Digital marketing was one of the most important advances in the history of the profession. I spent years inside it, and I would not give any of it back.
It gave businesses direct access to their customers. It made testing faster and cheaper. It let a small company reach a market that used to need a national media budget. And it let marketers watch what customers did instead of guessing.
It also had a consequence nobody planned. As the channels became measurable, running the channels became the centre of how marketing was organised, judged and understood. Marketers became specialists in search, social, automation, analytics, content and conversion. The larger decisions, which customers to serve, what to offer them, at what price and through which route to market, moved to other parts of the business.
The result is a contradiction I have watched in rooms I was sitting in. Marketing has more data, more technology and more specialist skill than at any point in its history, and less say over the decisions that decide whether the business grows. Forty-seven per cent of CMOs say their company views marketing as an expense rather than a strategic investment, according to a Gartner survey of 395 CMOs in early 2024. Only 52 per cent of senior marketing leaders say they can prove marketing’s value and get credit for it, according to a separate Gartner survey of 378 leaders the same year.
This is not an essay against digital marketing. It is an essay about what we traded away while we were getting good at it, because AI is about to offer us the same trade again.
Digital gave marketing more to measure and less to decide.
In the first edition, Everyone Can Now Build. Few Know How to Market., I argued that AI is creating far more builders than marketers. In the last, AI Isn’t Replacing Marketers. It’s Changing What Marketers Are Paid to Do., I argued that execution is becoming cheap and judgement is what employers will keep paying for. This edition is about how that judgement left the marketing department in the first place. It was not taken from us. We gave it away one trade at a time, and each trade looked sensible when we made it.
Digital was a real advance
Search let a business appear at the exact moment a customer expressed a need. Websites let customers research, compare and buy on their own terms. Email gave every company a direct, cheap channel to the people who had already bought. Social platforms let customers talk back. And a campaign could be launched, watched and adjusted in days rather than months.
Digital also gave marketing a way to prove its worth. The profession had always struggled to connect its spending to the company’s results. Digital platforms supplied a chain of measures that appeared to link exposure, behaviour and revenue: impressions counted, clicks tracked, leads attributed, conversion paths observed, and the cost of winning a customer set beside the revenue that customer produced.
Many of those measures are still useful. A conversion rate tells you whether a landing page works. Cost per lead tells you which of two tactics is cheaper. The problem was never that marketing became measurable.
The problem was that measurable activity, clicks, leads and conversions, became the definition of marketing.
The channel replaced the discipline
“Digital marketing” originally described a set of channels: search, websites, email and social. Then it became a profession of its own, with its own roles, teams, agencies and qualifications. Marketing departments were split into paid search, paid social, content, lifecycle, automation, ecommerce, conversion optimisation and analytics.
Specialisation was the right response. A search specialist has to understand auction dynamics and keyword intent. An automation practitioner has to understand data architecture and journey logic. An analyst has to make sense of enormous volumes of behavioural data. None of that is learned in a month, and doing it badly wastes real money.
The cost was that no single team was responsible for the customer’s full experience of the company. A customer does not experience a business as a set of channel teams. They meet the product, the website, the salesperson, the service desk, the advertising and the price as one relationship, and each of those contacts affects whether they buy again. Inside the company, each of those contacts is owned by a different team with its own targets. The search team optimises search. The social team optimises engagement. The website team lifts conversion. The media team hits its campaign numbers. Every team does its job well, and nobody is responsible for the decisions that determine growth: which customers to prioritise, what the business offers them that a competitor does not, and how much of this year’s budget should go to buyers who will not purchase until next year.
When a marketing department is organised by channel, the channel becomes the starting point for every conversation. The planning meeting opens with what to do on social, in search, in email and on the website. It should open with the customer and the commercial problem.
Organise marketing by channel and the channels will decide the strategy.
The measurable replaced the valuable
Digital did not only multiply the number of measures. It changed how fast they arrived. Traditional marketing effects built slowly and were hard to isolate. Digital platforms reported within hours, in numbers that could sit on a dashboard and be discussed at the next performance meeting. That made digital activity far easier to manage, and it handed short-term measures a decisive advantage inside the company.
A click can be counted today. The effect of brand advertising on memory can be measured too, through brand tracking, brand lift studies and marketing mix modelling, but those take longer, cost more and arrive as estimates rather than counts. A lead can be entered in a system today. Familiarity among buyers who will not purchase for two years shows up in next year’s tracking study. When a manager has to show results by the end of the quarter, the click wins, because it is on the dashboard now and the brand tracker is not due until next year.
I have sat in the meeting where this happens. A modest brand investment is on the table beside a retargeting budget. The retargeting budget arrives with a chart showing cost per conversion to two decimal places. The brand investment arrives with a theory about buyers who are not in the market this year. The budget follows the chart. Everyone in the room behaves reasonably, and the brand budget shrinks again.
Les Binet and Peter Field documented this in The Long and the Short of It, using the IPA databank to separate short-term activation, which converts demand that already exists, from long-term brand building, which creates demand that does not exist yet. Their warning was specific: using very short-term online metrics as the main measure of performance damages long-term results. A campaign can have a strong click-through rate and change nobody’s behaviour. A channel can report a handsome return while taking credit for customers who would have bought anyway. A team can beat its lead target and create very little revenue.
The problem deepens when a measure stops being an observation and becomes a target. Once a metric is a target, people organise their work around moving it. That is the idea usually associated with Goodhart’s law. Reward a team for lead volume and it will find the audiences that produce cheap leads, whether or not they ever become customers. Let cost per acquisition run the budget and the money goes to the people easiest to convert, not the ones worth the most. Treat return on ad spend as the measure of effectiveness and the channels that capture existing intent will always beat the channels that created it.
A team measured on lead volume will learn to produce leads. It can hit its lead target every quarter for a year while revenue falls, because the leads it found were never going to buy. Nobody in that team has done anything wrong. They have done what the target asked.
A measurement framework is not an admin choice. It decides where the money goes.
Attribution counted the last click and called it the cause
Attribution was digital marketing’s biggest promise. For the first time, marketers appeared able to follow a customer from exposure to purchase and assign value to every step, as if marketing spend could be audited like a ledger.
The difficulty is that seeing an event before a purchase does not prove it caused the purchase. A customer who searches for a company by name, clicks the ad and buys may have been shaped by years of recommendations, brand advertising and product reputation. The final click is visible because it happened close to the sale, not because it created the demand.
Observational attribution methods “often fail to accurately measure the true effect of advertising”, even after controlling for extensive demographic and behavioural data. That is the conclusion of Brett Gordon and colleagues in Marketing Science in 2019, after comparing 15 large randomised advertising experiments on Facebook with the attribution methods the industry normally relies on. Randall Lewis and Justin Rao found something harder still, in the Quarterly Journal of Economics in 2015. Across 25 large field experiments with major US retailers and brokerages, most reaching millions of customers, individual purchasing was so volatile relative to the effect of advertising that the median confidence interval on return on investment was more than 100 percentage points wide. Even experiments at that scale could not pin the answer down.
None of this means marketing cannot be measured. It means the answer is rarely as simple as a platform dashboard makes it look. Les Binet has written that in the early years of digital “not every click translated to a genuine, incremental conversion”, and his advice is to combine attribution, experiments and marketing mix modelling, because attribution shows which touchpoints came before a sale, experiments show whether the advertising caused it, and mix modelling shows how spending across channels relates to sales over time. Digital gave us far more information about what customers did. We treated it as a full account of why.
The last click gets the credit because it is closest to the sale, not because it caused the sale.
Optimisation replaced diagnosis
Optimisation is one of digital marketing’s real strengths. Audiences can be refined, creative tested, friction removed and money moved toward whatever is working. But optimisation always starts with a system that already exists. It improves a chosen activity against a chosen objective. It cannot tell you whether the activity was the right one to choose.
A team can lift the conversion rate of a landing page without asking whether the offer is strong enough. It can cut the cost of a lead without asking whether the company is chasing the right market. It can improve email open rates without asking whether anyone wants the emails.
Diagnosis starts earlier. It looks at the market, the customer, the category, the product and the price before deciding what to do. Digital tilted companies toward optimisation because improvement could be watched every day: the dashboard showed what moved since yesterday, the platform recommended the next change, and the next test was always ready to run.
Diagnosis is slower, and it carries a risk optimisation never does. It may find that the problem does not belong to the marketing team at all. The offer may be no different from the competitor’s. The price may not match what customers think the product is worth. The product may be wrong for the segment. The company may simply be hard to buy from. Those findings cross into other departments and ask them to change decisions they have already made.
It is always easier to adjust the campaign than to reopen a decision the company has already made.
Capture replaced creation
Digital channels are very good at finding people who already want to buy. Search catches a customer who is looking. Retargeting reaches someone who has already visited. Automation nurtures a known prospect. Review sites influence a buyer who is comparing options. All of that is worth doing, because a business should make it easy for an interested customer to find it, understand it and choose it. The problem starts when capturing demand is mistaken for the whole of marketing.
Up to 95 per cent of business buyers are not in the market for a category at any given time, according to John Dawes’s research with the Ehrenberg-Bass Institute and the LinkedIn B2B Institute. Dawes presents the ratio as a rule of thumb rather than a law, and the point holds across most categories: most of your future customers cannot be converted today, however precisely a platform can target them, because they already have a supplier, or have no need this quarter, or are under contract without budget. What marketing can do is shape what they remember when the need arrives. Dawes argues that advertising works mainly by creating and refreshing the memories a buyer draws on when the buying situation comes around.
Digital performance systems favour the people closest to purchase, because their behaviour is easy to see and their response arrives fast. So the money accumulates around search, retargeting, lead generation and conversion, because those activities can show they are close to revenue.
Being close to the revenue is not the same as having created it.
Capture and creation are both necessary. The danger is that one of them looks more accountable because its effects are easier to count.
Promotion replaced marketing
The narrowing of marketing was never only a measurement problem. Over time it changed where marketing sat in the company.
Marketing in its full sense covers the creation, communication, delivery and exchange of value. That is the American Marketing Association’s definition, and communication is one of its four verbs. Philip Kotler’s planning sequence in Marketing Management starts with research and moves through segmentation, targeting and positioning before it reaches the marketing mix and implementation. The discipline was designed as a series of decisions about the market and the offer, with execution near the end.
In many companies today, marketing enters near the end instead. Product decides what gets built. Leadership picks the growth market. Finance sets the price. Sales chooses the priority accounts. Customer experience sits in a function of its own. Marketing receives the finished offer and is asked to create awareness, generate leads and speed up revenue. It was not in the room when the product, the price or the target segment was decided, and running the campaigns well does not earn it a place in that room.
How marketing leaders spend their time points the same way. Marketing leaders spend 68 per cent of their time managing the present and 32 per cent preparing for the future, a split that has held every year since 2019, according to the 2026 CMO Survey of 308 US marketing leaders.
When growth falls short in a company organised this way, marketing is asked to increase demand for an offer it did not help shape, among customers it did not choose, at a price it did not set. Better communication sometimes helps. More often the problem is the offer, the price or the segment, and no campaign can fix those.
A marketing team that only enters after the offer, the price and the segment are fixed is a promotions department, whatever it is called.
The problem was never digital
The purpose of marketing did not change when customers moved online. A business still has to understand its market, decide which customers to serve, build an offer those customers value, price it, distribute it and make it easy to buy. It still has to create demand among people who are not ready to buy today, which means building familiarity and trust over years, while being ready to convert that demand when it arrives.
Digital tools can serve every part of that work. Search data shows how customers describe their own problems. Website behaviour shows where they get stuck. Customer systems show how a deal actually moves. Online communities show what a category argues about. Experiments test an offer before serious money is spent. But a dashboard cannot decide which market to enter. A platform cannot decide what the company should stand for. An attribution model cannot decide how much of this year’s revenue to trade for next year’s.
Responsibility for the split between the tools and the decisions is widely shared. Companies promoted the people who could show a number every month. Quarterly targets made short-term response more attractive. Org charts broke responsibility for the customer into pieces. Technology companies sold measurement systems that made their own platforms look accountable. And marketers played a part. It was easier to build a career on channel expertise, which showed up on a dashboard every month, than on commercial judgement, which had to be argued for.
The industry also invented a false split between “traditional” and “digital” marketing, as if customer value, positioning and brand building belonged to an earlier era and data, automation and performance were the future. Customers never experienced that split. They met advertising, recommendations, salespeople, websites, products and service as one relationship. The answer is not to go back to how marketing worked before the internet.
The answer is to stop treating digital marketing as a substitute for marketing.
Start with a diagnosis of the growth problem before choosing a channel. Design measurement around the commercial objective rather than inheriting it from the platform, and keep the metrics that manage activity separate from the measures that show whether the business grew. And put marketing back into the decisions about the offer, the price and the segment before the company commits to them and asks a campaign to rescue them.
Specialist skills stay valuable. They are worth more, not less, when the specialist understands the market their channel operates in. The strongest search strategist understands demand beyond search. The strongest automation practitioner understands customers beyond the database. The strongest performance marketer understands that most of the effect of advertising arrives after the conversion window closes.
Before your next campaign plan
Run these before the brief is written.
Diagnose before you optimise. Name the growth constraint, whether awareness, relevance, distinctiveness, availability, price, product or conversion, before choosing what to do about it. A campaign without a diagnosis is a guess.
Design measurement around the objective, not the platform. Decide what business outcome the activity has to change, then choose measures that can detect it.
Separate activity metrics from impact measures. Clicks and cost per lead help manage execution. Never report them as evidence that the business grew.
Write down the split between capture and creation. Decide how much goes to converting today’s demand and how much to building tomorrow’s, and defend it as a choice rather than inheriting it from last year’s dashboard.
Say when the problem is upstream. If the offer, the price or the segment is the real constraint, say so before promotion is asked to make up for it.
A brief that cannot answer these is asking a campaign to fix a problem nobody has named. A brief that can is a marketing plan, not a media plan.
AI makes the same mistake easier to repeat
The digital era taught marketers to equate progress with more speed, more data and tighter optimisation. AI now offers more of each. It can produce more content, analyse more data, automate more decisions and let a small team put out the work of a large one.
That raises the cost of acting without a marketing foundation. A weak offer can now be promoted at a scale nobody could afford before. An undifferentiated position can generate hundreds of content variations. A badly chosen metric can be optimised every hour. A broken customer experience can be automated end to end. Left undirected, AI will speed up every habit that narrowed marketing in the digital era, and the company will get more efficient at producing and measuring activity while staying unclear about whether any of it produces growth.
The lesson is not to slow the technology down. It is to put the decisions back before the tools. Digital was the first time the profession had more to measure than to decide. AI is the second, and this time we know how the trade ends.
We believe marketing is a commercial discipline, not a promotional service. Its job was never to promote whatever the business decided to build. It was to help the business decide what to build, for whom, at what price, and how that turns into growth that lasts.
We believe measurement should serve judgement, not replace it. A dashboard can tell you what moved. It cannot tell you what mattered.
Above all, we believe AI hands marketers the same choice digital did, faster. We can use it to produce more of the same at greater speed, or we can use it to take the execution load off the profession and put the time back into customers, markets and strategy.
Digital made marketing measurable. It also reduced it to tactics. Putting marketing back into the decisions about customers, offers and price does not mean giving up digital tools. It means using them to carry out a plan that marketing helped write.
Back2Marketing exists to help marketers get back into the decisions about customers, offers and price.
Evidence informs. Judgement decides.
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And if you want to build the judgement, not just the output, Back2Marketing’s B2B Marketing Fundamentals course teaches marketing from first principles.
Sources
American Marketing Association, Definitions of Marketing, on marketing as the creation, communication, delivery and exchange of value.
Philip Kotler, Marketing Management (planning framework), on research, segmentation, targeting, positioning and the value proposition preceding implementation.
Les Binet and Peter Field, The Long and the Short of It, IPA, 2013, on short-term activation versus long-term brand building, and the risk of using very short-term online metrics as primary performance measures.
Les Binet, Unlocking Marketing Effectiveness in the Digital Age, Think with Google, March 2025, on early click-based misattribution (“not every click translated to a genuine, incremental conversion”) and combining marketing mix modelling, experiments and attribution.
Brett Gordon, Florian Zettelmeyer, Neha Bhargava and Dan Chapsky, A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook, Marketing Science, vol. 38, no. 2, 2019. 15 US advertising experiments; observational methods “often fail to accurately measure the true effect of advertising” even after conditioning on extensive demographic and behavioural variables.
Randall Lewis and Justin Rao, The Unfavorable Economics of Measuring the Returns to Advertising, Quarterly Journal of Economics, vol. 130, no. 4, 2015. 25 large field experiments with major US retailers and brokerages, most reaching millions of customers; median confidence interval on return on investment more than 100 percentage points wide.
John Dawes, Ehrenberg-Bass Institute for Marketing Science with the LinkedIn B2B Institute, The 95:5 Rule, 2021, on out-of-market buyers and advertising’s role in building brand-relevant memories; the ratio presented as a heuristic.
Charles Goodhart, Problems of Monetary Management: The UK Experience, 1975, origin of the principle that a measure loses its usefulness once it becomes a target.