Meta Ads and lead generation glossary

Cost per lead (CPL)

Cost per lead (CPL) is the average ad spend required to generate one filled form or qualified contact, calculated by dividing total spend by the number of leads.

CPL is the most useful day-to-day metric for a local service business, because it links ad spend directly to inbound contacts without waiting for the sales cycle, which can take weeks, to close.

It should always be read against the price of the service sold and the real closing rate, never in isolation. A 30 dollar CPL is excellent for a 5,000 dollar contract and a problem for a 150 dollar service if closing doesn't make up the difference.

Comparing CPL over time, on the same audience and the same form, tells more than a generic market benchmark: gaps between local service categories are wide, and an external figure is mostly a starting point, never an absolute standard.

How it is calculated : Ad spend ÷ number of leads

The common mistake : A falling CPL alongside a collapsing closing rate is not an optimization, it's a quality drop hidden by volume: driving CPL down by loosening targeting or the form costs more across the full funnel than it saves.

Cost per acquisition (CPA)

Cost per acquisition (CPA) is the average ad spend required to turn a prospect into a paying customer, calculated by dividing total spend by the number of sales.

CPA extends CPL all the way to the sale, not just the contact: it answers the question CPL leaves open, the real price paid for a customer rather than for a mere prospect.

Reading it requires knowing the margin on the service sold: a high CPA can stay profitable if the average ticket and margin allow it, and a low CPA can still be a bad trade if the service sold doesn't cover what it cost to win.

Compare it over a window long enough to cover the business's real sales cycle, not over a campaign's first few days, when too few leads have had time to become customers yet.

How it is calculated : Ad spend ÷ number of customers acquired

The common mistake : The CPA shown in Ads Manager is often based on an automatically tracked conversion event, not a sale confirmed against a signed contract: mistaking it for the real CPA calculated from the CRM skews the decision to cut or scale a campaign.

ROAS, return on ad spend

ROAS, or return on ad spend, expresses the revenue generated for every dollar spent on advertising, shown as a ratio or a multiple.

ROAS translates ad performance into direct financial language, which makes it the number most owners look at first to judge whether a campaign is working.

It should always be read next to the margin on the service sold, never alone: a ROAS of 4 on a low-margin service can generate less net profit than a ROAS of 2 on a high-margin one, because ROAS measures revenue, not profit.

For a local service business where the sale often closes over the phone after the lead comes in, the ROAS Meta calculates automatically usually captures only purchases tracked by the pixel: it needs to be rebuilt from the CRM to reflect sales actually closed.

How it is calculated : Revenue generated ÷ ad spend

The common mistake : A high ROAS shown in Ads Manager means little if the attributed sales don't match sales actually collected: for a service sold by phone or in-person appointment, platform-reported ROAS remains an estimate to verify against real sales figures.

CPM

CPM, or cost per thousand impressions, is the price paid for an ad to be shown one thousand times, regardless of the clicks or conversions it generates.

CPM reflects the price of the audience itself, before any click or conversion: it rises when several advertisers compete for the same audience, for example during periods of heavy commercial activity on Meta.

It mainly works as an early warning signal: a CPM that climbs without CTR or CPL degrading at the same time usually isn't a problem, while a stable CPM paired with a rising CPL points to a creative or targeting issue, not an audience-price issue.

Comparing it week over week on the same account gives more information than a market benchmark: CPM gaps between industries and geographic areas are large, and a national average figure says little about a specific local market.

How it is calculated : (Ad spend ÷ impressions) × 1,000

The common mistake : Judging a campaign on CPM alone, whether rising or falling, ignores that CPM by itself says nothing about the quality of the leads obtained: it should always be read together with CTR and CPL, never in isolation.

Click-through rate (CTR)

Click-through rate (CTR) measures the share of people who click an ad among those who saw it, expressed as a percentage of impressions.

CTR measures an ad's immediate appeal, the ability of the visual and copy to make someone want to click before they even know what the business behind it offers.

It varies significantly by format and placement: a normal CTR in Stories differs from a normal CTR in Feed, which makes comparing across placements more useful than comparing against a single reference figure.

For a local service business, a decent CTR paired with a high CPL usually points to the landing page or the form, not the creative: people click but drop off before leaving their details.

How it is calculated : (Number of clicks ÷ number of impressions) × 100

The common mistake : Optimizing a creative purely to maximize CTR often pushes toward clickbait hooks that attract curious scrollers rather than real prospects: a high CTR paired with a low conversion rate is a warning sign, not a win.

Conversion rate

Conversion rate is the share of visitors or clicks that complete the intended action, such as filling out a form, expressed as a percentage of total traffic.

Conversion rate is where most ad budgets actually get lost: a campaign that brings in qualified traffic at a good price is worthless if the landing page or the form fails to turn that traffic into leads.

It exists at several stages, not just one: click-to-form rate, form-completion rate, lead-to-appointment rate, appointment-to-sale rate. Conflating these stages hides where the real problem sits.

Comparing it across traffic sources, creatives, or versions of the same page says more than a single isolated figure: a 5 percent conversion rate is excellent or mediocre depending on what it's compared against.

How it is calculated : (Number of conversions ÷ number of visitors or clicks) × 100

The common mistake : Measuring only a form's completion rate, without tracking what happens to those leads once called back, hides the real weakness: a page that converts well but feeds a poorly prepared sales process creates the illusion of an ad problem when the problem is commercial.

Frequency

Frequency is the average number of times a person in the targeted audience has seen an ad over a given period.

Frequency shows how repeatedly a limited audience, typical of a local geographic area, is being reached: on a small market, an audience saturates faster than it would on a national one.

A rising frequency that isn't degrading results isn't a problem by itself: it's the combination with a rising CPM and a falling CTR that signals an audience grown tired of seeing the same creative too often.

For a narrow service area, tracking frequency over short cycles, one to two weeks, gives more information than a generic online threshold, because a smaller local audience pushes frequency up faster than elsewhere.

How it is calculated : Impressions ÷ reach

The common mistake : Relying on a universal threshold like three or four as the ideal frequency cap ignores that the right number depends on audience size and the variety of creatives in rotation: the real signal to watch is CPM and CTR degrading together, not frequency in isolation.

Reach and impressions

Reach counts the number of unique people exposed to an ad, while impressions count every display, including repeated views by the same person.

Reach answers how many different people did I touch, while impressions answer how many times was my ad shown, including several times to the same person.

For a local service business whose addressable audience is limited by geography, reach sets a realistic ceiling: past a certain daily budget, extra spend stops reaching new people and only raises frequency instead.

Comparing reach to the estimated size of the targeted audience, shown in Ads Manager, indicates whether a campaign is approaching its natural growth limit in that specific market.

The common mistake : Presenting impressions as if they measured the size of an audience reached artificially inflates the perceived scale of a campaign: the two figures answer different questions and are never interchangeable.

Hook rate

Hook rate measures the share of people who keep watching a video ad past the first three seconds, revealing how strong the opening is.

Hook rate isolates the very first split-second decision a viewer makes when a video starts, stay or scroll past. For video formats, it's the metric that judges the creative before the offer or targeting even come into play.

A low hook rate signals a problem with the opening, the first three seconds, not necessarily a problem with the overall message: often the fix is reworking only the beginning of the edit without touching the rest of the script.

Always read it alongside hold rate, the share of viewers who watch through to the end, and conversion rate: a strong hook that doesn't lead to leads points to an opening promise disconnected from the real offer.

How it is calculated : (Views at three seconds ÷ impressions) × 100

The common mistake : Optimizing a creative for hook rate alone pushes toward shocking or clickbait openers that grab the wrong audience's attention: a high hook rate followed by a low conversion rate ends up costing more than a plainer, better-targeted opening.

Daily and lifetime budget

Daily budget sets a target average spend per day, while lifetime budget caps total spend across the entire scheduled run of the campaign.

Daily budget sets a target average daily spend that the delivery algorithm can exceed on some days and offset on others, while lifetime budget strictly caps the total amount spent across the campaign's defined run.

For a local service business testing a new offer or a new creative, daily budget usually works better because it allows quick adjustment or cutoff, while lifetime budget suits a campaign with a known end date, such as a time-limited promotion.

Comparing the amount actually spent each week against the stated daily budget gives a better picture of the real delivery pace than a single figure read at the start of the campaign.

The common mistake : Assuming daily budget is a hard day-by-day cap leads to unwarranted concern on a day when spend clearly exceeds the target: the platform can spend up to roughly double on a given day and offset it over following days, so the real limit shows up over a week, not over 24 hours.

Lookalike audience

Lookalike audience is a Meta-generated audience of users who statistically resemble a source audience the advertiser provides, such as a customer list.

Meta analyzes the source audience (customers, site visitors, people who filled out a form) to extract shared characteristics, then searches the targeted country or region for the profiles that match them most closely. Size is set as a percentage of the population, typically 1 to 10 percent: a lower percentage gives a smaller audience that stays closer to the source.

For a local service business, the hard part isn't the algorithm, it's the size of the source. A few dozen or a few hundred customers make a lookalike far less reliable than an e-commerce list running into the thousands. A lookalike also defaults to searching the whole country, so it must always be layered with geographic targeting to stay inside the area the business actually serves.

The most useful sources in practice are the past customer list, people who submitted a quote request form, and people who engaged with the Facebook page or Instagram account.

The common mistake : A source that is too small or too mixed (cold prospects blended with paying customers, for example) produces a lookalike with no real value. A local business also often never reaches the volume Meta recommends for a reliable source, so it pays to focus on the quality of the list rather than trying to inflate its size.

Custom audience

Custom audience is a Meta audience built from data the advertiser already owns, such as a contact list, site visitors, or page followers.

It's built from several source types that can be combined: an imported contact list (email or phone), site traffic via the pixel, engagement on a page or Instagram account, video views, or people who opened a lead form (Instant Form) without necessarily submitting it.

For a local tradesperson or service provider, the most useful source is usually the past customer list and leads already received by phone, richer in volume than web traffic, which stays thin as long as the site doesn't draw much visitor volume.

A custom audience serves two main purposes: direct targeting (retargeting) or exclusion (not showing an ad to someone who is already a customer), and it can also seed a lookalike audience.

The common mistake : An imported list that's too old or too small gives a low match rate on Meta's side, meaning few contacts are actually found among its users, which makes the audience nearly unusable. It also goes stale quickly if it isn't refreshed after every new customer or lead.

Retargeting

Retargeting is the practice of showing ads to people who already interacted with the business, for example by visiting the site or opening a form without completing it.

It relies on a time window (often 7, 14, 30, or 180 days) and an interaction source: site visits via the pixel, engagement on Facebook or Instagram, a video view, or an opened but unsubmitted lead form.

For a local service with a long decision cycle, such as a conservatory or pergola installer, retargeting is often more cost-effective than cold prospecting, because the traffic volume is small but already qualified. Segmenting by intent (a simple site visit versus a started-and-abandoned form) allows the message to adapt instead of repeating the same ad to everyone.

With low local traffic volume, wide retargeting windows (30 to 180 days) are often necessary just to gather enough people for delivery to run properly.

The common mistake : Retargeting everyone with the same message used for cold prospecting, with no progression, wastes the advantage of an already-warm audience. Another common mistake is leaving retargeting running indefinitely on people who became customers in the meantime, because the exclusion list wasn't updated.

Cold, warm and hot audience

Cold, warm and hot audience classifies prospects by how familiar they are with the business, from total strangers (cold) to people who already started a buying process (hot).

A cold audience has never heard of the business: it's built through geographic targeting, interest targeting, or a lookalike audience. A warm audience already had some contact, such as a site visit or a page follow. A hot audience has shown strong intent: a completed quote form, a phone call made, an ongoing conversation.

The classic multi-stage funnel, designed for high volume, quickly hits its limit for a local business: warm and hot audiences stay tiny there, often just a few dozen or a few hundred people, leaving little room to split them further.

In practice, it's usually better to split budget and message into two broad buckets: cold, which needs proof (reviews, past work, guarantees) and a clear offer, and warm/hot, which needs a reminder of the action already in motion or a reason to act now.

The common mistake : Copying a five-stage e-commerce segmentation onto a local audience of a few hundred people breaks each segment into pieces too small for the algorithm to learn from properly.

Advantage+ Audience

Advantage+ Audience is Meta's automated targeting mode that lets the algorithm find the people most likely to convert, based on optional advertiser suggestions rather than detailed manual targeting.

The advertiser can supply suggestions (interests, a lookalike audience, location) but Meta can move beyond them if it judges that performance improves, except for exclusions set as hard limits, such as geographic boundaries.

For a local business, geographic targeting remains one of the few settings that must stay locked, otherwise Advantage+ can chase performance outside the area the business actually serves. Confirming that the radius or city list is fixed isn't optional with this targeting mode.

Advantage+ needs conversion data to learn well (pixel, tracked events). Without history, it runs blind at the start, which makes the first few days a weak signal of true performance.

The common mistake : Turning on Advantage+ without locking the geographic area and without reliable conversion tracking lets the algorithm potentially spend outside the service area, or misidentify what actually counts as a conversion (the call, the quote request).

Detailed targeting

Detailed targeting is the manual addition of demographic, interest, or behavior criteria to narrow a Meta audience, an option playing a smaller role as Meta pushes automated targeting.

It covers three families of criteria: demographics (age, status), declared or inferred interests (liked pages, viewed content), and behaviors. These criteria combine to narrow the starting audience.

For a local service business, interest targeting often stays imprecise, because Meta infers these interests from broad signals that aren't always relevant to a one-off purchase (a pergola, a roofing job). The most useful filter remains geographic targeting, sometimes paired with age or homeowner status.

Detailed targeting still has a role for excluding clearly irrelevant groups, or for running a comparison test against an automated mode like Advantage+.

The common mistake : Stacking too many interest criteria shrinks the audience below the size where Meta can still optimize properly, which drives up cost per result without improving lead quality.

Audience exclusion

Audience exclusion is the explicit removal of certain people or groups from a Meta campaign, for example already-signed customers or people who already submitted the form.

The most common uses: excluding existing customers from a list, excluding leads already handled by the sales team, excluding a lookalike's source audience to avoid overlap, or excluding geographic areas outside the service area.

For a local business, exclusion is what prevents paying to reconvert an already-signed customer, or showing an ad to people dozens of kilometers outside the area the business actually serves.

An exclusion only holds its value if it's kept current: new customers, quotes in progress, and changes to the service area all need to be reflected.

The common mistake : Forgetting to update the exclusion list after each newly signed customer wastes budget retargeting people who already converted, which also distorts the true cost per new lead.

Geographic targeting

Geographic targeting is the area the advertiser defines on Meta, by radius or by a list of cities, matching where the business can actually deliver its service.

Meta offers several technical options: a radius in kilometers around a point, a list of cities, postal codes, or regions, and a choice between targeting people who live in the area versus people who simply passed through it recently, an important distinction to avoid reaching passers-by with no real tie to the area.

This is the setting that separates a local campaign from a national one: it must match the provider's actual service area, the one where a job can actually take place, not an area widened just to inflate audience size.

This geographic lock needs to be checked even when automated targeting (such as Advantage+ Audience) handles the rest of the criteria, otherwise budget can leak outside the useful area.

The common mistake : Widening the radius to artificially inflate the audience and ease delivery, forgetting that every lead generated outside the area will never turn into a job.

Audience size and saturation

Audience size is the number of people reachable by a Meta campaign, and saturation happens when that audience is too small to absorb the available budget.

Every audience has a limited delivery potential. Frequency, meaning the average number of times a given person sees the ad, climbs mechanically once the budget exceeds what the audience can absorb over a given period.

This is a structural problem for a local business: the service area limits the possible audience to roughly a few tens of thousands of people in a rural or suburban zone, a constraint a national brand rarely faces so early. That's why watching frequency and refreshing creative regularly matters more than pushing budget upward without limit.

These rough figures vary a lot by area and never replace a regular look at the account's own frequency and reach numbers.

The common mistake : Raising the daily budget expecting more leads to follow mechanically, when the local audience is already saturated: cost per result climbs instead of falling, because Meta repeats the ad to the same people instead of reaching new ones.

Customer list matching

Customer list matching is the process by which Meta links a contact list uploaded by the advertiser to real user accounts, to build a custom audience.

Before upload, emails and phone numbers are hashed (run through an irreversible process such as SHA-256) to preserve privacy. Meta then compares these fingerprints against its own user base and calculates a match rate, the share of contacts actually found among its users.

For a tradesperson whose customer file is sometimes loosely kept (a shared business landline, a generic company email), this match rate tends to run lower than for a clean e-commerce database. Cleaning and enriching the file before upload, favoring a personal mobile number and personal email over generic business contact details, noticeably improves the result.

This matching underpins two uses: building a custom audience of customers to exclude, or using it as the source for a lookalike audience.

The common mistake : Uploading a list with badly formatted columns, duplicates, or too few contacts (a few dozen) produces a match rate so low that the resulting audience becomes unusable.

Campaign, ad set, ad

Campaign, ad set and ad are the three nested levels of a Meta Ads account, running from the objective and budget down to the exact creative a person sees.

A campaign sets the objective, for example generating quote requests, and can hold several ad sets. An ad set defines the budget, geographic targeting, audience and schedule. An ad, inside that ad set, is what the person actually sees: the image or video, the copy, and the destination, form or page, it leads to.

For a local service business, this hierarchy exists mainly to isolate what gets tested. One ad set per service area or service type shows which audience responds, while several ads inside the same ad set test different visuals or hooks without splitting the budget or the audience.

The common mistake : Splitting the budget across too many ad sets: each one needs enough daily volume to exit the learning phase, otherwise none of them delivers efficiently.

Campaign objective

Campaign objective is the outcome Meta optimises delivery for, chosen when the campaign is created, such as leads, traffic or messages.

Set at campaign creation, the objective shapes everything: who the ad is shown to, how the algorithm learns, and which result gets reported in the dashboard. A leads objective looks for people likely to fill in a form; a traffic objective looks for clicks, with no guarantee they convert into anything.

For a local service business, the right objective is almost always the one closest to the real action wanted, booking a call or requesting a quote, not the one producing the most visible volume. An awareness or traffic objective produces flattering numbers but rarely phone calls.

The common mistake : Picking traffic or awareness because it looks cheaper per click: Meta then optimises for clicks or views, not for people ready to become a customer.

Ad creative

Ad creative is the visual and text combination of an ad, image or video, headline, primary text and description, shown to the targeted audience.

Creative covers everything a person sees before even clicking: the image or video, the primary text, the headline and sometimes the description. It is the single biggest lever on cost and result volume, ahead of targeting or budget.

For a local service business, the creative that wins usually shows the real work, a job site, a finished project, a satisfied customer, rather than a generic stock visual. The copy does best when it names the problem solved and the area served plainly, since a local audience recognises itself through that first.

The common mistake : Running only one visual across a whole campaign: without variants, there is no way to tell whether a weak result comes from targeting or from the creative itself.

Instant form (lead form)

Instant form is a form that opens directly inside Facebook or Instagram without leaving the app, pre-filled with the person's account details.

Unlike a click to a website, the instant form stays inside the app: someone taps the ad, the form opens on top of it, their details are already filled in from their Facebook or Instagram profile, and they submit in one or two taps.

For a local service business, this sharply cuts friction and raises the number of submissions, but at a cost to quality: some people who submit have not really thought through their need, unlike someone who filled in a full form on a website. Both mechanics should be compared on cost per qualified lead, not on cost per lead alone.

The common mistake : Comparing an instant form's cost per lead to a landing page's without checking how many actually pick up the phone: the instant form often produces more volume, not more kept appointments.

Landing page

Landing page is the web page an ad sends people to, built around a single action, calling, booking or filling in a form.

Unlike a general homepage, a landing page exists for one campaign and one action: it repeats the ad's exact promise, strips out navigation and menus, and pushes a single button, call, book a slot or send a request.

For a local service business, the landing page needs to reassure fast, with the area served, real photos and a clickable phone number, since the decision is often made in a few seconds on a phone, before someone even scrolls. A good page saves the visitor time, not just the advertiser.

The common mistake : Sending the ad to the site's homepage instead of a dedicated page: the visitor then has to hunt for the exact information the ad just promised, and some give up before finding it.

Meta Pixel

Meta Pixel is a piece of code installed on a website that sends visitor actions back to Meta, to measure results and sharpen ad targeting.

Once placed on every page, the pixel reports visits, button clicks and form submissions back to Meta. That signal does two things: it measures how many results a campaign actually produced, and it feeds the algorithm so it can find more people who behave the same way.

On a local service business's brochure site, the pixel observes very little: it sees a visit and, at best, a click on 'call' or a contact form submission, never the sale itself, since that gets closed by phone or in person, off the site entirely. It is a useful but partial signal, one to supplement rather than treat as the final measurement.

The common mistake : Assuming the pixel measures sales on a brochure site: it only sees what happens on the website, not the phone call that follows or the quote that gets signed.

Conversions API

Conversions API, or CAPI, sends Meta the same events as the pixel but directly from the website's server, without depending on the visitor's browser.

The standard pixel runs in the visitor's browser, which makes it vulnerable to ad blockers, private browsing and the restrictions browsers and Apple's iOS impose. The Conversions API works around that by sending the same information, a visit, a submitted form, straight from the server hosting the website.

For a local service business whose traffic is largely mobile, running the pixel and CAPI together gives Meta more complete data, and therefore more reliable targeting and measurement, without changing anything the visitor sees or does on the site.

The common mistake : Installing the pixel and assuming measurement is complete: without the Conversions API alongside it, a growing share of events simply never get through, because of blockers and browser restrictions.

Conversion event

A conversion event is a specific action, such as a submitted form or a call, that the pixel or Conversions API reports to Meta to measure a result.

Each event matches an action defined in advance, for example 'Lead' for a submitted form or 'Contact' for a click on the phone number. Meta calculates cost per result against that event, and learns to target people likely to take the same action.

For a local service business, which event gets tracked matters more than its name: tracking form submissions alone misses people who call straight from their phone without ever filling in a field, often the dominant behaviour on mobile.

The common mistake : Tracking only the form event when most prospects call directly: the campaign then looks like it is underperforming when it is actually generating calls that simply never get counted.

Attribution and attribution window

Attribution links a result to the ad that caused it, and the attribution window sets the time limit, for example seven days, within which that link still counts.

Meta cannot see someone's actual journey: it applies a rule to decide that a click or a view, occurring within the chosen window, led to the measured result. The most common window is seven days after a click or one day after a view.

For a local service business, this matters because the journey is often long: someone sees an ad, searches for the business name a week later, then calls directly without ever clicking again. Depending on the window chosen, that result either gets credited to the campaign or disappears from the numbers entirely, even though the ad genuinely caused it.

The common mistake : Comparing two campaigns using different attribution windows: the one set to a longer window will show mechanically more results, without actually performing any better.

Campaign and ad set budget optimisation (CBO, ABO)

CBO and ABO describe where the ad budget sits, at the campaign level, which spreads it across ad sets automatically, or at each ad set individually.

With CBO (Campaign Budget Optimization), a single budget is set for the whole campaign and Meta shifts it automatically toward the ad sets producing the most results. With ABO (Ad Set Budget Optimization), each ad set gets its own fixed budget regardless of its relative performance.

For a local service business testing several areas or service types at once, ABO gives more control: each area keeps its budget even if another performs better in the short term. CBO works better once the winning targeting is already known and the algorithm can be trusted to allocate spend on its own.

The common mistake : Using CBO during the testing phase across very different areas or audiences: the budget quickly concentrates on whichever ad set is easiest to optimise, often the biggest town, leaving the other areas never really tested.

Lead

Lead refers to a person who has shared their contact details to be followed up about a specific need, before any qualification of their intent or budget.

For a local service business, a raw lead says almost nothing about its value on its own. It can come from someone outside the service area, just gathering information, or with a budget well below the trade's average ticket.

A lead marks the start of the funnel, not a guaranteed sale. Treating it as a result in itself pushes a business to optimize the wrong number: more leads does not mean more signed jobs if quality drops as volume rises.

The common mistake : Mistaking the number of leads for the number of real opportunities. A campaign can produce plenty of leads and zero sales if nothing filters them after the ad.

Qualified lead

Qualified lead refers to a contact who matches criteria set in advance (area, project type, budget), before any judgment on how likely they are to buy.

The word means nothing until the criteria are written down. For a tradesperson or a building company, qualified usually comes down to three things: service area, project type, and a budget compatible with the trade's average ticket.

That definition needs to be set before a campaign launches, not after the first review. It is what determines whether a disappointing lead is an ad targeting problem or a sales follow-up problem.

How it is calculated : Qualified leads ÷ total leads

The common mistake : Every business defines a qualified lead differently. The agency and the client need to agree on what counts as qualified before any campaign runs, otherwise both sides end up measuring different things.

MQL and SQL

MQL and SQL name two stages of lead qualification: an MQL meets minimum marketing criteria, an SQL has been confirmed as a real opportunity through a sales conversation.

This split comes from B2B software, where several teams hand off the same lead before a sale closes. In a local service business, the same person often takes the call, assesses the project, and writes the quote: the two stages collapse into a single conversation.

The split still matters when an agency does a first pass (area, stated budget, project type) before handing the contact to the owner, who then confirms whether the project is real. The label matters less than having a clear handoff point between the two.

The common mistake : Borrowing the MQL/SQL vocabulary without tying it to a real handoff step in the business's own process. Without a concrete step behind each label, the distinction stays theoretical and does not help anyone sort leads.

Acquisition funnel

Acquisition funnel refers to the full sequence of steps a person moves through between first seeing an ad and becoming a customer, with each step filtering out part of the volume.

The funnel describes the full path: someone sees an ad, clicks, fills out a form or calls, becomes a lead, then a qualified lead, gets an appointment or a quote, and signs or does not. Each step keeps only part of the people who made it through the previous one.

For a job worth several thousand euros, the funnel is usually short in number of steps but long in duration: the decision is rarely made the same day. The biggest drop in volume is often between the lead and the appointment, not between the ad and the click.

The common mistake : Judging a campaign only by the top of the funnel (impressions, clicks) when most of the loss happens further down, at the qualification and follow-up stage.

Lead nurturing

Lead nurturing refers to the messages sent to a lead who is not yet ready to buy, to stay top of mind until their need becomes urgent.

A lead who does not call right away is not a lost lead. For a job worth several thousand euros (veranda, pergola, home extension), the decision often takes weeks or months to mature, with several quotes compared side by side.

Nurturing means staying visible during that period without following up empty-handed: recalling proof already shown, answering a likely objection, or surfacing a useful piece of information at the right moment. The goal is to be the provider still present when the need becomes urgent.

The common mistake : Sending the same generic message to every lead regardless of where they are in their decision. A lead who just requested a quote and one who has gone quiet for three months do not need the same message.

Close rate

Close rate (or closing) refers to the share of appointments or quotes that end in a signed sale, over a given period.

Closing happens on the phone or in person, not in an online form: it is the conversation that turns an appointment or a quote into a signed sale.

This number separates two different problems. A low close rate with well-qualified leads points to the sales process (speed to lead, pitch, price). A decent rate but too few leads points to acquisition. Confusing the two leads to fixing the wrong thing.

How it is calculated : Signed sales ÷ appointments or quotes completed × 100

The common mistake : Blaming the ad campaign for a poor close rate when the real cause sits in the sales follow-up: a callback that took too long, a missing follow-up, or a pitch that did not address the prospect's actual objection.

Average order value

Average order value refers to the average amount billed per customer over a given period, across every job or service combined.

For a business whose services range from a small repair to a full renovation, average order value smooths out very different amounts. It is a reference point, not a typical price.

This number shapes what a lead or a customer is actually worth, and therefore what is reasonable to spend acquiring one. A poorly estimated average order value skews every calculation built on top of it, especially revenue scenarios.

How it is calculated : Revenue ÷ number of sales

The common mistake : Using a generic industry average instead of the business's own real average order value. Published sector averages blend very different trades and areas and produce unrealistic scenarios.

Customer lifetime value

Customer lifetime value refers to the total revenue a customer generates over the full length of the relationship, beyond the first sale.

The first sale is often not the only one. A customer happy with a new pergola may come back for a home extension, refer the business to a neighbor, or hire the same provider for another project years later.

Customer lifetime value tries to capture that full picture instead of just the first invoice. It informs, without ever guaranteeing, what a customer can represent over time.

How it is calculated : Average order value × number of purchases over the relationship

The common mistake : Calculating LTV from the first job alone and ignoring referrals and repeat jobs, which understates a customer's real worth. This number stays an estimate, never a promised revenue figure.

Speed to lead

Speed to lead refers to the time between the moment someone submits their details and the moment the business first calls them back.

Speed to lead measures the time between the moment someone submits their contact details and the moment the business calls them back for the first time.

Several studies cited in the industry link a fast callback to a better contact and close rate, but these numbers remain orders of magnitude, not verified data for every trade or area, and a fast callback guarantees no specific outcome.

For a need perceived as urgent (a leak, a breakdown, a quote needed fast), people often contact several providers in parallel: whoever answers first has a real edge over whoever answers three days later, even if the size of that edge varies by trade.

How it is calculated : Time of first contact minus time of form submission

The common mistake : Presenting a fast callback as a promise of results. It is one factor among others, never a guarantee of a sale or an appointment.

Cold prospect and inbound lead

Cold prospect refers to a person contacted on the business's own initiative with no interest shown beforehand, inbound lead refers to a person who initiated the contact themselves.

A cold prospect has asked for nothing: the business calls or approaches them on its own initiative, with no interest expressed beforehand. An inbound lead, by contrast, initiated the contact themselves, usually after seeing an ad, a website, or a piece of content.

That difference changes the whole conversation. An inbound lead already has some interest to confirm and clarify. A cold prospect has no expectation yet: a legitimate reason for the contact needs to be established before the offer comes up at all.

The common mistake : Using the same script or message for both. An inbound lead who receives a cold-outreach approach finds it pointless, since they already expressed interest; a cold prospect who gets a sales pitch too early experiences it as intrusive.