Your marketing is working if it is creating enough of the right commercial outcomes to justify the money, time and attention you are putting into it.

That does not automatically mean:

More followers.

More impressions.

More website visitors.

More likes.

More enquiries.

Even more leads.

Those can all be useful indicators.

But none, on its own, tells you whether the marketing is actually helping the business.

For most established small businesses, I would work backwards from the commercial outcome:

Revenue and profit

came from:

Customers

who came from:

Qualified sales opportunities

which came from:

Leads or enquiries

which came from:

People responding to marketing

which required:

The right people seeing something in the first place.

That is the marketing chain.

If you only measure one part of it, you can very easily convince yourself something is working when it isn't.

Start by deciding what marketing is supposed to achieve

This sounds obvious.

It isn't.

Ask:

“What is our marketing trying to do?”

and you may get:

Generate leads.

Build awareness.

Grow the brand.

Increase traffic.

Support sales.

Launch the new product.

Improve retention.

Enter another market.

All legitimate.

But they require different measures.

If the objective is generating sales opportunities, I care enormously about:

Qualified leads.

Opportunities.

Pipeline.

Customers.

Revenue.

If the objective is increasing awareness in a new market, expecting immediate sales from every activity may be unrealistic.

If the objective is retaining existing customers, acquisition metrics may tell you almost nothing useful.

You cannot judge whether marketing is working until you define what working means.

Marketing activity is not marketing performance

You posted 18 times.

Sent four newsletters.

Published six articles.

Spent £3,500 on Google Ads.

Ran an event.

Produced three videos.

Wonderful.

What happened?

Activity describes what Marketing did.

Performance describes what changed because of it.

This distinction matters because busy marketing departments can look incredibly productive.

Content calendar full.

Social posts scheduled.

Campaigns live.

Analytics dashboards everywhere.

Yet the sales team still says:

“We need more decent leads.”

That is a problem.

Not necessarily because marketing is failing.

Perhaps sales follow-up is poor.

Perhaps attribution is broken.

Perhaps the marketing is building future demand that has not matured yet.

But you need to investigate the relationship between the activity and the outcome.

Do not simply report the activity.

Your first measurement should sit at the bottom of the funnel

Start with what the business ultimately receives.

Depending on your model, that could be:

Revenue.

Gross profit.

New customers.

Recurring revenue.

Bookings.

Contracts.

Orders.

Customer lifetime value.

Do not necessarily demand immediate revenue attribution from every individual marketing action.

But your marketing system as a whole eventually has to produce commercial value.

Otherwise you have built an expensive publishing department.

Revenue alone is still not enough

Suppose two marketing channels each generate £100,000 of sales.

Channel A costs £10,000.

Channel B costs £30,000.

Easy.

Channel A looks better.

Except perhaps Channel A's customers buy low-margin work producing £20,000 gross profit.

Channel B's customers produce £50,000.

Now the picture changes.

Or perhaps customers from Channel A typically stay five years.

Channel B customers buy once.

Changes again.

This is why mature marketing measurement increasingly connects marketing data with:

Sales.

Customer.

Revenue.

Margin.

Not merely traffic.

The best metric depends on the economics of your particular business.

Work backwards from customers

Ask:

How many new customers did we win?

Then:

Where did they come from?

How much did we spend creating them?

What did they buy?

What margin did they generate?

How long did the sales process take?

What happens after the first purchase?

For some businesses, this is easy.

An e-commerce customer clicks an advert and buys online.

For many established B2B companies, it is much messier.

Someone:

Reads an article.

Sees you again on LinkedIn.

Signs up for a newsletter.

Hears your name from somebody else.

Returns through Google.

Downloads something.

Speaks to a salesperson.

Waits two months.

Then buys.

Which piece of marketing “caused” the sale?

Probably not one of them in isolation.

That is why marketing attribution needs some humility.

Attribution is a model, not a time machine

Marketing platforms can assign credit to different touchpoints.

Google Analytics 4, for example, allows marketers to analyse key-event paths and use attribution models to distribute credit across interactions leading to important actions. Google explicitly describes attribution models as rules or algorithms for deciding how credit should be assigned between touchpoints.

That wording matters.

Assigning credit.

Not discovering absolute truth.

A last-click model might say Google Search generated the customer because that was the final interaction.

But perhaps the customer searched for you because they had already:

Seen your article.

Heard your podcast interview.

Received your email.

Been referred by a customer.

Watched three videos.

The search click may have captured existing demand rather than created it.

Attribution can make measurement better.

It does not make customer behaviour beautifully linear.

This is why marketing and sales need to share data

For a lead-generation business, one of the biggest mistakes is allowing the measurement to stop at:

Form submitted.

That is not necessarily a successful marketing outcome.

Someone asking for a quote might be:

An ideal customer.

A student.

A competitor.

Somebody looking for a £500 service when your minimum engagement is £20,000.

A current customer submitting through the wrong page.

A salesman trying to sell you SEO.

All count beautifully as form submissions.

They are not commercially equal.

Google Analytics now has dedicated lead-generation reporting that can use recommended events to follow lead acquisition, while Google Ads supports feeding qualified and closed offline lead information and values back from CRM systems.

That is the direction I would want an established B2B business moving towards.

Not:

Which channel generated the most forms?

But:

Which channel generated the most commercially valuable opportunities and customers?

Agree what a lead actually is

Marketing says:

“We generated 120 leads.”

Sales says:

“No you didn't.”

Marketing opens dashboard.

1. 
   

Sales opens CRM.

18 worth calling.

Neither side is necessarily lying.

They are using different definitions.

Create clear stages.

For example:

Enquiry

Someone has contacted you.

Marketing-qualified lead

They broadly fit defined criteria and have shown meaningful interest.

Sales-qualified opportunity

Sales has established that there is a credible requirement, fit and commercial possibility.

Proposal or quotation

A genuine commercial opportunity has reached that stage.

Customer

Money changed hands.

Your exact language does not matter.

Consistency does.

Once marketing and sales use the same definitions, you can finally measure the journey.

Measure lead quality, not merely lead quantity

Suppose Campaign A produces:

100 leads.

Campaign B produces:

1. 
   

At first glance, A wins.

But then Sales qualifies:

10 from Campaign A.

20 from Campaign B.

Suddenly the smaller campaign created twice as many meaningful opportunities.

Then suppose:

2 of Campaign A's opportunities buy.

8 of Campaign B's buy.

The original lead-volume comparison has become almost meaningless.

This is why cost per lead can be a dangerous metric when used alone.

A £20 lead that never becomes a customer is infinitely more expensive than it first appeared.

A £200 lead that regularly produces £20,000 of profitable work may be excellent value.

Build the marketing measurement chain

I would measure marketing across several levels.

Not because every company needs an enormous dashboard.

Because each level diagnoses a different problem.

Level 1: Visibility

Are enough of the right people seeing you?

Depending on the channel, this might include:

Impressions.

Reach.

Search visibility.

Advertising exposure.

Email delivery.

Audience growth.

These are leading indicators.

Useful.

Not the finish line.

If nobody sees the marketing, nothing else can happen.

But seeing something is not buying something.

Level 2: Response

Did people do anything?

That might include:

Website clicks.

Email clicks.

Search clicks.

Calls.

Downloads.

Video engagement.

Event registrations.

Direct messages.

Responses.

Search Console is particularly useful for organic search because its performance reporting shows Google Search impressions, clicks, click-through rate and average position and can break the data down by query, page, device, country and other dimensions.

This can tell you whether your visibility in Google is improving and whether that visibility is translating into visits.

It still cannot tell you whether those visits became good customers.

That requires the next stage.

Level 3: Website or landing-page conversion

Once people arrive, do they respond?

For a lead-generation business:

How many visitors become enquiries?

Which pages generate them?

Which traffic sources produce them?

Which campaigns?

Google Analytics' acquisition reporting can show how users and sessions reached the website across sources and channels, while businesses can define key events for actions considered important to business success.

But do not mark every remotely interesting website behaviour as equally valuable.

Someone scrolling down a page is useful behavioural information.

Someone requesting a consultation is considerably closer to a commercial outcome.

Know the difference.

Level 4: Lead quality

Now connect the website to the CRM.

For each meaningful source or campaign:

How many enquiries?

How many were qualified?

How many became genuine opportunities?

How many were rubbish?

How many came from existing customers?

How many were outside your market?

This is where marketing starts receiving useful feedback rather than merely website statistics.

Level 5: Sales pipeline

How much opportunity value did marketing create?

Suppose Marketing Generated Source A creates:

20 qualified opportunities worth £400,000.

Source B creates:

8 opportunities worth £500,000.

Which is better?

We still don't know.

What is the probability of winning?

What margin?

What sales cycle?

What happens historically?

But now we are discussing commercial value rather than web traffic.

Level 6: Customers and revenue

How many opportunities became customers?

What did they spend?

What did it cost to acquire them?

How quickly?

What was the average deal value?

If the marketing objective is customer acquisition, this is where it eventually has to arrive.

Level 7: Profit and customer quality

Then ask the question many marketing dashboards never reach.

Were they actually good customers?

Article #65 explored why revenue and customer value are not the same thing.

Marketing can generate customers that:

Buy low-margin work.

Pay late.

Consume enormous service capacity.

Churn immediately.

Create fantastic revenue and dreadful profit.

If Marketing is rewarded exclusively for acquisition volume, it may rationally produce customers the rest of the business does not particularly want.

Feed profitability and customer quality back into the marketing system.

Cost per acquisition matters more than cost per click

Cost per click is useful for diagnosing advertising performance.

It is not the ultimate commercial measure.

Imagine one campaign:

£1 per click.

Another:

£5.

The first appears dramatically cheaper.

But if the £1 clicks produce almost no qualified opportunities while the £5 clicks produce customers, the expensive traffic may be vastly better.

Move through the funnel.

Ask what you actually paid for:

The lead.

The qualified opportunity.

The customer.

Then compare that with the commercial value created.

Calculate customer acquisition cost properly

At a simple level:

Customer acquisition cost = total relevant sales and marketing acquisition cost divided by new customers acquired.

But decide what you are including.

Advertising?

Agency?

Software?

Content production?

Marketing employee salaries?

Sales development?

Sales commissions?

Event costs?

Your answer depends on what you are trying to understand.

Do not compare:

A fully loaded acquisition cost from one channel

with:

Ad spend only from another.

Keep definitions consistent.

Return on ad spend is useful but narrower

If you spend £5,000 on advertising and attribute £25,000 of revenue to it, your return on ad spend is:

5:1.

Useful.

But it ignores:

Cost of goods or service delivery.

Agency costs.

Internal marketing costs.

Sales costs.

Customer quality.

So ROAS can help compare advertising performance.

It is not identical to marketing profitability.

Google Ads itself supports conversion-value reporting and metrics based on conversion value relative to advertising cost, precisely so advertisers can move beyond counting conversions and towards the value those conversions generate.

The closer your measurement gets to actual economic value, the more useful it becomes.

Use gross profit where revenue is misleading

Suppose Marketing generates £1 million in sales.

Sounds excellent.

But the work averages 15 per cent gross margin.

Another channel generates £600,000 at 45 per cent.

The smaller revenue source creates:

£270,000 gross profit.

The larger one:

£150,000.

That changes the marketing conversation considerably.

For businesses with materially different margins across customers, services or products, connecting marketing to gross profit can be far more informative than revenue alone.

Beware vanity metrics

I do not believe impressions, followers and engagement are automatically useless.

They become vanity metrics when they are reported without a clear relationship to the objective.

If the goal is brand awareness, reach matters.

If the goal is selling £30,000 consulting projects, celebrating 400 Instagram likes while pipeline collapses deserves questions.

The metric is not vain.

The interpretation is.

Ask:

Why are we measuring this?

What decision will it help us make?

If nobody can answer, remove it from the management dashboard.

Website traffic is particularly easy to celebrate

Traffic up 40 per cent.

Brilliant.

From where?

For what searches?

To what pages?

From which countries?

Did those visitors fit the market?

Did they enquire?

Did enquiries qualify?

Traffic can increase because you published something enormously popular with people who will never buy from you.

That might still create awareness or links.

Fine.

But do not automatically equate more traffic with better marketing.

Search Console lets you inspect which search queries and pages are generating Google visibility and clicks, while GA4's traffic-acquisition reports allow traffic to be segmented by source, medium and channel.

Use that information to understand why traffic changed.

SEO should not be judged purely by rankings

This matters particularly for an article-led strategy.

People obsess over:

“We're number three for this keyword.”

Useful.

But rankings fluctuate.

Different searches produce different results.

And a ranking for a query nobody relevant uses has limited commercial value.

For SEO, I would look across:

Impressions.

Relevant query visibility.

Clicks.

Traffic to commercially useful pages.

Enquiries influenced or generated.

Qualified opportunities.

Ultimately customers and revenue where attribution is possible.

Search Console itself makes impressions, clicks, CTR and average position available precisely because search performance contains several dimensions, not one magic ranking number.

The best SEO creates visibility around problems your potential customers genuinely have.

Then gives them something useful enough to remember you.

Some will convert immediately.

Many will not.

Marketing can work before somebody is ready to buy

This is where direct attribution becomes dangerous.

Imagine an owner searches:

How much cash should a small business keep in reserve?

They read your article.

Useful.

They leave.

Three months later, they search:

business coach for established business owners

See you again.

Then they hear your name from someone.

Then visit directly.

Then book.

What generated the customer?

The final Google search?

The original article?

The referral?

All of them?

Probably some combination.

GA4's attribution-path reporting exists specifically because customers can encounter multiple touchpoints before completing a key event, and it can show channels that initiate, assist and close those paths.

This is why I would never judge useful long-form content solely on whether somebody clicked Book a Call immediately after reading one article.

Content can create memory before it creates action.

But do not use “brand building” to avoid accountability

The opposite problem also exists.

Marketing performs badly.

Someone says:

“It's brand awareness.”

For eighteen months.

Fine.

What evidence suggests awareness is changing?

You might look at:

Relevant reach.

Branded search.

Direct demand.

Search volume for your name or company where available.

Survey evidence.

Share of voice.

More people mentioning they already know you.

Inbound opportunities citing content.

Organic/direct traffic trends interpreted cautiously.

Event attendance.

Newsletter growth among the right audience.

Sales conversations becoming easier because prospects have already consumed your work.

Brand marketing is harder to attribute.

That does not mean it is impossible to measure anything.

Ask new customers how they found you

High technology solution:

Ask them.

Seriously.

Add a question.

“How did you first hear about us?”

Not:

“What was your last click before purchasing?”

Their answer may reveal things analytics misses.

Podcast.

Friend.

Saw your vans everywhere.

Read one of your books.

LinkedIn.

Google.

Trade association.

Can't remember, but have known the company for years.

Self-reported attribution has limitations too.

Human memory is imperfect.

Use it alongside digital data.

Not instead of it.

Track source properly inside the CRM

A surprisingly good measurement system might begin with a handful of fields.

Original source.

Current or latest meaningful source where useful.

Campaign.

Lead date.

Qualification status.

Opportunity value.

Sale date.

Revenue.

Perhaps gross profit or customer category.

Then make sure employees actually complete them consistently.

A breathtaking dashboard built on incomplete CRM data is merely a more expensive way to be wrong.

Use campaign tagging consistently

If you send people to the website from:

Email.

LinkedIn.

Partners.

Paid campaigns.

Online events.

Other trackable campaigns.

use consistent campaign tagging where appropriate.

Otherwise GA4 may struggle to distinguish one marketing initiative from another accurately.

Google's traffic-source dimensions are specifically designed to help identify sources, media and campaigns associated with visits and acquisition.

Naming discipline is boring.

It is also the difference between:

October_Newsletter

and:

email / something / maybe

six months later.

Check whether the tracking actually works

This sounds embarrassingly obvious.

Form submitted.

Does Analytics record it?

Phone call.

Is it captured where appropriate?

Purchase.

Does the value pass through correctly?

CRM status changes.

Can you connect it back?

Google Analytics provides Realtime and DebugView specifically so key-event implementations can be checked rather than simply assumed to be recording properly.

I have seen businesses make serious marketing decisions using tracking everybody assumed worked.

Test it.

Your tracking must also be legally appropriate

Measurement is not a licence to collect everything imaginable about everybody visiting your website.

The Information Commissioner's Office published final updated guidance on storage and access technologies in April 2026, covering technologies including cookies, tracking pixels and device fingerprinting and incorporating changes introduced by the Data (Use and Access) Act.

Make sure your measurement setup complies with the current rules applicable to what you are using.

Particularly where:

Personal data.

Tracking technologies.

Advertising.

Profiling.

Third-party platforms

are involved.

The ICO guidance is the sensible place to start, and specialist advice may be appropriate for more complex setups.

Marketing data will never be perfect

This is important because businesses can disappear down a measurement rabbit hole.

Cookie restrictions.

Multiple devices.

Offline conversations.

Word of mouth.

Long sales cycles.

Several decision-makers.

People seeing things without clicking.

Someone forwarding your article to their business partner.

A customer Googling your brand from another device three weeks later.

You are not going to reconstruct every journey perfectly.

Google itself uses modelling in some Analytics reporting where key events cannot be directly observed because of privacy or technical limitations.

So aim for decision-useful evidence.

Not omniscience.

Compare periods sensibly

One month can lie.

Seasonality.

A large contract.

An event.

Budget timing.

A campaign launch.

A bank holiday.

A particularly strong salesperson closing old pipeline.

Marketing should be reviewed over a period appropriate to your sales cycle.

If the average journey from first enquiry to sale is six months, judging last month's marketing solely against last month's revenue makes little sense.

You need cohorts and pipeline.

For example:

What happened to leads created in January?

How many qualified?

How many eventually purchased?

What value did they create?

That gives marketing enough time to mature.

Long sales cycles need leading and lagging measures

If customers take nine months to buy, you cannot wait nine months before deciding whether marketing is heading in the right direction.

Use both.

Leading measures

Relevant visibility.

Traffic.

Responses.

Enquiries.

Qualified leads.

Opportunity creation.

Pipeline value.

Lagging measures

Customers.

Revenue.

Gross profit.

Customer acquisition cost.

Lifetime value where meaningful.

Leading indicators help you steer.

Lagging indicators tell you whether the journey ultimately arrived anywhere useful.

You need both.

Compare channel quality, not only channel volume

Perhaps:

Organic search creates fewer enquiries but excellent buyers.

Google Ads creates strong volume but high acquisition cost.

LinkedIn rarely creates direct leads but appears repeatedly in customer journeys and self-reported attribution.

Email converts existing demand exceptionally well.

Referral partnerships create the highest-value customers.

Now you have a portfolio.

The question becomes:

What role does each channel play?

That is much more sophisticated than:

“Which channel won?”

Different channels can perform different jobs.

Stop comparing channels using different scoreboards

Marketing reporting often does this:

Google Ads reports attributed conversions.

LinkedIn reports engagement.

SEO reports traffic.

Email reports opens.

Events report attendees.

Then management tries to compare them.

You cannot meaningfully compare:

Clicks

with:

Revenue

with:

Attendees

as though they represent equivalent outcomes.

Bring channels onto a shared commercial funnel where possible.

How many:

Responses?

Leads?

Qualified opportunities?

Customers?

How much:

Revenue?

Gross profit?

What did each channel cost?

Now comparison becomes better.

Not perfect.

Better.

Watch conversion rates through the funnel

If marketing feels weaker, find where the change happened.

Imagine:

Visibility unchanged.

Traffic unchanged.

Enquiries down.

That suggests a conversion problem.

Or:

Traffic up.

Enquiries up.

Qualified opportunities down.

That suggests lead quality deteriorated.

Or:

Qualified opportunities healthy.

Sales down.

Maybe the issue is further downstream.

Sales conversion.

Pricing.

Competitors.

Response speed.

Do not blame marketing for every revenue problem merely because marketing sits near the beginning.

Article #59 made the same point about diagnosing falling sales before taking action.

Follow the numbers through the system.

Marketing and sales should disagree less about facts

They can disagree about interpretation.

Healthy.

But they should share the basic numbers.

How many leads?

How many qualified?

How many opportunities?

How many sales?

What values?

What sources?

If Marketing has one version and Sales another, your first priority is data plumbing.

Not campaign optimisation.

A simple worked example

Imagine you spend £6,000 per month on marketing.

It creates:

120 enquiries.

Forty become qualified opportunities.

Twelve become customers.

Those customers generate £72,000 of initial revenue.

Average gross margin is 40 per cent.

That creates £28,800 of gross profit before wider sales and marketing costs.

Your basic marketing spend per customer is:

£500.

Now suppose next month marketing celebrates because enquiries rise to 180.

Fantastic?

Perhaps.

But only 25 qualify.

Six become customers.

Revenue becomes £36,000.

Lead volume increased 50 per cent.

Commercial output halved.

The marketing dashboard looks better.

The business outcome looks considerably worse.

That is why you measure the whole chain.

Build a monthly marketing scorecard

Keep it short enough that management actually reads it.

I would usually want visibility across five areas.

Investment

How much did we spend?

Include the costs relevant to the decision you are making.

Reach and acquisition

Where did attention and website traffic come from?

What materially changed?

Lead generation

How many enquiries?

From where?

At what cost?

Lead quality and pipeline

How many qualified?

How many opportunities?

What pipeline value?

Commercial return

How many customers?

Revenue?

Gross profit where practical?

Acquisition cost?

Then add commentary.

What happened?

Why?

What are we changing?

A scorecard should provoke decisions.

Not merely prove Marketing has statistics.

Review trends, not isolated numbers

Look over:

Three months.

Six months.

Twelve months.

Depending on the metric and sales cycle.

Which channels are strengthening?

Which are deteriorating?

Is acquisition cost moving?

Are lead volumes stable?

Is quality improving?

Is website conversion changing?

Are customer values changing?

One number is a photograph.

A trend is a film.

You need both.

Review marketing with Sales in the room

Marketing should hear:

“The leads from that campaign look great in Analytics but almost none have budget.”

Sales should hear:

“Thirty-eight per cent of the leads we sent received no recorded follow-up within three days.”

Now you have a useful discussion.

Without shared review, each department can blame the other indefinitely.

Marketing:

“Sales can't close.”

Sales:

“Marketing leads are shit.”

Perhaps both are partly right.

Find out.

Response speed belongs in the measurement too

Marketing can generate an excellent lead and still receive the blame for a poor outcome if nobody responds properly.

Measure:

How quickly are enquiries contacted?

How many attempts occur?

What happens after the first conversation?

Are follow-ups consistent?

Do people disappear because your sales process is weak?

Marketing ends where Sales begins only on an organisation chart.

The customer experiences one journey.

Measure accordingly.

Sometimes your best marketing channel is invisible in the dashboard

Referrals are the obvious example.

A customer recommends you privately.

Someone searches the company name.

Google Analytics records organic search.

Did SEO generate the customer?

It helped them find you.

But the referral created the demand.

This is another reason source-of-awareness questions matter.

Likewise, a person may read months of LinkedIn content and later type the web address directly.

The dashboard sees direct traffic.

The person experienced months of marketing.

Do not become so obsessed with measurable clicks that you stop investing in things known to influence buyers but poorly captured by attribution.

But equally, do not let unmeasurable become unquestionable

Someone tells you:

“You can't measure this stuff.”

You probably can measure something.

Not everything.

Something.

What changed after the campaign?

Relevant demand?

Website behaviour?

Brand search?

Enquiry volume?

Sales conversations?

Customer awareness?

Event attendance?

Pipeline?

At minimum, define the hypothesis.

What do we think this marketing will cause?

Over what period?

What evidence would support or challenge that belief?

That is better than:

“It feels like good exposure.”

Ask what would happen if you stopped

This is a powerful question for recurring marketing spend.

If we stopped this channel for three months:

What do we expect to happen?

Would leads fall?

Would branded demand fall?

Would nothing change?

Could we test it safely?

You do not have to switch everything off.

But thinking counterfactually helps.

Marketing expenditure often survives because:

“We've always done it.”

The same reason bad processes survive.

Run controlled tests where practical

Change one meaningful thing.

Offer.

Audience.

Landing page.

Message.

Channel.

Budget.

Then measure.

If you change:

Website.

Pricing.

Campaign.

Offer.

Targeting.

Sales script.

and lead qualification

all in the same fortnight, good luck explaining which one caused the result.

Perfect laboratory testing is rarely possible inside an SME.

But disciplined experimentation is.

Make it easier to learn.

Do not optimise too early

Twenty website visits is not enough information to conclude:

“The new landing page doesn't work.”

Likewise one enormous deal can make a weak channel look extraordinary.

Use enough data to make the decision proportionate.

The lower the volume, the more judgement and patience you may need.

This is especially true for high-value B2B businesses where ten new customers might represent an exceptional year.

Marketing measurement needs to fit the business model.

Marketing effectiveness is ultimately about decisions

This is the purpose of all the numbers.

Do we:

Spend more?

Spend less?

Change the message?

Change the audience?

Improve the landing page?

Stop the campaign?

Create more content around a particular problem?

Improve sales follow-up?

Increase capacity because demand is working?

Reallocate budget?

If the dashboard contains 64 metrics and produces no decisions, it is decoration.

The five questions I would ask every month

1. Did we create enough demand?

Not simply enough attention.

Enough relevant response.

2. Was the demand good enough?

Qualified prospects, not merely contacts.

3. Did Sales convert it?

If not, why?

4. Was the resulting business commercially attractive?

Revenue, margin and customer quality.

5. What are we going to change because of what we learned?

That final question turns reporting into management.

So, is your marketing working?

You should eventually be able to explain something like:

“We spend approximately £12,000 per month across search, content, email and events. That produces around 70 monthly enquiries, of which roughly 30 become qualified opportunities. We win around nine new customers, generating approximately £110,000 of initial revenue at our normal margin. Organic search creates fewer leads than paid search but a higher proportion qualify, while events produce low volume but our highest-value opportunities. Website conversion has fallen over the past two months, so that is the current priority.”

That is useful.

Compare it with:

“Website traffic is up 22 per cent and we got loads of LinkedIn impressions.”

Maybe your marketing is working.

Maybe it isn't.

You haven't told me enough to know.

Marketing measurement becomes useful when you stop asking:

“How much activity did we create?”

and start asking:

“What commercial movement did this activity produce?”

Measure from attention to response.

Response to lead.

Lead to opportunity.

Opportunity to customer.

Customer to revenue and profit.

Accept that attribution will never be perfect.

Then use the evidence you do have to make better decisions.

The objective is not a beautiful marketing dashboard.

It is knowing which marketing deserves more of your money and which deserves less.