Are Your Home Improvement Leads Working?

A low cost per lead does not answer the question. Neither does a high rejection rate. You need to know what you spent, which leads became sales, how much revenue survived cancellations, and what it took to deliver those jobs.

How to calculate cost of marketing

For this guide, the numerator is purchased-lead spend. Start with what you were charged, subtract confirmed credits, and match that spend to revenue from the same leads. A group of leads bought during the same period is called a cohort. Do not mix this channel calculation with your company’s total marketing expense ratio. Include software, call-center payroll, commissions, and other costs when you assess overall profitability.

What is a good cost of marketing for home improvement leads? In Opta’s practical experience, roughly 12–20% can be a useful working range for aggregator leads, with many strong operators targeting 15% or better. This is operating context, not a universal industry benchmark. Confirm whether any target uses gross sales, net sales, or collected revenue before comparing it with your results.

Your target depends on gross margin, average sale, sales costs, financing costs, cancellations, and growth strategy. A growing branch may accept a higher acquisition cost to build volume, but it still needs to know how much profit is left after delivering the job and paying its operating costs.

Why cost per lead is only part of the picture

Cost per lead tells you what you paid for an inquiry. Cost of marketing connects that price to the revenue the leads actually produced.

For a hypothetical comparison, suppose 6% of the leads from a $120 source become retained sales. That is $2,000 in lead spend per sale. If only 1% of the leads from a $50 source become retained sales, that source costs $5,000 per sale. At a $20,000 average net sale, the cost of marketing is 10% for the higher-priced leads and 25% for the lower-priced ones.

The higher-priced source produces better revenue economics in that example. Different average sales or margins could change the decision. Compare price, conversion, and job economics together.

The metrics behind the result

Cost of marketing tells you whether lead spend meets your revenue target. These metrics help explain why. Count unique leads at each stage so repeated calls or rescheduled appointments do not inflate the results. Multiply the rate calculations below by 100 to express them as percentages.

Pull revenue and lead outcomes, often called dispositions, from your CRM or job system and match them to purchase records. Flag unmatched records and missing outcomes. Unknown revenue is not the same as a confirmed zero.

Choose the right revenue figure

Gross sales are booked contract dollars before cancellations and adjustments. Using them gives you an early view of selling performance, but some of that revenue may not survive.

Net sales are retained contract dollars after the cancellations and adjustments included in your reporting policy. Specify the reporting date and how you handle financing failures, scope changes, and partial cancellations. This gives you a better view of the business you kept.

Collected revenue is cash received from those jobs, after refunds under your policy. It helps you assess cash recovery, but unfinished jobs and unpaid balances can make recently purchased leads look worse than older ones.

Track dollar gross-to-net separately from cancellation rate by job count. Losing one large job can hurt revenue more than losing several small ones. Net sales are not profit, and neither signed contracts nor approved financing are cash collected.

Compare lead sources fairly

Start with the same revenue definition, lead purchase period, and outcome cutoff. Then compare similar products, territories, ticket sizes, and lead formats. A shared form lead, an exclusive lead, a live transfer, and a revenue-share arrangement have different pricing and sales processes. Our home improvement lead sources guide covers those buying differences.

Check whether sources received comparable response times, contact attempts, appointment availability, and rep coverage. Slow routing can hurt results even when a source is a good fit. Use a defined aggregator follow-up process and review execution before drawing a source-level conclusion.

Break results out by source, campaign, product, and geography where volume supports it. Keep a consistent attribution rule so one job is not credited in full to multiple sources. Compare both cost of marketing and retained sales dollars. A small source with an excellent percentage may not replace the sales volume of a larger one.

Share the findings with your provider before changing the buying program. Review campaign mix, service areas, lead criteria, and follow-up together. The same lead can be a good fit for one contractor and a poor fit for another; the aim is to improve the match and preserve productive volume.

Give leads time to produce revenue

Follow each purchase cohort through contact, sale, cancellation, installation, and collection. Do not divide this month’s lead spend by this month’s total revenue if much of that revenue came from older leads.

Choose review windows from your actual sales and installation cycle. Compare cohorts at the same age, such as their first 30, 60, or 90 days where those checkpoints fit your business. Those are review examples, not required waiting periods.

Keep early operational signals separate from mature financial results. You can investigate failed delivery or slow response immediately. A new lead with two attempts and no sale is not yet evidence that a segment should be blocked.

Check the sample before changing a rule

There is no universal number of leads that makes a filtering decision reliable. The required evidence depends on conversion frequency, average sale variation, cohort maturity, and how narrow the segment is.

Before acting, ask whether one additional sale would reverse the conclusion. Look for a repeated pattern across mature cohorts, enough recorded outcomes, and a plausible reason for the difference. Do not turn missing dispositions into losses.

Testing dozens of attributes will usually reveal something that looks bad by chance. Check a proposed rule against a separate period before expanding it. Where evidence is thin, keep monitoring or run a limited test instead of a broad exclusion.

Find where performance breaks down

Work backward from retained revenue to the point where performance changes. These patterns suggest what to investigate; they do not prove the cause.

If the break is operational, fix the handoff, staffing, or sales process. The home services lead management guide covers qualification and routing in more detail.

Test filters against spend and sales

The goal is to remove wasted spend while preserving productive lead volume and sales. A segment performing below average can still produce valuable jobs. Rejecting it may lower volume without improving the business.

Use historical dispositions and sales to model the leads a rule would remove. Count both their avoidable cost and their gross sales, net sales, and collected revenue. Recalculate cost of marketing on the leads that remain. Show overlapping rules together so the same savings are not counted twice.

Check that the attribute was available and accurate when the lead arrived. A phone status checked months later, for example, may not describe that number at purchase. Confirm the provider supports rejection before billing; a theoretical rejection is not automatically an invoice saving.

Apply promising changes only to the relevant campaign or source. Record the expected sales impact, test against another mature period, and monitor accepted volume and retained revenue after rollout. Historical modeling suggests a change worth testing; it does not guarantee future savings.

Worked example: what a filter would change

This is a hypothetical example, not a customer result. You bought 500 leads at $90 each and have allowed enough time to observe sales and cancellations.

A proposed rule would have removed 100 leads costing $9,000, with no recorded sales in this completed dataset. Assuming those charges were avoidable, modeled spend falls to $36,000 while net sales stay at $250,000. Cost of marketing on net sales becomes 14.4%.

That is a 3.6 percentage-point reduction, or 20% relative improvement. It is not proof that the next 100 similar leads would produce no sales.

Now suppose a broader rule removes another $5,000 in spend but also $50,000 in net sales. The remaining $31,000 in spend divided by $200,000 in net sales produces a 15.5% cost of marketing. More rejection makes the modeled result worse than the narrower rule and removes productive sales.

A simple lead-source scorecard

Use one scorecard per source and purchase cohort. Add campaign or product detail only when the outcomes support it.

Review early funnel issues regularly, and revisit financial decisions as cohorts mature. Put the reason for each change next to the numbers so the next review can tell whether it worked.

Put the findings to work

Once you know which characteristics are associated with wasted spend, Opta can help apply customer-defined validation and filtering before eligible third-party leads are purchased, where the source supports real-time rejection. The rules are customer-controlled. Opta does not automatically know which lead will become a profitable job.

Opta’s team can help review historical dispositions to identify changes worth testing. For a public example of measuring beyond rejected leads, the Bath Experts case study tracks lead savings alongside downstream sales outcomes. Its results are specific to that operation.

Use the ROI calculator to estimate potential filtering savings and Opta costs. Use your cohort scorecard to judge actual lead-source performance.