Marketing KPIs: Are You Measuring What Matters?

The metrics you are measured against shape every decision you make. If your KPIs are wrong, or disconnected from what the business actually needs, you will optimise for the wrong things and still feel like you are doing your job. That is one of the more quietly damaging problems in marketing today.

Most marketing teams are not short of data. They are short of the right data, framed in the right way, connected to outcomes that matter to the people who sign off budgets. The question is not whether you have metrics. It is whether the metrics you have are honest proxies for business performance, or just activity dressed up as progress.

Why Most Marketing KPI Frameworks Start in the Wrong Place

When I was running agencies, one of the most revealing conversations I could have with a new client was asking them what metrics their marketing team reported on. The answer told me almost everything I needed to know about the state of their marketing function. Not because the metrics themselves were always wrong, but because of how they had been chosen and who they were chosen for.

The most common pattern was this: the team had inherited a set of metrics from whoever set up the analytics platform, added a few more over time as new channels came online, and ended up with a dashboard that reported on everything and meant very little. Sessions, impressions, followers, open rates, bounce rate. A clean PDF sent to the leadership team every month. Nobody questioned it. Nobody connected it to anything.

The problem with building a KPI framework from the tool upwards is that you end up measuring what is available rather than what is important. HubSpot has written about the difference between web analytics and marketing analytics, and it is a distinction worth sitting with. Web analytics tells you what happened on a page. Marketing analytics should tell you whether marketing is working as a business function. Those are very different questions.

If you want to build a measurement framework that holds up under scrutiny, you have to start with the business objective and work backwards. What does the business need marketing to deliver this year? Revenue contribution, qualified pipeline, customer acquisition at a target cost, brand consideration in a new segment. Start there, then ask what you would need to see in the data to know you are on track. That sequence matters.

If you are thinking more broadly about how analytics should sit within your marketing operation, the Marketing Analytics and GA4 hub covers the full landscape, from measurement strategy through to the tools and models that make it work in practice.

What Makes a Good Marketing KPI

A good KPI does four things. It is measurable with reasonable accuracy. It is connected to a business outcome, not just a marketing activity. It is something the team can actually influence. And it is honest about what it is a proxy for, rather than pretending to be something more precise than it is.

That last point is one most frameworks skip. Every marketing metric is a proxy. Cost per acquisition is a proxy for profitability. Click-through rate is a proxy for ad relevance. Brand search volume is a proxy for awareness. None of them are the thing itself. When you treat a proxy as a direct measure, you start optimising for the proxy rather than the underlying outcome, and that is where measurement goes wrong.

I spent time judging the Effie Awards, which measure marketing effectiveness. One of the things that stood out across the entries was how the strongest campaigns were built around a very small number of clearly defined outcomes, and how the measurement frameworks were designed to track those outcomes honestly, including acknowledging what could not be directly attributed. The weaker entries tended to have more metrics, not fewer, and the connection between those metrics and actual business results was often thin.

Fewer, better metrics almost always outperform broader, busier dashboards. Forrester has made this point directly: just because you can report on something does not mean you should. Every metric you add to a dashboard costs attention. Attention is finite. Use it on the numbers that drive decisions.

The Metrics That Tend to Matter Most, by Channel and Objective

There is no universal set of KPIs that works for every business. But there are patterns. What follows is not a definitive list, it is a set of principles about which metrics tend to carry real signal versus which ones tend to look good in a deck without telling you much.

Paid search and paid social are two channels where the temptation to optimise for the wrong thing is highest. Click-through rate, cost per click, and impression share are all useful diagnostic metrics, but they are not business outcomes. The metrics that matter are cost per acquisition, return on ad spend, and, if you can connect them, contribution to pipeline or revenue. I have managed hundreds of millions in ad spend across more than 30 industries, and the single most common mistake I saw was teams celebrating low CPCs while the business was acquiring customers at an unsustainable cost. The channel looked efficient. The economics did not work. Understanding how keyword data flows through your analytics is part of making that connection visible.

Content and organic search have a different problem. The metrics are often too long-cycle to be useful in monthly reporting, so teams default to traffic and rankings, which are activity metrics rather than outcome metrics. The metrics worth tracking here are qualified organic traffic to high-intent pages, assisted conversions from organic, and, where you can measure it, the role of content in shortening sales cycles or increasing conversion rates from other channels. Buffer’s breakdown of content marketing metrics is a useful reference for thinking through which signals are worth tracking at each stage of the funnel.

Email is a channel where vanity metrics have done a lot of damage. Open rates were always a flawed metric, and Apple’s Mail Privacy Protection changes made them even less reliable. The metrics that matter in email are click-to-open rate, conversion rate from email, revenue per email sent for e-commerce, and unsubscribe rate as a negative signal. Crazy Egg’s guide to email marketing metrics covers the mechanics of what each metric actually measures and where the gaps are.

Brand and awareness metrics are where most performance-focused teams fall short. Not because brand does not matter, it absolutely does, but because the metrics available are genuinely harder to connect to short-term outcomes. Brand search volume, share of voice, and sentiment tracking all carry signal, but they require longer time horizons and a willingness to hold uncertainty. The mistake is either ignoring brand metrics entirely because they are hard to attribute, or reporting them as if they are proof of business impact when they are really leading indicators at best.

The Vanity Metric Problem Is Worse Than Most Teams Admit

Vanity metrics are not just harmless noise. They actively distort how marketing is perceived and how decisions get made. When a leadership team sees a slide showing 2.4 million impressions and a 4.2% engagement rate, they are not necessarily seeing evidence of marketing effectiveness. They are seeing evidence of activity. Those two things are not the same, and the difference matters when it comes to budget decisions, headcount, and strategic direction.

I have sat in enough board rooms to know that senior stakeholders are often more sophisticated about this than marketing teams give them credit for. The CFO asking “what did that campaign actually deliver?” is not being obstructive. They are asking the right question. If your answer is a set of engagement metrics with no connection to revenue or pipeline, you have a measurement problem, not a communication problem.

The reason vanity metrics persist is partly structural. They are easy to generate, they look impressive at scale, and they are hard to argue with directly because they are technically accurate. But accuracy is not the same as relevance. A metric can be precisely measured and entirely useless at the same time.

One of the more useful exercises I have run with marketing teams is asking them to go through every metric on their standard report and answer one question: if this number doubled, would the business be materially better off? If the answer is no, or even uncertain, that metric probably should not be in the report. It is a blunt test, but it forces the right conversation.

How to Build a KPI Framework That Holds Up

Building a measurement framework that is actually useful requires a few things that most teams skip in the rush to get a dashboard live.

Start with a conversation about business objectives, not marketing objectives. What does the business need to achieve in the next 12 months? Revenue growth, customer retention, expansion into a new segment, reducing cost to serve. Marketing KPIs should be derived from those objectives, not from what the marketing team finds interesting to track. MarketingProfs has a practical framework for building a marketing dashboard that starts from this principle and works outward.

Then distinguish between outcome metrics, which measure whether you are achieving the objective, and diagnostic metrics, which help you understand why performance is moving in a particular direction. Outcome metrics belong in the leadership report. Diagnostic metrics belong in the team’s working view. Conflating the two is one of the main reasons marketing dashboards become unreadable.

Be explicit about what each metric is a proxy for and what its limitations are. This is not a sign of weakness in your measurement approach. It is a sign of intellectual honesty, and it builds more trust with senior stakeholders than a dashboard that implies false precision. I would rather present a CFO with three metrics I can defend completely than twelve metrics that look comprehensive but fall apart under a single probing question.

Set targets that are grounded in historical performance and business context, not aspirational numbers pulled from a planning template. A target that nobody believes is not a target. It is a fiction that makes quarterly reviews uncomfortable and annual planning worse. When I was growing teams through significant scale, the targets that actually drove behaviour were the ones the team had helped set, understood the rationale for, and could see a credible path to hitting.

Review the framework regularly. Business priorities shift. Channel mix changes. What was a meaningful metric eighteen months ago may have become a lagging indicator or an irrelevant one. A KPI framework that is never questioned becomes a ritual rather than a tool. Tools that surface trends automatically can help flag when the patterns in your data are shifting, but the interpretation and the decision about whether to update your framework is still a human one.

The Benchmarking Trap

One thing I want to call out directly is the way benchmarking is used in marketing measurement, because it is frequently misleading. Industry benchmarks for click-through rates, email open rates, conversion rates, and cost per acquisition are averages across a wide range of businesses, contexts, and objectives. They are interesting as a rough orientation but they are not a meaningful standard to be measured against.

I have seen too many marketing teams celebrate because their CTR is above the industry average, when the industry average is itself low and the conversion rate from those clicks is poor. Beating a low benchmark is not the same as performing well. The relevant benchmark is your own historical performance in the same context, not a sector average that aggregates very different businesses with very different models.

This is also true of AI-driven marketing performance claims. A lot of what gets reported as AI-driven improvement in marketing metrics is benchmarked against a very low baseline, either the team’s own underperforming prior period or an industry average that is not a meaningful comparator. The improvement is real in the narrow sense that the number went up. Whether it represents genuine progress for the business is a different question, and one that tends not to get asked.

The same critical lens applies to any metric that is improving. Ask what it is improving against, and whether that baseline is a meaningful one. If you cannot answer that question clearly, the improvement is not yet a result.

There is a lot more ground to cover when it comes to building measurement systems that actually serve the business. The Marketing Analytics and GA4 hub brings together the full set of frameworks, tool guides, and analytical thinking you need to make measurement work in practice, not just in theory.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

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