed with Axis intelligence, the brand:

1. Analyzed which audience segments had better metrics
2. Discovered that “skincare enthusiasts interested in natural products” had a 23% return rate and 28% repeat purchase rate
3. Redesigned creative to emphasize product ingredients and realistic expectations
4. Adjusted landing page to include more detailed FAQs and usage instructions
5. Limited discount codes to first-time buyers only

Six weeks later:

• Return rate dropped to 26%
• Repeat purchase rate increased to 31%
• Customer service contacts dropped to 1.1 per customer
• Actual profit per order: $12.30

The channel went from unprofitable to one of their best performers—but only because they had the profit visibility to diagnose and fix the problem.

This is the insight gap Google Analytics can never fill.

What to Use Google Analytics For vs LayerFive Axis

GA + Axis Together: The Modern Stack

The right answer isn’t to abandon Google Analytics entirely—it’s to understand what each platform does best and use them in combination.

Use Case	Google Analytics	LayerFive Axis
Traffic reporting	✅ Excellent	⚠️ Available but secondary
Content engagement	✅ Strong	⚠️ Basic
Funnel events	✅ Strong	✅ Enhanced with profit context
Profit tracking	❌ Not designed for this	✅ Core functionality
Margin-based attribution	❌ Impossible	✅ Primary feature
Customer lifetime value	❌ Limited	✅ Predictive models
Executive decisioning	❌ Limited utility	✅ Built specifically for this
Multi-platform unification	❌ Website-only	✅ Cross-platform identity
CAC payback period	❌ Cannot calculate	✅ Real-time tracking
Cohort profitability	❌ No cost data	✅ Complete visibility

The optimal setup:

Keep Google Analytics for website behavior analysis, content performance, and basic conversion tracking. It’s free, it’s familiar to your team, and it serves specific purposes well.

Add LayerFive Axis as your profit intelligence layer—the system that connects all your data sources, calculates true profitability, and provides executive-level insights for strategic decisions.

Many Axis customers use GA4 for daily operational checks and Axis for weekly strategy meetings, monthly forecasting, and budget allocation decisions.

Frequently Asked Questions

Can Google Analytics track profit?

No. Google Analytics 4 cannot track profit because it lacks the foundational data required for profit calculation.

Profit requires connecting:

• Revenue (which GA tracks)
• Cost of goods sold (which GA doesn’t have)
• Shipping and fulfillment costs (outside GA’s scope)
• Returns and refunds with associated costs (GA sees refunds but not their cost impact)
• Payment processing fees (GA doesn’t track)
• Customer acquisition costs across all channels (GA has incomplete data)
• Customer lifetime value (GA provides basic cohort analysis but lacks predictive capability)

GA can tell you revenue per channel. It cannot tell you profit per channel. This distinction becomes critical as you scale and margin compression becomes a growth constraint.

What is profit-based attribution?

Profit-based attribution is a marketing performance measurement methodology that assigns channel credit based on contribution margin rather than raw revenue or conversion volume.

Traditional attribution (including GA4’s data-driven model) treats all conversions equally. A $100 sale with 60% margin gets the same weight as a $100 sale with 10% margin.

Profit-based attribution recognizes that:

• High-margin products deserve more attribution credit
• Channels that attract repeat buyers are more valuable than those driving one-time purchases
• Discounted sales should be weighted less than full-price sales
• Customers with high return rates shouldn’t generate equal attribution credit to customers with low return rates

LayerFive Axis implements profit-based attribution by connecting revenue data with cost data, margin data, and behavioral data to calculate true channel performance based on economic value created—not just transactions completed.

Why do ecommerce brands need LayerFive Axis?

Ecommerce brands need LayerFive Axis because scaling profitably requires knowing which channels, customers, and products generate real profit—not just traffic or revenue.

As brands move from startup phase ($0-2M revenue) to growth phase ($2M-20M) and eventually scale phase ($20M+), the questions change:

Startup phase questions:

• Is anyone buying our product?
• Where is traffic coming from?
• What’s our conversion rate?

Google Analytics answers these perfectly.

Growth phase questions:

• Which channels drive profitable customers?
• What’s our true CAC including hidden costs?
• Which products have the best margins?
• How do we improve customer lifetime value?

Google Analytics cannot answer these. LayerFive Axis can.

Scale phase questions:

• Where should we allocate our next $1M in marketing spend?
• Which customer cohorts should we invest in retaining?
• What’s the profit impact of opening a new acquisition channel?
• How do we maintain margins while scaling revenue?

These questions are mission-critical at scale—and completely invisible in Google Analytics.

Is LayerFive Axis a replacement for GA4?

Not exactly. LayerFive Axis and Google Analytics serve different but complementary purposes.

Google Analytics is a traffic and behavior measurement tool. It excels at showing you what’s happening on your website: where visitors come from, what they do, what pages they view, where they convert.

LayerFive Axis is a profit intelligence platform. It connects your website data with advertising data, ecommerce data, customer service data, and financial data to show you which activities generate profit and which destroy it.

Think of it this way:

• GA4 = Your website’s activity monitor
• Axis = Your business’s profit GPS

Many brands use both:

• GA4 for daily operational metrics and website optimization
• Axis for strategic planning, budget allocation, and executive reporting

If you had to choose only one, the answer depends on your business stage:

• Pre-revenue or early traction → GA4 is sufficient
• $2M+ revenue with meaningful ad spend → Axis becomes essential

But most brands in growth mode keep both and use them for different purposes.

How much does LayerFive Axis cost compared to other solutions?

LayerFive Axis is positioned as an affordable alternative to enterprise platforms like TripleWhale, Northbeam, and Rockerbox—which typically cost $1,500-$3,000+ monthly.

Axis starts at a lower price point while providing comparable or superior functionality, specifically:

• Higher visitor identification rates (40-60% vs. industry standard 5-15%)
• More comprehensive platform integrations
• Profit-focused attribution vs. revenue-focused
• Better customer intelligence and LTV prediction

The ROI calculation for most Axis customers is straightforward:

If Axis helps you:

• Reduce wasted ad spend by 10% on a $50K/month budget = $5K/month saved
• Improve margin on discounting by 5% on $300K monthly revenue = $15K/month recovered
• Identify and cut one unprofitable product line losing $8K/month = $8K/month saved

Total monthly value = $28K from reducing waste alone—not counting upside from better allocation of profitable spend.

For specific pricing, contact the LayerFive team for a customized quote based on your revenue, order volume, and integration requirements.

How long does LayerFive Axis implementation take?

Most brands complete LayerFive Axis implementation in 7-14 days, depending on technical complexity and data sources.

The typical implementation process:

Week 1:

• Connect Shopify or ecommerce platform (30 minutes)
• Integrate advertising platforms (Meta, Google, TikTok, etc.) (1-2 hours)
• Configure product margin data (2-3 hours)
• Set up user permissions and dashboard preferences (30 minutes)

Week 2:

• Data validation and quality checks
• Historical data import and reconciliation
• Team training on dashboard usage
• Custom reporting setup

After implementation, Axis continuously syncs data from all connected platforms, providing real-time profit analytics with no ongoing maintenance required.

Complex implementations with custom ecommerce platforms, multiple regional stores, or extensive historical data migration may take 3-4 weeks.

What data sources does LayerFive Axis integrate with?

LayerFive Axis integrates with the complete ecommerce and marketing technology stack:

Ecommerce Platforms:

• Shopify, Shopify Plus
• WooCommerce
• BigCommerce
• Magento
• Custom platforms via API

Advertising Platforms:

• Meta (Facebook & Instagram)
• Google Ads
• TikTok Ads
• Pinterest Ads
• Snapchat Ads
• Microsoft Advertising

Email & SMS Marketing:

• Klaviyo
• Attentive
• Postscript
• Mailchimp

Customer Service:

• Gorgias
• Zendesk
• Kustomer

Marketplaces:

• Amazon Seller Central
• Walmart Marketplace

Analytics & Attribution:

• Google Analytics 4
• Segment

Other Integrations:

• Stripe, PayPal for payment data
• ShipStation, ShipBob for fulfillment
• Recharge for subscriptions

Don’t see your platform? Axis offers custom integrations for brands with specific technical requirements.

Profit Isn’t a Metric Google Analytics Was Designed to Measure

Here’s what this all comes down to:

Google Analytics tells you:

• How many visits your site received
• Which pages people clicked
• When conversions happened

LayerFive Axis tells you:

• What’s actually profitable
• What’s waste disguised as success
• What will scale without destroying margins

If you’re making million-dollar growth decisions based on traffic reports and revenue metrics alone, you’re flying blind. You’re optimizing for activity instead of outcomes. You’re confusing motion with progress.

Every scaling ecommerce brand eventually hits the wall where revenue growth stops translating to profit growth. Where your marketing “wins” are actually margin compression in disguise. Where your top products are the ones losing money.

That wall is invisible in Google Analytics. It’s blindingly obvious in LayerFive Axis.

The difference between a brand that plateaus at $10M and one that scales to $100M isn’t hustle or luck—it’s intelligence. It’s knowing, with absolute certainty, which levers to pull and which to leave alone.

Google Analytics gives you data.

LayerFive Axis gives you the profit context Google Analytics will never provide.

---

Ready to See What Google Analytics Can’t Show You?

If you’re scaling past $5M in revenue and still relying on GA4 for strategic decisions, you’re leaving seven figures of profit on the table.

LayerFive Axis shows ecommerce brands:

• Which channels actually drive profit (not just conversions)
• Where margin is leaking across your entire customer journey
• What your true CAC is after all hidden costs
• Which customers are worth acquiring and which destroy unit economics
• Where to invest your next dollar for maximum profit impact

Book a LayerFive Axis Profit Analytics Demo and see exactly where your profit is hiding.