Only 39% of marketers measure business outcomes
What is measured shapes what the business values. Recent data suggests many teams still stop short of linking marketing activity to wider commercial outcomes.
What marketers measure shapes what the business values, yet recent data suggests many teams still stop short of linking marketing activity to wider commercial outcomes. Marketing Week’s Language of Effectiveness 2025 survey (in partnership with Kantar and Google), based on responses from more than 1,000 brand marketers, finds only 39.2% of brand marketers measure whether their work is delivering business outcomes. That gap helps explain persistent tensions between short-term performance metrics and longer-term brand health.
Measurement choices: prevalence and blind spots
Conversion rate is the single most commonly tracked metric, cited by 60.8% of respondents, followed by return on investment and click-through rate (both 57.5%). New customer acquisition (53.7%) and brand awareness (51.9%) also rank highly.
Less commonly measured metrics include campaign views (48.6%), leads generated (44.5%) and customer retention (31.8%). Deeper brand measures such as brand recall (30.8%), Net Promoter Score (29.8%), customer lifetime value (26.2%) and brand affinity (21.6%) sit near the bottom of priorities.
These patterns reveal a strong bias toward performance signals that are immediate and measurable in digital channels, while more holistic indicators of long-term value and business contribution are less uniformly adopted. The survey also highlights differences by business type and size: B2C teams favour conversion and click-through metrics, B2B teams prioritise lead generation, and both SMEs and large corporates show similar shortfalls in measuring business outcomes (around 39% each).
Threats of focusing on performance metrics only
When teams prioritise short-term digital metrics – click-through rates, last-click conversions, cost-per-acquisition – they gain rapid feedback loops that support quick optimisation and efficient budget allocation. This focus can improve tactical efficiency: creative iteration speeds up, bid strategies become data-driven, and channels that deliver immediate sales or leads are scaled quickly. However, applying this performance-only lens regardless of client type creates several material threats.
This approach biases investment toward channels that are easiest to measure. Retail media, paid search and direct-response social attract disproportionate spend because their results are trackable in-session, while channels with longer or more diffuse impact – sponsorships, upper-funnel video, public relations, experiential – are defunded despite contributing to reach and future demand. The outcome is a suboptimal media mix that under-invests in long-term growth drivers.
It also encourages myopic optimisation and fragility. Optimising for immediate conversion can lead to creative and UX choices that maximise short-term click-throughs but degrade user experience or reduce long-term retention. Teams may stop tests as soon as a lift is observed without assessing durability, sample bias or broader customer value, producing gains that do not persist at scale.
Finally, organisational and culture risks emerge. When marketing is measured mainly on immediate digital outputs, cross-functional collaboration with product, sales and finance can weaken, because shared business metrics (margin, retention, customer lifetime value) are not central to marketing reporting. Senior stakeholders may thus view marketing as a short-term cost centre rather than a strategic growth function.
Mitigations: balance short- and long-term metrics, adopt mixed-method measurement (experiments for causal short-term effects, econometrics for aggregate long-term effects), embed customer lifetime value and retention in reporting, and build governance that ties channel decisions to business outcomes. Tailor the measurement mix to client type: shorter attribution windows and performance metrics for transactional e-commerce; longer-horizon econometric and cohort analysis for subscription and high-consideration purchases.
Digital Attribution
Digital attribution is widely used, with 51.5% of marketers reporting its use; 64.3% of those take an always-on approach.
Digital attribution is the process of identifying which online touchpoints (ads, search, email, social posts, website interactions, etc.) contributed to a desired customer action – such as a purchase, sign-up, or lead – and assigning credit to those touchpoints to understand their relative impact.
A user typically encounters many digital interactions before converting. Attribution systems collect signals about those interactions (clicks, impressions, page views, sessions) and apply a model to allocate credit across them.
Common models include last-click (all credit to the final click), first-click (all credit to the first touch), linear (equal credit across touches), time-decay (more credit to recent touches), and position-based (more weight to first and last interactions). More advanced approaches use statistical or algorithmic models – multi-touch attribution, probabilistic attribution, or data-driven attribution – that infer contribution from patterns in the data.
Rule-based attribution models and platform-reported conversions systematically overcredit lower-funnel channels; attribution windows, cross-device gaps and privacy-driven signal loss further skew results. Relying solely on these signals can misallocate budget and obscure the causal role of brand-building or offline touchpoints.
Controlled Experiments
Controlled experiments such as conversion uplift tests are used by 35.3% of respondents, with about a third conducting them continuously.
35% adoption of A/B testing (as in the survey) is low compared with many other industry studies. Lower A/B adoption usually signals a few structural issues: limited testing skillsets, insufficient traffic or data to run meaningful experiments, lack of tooling or governance, risk-averse culture, or prioritising short-term activation metrics over systematic learning. Those constraints reduce a team’s ability to iterate, optimise creative and UX, and compound gains over time – so, in practice, lower adoption often correlates with slower improvement in conversion and lower marketing efficiency.
Vendor and industry compilations (VWO, CXL and similar summaries) report that many digitally mature companies run A/B testing routinely; some aggregated surveys place organizational A/B adoption in the 50 – 60% range among companies with active digital commerce or product teams.
Econometric approaches (market mix modelling and similar) are applied by roughly 32% overall, but uptake varies sharply: 46.4% of B2C brands use econometrics versus 16.3% of B2B brands. Larger organisations are substantially more likely than SMEs to run econometric analysis on a regular basis (38.1% vs 19.4%).
Why this matters
When fewer than four in ten marketers explicitly measure the business outcomes of their work, marketing risks being framed primarily as a cost centre focused on short-term KPIs. This leaves boards and finance teams with less rigorous evidence linking brand investment to pricing power, margin expansion or sustainable growth. The report also flags that only 17.3% of respondents believe their business is investing for long-term brand health, compounding the risk of short-termism.
Industry studies and forecasts echo the shift toward digital, attention-focused metrics while warning of measurement gaps. Kantar’s 2024-25 trend analysis highlights video and retail media growth: streaming and retail media are reshaping reach and targeting opportunities, with retail media expected to account for an increasing share of ad spend over the coming years.
Kantar’s media research finds attention quality is declining on some social platforms (global ad receptivity on social fell in 2024 vs 2023), reinforcing why marketers lean on immediate performance metrics as proof of impact. Independently, other surveys of marketing leaders show a persistent struggle to quantify brand contribution to price premium and profitability: many organisations recognise the strategic value of brand but lack the models or cross-functional processes to demonstrate it in financial terms.
Practical implications for marketing leaders
Align measurement with business questions by mapping each campaign objective to a commercial outcome–short-term revenue, margin, new customer value or long-term brand equity–and use a mix of methods (always-on attribution, controlled experiments, and periodic econometrics) so findings are mutually reinforcing. Increase investment in econometric or MMM approaches where feasible to quantify brand impact on sales and price power, and embed experimental design for causal insights.
Finally, present a balanced dashboard to senior stakeholders: retain performance metrics for near-term optimisation but elevate brand health indicators and customer lifetime measures to demonstrate longer-term value.
Bridging that gap requires more disciplined use of mixed methodologies, stronger cross-functional reporting, and a willingness to tie brand metrics to firm-level financial questions–only then can marketing credibly claim a seat at strategic decision-making tables.
