How fast do you really answer new leads? A 20 minute way to find out

Why you need a number, not a feeling

When owners are asked how quickly they respond to new inquiries, the typical answer is “pretty fast.” When the call log is opened, the answer is usually more complicated. The phone was on silent during a job. A form notification landed in a spam folder. An email sat unread overnight. A listing-site lead went to an inbox nobody checks.

A feeling about response time is shaped by the inquiries you remember, which are usually the ones you answered quickly and won. The ones you answered late, or never, leave no trace. That is why measurement is useful: it shows the inquiries you cannot remember.

The reason to care is economic. You already spend money and effort to make people reach out: advertising, a website, listings, referrals. An inquiry that waits is spend with nothing to show for it. Our guide to what slow replies cost your business turns your measurement into a monthly figure.

Step 1: decide what counts as a reply

Before you collect anything, agree on a definition. A reply is a response from a person, or from your assistant, that moves the conversation forward. Be strict about it.

Measure the time from the moment the inquiry arrived to the moment the customer first heard back. If the inquiry arrived at 9:47 PM and the first real reply went out at 7:31 AM, the wait is nine hours and forty-four minutes, whatever time you saw it.

Step 2: collect the last ten inquiries from every source

Ten per source is enough to see a pattern. If you have a high volume, twenty is better. The goal is not statistical precision. It is to see whether a gap exists and where.

Phone calls

Open your call log. Find the missed calls and note the time of each call and the time of your first successful callback. If your phone system exports call records, use that. If you use a mobile phone, scroll the history and write it down. Count a callback only if it reached the person. A voicemail you left that was never returned does not count.

Web forms and email

Compare the timestamp on the notification email or the form entry with the timestamp of your first reply. If you use a form tool or a CRM, it will show the arrival time. Check your spam folder too, because some of the slowest replies are caused by messages that were never seen.

Direct messages

Use the message timestamps. For social platforms, check each inbox, including message requests, which are often hidden in a separate folder.

Listing sites and ad platforms

Google Business Profile messages, Local Services Ads, Yelp, Angi, Thumbtack, Facebook lead forms: each has its own inbox. Check the platform’s lead inbox for the time received and compare it with your first response.

Step 3: build the sheet

Use any spreadsheet. Create one row per inquiry with these columns.

The outcome column is optional, but it is the most revealing. When you sort by wait, you will often see that the long waits cluster among the lost inquiries.

Step 4: calculate three numbers

You need only three figures. Each one tells you something the others do not.

1. The median time to first reply. The middle value when you sort all waits from shortest to longest. Use the median, not the average, because one very slow case should not distort the picture. Treat “never answered” as infinitely long so it sits at the end.
2. The share answered within five minutes. Count the inquiries with a wait of five minutes or less and divide by the total.
3. The share never answered. Count the inquiries with no real reply and divide by the total.

A worked example with hypothetical data

Here are ten invented inquiries, sorted by wait. These numbers are made up to show the arithmetic, not to describe any real business.

With ten values, the median is the average of the fifth and sixth: (15 + 45) / 2 = 30 minutes. Two of ten were answered within five minutes, so the share is 20 percent. Two of ten were never answered: 20 percent. The honest summary of this hypothetical business is: half of inquiries wait longer than half an hour, one in five is ignored, and only one in five gets a fast reply.

You can enter your own ten values in the free self-audit. It computes all three numbers instantly and shows what they imply at your customer value.

Step 5: read the result

Numbers need context. The picture below is a simple way to think about waiting time. It is illustrative, not a statistic: it shows how a customer’s situation tends to change as time passes.

What is a good result? There is no universal benchmark that fits every trade. A same-day emergency service and a kitchen remodel behave very differently. The practical test is simple: do you reply before the customer contacts someone else? If your median is measured in hours, fixing that comes before any other marketing spend.

The widely cited Harvard Business Review analysis of online sales leads examined how the speed of first contact related to whether a lead was qualified, and found that faster contact was linked to a much higher chance. The full article is behind a paywall, but the lesson is easy to apply: the clock starts when the person writes to you.

The blind spots that distort your number

• Counting a next-morning callback as fast. If the person wrote at 9:47 PM, a reply at 8 AM is a ten-hour wait.
• Forgetting channels nobody checks. A listing-site inbox or a social message-request folder can hold leads for weeks.
• Ignoring after-hours inquiries because they are not real leads. They are real. The person is simply awake when you are not.
• Measuring only the inquiries that became jobs. This hides the ones you lost, which is exactly what you want to see.
• Counting auto-replies. An automatic acknowledgement is not a reply. Judge the first human or assistant response that moves things forward.
• Mixing up “seen” and “answered.” A read receipt is not a reply.

Step 6: look for patterns

Once you have the numbers, sort the data three ways to find the cause.

A common finding is that daytime response is acceptable and the damage is done in the evening and on weekends. Another is that the phone is covered but web forms and messages are not. Both are fixable, and both are easier to fix once you can see them.

Step 7: fix in the right order

Do not try to fix everything at once. Work from the biggest gap to the smallest.

1. Cover nights and weekendsThis is usually the largest and most expensive gap. An assistant that replies in under a minute, qualifies the request and books the slot closes it. Sort inquiries into emergency, urgent and routine so only true emergencies wake someone up.
2. Close the forgotten channelsConnect listing-site inboxes, social messages and web forms to one place so nothing waits for a person to check.
3. Tighten the daytime gapsWhen the crew is on a job and nobody answers, forward missed calls to an AI voice assistant so the caller is answered right away. See how to forward missed calls to an AI assistant.
4. Improve the first messageUse a simple structure for the first reply: name, acknowledgement, one question, a clear next step.
5. Measure againRepeat the ten-inquiry exercise after thirty days and compare the three numbers.

Tools that make measurement easier

You do not need special software to start, but a few tools make it repeatable.

• Your phone system or carrier portal. Most business lines can export call records with timestamps.
• Your form tool or CRM. Entries carry an arrival time. Compare it with the first outbound message.
• Platform inboxes. Google Business Profile, Local Services Ads, Yelp and similar platforms show lead timestamps in their dashboards.
• A shared inbox. Routing every channel into one place makes the clock visible to everyone.
• The weekly report from an assistant. If a system answers for you, it should report inquiries, median first reply, the share answered within five minutes and what was booked.

With NabLead, a plain-language summary arrives every Monday with exactly those numbers. You can see how it works on the home page and the pilot plan.

How response time plays out by industry

The same measurement reveals different patterns depending on the trade.

A hypothetical week, hour by hour

Numbers on a sheet are abstract until you see them against a real week. The scenario below is invented to illustrate where waits come from. It is not data from any business.

Imagine a four-person plumbing company. On Monday at 7:40 AM the owner is already under a sink and the phone is in the truck. A caller leaves a voicemail at 7:52. The owner checks messages at lunch, calls back at 12:30 and reaches the person at 12:34. The wait was four hours and forty-two minutes, and it never appears as a problem because the job was eventually booked.

On Tuesday at 9:47 PM a homeowner fills in the website form about a water heater that is leaking. The form notification goes to an email inbox nobody opens at night. The owner sees it at 6:50 the next morning and calls at 7:05. The homeowner already booked another company at 10:20 PM. The wait was nine hours and eighteen minutes, and this one shows up nowhere, because the owner never learns the person was ready to buy.

On Saturday at 11 AM someone calls the number printed on the truck. The office is closed on weekends and the call goes to a voicemail nobody checks. The reply comes Monday morning, more than forty-eight hours later.

Three inquiries, three different channels, three different causes, and none of them is about effort. Each is about where the message landed and who was looking. That is why the exercise asks for every source. It is also why the median alone is not enough: it tells you how bad the typical wait is, and the slicing in step 6 tells you why.

Choosing your own targets

A target turns a number into a decision. Since no universal benchmark fits every trade, set targets from your own situation and revise them after the first month.

Write the target down, put it next to the weekly number and review both at the same time every week. A target nobody looks at is decoration.

Objections you will hear from your own team

Measurement can feel like an accusation. Expect these reactions and answer them calmly.

• “We answer everything eventually.” True, and the sheet will show how long eventually is. The goal is not to blame anyone. It is to see the wait from the customer’s side.
• “Nights and weekends are not our job.” Perhaps not, which is exactly why a system should cover them so that no person has to. See the after-hours lead playbook.
• “Most of those inquiries are tire kickers.” Some are. You cannot know which until someone replies. A fast, short reply that asks one question sorts them at almost no cost.
• “We are too busy to track this.” The first pass takes twenty minutes. After that, a weekly summary takes seconds, particularly if an assistant reports it for you.
• “Our customers prefer calling.” Some do, and the call log is part of the sheet. Many customers now start with a form or a call outside business hours, when nobody is there to answer.

What to do with the result this week

Whatever your numbers are, do three things within seven days. Write the three figures at the top of the sheet with today’s date. Pick the single biggest gap from the slicing step and name an owner for it. Decide how you will measure again in thirty days.

If you want the numbers computed for you, the self-audit takes ten values and returns the three figures instantly. If you want a second pair of eyes, the 15 minute audit goes through your last 30 days with you and leaves you with the numbers whether or not you ever work with us.

What you gain from measuring

• You see the leakFor the first time you know whether leads are lost to speed, to a channel or to the clock.
• You stop guessingDecisions about hiring, tools or marketing rest on your own numbers.
• You can prove improvementThirty days later you can compare the same three numbers and see what changed.
• You protect your marketing spendFixing response speed raises the return on the money you already spend to get inquiries.
• You build a habitA weekly number keeps the team focused on the moment that matters most.
• You spot problems earlyA sudden jump in median wait warns you before it shows up in revenue.

Frequently asked questions