Client name withheld under NDA.
The company cleaned offices, shopfronts and condominium common areas across Singapore, with a team of 60. Most of its work came from referrals and from a handful of property managers who had used it for years. The owner wanted steadier growth in lead generation in Singapore that did not depend on who happened to call that month. A Google Ads account already existed, set up by a staff member some time before, and the website had one general page for all cleaning services with a contact form at the bottom.
The account produced 96 enquiries a month, which sounded healthy. But when we sat down with the sales manager and went through them, only 15 were jobs the company wanted to quote: multi-floor offices, retail units, and condo management contracts with regular schedules. The rest were one-off cleans for a single small office, home cleaning requests and people looking for jobs. Enquiries also sat in a shared inbox, and the median wait for a first call-back was 6 hours. Spend was S$4,050 a month, so each useful lead cost S$270. We recorded the starting position in the table below before changing anything.
Before touching the ads, we agreed with the sales manager what a qualified lead meant: a business site above an agreed size, a regular cleaning schedule, in an area the company serves. We added call tracking and a quote form that asked for site type, floor area and how often cleaning was needed. Every enquiry was tagged in a shared sheet and passed to sales the same day.
Nobody could improve lead quality while the definition lived in the sales manager's head. Once the definition was written down, we could count qualified leads and cost per qualified lead instead of raw enquiries, which is the number the business actually lives on.
We split the single campaign into separate groups for office cleaning, retail cleaning and condo management cleaning. We added negative keywords for home cleaning, maid services, jobs and one-off requests, and cut terms that brought in small single-office jobs. Ad copy named the property type and mentioned scheduled contracts, so people who wanted a one-time clean were less likely to click.
The old campaign paid for every cleaning-related search. Separating by property type let us see which kinds of accounts came from which searches, and negative keywords stopped spend on people the company could not help or would not quote.
We built three landing pages, one each for offices, retail and condo management. Each had a short explanation of the service, the cleaning scope, a plain description of how a quote works, a quote form and a click-to-call number. The forms asked fewer questions than before but still collected the details sales needed to price the job.
A visitor searching for condo common area cleaning should land on a page about that, not a general services page. Matching the page to the search raised the share of enquiries that came with usable site details.
We set up an alert so every new quote request reached the sales manager and one back-up within minutes. We wrote a short call script, a rule to call within two hours on weekdays, and a standard quote email with a site visit offer. Leads that went quiet received two follow-up messages over ten days. Every call was logged against its source.
Many commercial buyers ask two or three companies for a quote and go with whoever replies first and clearly. Faster call-backs and a consistent process lifted the share of qualified leads that received a quote and the share of quotes that closed.
Each week we met the sales manager for 20 minutes, read through the new leads together and marked each as qualified or not, with a reason. We moved budget toward the search terms behind signed work, paused terms that kept sending small jobs, and adjusted ad copy and form questions. Results were recorded by property type and search term.
Sales sees what a lead is like on the phone, and the ad account only sees a click. Putting the two together every week meant the campaigns learned from real outcomes, not just form fills.
After five months, qualified leads had risen from 15 to 34 a month, even though raw enquiries fell from 96 to 71. The share of enquiries worth quoting went from 16% to 48%. Spend rose modestly from S$4,050 to S$4,760 a month, so cost per qualified lead fell from S$270 to S$140. More of those leads received a quote, 68% against 53%, and 30% of quotes were signed, up from 25%. New contract value signed each month grew from S$48,000 to S$150,500 over a first year of service.
Qualified lead definition agreed, tracking live, search campaign split by property type with negative keywords added.
Three landing pages published, quote form tightened, same-day alerts and follow-up routine running with sales.
Weekly lead quality reviews guiding budget, search terms and form questions toward signed work.
Raw enquiries fell 26% over the engagement, and the business was better off. Qualified leads rose from 15 to 34 a month and cost per qualified lead fell to S$140. A falling enquiry count can be a good sign when the lost enquiries were jobs you would never have quoted.
Median time to first call-back dropped from 6 hours to 1.5 hours, and the quote rate went from 53% to 68%. Buyers who ask several firms for a price often choose the first clear reply. A shared follow-up routine costs nothing in media spend.
The weekly review with the sales manager showed which search terms brought signed work. Signed contracts rose from 2 to 7 a month, with a slightly lower average first-year value of S$21,500. The ad account learns faster from the sales team than from clicks alone.
How we build lead generation for Singapore businesses that sell through quotes.
Pages built around one search, one offer and one clear next step.
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