Running a freemium SaaS business means you're attracting thousands of signups. Your traffic looks healthy. Conversion rate to free users hits 4%. You've built a funnel that looks productive on paper.
Then you look at revenue. Of those 1,000 new free users this month, only 18 actually upgraded to paid plans. And six of those upgraded because your sales team called them — not because your marketing channels identified them as qualified.
Here's the uncomfortable truth: most freemium marketing campaigns optimize for volume, not value. You're measuring keyword performance by signups, clicks, or even Cost Per Lead (CPL). But the keywords that flood your funnel with tire kickers are different from the keywords that bring in users who'll actually pay.
This guide shows you exactly how to track which keywords drive users who convert to paid customers — and how to cut the ones that waste your budget on curiosity-driven traffic.
Why Most Freemium Attribution Tracking Fails
The average freemium-to-paid conversion rate sits between 2–5%. If you're running paid search, organic content, or display campaigns, you're probably attracting ten to twenty times more signups than paying customers.
Traditional analytics tools like Google Analytics track top-of-funnel events: clicks, pageviews, form submissions, free signups. These metrics look impressive in monthly reports, but they don't answer the question that actually matters: which keywords drive users who upgrade to paid plans?
Here's where most tracking setups break:
1. Conversion Events Are Defined Too Early
Most marketers define a "conversion" as a free signup. Google Ads reports show 150 conversions. The dashboard looks green. But when you check Stripe or your billing system, only 8 of those free users upgraded to paid.
Your attribution data is fundamentally disconnected from revenue. You're optimizing for the wrong goal.
2. Last-Click Attribution Hides the Real Journey
A user discovers your tool through a blog post targeting "how to automate email workflows." Three weeks later, they Google "competitor name alternative" and click a paid ad. Then they upgrade.
Last-click attribution gives 100% credit to the paid ad. The original keyword that brought them in — the one that actually introduced them to your product — gets zero credit. You scale the wrong channels and starve the ones that work.
3. Product Usage Data Isn't Connected to Marketing
You know which users hit usage limits, activated key features, or invited teammates. But your analytics can't tell you which keyword or campaign brought in those high-intent users versus the students, competitors, and hobbyists who signed up and vanished.
Without connecting in-product behavior back to acquisition sources, you're flying blind.
What "Qualified" Means in Freemium SaaS
Before you can track which keywords drive qualified users, you need to define what "qualified" actually means in your business.
Qualified users in freemium SaaS share three characteristics:
They match your Ideal Customer Profile (ICP): Company size, industry, role, and budget align with your target buyer.
They engage with core product features: They don't just sign up — they activate, use key workflows, hit usage gates, or invite teammates.
They convert to paid: They upgrade to a paid plan within a reasonable timeframe (30, 60, or 90 days depending on your sales cycle).
A keyword that drives 500 signups with a 0.5% conversion rate is worse than a keyword that drives 50 signups with a 6% conversion rate. Volume is a vanity metric. Conversion to revenue is what matters.
Tire Kickers vs. Qualified Leads: Keyword Intent Signals
Not all keywords signal the same intent. Understanding the difference helps you filter out low-quality traffic before it wastes budget.
Tire Kicker Keywords (Low Intent):
Educational and informational queries: "what is CRM," "how to build a landing page"
Free-focused terms: "free email marketing tool," "best free alternative to competitor"
Generic high-volume terms: "productivity app," "project management"
These keywords attract users who are exploring, learning, or looking for permanent free solutions. They sign up, poke around, and leave. Conversion rates to paid hover below 1%.
Qualified Lead Keywords (High Intent):
Solution-specific queries: "CRM for real estate agencies," "email automation for e-commerce"
Comparison and alternative searches: "competitor vs your tool," "best competitor alternative"
Integration-focused queries: "your category with Salesforce integration"
Pricing and purchase intent: "tool name pricing," "buy software category"
These keywords attract users who know what they need, have a specific problem, and are evaluating solutions. They're ready to pay if your product solves their problem.
How to Track Keywords That Drive Paying Customers (Step-by-Step)
Tracking freemium keyword performance to revenue requires connecting four data sources: your ad platforms, website analytics, product usage data, and billing system. Here's how to build that connection.
Step 1: Define Revenue Conversion Events (Not Just Free Signups)
Stop treating free signups as your primary conversion goal. Define events that correlate with paying customers:
Paid plan upgrade: The moment a user enters payment details and converts to a paid subscription.
Product Qualified Lead (PQL) signals: Users who hit usage limits, activate premium features, or invite teammates.
Sales-qualified actions: Requests for demos, sales calls, or enterprise pricing.
Set up these events as conversion goals in Google Analytics 4 (GA4), your CRM, and your attribution platform. Now your reporting can show which keywords drive paying customers, not just free signups.
Step 2: Implement UTM Tagging and Tracking Parameters
Every marketing channel — paid search, organic, social, email — should pass standardized UTM parameters that identify the source, campaign, keyword, and ad creative.
For Google Ads, enable auto-tagging to capture the Google Click ID (GCLID). This unique identifier ties a user's entire journey back to the exact keyword and ad they clicked.
For organic search, connect Google Search Console to GA4 to capture which queries drive traffic and conversions.
For all other channels, use consistent UTM structures:
utm_source: google, bing, linkedinutm_medium: cpc, organic, emailutm_campaign: your campaign nameutm_term: keyword (for paid search)utm_content: ad variant or creative ID
Store these parameters in your CRM when a user signs up so you can track them through the entire lifecycle.
Step 3: Connect Product Usage to Acquisition Source
Your product analytics tool (Mixpanel, Amplitude, or similar) tracks in-app behavior: feature adoption, session frequency, and engagement milestones. But most product teams don't connect this data back to the keyword or campaign that brought the user in.
Pass UTM parameters and GCLID into your product analytics system when a user signs up. Now you can segment users by acquisition source and see which keywords drive users who:
Activate core features within 7 days
Hit freemium usage limits (a strong signal of upgrade intent)
Invite teammates or collaborate
Return weekly for 30+ days
This is where you identify the difference between tire kickers and power users. A keyword might drive 200 signups, but if only 3% of those users activate a core feature, it's not a qualified keyword.
Step 4: Link Paid Upgrades Back to Original Keywords
The final step is connecting paid conversions back to the keyword that first brought the user in. This requires passing acquisition data from your CRM or product analytics tool into your billing system (Stripe, Chargebee, Recurly).
When a user upgrades, your billing system should trigger a conversion event that includes:
User ID
Original UTM parameters (source, medium, campaign, keyword)
GCLID (for Google Ads offline conversion tracking)
Subscription plan and MRR
Now you can report on revenue per keyword, not just clicks or signups. This is how you identify which keywords drive high-LTV customers versus which ones flood your funnel with free users who never pay.
Step 5: Send Offline Conversions Back to Ad Platforms
Google Ads and other platforms optimize campaigns based on the conversion data you send them. If you only send "free signup" conversions, Google will optimize for volume — not revenue.
Use offline conversion tracking to send paid upgrade events back to Google Ads using the GCLID. Now Google knows which keywords drive paying customers, and its algorithm will prioritize those keywords in bidding and targeting.
This closes the loop. Your ad platform optimizes for the conversions that matter, not the ones that look good on a dashboard.
The Attribution Model That Works for Freemium SaaS
Choosing the right attribution model determines how you assign credit to marketing touchpoints. For freemium SaaS, where users interact with multiple channels over weeks or months before converting, single-touch models fail.
Why Last-Click Attribution Fails in Freemium
Last-click attribution gives 100% credit to the final touchpoint before conversion. In freemium SaaS, this is almost always a retargeting ad, a direct visit, or a branded search query.
But the keyword that originally introduced the user — the blog post, webinar, or comparison page — gets zero credit. You end up under-investing in top-of-funnel channels and over-investing in bottom-of-funnel retargeting.
Why First-Click Attribution Also Fails
First-click attribution gives all credit to the initial touchpoint. This works if your sales cycle is short and users convert immediately. But in freemium SaaS, users explore for weeks. The first touchpoint might be educational content that attracts tire kickers, while the final touchpoint (a demo request or pricing page) signals actual intent.
Use Multi-Touch Attribution for Freemium
Multi-touch attribution assigns credit across the entire customer journey, acknowledging that conversions result from multiple interactions.
For freemium SaaS, three models work well:
Linear Attribution: Distributes credit equally across all touchpoints. Use this if you want to value awareness, consideration, and conversion stages equally.
Time-Decay Attribution: Gives more credit to touchpoints closer to conversion. This works well if your free-to-paid conversion cycle is short (under 30 days).
Position-Based (U-Shaped) Attribution: Assigns 40% credit to the first touchpoint, 40% to the conversion touchpoint, and 20% distributed among middle touches. This balances awareness and conversion while acknowledging the nurture journey in between.
Choose a model that reflects how your customers actually convert, then apply it consistently across all channels.
Key Metrics to Track for Keyword Performance
Once your tracking infrastructure is in place, focus on these metrics to identify which keywords drive paying customers:
Free-to-Paid Conversion Rate by Keyword
Calculate the percentage of free signups from each keyword that convert to paid plans within 30, 60, or 90 days.
Formula: (Paid conversions from keyword / Free signups from keyword) × 100
A keyword with a 3% free-to-paid conversion rate is more valuable than a keyword with a 1% rate, even if the second keyword drives more volume.
Cost Per Paying Customer (CPPC)
Calculate how much you spend to acquire one paying customer from each keyword.
Formula: Total ad spend on keyword / Number of paid conversions
This is more meaningful than Cost Per Lead (CPL). A keyword with a $120 CPPC and a $50/month average revenue per user (ARPU) might look expensive, but if those customers stick around for 18 months, the lifetime value (LTV) justifies the cost.
Product Activation Rate by Keyword
Track what percentage of signups from each keyword activate core product features within the first 7 days.
Users who activate are 3–5× more likely to convert to paid. A keyword that drives high activation rates signals better user intent than a keyword that drives signups with low engagement.
Lifetime Value (LTV) by Keyword
Not all paying customers are equal. Some churn in 3 months. Others stay for years. Calculate the average LTV of customers acquired from each keyword.
Formula: Average monthly revenue per user × Average customer lifetime (in months)
A keyword that drives users with a $1,200 LTV is worth more than a keyword that drives users with a $300 LTV — even if the second keyword has a lower CPPC.
Platforms like Spectacle track LTV by acquisition source automatically, making it easy to see which campaigns, keywords, and ads drive the highest-value customers.
How to Optimize Campaigns for Paying Users (Not Just Signups)
Once you've identified which keywords drive paying customers, shift your campaigns to scale what works and cut what doesn't.
1. Reallocate Budget to High-Converting Keywords
Increase bids and budgets on keywords with high free-to-paid conversion rates and strong LTV. Even if these keywords have lower search volume, they're more profitable than high-volume, low-intent terms.
2. Add Negative Keywords to Filter Tire Kickers
For paid search campaigns, ruthlessly add negative keywords to exclude low-intent traffic:
-free-cheap-jobs-training-tutorial-what is-how to(depending on context)
These terms attract users who aren't ready to buy. Removing them can cut wasted spend by 20–40% without hurting qualified lead volume.
3. Optimize Landing Pages for High-Intent Keywords
Users arriving from high-intent keywords (pricing, alternatives, integrations) should land on pages that match their intent. Don't send them to a generic homepage or educational blog post.
Create dedicated landing pages for:
Pricing and plan comparison
Competitor alternatives
Integration-specific use cases
Industry-specific solutions
Match the landing page to the search intent, and conversion rates will increase by 30–50%.
4. Use Lookalike and Similar Audiences Based on Paying Customers
Most SaaS marketers build lookalike audiences based on free signups. This scales the wrong behavior.
Instead, create lookalike audiences based on users who:
Converted to paid plans within 60 days
Have high product engagement scores
Match your ICP profile
Platforms like Google Ads allow you to upload customer lists and build Similar Audiences that mirror your best customers, not your tire kickers.
5. Test Long-Tail, Niche Keywords with High Intent
Long-tail keywords have lower search volume but higher intent. Instead of targeting "CRM software" (high volume, low intent), target "CRM for real estate teams under 20 people" (low volume, high intent).
These keywords attract users who know exactly what they need and are ready to evaluate solutions. Conversion rates are often 3–5× higher than broad, generic terms.
Common Mistakes That Hide Your Best Keywords
Even with tracking in place, most freemium SaaS teams make these mistakes that obscure which keywords actually drive revenue:
Mistake 1: Treating All Free Signups as Equal Conversions
You celebrate 500 new signups this month. But 450 of them came from a single blog post targeting "free project management tool." Only 2 upgraded to paid.
Not all signups are created equal. Track activation, engagement, and paid conversion separately.
Mistake 2: Optimizing for Top-of-Funnel Metrics
You prioritize keywords with the highest click-through rate (CTR) or lowest cost per click (CPC). But those keywords might drive low-quality traffic that never converts.
Optimize for revenue metrics (CPPC, LTV) instead of top-of-funnel metrics (CTR, CPL).
Mistake 3: Ignoring Multi-Currency or Multi-Region Attribution
If you run campaigns in multiple countries, make sure your attribution platform handles multi-currency reporting. A keyword might look unprofitable in USD but highly profitable when analyzed in local currency with regional LTV benchmarks.
Mistake 4: Not Segmenting by Customer Type
Freemium businesses attract different user types: individuals, small teams, enterprises, students, competitors. Each group has different conversion behavior.
Segment your attribution data by company size, industry, and role. A keyword might drive low overall conversion rates but high conversion rates among enterprise buyers — your most valuable segment.
Tools and Platforms for Tracking Keyword-to-Revenue Attribution
Building a complete attribution system requires integrating multiple tools across your marketing, product, and revenue stack. Here are the essential categories:
Attribution and Analytics Platforms
Spectacle tracks the full customer journey from first ad click through in-product behavior to paid conversions, connecting marketing channels directly to LTV. It's purpose-built for SaaS and subscription businesses running freemium or hybrid go-to-market motions, with automatic multi-currency reporting and audience syncing back to ad networks.
Google Analytics 4 (GA4) provides free, robust web analytics with data-driven attribution models. It's ideal for linking organic and paid search traffic to website conversion events.
Mixpanel and Amplitude excel at product analytics, tracking in-app user behavior and feature adoption by acquisition source.
CRM and Marketing Automation
HubSpot and Salesforce connect marketing touchpoints to CRM records, tracking which campaigns and keywords drive qualified leads and closed deals.
Ad Platform Integrations
Use native integrations or tools like Segment to pass conversion data back to Google Ads, Facebook Ads, and LinkedIn Ads via offline conversion APIs. This ensures ad platforms optimize for revenue, not just volume.
Billing and Revenue Systems
Stripe, Chargebee, and Recurly should trigger conversion events when users upgrade to paid plans. Pass subscription data back into your attribution platform to calculate revenue per keyword.
Start Tracking What Actually Drives Revenue
Most freemium SaaS businesses track signups, clicks, and vanity metrics. The winners track which keywords, campaigns, and channels drive users who convert to paying customers and stick around.
If you're still optimizing for free signups instead of paid conversions, you're wasting budget on tire kickers and starving the channels that drive revenue.
Start by defining what "qualified" means in your business. Set up revenue conversion events. Connect product usage data to acquisition sources. Implement multi-touch attribution. Optimize campaigns for paying customers, not just free signups.
The keywords that drive revenue aren't always the ones with the highest search volume. They're the ones that attract users with real problems, real budgets, and real intent to buy.
Stop tracking what's easy to measure. Start tracking what actually matters.