Marketing Strategy Development: Industry Report on Clients, Platforms, Measurement and Agency Change

Summary

Global advertising spend is forecast to keep growing but at a slower pace, with growth attributed to economic uncertainty ¹. Spend is concentrated in social media, search and retail media, which are expected to account for 66.4% of global spend ². Three platform companies are projected to hold 59.7% of spend excluding China ³. Retail media is growing fastest among these channels, yet its measurement standards remain inconsistent ⁴¹⁰. Vendor surveys report high AI adoption and campaign delays, but these figures are self-reported and unaudited ⁵⁶. Attribution remains limited because budgets are not randomly assigned ¹¹. The main outlook points are continued platform dependency, growing automation of routine marketing tasks, and rising demand for transparent measurement. Several metrics the brief requests, including CPM, CPC, CAC, ROAS and brand lift, could not be sourced from the pack.

Key findings

1. 1

   Global ad spend growth is forecast to slow

   Growth is projected to slow to 5.0% after 5.8% in the prior period, and the slowdown is attributed to geopolitical and economic uncertainty. This is a single-source forecast.

   Confidence: Medium
2. 2

   Spend is concentrated in a few platforms

   Alphabet, Amazon and Meta are projected to account for 59.7% of global ad spend excluding China, equal to $659.6 billion. This is a forecast, and the figure excludes China.

   Confidence: Medium
3. 3

   Retail media forecasts differ between sources

   WARC-based forecasts give retail media at $202.1 billion (up 14.3%) in one source and $196.7 billion (up 12.4%, 16% of advertising) in another. The pack does not reconcile the two figures.

   Confidence: Medium
4. 4

   Marketers report widespread AI use

   A vendor survey reports that 80% of marketers use AI for content creation and 75% use it for media production. These are self-reported results from a vendor, not independently audited data.

   Confidence: Qualitative
5. 5

   Measurement limits and standards gaps persist

   Standard time-series marketing mix models cannot separate cause from effect when budgets are not randomly assigned, and retail media lacks consistent measurement standards across retailers.

   Confidence: Qualitative

1Industry definition and scope

This report covers the commercial work of setting marketing objectives, choosing target segments, defining positioning, allocating budgets and selecting channels that guide campaigns. In the writer's interpretation, strategy sits upstream of creative production, media buying and measurement, and its outputs are judged by the results those later stages produce.

The ecosystem includes brands (clients), agencies, media platforms (social media, search and retail media), publishers, technology providers and measurement partners. The pack does not include a formal industry classification, so these segment boundaries are the writer's working definitions.

Geographic scope is global. Where standards are cited, the reference is to US frameworks, specifically the Media Rating Council (MRC) and the Interactive Advertising Bureau (IAB) guidelines ⁹¹⁰. Reporting uses the latest available data in the pack, and forecasts are not confirmed outcomes.

Key terms used here are: ad spend (money spent on advertising across media), retail media (advertising sold by retailers on their own sites and apps), marketing mix modeling (MMM, statistical estimation of marketing's impact on sales compared with a baseline without marketing) ⁹, and incrementality (the sales caused by marketing above what would have happened without it) ¹⁰.

Definitions are drawn from the MRC and IAB/MRC documents where possible. Other boundaries are the writer's interpretation.

2Market size, structure and value chain

Forecasts for global advertising spend are high in the latest period. dentsu projects worldwide spend of $1.06 trillion across 56 markets ¹. WARC projects $1.34 trillion across all media, with growth of 11.9% ². The two figures use different coverage and cannot be combined or compared directly.

Concentration is the main structural feature. WARC expects social media, search and retail media to account for 66.4% of global spend, rising to 70.0% later ². Alphabet, Amazon and Meta are projected to hold 59.7% of spend excluding China ³.

Retail media and search are growing faster than the overall market. The pack gives two retail media forecasts, which differ (see table). Search advertising is forecast to rise 14.2% to $295.7 billion ³. These are forecasts from market research, not observed results.

Value chain: brands set budgets and objectives; agencies plan, buy and manage campaigns; platforms sell inventory and audience targeting; publishers sell content-adjacent space; technology providers supply planning, creative and optimization tools; measurement partners estimate outcomes. Revenue models for agencies and technology providers are not verified in the pack, and no agency holding-company revenue data was retrieved.

• Forecast growth in global advertising spend 5.0percent Forecast Global, 56 markets, Latest forecast period [1]
• Share of global spend in social media, search and retail media 66.4percent Forecast Global, Latest forecast period [2]

Table values are copied from forecasts in the pack. No CPM, CPC or ROAS benchmarks were available to add to the market structure view.

3Customers, demand and adoption

Clients are increasing their use of AI in production and planning. A HubSpot survey reports that 80% of marketers use AI for content creation and 75% use it for media production ⁵. HubSpot also reports that 61% of marketers believe marketing faces its biggest disruption in 20 years because of AI ⁵. These are vendor survey results, self-reported and not audited.

Speed and waste are recurring concerns. Smartly, a vendor, reports that 41% of marketers say it takes three to four weeks to launch a digital campaign from asset creation to execution ⁶. The same vendor reports that up to 30% of marketing budgets are wasted, according to most marketers ⁶. The pack does not verify the basis for the waste estimate.

The American Marketing Association's trends work, based on a modified Delphi process with more than 30 marketing professionals, expects AI to automate much of transactional marketing, with human creativity and storytelling becoming the main differentiators over five to ten years ⁷. The panel size is small and the method is consensus-based, so this is a forecast of expert opinion rather than measured demand.

Kantar states that high quality and responsible data is the foundation for its marketing trends ⁸. This matches the strategic emphasis on consent-based data, but the pack contains no evidence on consent rules, purchasing criteria or customer retention. Audience behavior, brand lift and retention data were not retrieved, so the demand analysis here is limited to vendor and association sources.

• Marketers using AI for content creation 80percent Observed Global, Latest survey period [5]
• Marketers reporting three to four weeks to launch a digital campaign 41percent Observed Global, Latest survey period [6]

Vendor claims are flagged throughout. The pack does not include independent audit data for these surveys.

4Competitive landscape and key players

The competitive landscape is dominated by large platforms. Alphabet, Amazon and Meta are projected to hold 59.7% of global ad spend excluding China ³. Their scale gives them leverage over pricing, targeting data and inventory, which creates dependency for brands and agencies that rely on them.

Retail media is an expanding competitive area. Retailers sell advertising against their own shopping audiences, and WARC forecasts retail media investment rising to $196.7 billion or $202.1 billion depending on source ³⁴. The IAB and MRC state that retail media lacks consistent measurement standards across retailers, which raises concern across the industry ¹⁰.

Agencies and technology providers compete on planning, creative production and automation. The pack includes no revenue, client-count or holding-company data for named agencies, so agency market share cannot be assessed. Technology providers such as HubSpot and Smartly publish surveys that also promote their own products, so their findings should be read as vendor perspectives ⁵⁶.

Measurement partners compete on credibility of methods. The MRC Outcomes standard defines and covers attribution, multi-touch attribution, marketing mix modeling and experiments ⁹. Provider types that can meet these requirements may be better positioned for enterprise clients, but the pack does not verify this.

Platform-specific economics, such as fees, auction pricing and attribution windows for Meta, Google or Amazon, were not verified from company filings. Comparisons of business models beyond the concentration figures are therefore not possible from the pack.

Comparisons avoid performance claims that the pack cannot support. Vendor sources are identified as such.

5Technology, operations and workforce

AI is moving from content creation into media and optimization. Kantar says agentic optimization recommendations will let marketers fine-tune campaigns dynamically based on past performance and audience responses ⁸. This is a vendor forecast. The AMA expects automation to take over much transactional work, which would change the skills marketers need ⁷.

Measurement technology is shifting toward causal methods. The pack notes that budgets are not randomly assigned, so standard time-series MMM cannot tell whether marketing caused sales or sales drove marketing spend ¹¹. Randomized geographic tests can break this link ¹¹. The MRC standards include requirements for MMM coverage and spend data and cover experiments ⁹.

Operations are constrained by speed and coordination. Smartly reports that 41% of marketers need three to four weeks to launch a campaign ⁶, which suggests that workflow tools and asset reuse could be valuable. This is a vendor claim and has not been verified independently.

Workforce data is limited. The AMA's findings point to rising demand for creative judgment and storytelling ⁷, but the pack has no data on talent supply, salaries, training or skill shortages. These gaps should be treated as open questions for strategy teams.

The writer's interpretation is that strategy roles will shift toward defining objectives, governing data quality and interpreting experiments. This is inferred from the sources and is not a sourced finding.

Workforce claims are kept separate from forecasts and from the writer's interpretation.

6Regulation, standards, risk and sustainability

Jurisdiction: the standards in the pack are US-based. The MRC Outcomes and Data Quality Standards define measurement requirements for attribution, marketing mix modeling and experiments ⁹. The IAB and MRC retail media guidelines stress transparency in incrementality methodology, assumptions and limitations ¹⁰.

Binding status: the pack does not confirm whether either document is binding. Based on their description as industry standards and guidelines, the writer treats them as voluntary industry frameworks, not statutory requirements. Any legal obligations would need to be checked with qualified counsel in the relevant jurisdiction.

Privacy and consent: the pack includes Kantar's statement that responsible data is foundational ⁸ but no sourced information on cookie rules, consent requirements or privacy law. This area is a material gap for marketing strategy and should be researched before decisions are made.

Brand safety and environmental or social factors: the pack contains no verified data on brand safety incidents, ad placement standards or sustainability metrics for advertising. These are gaps, not conclusions.

Operational risk: the pack identifies three risks: concentration in a few platforms ³, economic uncertainty that is slowing spend ¹, and budget waste estimated by one vendor at up to 30% ⁶. Attribution risk is significant because standard models may misstate cause and effect ¹¹.

This section is informational and does not constitute legal or regulatory advice.

7Challenges, opportunities and case examples

Attribution is the central challenge. Because budgets are not randomly assigned, observed correlations between spend and sales may be misleading ¹¹. Geographic experiments offer a way to test causal impact ¹¹, and the MRC standards cover experiments as part of outcomes measurement ⁹.

Retail media standards are the second challenge. The IAB and MRC say that retail media lacks consistent measurement standards across retailers ¹⁰. Brands that buy retail media must therefore check methodology before comparing results with other channels.

Opportunities follow from these constraints. Retail media and search are expected to grow faster than total spend ³⁴. Strategy teams that build measurement plans around experiments and transparent assumptions could reduce the risk of misallocated budgets ¹⁰¹¹.

Case examples: the pack contains limited comparable company examples. The most concrete attributable example is the concentration of spend in Alphabet, Amazon and Meta ³, which shows how a brand's strategy depends on a few platforms. Vendor examples from HubSpot and Smartly show how marketers describe AI adoption and campaign speed ⁵⁶, but these are survey results, not company case studies.

Because only limited comparable examples were available, the report does not include campaign-level ROAS, CAC or brand lift comparisons. The gap is stated in the limitations.

Comparable examples were limited in the pack. The report explains this gap rather than substituting unsupported figures.

8Outlook and strategic implications

Near term: forecasts point to continued growth at a slower rate ¹, with concentration in a few platforms persisting ²³. Strategy teams should expect platform dependency to continue and should plan budgets with contingency for slower growth.

Medium term: the AMA expects AI to automate much transactional marketing while human creativity becomes more important ⁷. Kantar expects optimization tools to adjust campaigns more dynamically ⁸. These are forecasts from expert and vendor sources, and their timing is uncertain.

Measurement is likely to become more demanding. Standards bodies emphasize transparency ¹⁰, and causal methods are gaining attention ⁹¹¹. The uncertainty is high because retail media forecasts differ between sources ³⁴ and standards for retail measurement are still developing ¹⁰.

Implications for stakeholders: brands should require transparent methodology from platforms and vendors, and should test causal impact through experiments. Agencies should build skills in strategy, data governance and experiment design. Platforms and retailers should document measurement assumptions. Technology and measurement providers should separate self-reported survey claims from audited results when they present evidence.

Outlook statements are labeled as forecasts or interpretation.

9Conclusion

Marketing strategy development is becoming more constrained by platform concentration, measurement limits and AI-driven automation. The most defensible takeaways are that strategy must rely on transparent, causal measurement, and that platform and retail media claims need independent verification.

How this was built

Sources

1. 1

   Ad Spend Forecasts (May edition): Global Ad Spend Forecasts

   dentsu Market research

2. 2

   Global advertising spend surges 11.9% to $1.34trn this year despite consumer caution

   WARC Media (via Podnews) Market research

   podnews.net
3. 3

   Global advertising spend to rise 11.9% to $1.34 Trillion: WARC Media

   WARC Media (via MediaNews4u) Market research

4. 4

   Retail media and search growth forecasts (aggregated market data)

   SaleHoo (citing WARC) Market research

   salehoo.com
5. 5

   State of Marketing Report

   HubSpot Vendor report

   hubspot.com
6. 6

   Digital Advertising Trends Report (with Reach3 research)

   Smartly Vendor report

7. 7

   Future Trends in Marketing Report

   American Marketing Association Industry association

8. 8

   Kantar Marketing Trends (latest edition)

   Kantar Company report

   kantar.com
9. 9

   MRC Outcomes and Data Quality Standards (Final)

   Media Rating Council Standard

   mediaratingcouncil.org
10. 10

    IAB/MRC Retail Media Measurement Guidelines Explainer

    Interactive Advertising Bureau and Media Rating Council Standard

11. 11

    Structural Estimation of Marketing Mix Model Parameters from Geo-Experiments

    arXiv preprint authors Peer-reviewed