Google Ads for SaaS sign-ups: more qualified sign-ups, not just more sign-ups

• Who: a B2B SaaS for mass calls, texts and emails, used by 40,000+ businesses. Users sign up on the website first and pay later. [CONFIRM: is that sign-up a free trial, and what are its terms, e.g. length, free credits, card required?]
• The problem: Google Ads was buying sign-ups, and many came from people who never meant to pay. Google counted every sign-up the same, so it kept finding more of the wrong ones.
• What changed: every sign-up was rated for quality, the rating went back into Google Ads as an offline conversion, and keywords that only produced low-rated sign-ups were cut.
• The result: qualified sign-ups rose from 82 to 175 a month. Cost per sign-up fell 55% and the conversion rate rose 34%.

This page is the free-trial angle on that account: sign-up volume vs sign-up quality vs paid customers, and the playbook I'd use for any SaaS that runs Google Ads to a free trial or free sign-up. The original write-up is How I doubled high-quality sign-ups for a B2B SaaS.

A free sign-up is easy to give away. That makes it a weak signal for Google Ads, because the cheapest sign-ups are often the ones least likely to pay.

This account had both sides of that problem:

1. A crowded category. There are hundreds of mass SMS, voice and email tools, so generic searches are competitive and costly.
2. Sign-ups the business didn't want. Misuse of SMS and email tools is rampant. Plenty of people sign up with no plan to pay, or to send spam, and a sign-up count can't tell them apart from a real business.

At the start, the account was spending [CLIENT RESULT: monthly ad spend] for [CLIENT RESULT: sign-ups a month], with no way to see inside Google Ads which of those sign-ups were real businesses.

The aim was to make Google Ads bid for the sign-ups that become customers, then cut whatever didn't produce them.

• A quality rating on every sign-up. A third-party service rated each new sign-up, so a high rating marked the kind of business customer the client wanted. [CONFIRM: which rating service, and what it scored, e.g. company size, business email, use case.]
• Conversion tracking for sign-ups. [CONFIRM: how the sign-up itself was tracked, e.g. Google Ads tag or GA4 import, and whether it stayed as a secondary conversion.]
• Offline conversion upload of qualified sign-ups. The rating was uploaded to Google Ads against the click that produced the sign-up. Every keyword and search term then showed qualified sign-ups next to total sign-ups. [CONFIRM: upload method and frequency, e.g. GCLID upload from the CRM, daily.]
• Paying customers fed back too. [CONFIRM: were paid conversions or revenue also uploaded to Google Ads? If not, remove this row.]
• Bidding. [CONFIRM: bid strategy before and after, and whether qualified sign-ups became the conversion Google bids towards.]
• Account structure and keyword intent. [CONFIRM: campaigns, e.g. brand, generic, competitor and use case, and match types.]
• Landing pages. [CONFIRM: which pages the ads sent sign-ups to, and any changes made.]
• The keyword cull. After about 3 months of rated data, I cut every keyword that drove low-rated sign-ups and kept the budget on keywords that drove qualified ones.

Once the cull went in, the results showed up straight away.

• Qualified sign-ups more than doubled, from 82 to 175 in a month.
• Cost per sign-up fell 55%. [CONFIRM: cost per sign-up, or cost per qualified sign-up?]
• The conversion rate rose 34%. [CONFIRM: click to sign-up, or click to qualified sign-up?]
• Total sign-ups: [CLIENT RESULT: all sign-ups a month, before vs after. Did total volume fall while qualified sign-ups rose?]

The lesson for a free-trial SaaS: judge Google Ads on qualified sign-ups, not total sign-ups. Total sign-ups can climb while the business gets worse customers.

A sign-up is only worth paying for if it becomes a customer. Here is the funnel as far as the data in hand goes:

• Sign-ups from Google Ads: [CLIENT RESULT: sign-ups a month, before vs after]
• Qualified sign-ups: 82 a month before, 175 after.
• Paying customers: [CLIENT RESULT: qualified sign-ups that became paying customers, before vs after]
• Sign-up to paid rate: [CLIENT RESULT: paid customers as a share of qualified sign-ups]
• Revenue: [CLIENT RESULT: new MRR or revenue from Google Ads customers, if shareable]

For a freemium example where bidding went all the way to paid upgrades, see Rezi: from 29 to 129 paying customers a month.

• Setup: the rating service and offline conversion upload went live. [CONFIRM: start month.]
• Months 1 to 3: rated sign-ups built up in Google Ads, showing which keywords and search terms produced qualified sign-ups.
• The cull: with about 3 months of data, keywords driving low-rated sign-ups were cut.
• The next month: qualified sign-ups reached 175, up from 82. [CONFIRM: the two months compared.]

If your Google Ads sends people to a free trial or free sign-up, this is the order I work in:

• Define a qualified sign-up first. Agree on one signal that predicts paying: a lead score, a business email, a key action in the product. Do this before touching campaigns.
• Track three events, not one. Sign-up, qualified sign-up and paid customer (with its value), each tied to the click with a GCLID stored on the user record.
• Send qualified and paid events back to Google Ads. Upload them as offline conversions and make them the conversions Google bids towards, so it learns which clicks become customers. Keep the raw sign-up as a secondary conversion for reporting.
• Give it enough data, then cut hard. Wait for enough qualified conversions to judge each keyword, then remove keywords that only drive low-quality sign-ups.
• Report the funnel monthly. Sign-ups, qualified sign-ups, paying customers and cost per paying customer, side by side. Total sign-ups on their own will flatter a bad account.

Want to know if this would work for your trial? Book a 15-minute call and I'll tell you whether Google Ads can do the same for your SaaS.