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Google Ads — Case Study
Published 2026-09-28
For approximately S$1,300 in Google Ads spend, a Singapore service business generated 126 leads, 21 bookings, and approximately S$5,600 in reported revenue associated with the analysed results. The lead-to-booking rate was 16.7% and the ratio of reported revenue to advertising spend was approximately 4.31 times. This is a single-business case study, not a universal benchmark. The central lesson: generating leads is not the same as generating customers.
This case study examines a Google Ads lead-generation campaign for a Singapore service business. The figures below represent one campaign period for one business. They are not Singapore industry averages, Google Ads benchmarks, or guaranteed results. Google Ads spend: approximately S$1,300. Leads: 126. Bookings: 21. Reported revenue: approximately S$5,600. Revenue / ad spend: approximately 4.31 times. The revenue figure (approximately S$5,600) represents reported revenue associated with the analysed results. It is not described as guaranteed or exclusively Google-attributed revenue. The ratio of revenue to advertising spend (approximately 4.31 times) is labelled as revenue / advertising spend, not as guaranteed ROAS. Profit margin, customer lifetime value, and organic or referral revenue during the same period are not included in this dataset.
126 leads sounds substantial. But 21 bookings means 105 leads did not convert into revenue. Lead volume is a campaign metric. Bookings and revenue are business metrics. The gap between them is where the real work happens. A campaign that generates 200 leads but only 2 bookings may be less valuable than one that generates 126 leads and 21 bookings. What sits between the lead and the booking determines whether advertising spend creates business growth or just activity. That includes lead quality, qualification, sales follow-up, booking rate, and the revenue each booking produces. This is why looking at lead count alone or cost per lead alone gives an incomplete picture.
The lead-to-booking conversion rate is calculated by dividing bookings by leads and multiplying by 100: 21 divided by 126 times 100 equals 16.7%. This means approximately 1 in 6 leads became a confirmed booking. The remaining 105 leads either did not respond to follow-up, were not a fit for the service, were price-shopping, or did not complete the booking process. What this metric can tell us: it provides a snapshot of how effectively leads are being converted into customers by the combined marketing and sales process. What this metric cannot tell us: it does not reveal which specific stage is responsible for the drop-off. A 16.7% booking rate could result from poor lead quality, slow response times, pricing mismatch, or a combination of all three.
Cost per lead (CPL) is a useful metric but it is only one metric. A low CPL tells you that leads are inexpensive to acquire. It does not tell you whether those leads become customers. The distinction that matters more is cost per acquired customer. A campaign with a low CPL but a poor booking rate can be more expensive per customer than a campaign with a higher CPL and a stronger booking rate. Consider two scenarios: Campaign A at S$5 per lead with a 5% booking rate costs S$100 per booking. Campaign B at S$10 per lead with a 17% booking rate costs S$59 per booking. Campaign B has a higher CPL but a lower cost per customer. This is why businesses should eventually connect advertising data with actual commercial outcomes. CPL is not useless. It is a useful early-stage metric when a campaign is starting and booking data is not yet available.
To understand what the 126 leads actually produced, we evaluated several areas beyond the lead count: Search intent — which keywords produced leads that were genuinely looking to book a service. Lead quality — not all 126 leads were equal. Some were ready to book immediately. Others were exploring, comparing, or not a fit. Conversion action — what counted as a lead, including form submissions, WhatsApp messages, and phone calls. Follow-up speed — how quickly the business responded to enquiries. Booking rate — the 16.7% lead-to-booking rate was the bridge between campaign performance and business outcome. Revenue — approximately S$5,600 in reported revenue put the booking count into commercial context. Landing-page experience — message match, CTA clarity, trust signals, form length, and mobile experience. Tracking accuracy — was every meaningful action being measured.
Google Ads performance and website conversion are not separate concerns. They work together. The ad gets the click. The landing page determines what happens next. Several factors affect whether a visitor who clicks an ad becomes a lead: Message match — the landing page must immediately reinforce what the ad promised. Clear CTA — the primary action should be visible within seconds. Trust signals — professional design, contact information, and proof of credibility build confidence. Friction — long forms, unnecessary fields, slow loading, and confusing navigation reduce conversion. Mobile experience — a significant portion of traffic arrives on mobile. Relevant service information — the page must answer the visitor implicit questions. We are not claiming that any specific landing-page change produced a specific result in this case study. The campaign used a dedicated landing page rather than a generic homepage, and form fields were reduced to essentials. These are standard conversion optimization principles.
The funnel for a service business looks like this: Search, Click, Lead, Qualified Lead, Quotation or Conversation, Booking, Revenue. Each stage has its own metric: cost per click, cost per lead, lead quality rate, lead-to-booking rate, revenue per booking, and revenue relative to ad spend. Measuring only one stage means optimising blind around a single number. When a business tracks the full funnel, several things become possible: bottleneck identification, smarter budget allocation, progressive improvement, and commercial decision-making. The objective is not to maximise the first number in the funnel. It is to understand and improve every stage so that advertising spend creates customers, not just clicks.
This is one case study, not a universal rule. But the lessons are practical for any Singapore service business using Google Ads for lead generation: 1. Track more than leads. 2. Separate lead volume from lead quality. 3. Connect advertising to actual bookings where possible. 4. Review landing-page conversion. 5. Monitor follow-up and sales handling. 6. Avoid making decisions from one metric. 7. Give campaigns enough data before making major conclusions.
Rather than asking how many leads did we get, a more useful framework is: Traffic, Intent, Leads, Qualified Opportunities, Customers, Revenue. The objective is not simply to maximise the first number. More traffic to a poor landing page wastes budget. More leads without qualification creates noise. More bookings without revenue is not growth. Each transition in the framework has a conversion rate and a cost. Understanding those rates and costs and improving them progressively is what turns Google Ads from an expense into a system. This case study illustrates the framework with real numbers: 126 leads entered the funnel, 21 became customers, and approximately S$5,600 in revenue came out.
This is a first-party case study based on actual campaign experience conducted by Rise Radius Labs. The figures are drawn from Google Ads campaign data and the business own booking records. Limitations: This is a single-business case study. Results are not generalisable to all Singapore service businesses. The reported revenue figure is associated with the analysed results but is not exclusively verified as Google-attributed revenue. Profit, profit margin, and customer lifetime value were not available and are not reported. The ratio of revenue to advertising spend is labelled as revenue / advertising spend, not as guaranteed ROAS.
No. Cost per lead tells you how inexpensive leads are to acquire, but not whether those leads become customers. A campaign with a low cost per lead and a poor booking rate can be more expensive per customer than one with a higher cost per lead and a stronger booking rate. The more useful metric is cost per acquired customer.
Bookings. Leads are a campaign metric; bookings are a business metric. A campaign that generates 126 leads but only 2 bookings is less valuable than one that generates 50 leads and 15 bookings. Lead quality is as important as lead quantity.
Divide the number of bookings by the number of leads, then multiply by 100. In this case study: 21 bookings divided by 126 leads times 100 equals 16.7%. This means approximately 1 in 6 leads became a confirmed booking.
Because cost per lead does not capture lead quality, booking rate, or revenue per booking. Two campaigns may both cost S$10 per lead, but if one converts 17% of leads into bookings and the other converts 3%, the first will produce far more revenue for the same spend.
Beyond clicks and impressions, track: cost per lead, lead quality, lead-to-booking rate, cost per booking, revenue per booking, and revenue relative to ad spend. The more of the funnel you can measure, the better your decisions about where to invest and what to improve.
A campaign needs enough data to produce meaningful patterns. As a general guide, wait until you have at least 30 to 50 conversions before drawing conclusions about lead quality and booking rate. For most Singapore service businesses, this typically means 2 to 4 weeks of consistent spend.
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