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⏱ 6 min read

2024 Advertising Trends: Retail Media, AI, Measurement

Despite economic headwinds throughout 2023, global digital ad spend continued to grow. That headline number looks reassuring until you examine where growth actually landed. Much of the incremental spend flowed to search and commerce-driven channels, retail media networks increased their share, and growth on some traditional social platforms slowed.

Rather than leaning on vendor announcements or industry chatter, this analysis works backward from 2023 performance signals to identify where budget and strategy decisions may need to shift in 2024. Three platform categories generated the clearest signals: search and commerce-driven channels, AI-optimized creative workflows, and a fragmented measurement environment.

Where the Money Actually Moved in 2023

The split between search and social spending reveals advertiser preferences by channel more clearly than surveys often do. Large search advertisers reported stronger growth than many social platforms, while some social channels showed slower recovery from prior declines. This is less about preference and more about performance predictability under economic pressure.

Retail media networks delivered one of the more pronounced structural shifts. Major retail ad businesses grew and expanded advertiser bases beyond endemic CPG brands. Non-endemic advertisers — including financial services, automotive, and technology companies — increased retail media spend in the back half of the year. Retail media helps address first-party data scarcity by enabling brands to track purchase behavior in closed-loop environments even as traditional attribution models fragment.

In practice, some advertisers running retail network campaigns have been able to measure store visits and short-term purchase lift in ways that standard display or social campaigns rarely permit.

Connected TV and streaming inventory expansion opened new opportunities while also putting upward pressure on prices. Several streaming platforms launched ad tiers with CPMs noticeably higher than traditional linear TV and reported higher completion rates. These platforms command premiums in part because they can deliver more engaged audiences, though constrained inventory can sustain pricing power.

Under economic pressure, the balance between brand and performance spending shifted: many advertisers reduced brand awareness budgets while maintaining or growing performance marketing spend. If sustained across multiple quarters, that adjustment risks weakening brand metrics and creates opportunities for competitors that maintain upper-funnel investment.

Platform-reported engagement and reach metrics should be verified against first-party data. Reported reach can include overlap across placements, and some engagement metrics do not fully account for passive behaviors like scroll-throughs. CRM-verified conversion data often shows sizable gaps compared to platform attribution across industries.

Three Digital Advertising Trends With the Strongest 2024 Signal

Retail Media Moves from Experimental to Core Budget Line

Adoption by non-endemic brands accelerated in the second half of 2023. Financial services and automotive brands notably increased retail media investments, in some cases shifting budget from traditional display and social channels. As the space matures, vendor consolidation is likely: hundreds of retail media networks compete today, but many lack the infrastructure to scale efficiently. Consolidation may concentrate market share around a smaller set of players with robust first-party data assets and measurement capabilities.

Practical actions:

• Evaluate retail media vendors now and prioritize networks with strong first-party data and measurement tools.
• Establish unified measurement frameworks so cost-per-acquisition and conversion definitions align across networks.
• Concentrate spend on 1–2 networks that align with your category to reach statistical significance in optimization systems.

AI-Driven Creative Optimization: Testing Velocity, Not Creative Quality

Adoption of dynamic creative optimization and automated asset testing increased in 2023. Performance gains often come from the ability to test many asset combinations at a velocity human teams cannot match. Some advertisers reported better cost-per-acquisition or conversion outcomes with automated optimization, though results vary by category and implementation.

Traditional A/B testing evaluates a handful of variants over weeks. AI-driven systems can test dozens to hundreds of combinations across audiences, placements, and contexts simultaneously. Success tends to follow teams that think in asset libraries rather than single campaigns: the volume and variety of inputs — headlines, images, video lengths, calls-to-action — influence what optimization systems can extract.

Practical actions:

• Design asset libraries (many headlines, images, and video lengths) instead of one-off creative assets.
• Prioritize processes that increase testing velocity and automate where measurement supports it.
• Pilot AI-driven testing but retain human oversight for brand alignment and creative strategy.

Privacy-Driven Measurement Fragmentation Gets Worse Before It Gets Better

Shifts like Chrome’s third-party cookie deprecation — which moved timelines several times — have delayed investment in privacy-compliant measurement for some advertisers. Current attribution models are being disrupted and replacement solutions are not yet standardized. The gap between platform-reported conversions and CRM-verified conversions widened in many cases during 2023.

E-commerce clients frequently report fewer verified purchases than platform dashboards suggest; platform attribution can overstate conversions compared to server-side or CRM-based tracking. This gap can grow as operating system and browser changes limit tracking capabilities further.

Practical actions:

• Audit your attribution stack against CRM data and prioritize server-side tracking for major accounts where feasible.
• Treat measurement infrastructure as a revenue-impacting priority, not mere technical housekeeping.
• Invest in measurement standardization and cross-network reporting where possible.

One Trend Worth Watching Carefully: Generative AI for Creative

Generative AI for ad creative at scale warrants attention but requires realistic expectations. Text-to-image and AI video tools reduced production time and costs in many tests during 2023, making rapid asset generation attractive for direct-response use cases. Some companies produced hundreds of variants at a small fraction of traditional production costs, and early tests sometimes showed comparable click-through rates for AI-generated assets in performance placements.

However, results are mixed and context-dependent. Brand safety concerns, legal ambiguity around training data, and potential audience fatigue with obviously AI-generated content remain unresolved. Brand campaigns have not uniformly shown consistent performance lift at scale, and some research suggests engagement can decline when content is clearly synthetic.

Practical actions:

• Pilot generative AI in low-risk placements — retargeting, A/B test variants, or performance-focused social ads — and measure outcomes closely.
• Engage legal and brand teams early to set guidelines around usage, IP and disclosure.

What This Means for Your 2024 Strategy

Search advertising requires tighter campaign controls. Automated products like Google’s Performance Max are increasingly common; 2023 signals showed variation across asset groups and limits to auction transparency. Use tighter creative inputs per asset group and actively manage negative keyword lists. Microsoft Advertising can offer automation and competitive cost efficiency for some B2B use cases, but it may benefit from distinct creative assets rather than simple repurposing.

Paid social tends to perform better with broader targeting and more creative variants. Inventory shifts and new formats drove recovery on several platforms, and manual audience segmentation often competes with platform algorithms. Creative volume is frequently the better lever: more variants fed into broader targeting often outperform narrow audiences supported by few assets. TikTok similarly rewards frequent creative testing over hyper-precise targeting in many campaigns.

Connected TV requires first-party audience data to justify premium CPMs. Streaming CPMs are generally higher than traditional video; the premium is more defensible when buying against customer lists or high-quality lookalikes and less defensible when buying purely contextually. Ensure attribution is addressed before scaling spend, as current streaming measurement approaches can undercount conversions relative to search or social and distort ROI calculations.

Retail media rewards depth over breadth. Spreading budget thinly across many networks produces sparse data and weak optimization. Concentrate investment on a small number of networks aligned with your category and scale to reach statistical significance in their optimization systems. Major platforms offer developed measurement tools, but category-specific networks can outperform for highly relevant brands.

The Actual Takeaway

A common theme across these trends is clear: data infrastructure quality is becoming a primary differentiator in digital advertising performance. Platform choice, budget size, and creative execution still matter, but the ability to collect, process, and activate data effectively is increasingly decisive.

Teams likely to outperform in 2024 are investing now in three capabilities:

• First-party data collection and activation to reduce reliance on third-party cookies.
• Measurement frameworks that verify conversions via CRM integration rather than sole reliance on platform attribution.
• Creative production systems able to generate sufficient volume and variety to feed optimization tools.

Before allocating 2024 budgets, audit your measurement stack against these criteria: Can you track customer behavior without third-party cookies? Can you verify platform-reported conversions against actual sales data? Can you produce creative assets quickly and at scale to supply automated systems?

Channel allocation decisions become clearer once these infrastructure gaps are visible. What measurement capability will you prioritize first: attribution accuracy, creative production velocity, or first-party data activation?