DoubleVerify study reveals marketers spend 10 hours weekly on manual tasks

DoubleVerify released comprehensive findings today, examining artificial intelligence adoption patterns across digital advertising workflows. The 2025 Global Insights report draws from platform intelligence, campaign analytics, and survey responses from 1,970 marketing professionals across four regions. Manual campaign optimization consumes substantial resources within marketing teams globally. The research shows marketers spend 10 hours and 12 minutes weekly on routine tasks including bid modifications, budget allocations, and viewability threshold adjustments.

According to the study findings, 42% of marketers currently utilize third-party AI or automated bidding solutions outside their demand-side platforms. An additional 49% plan to implement such technologies, indicating widespread recognition of AI's operational value. The shift represents a fundamental change from experimental applications to essential workflow components in media buying and campaign management.

Time allocation data reveals significant regional variations in manual optimization efforts. North American marketers average 9 hours and 14 minutes weekly, while APAC professionals spend 11 hours and 1 minute on similar tasks. LATAM shows the highest commitment at 11 hours and 15 minutes, with EMEA falling in the middle range at 9 hours and 38 minutes weekly.

The financial implications prove substantial for advertising organizations. North American agencies lose approximately $17,000 annually per team member to repetitive tasks, calculated using average programmatic trader wages of $34.63 per hour. This cost represents time diverted from strategic planning, creative development, and performance analysis activities that drive campaign innovation.

Campaign activation demonstrates the strongest year-over-year growth in planned AI usage, increasing 32% from 2024 levels. The data indicates 31% of marketers used AI for campaign activation in 2024, rising to 41% for planned 2025 implementation. This represents the largest percentage increase across all measured workflows.

Bidding optimization and mid-flight plan optimization show steady growth patterns, with 12% year-over-year increases. These functions moved from 41% usage in 2024 to planned 46% adoption in 2025. The consistent growth reflects AI's proven effectiveness in managing complex optimization variables that challenge human processing capabilities.

Industry vertical analysis reveals significant adoption patterns across different business sectors. Food and drink companies lead campaign activation AI usage with 68% year-over-year increases, rising from 28% in 2024 to 47% planned for 2025. Technology, telecommunications, and electronics sectors show 41% growth, while fashion and clothing demonstrates 42% increases.

The research identifies five priority areas where marketers apply AI across media lifecycles. Automation of routine optimization tasks ranks highest, addressing the time burden that prevents strategic focus. Real-time campaign optimization through AI bidding solutions follows, enabling continuous adjustment of budget allocation, pacing, and campaign parameters based on performance data.

The timing of this study coincides with DoubleVerify's strategic positioning in the AI bidding market. The company acquired Scibids, a Paris-based artificial intelligence startup specializing in automated bidding optimization, for $125 million in August 2023. The acquisition integrated approximately 70 employees, including over 20 AI engineers and data scientists, into DoubleVerify's operations. Scibids technology dynamically adjusts bids for every impression based on advertiser key performance indicators, utilizing first-party data and media cost information from demand-side platforms.

The acquisition followed a June 2023 partnership between the companies that launched the DoubleVerify Algorithmic Optimizer, combining attention metrics with AI-powered decision-making. Initial testing showed 45% lower media CPMs, 63% higher attention levels, and 95% more impressions compared to standard optimization approaches. These performance improvements positioned Scibids as a valuable asset for DoubleVerify's expansion beyond traditional verification services into campaign optimization.

According to DoubleVerify CEO Mark Zagorski, the company selected Scibids after testing various AI algorithm optimization providers, describing the acquisition as wanting the technology "all to ourselves." The deal represented one of only four transactions above $100 million in the advertising technology sector during the first half of 2023, highlighting its significance within a relatively quiet merger and acquisition environment.

Scibids operates as an independent custom bidding provider, competing with platform-based solutions like Google's Performance Max and Meta's Advantage+ Shopping Campaigns. Unlike these walled garden approaches, Scibids offers transparency into bidding decisions and campaign mechanics, allowing advertisers to maintain control over targeting parameters and optimization strategies. The technology integrates with major demand-side platforms including The Trade Desk, Google DV360, Microsoft Xandr, and Comcast Beeswax.

Industry observers note the study's findings align closely with Scibids' core value propositions, potentially serving dual purposes of market education and indirect product promotion. The research emphasizes automation benefits and cost savings that directly parallel Scibids' technical capabilities, including real-time bidding adjustments and multi-variable optimization. This strategic alignment raises questions about whether the study functions primarily as industry analysis or as supportive marketing for DoubleVerify's AI bidding technology.

Faster campaign activation represents another key priority, with AI streamlining setup processes and eliminating repetitive manual workflows. Precision targeting emerges as the fourth focus area, with 44% of marketers identifying audience segment reach as their primary optimization challenge across all regions and vertical markets.

Walled garden optimization completes the priority framework, addressing challenges in social media advertising environments. The study shows 88% of marketers invest in social platforms, with 9% planning future investment and only 2% avoiding these channels entirely.

Upper-funnel campaign AI activations increased 106% globally at DoubleVerify from first half to second half 2024. APAC demonstrated particularly strong growth with 129% increases during this timeframe. These campaigns typically represent brands' largest investments, making optimization precision critical for return on investment.

Performance improvement metrics demonstrate substantial gains from AI implementation. Upper-funnel campaigns achieve 50% CPM efficiency improvements, 75% reach increases, and 15% view-through rate enhancements. Middle-funnel operations show 35% CPC efficiency gains, 28% CPCV efficiency improvements, and 137% click-through rate increases. Lower-funnel activities deliver 61% CPA efficiency improvements.

The multi-outcome framework enables complex campaign configuration through customizable parameters. Marketers can establish CPM caps, viewability rate minimums, budget delivery requirements, and performance thresholds within single optimization systems. Third-party signal integration shows 35% cost per action reductions when external verification data feeds into AI bidding engines, a capability that directly showcases DoubleVerify's integrated verification and optimization approach through its Scibids acquisition.

DoubleVerify's Scibids AI technology performs up to 1,500 optimizations daily on single insertion orders, averaging 400 daily optimizations. This processing capability represents the type of automation scale that the study advocates, positioning the acquired technology as a practical solution to the manual optimization challenges identified in the research. The platform integrates with major demand-side platforms including The Trade Desk, Google DV360, Microsoft Xandr, and Comcast Beeswax, providing broad market access for automated bidding implementation.

The custom bidding market remains relatively small, with Scibids competing primarily against Chalice Custom Algorithms as the other notable independent provider. Both companies differentiate from platform-based solutions through transparency and control, though they employ different pricing models. Scibids operates as a software-as-a-service business, while Chalice charges a cost-per-mille fee structure, creating distinct market approaches within the limited competitive landscape.

Scibids' client portfolio includes major advertising holding companies and brands such as Diageo, Dell, Allianz, and Spotify. The technology pulls impression-level data from demand-side platforms, gathering first-party and third-party information along with pricing, contextual, and performance measurement data. This comprehensive data integration enables dynamic creation of bespoke bidding algorithms tailored to specific advertiser requirements and key performance indicators.

Campaign complexity continues expanding as marketers manage varied audiences, budgets, and creative elements across multiple channels simultaneously. Traditional manual approaches struggle with the scale and speed required for effective optimization across hundreds or thousands of campaigns. AI systems process millions of data points within seconds, enabling real-time decision making that exceeds human analytical capabilities.

The methodology encompasses multiple data collection approaches for comprehensive industry insight. Survey data comes from online partner panels with interviews conducted in March 2025. Regional distribution includes APAC, EMEA, LATAM, and North America markets with 95% confidence levels and 2.2 percentage point margins of error.

Platform intelligence derives from DoubleVerify's global advertising verification and optimization activities. Performance comparisons utilize business-as-usual control optimizations against AI-driven optimization results across identical insertion orders. The analysis encompasses activations globally throughout 2024 for comprehensive performance assessment.

Technological investment trends support continued AI development within advertising workflows. McKinsey research indicates 92% of companies plan to increase AI investments despite only 1% achieving full deployment maturity. The disconnect between planning and implementation suggests leadership barriers rather than workforce resistance to AI adoption.

The advertising industry's AI transition reflects broader technological shifts affecting multiple business sectors. Unlike previous automation waves focused primarily on manufacturing or data processing, current AI applications target creative and strategic functions traditionally requiring human judgment and intuition. DoubleVerify's research and subsequent Scibids acquisition position the company as both analyst and solution provider in this market transformation.

The study's methodology and conclusions warrant examination within this commercial context. While the research provides valuable industry insights based on comprehensive survey data and platform intelligence, the findings consistently reinforce narratives that support AI bidding adoption. The emphasis on cost savings, efficiency gains, and automation benefits directly parallels the value propositions that DoubleVerify promotes for its Scibids-powered solutions, suggesting potential influence of commercial interests on research framing and conclusions.

However, the transition from verification to optimization presents inherent conflicts that may limit adoption among certain advertisers. DoubleVerify's traditional role as an independent measurement provider established trust through neutrality in campaign evaluation. The company's expansion into bidding optimization creates potential conflicts of interest, as the same entity now both executes campaign decisions and measures their effectiveness. This dual role may concern advertisers who prefer separation between optimization execution and performance verification.

The shift represents a fundamental change in DoubleVerify's market positioning from independent arbiter to active participant in campaign management. Advertisers traditionally relied on DoubleVerify for unbiased measurement of viewability, brand safety, and fraud detection. The Scibids acquisition introduces optimization algorithms that actively influence where advertising budgets are allocated, potentially creating scenarios where the company optimizes toward metrics it simultaneously measures and reports.

Some advertisers may resist ceding bidding control to a verification provider, particularly given concerns about transparency in automated decision-making. While Scibids offers more visibility than platform-based solutions like Google's Performance Max, advertisers still sacrifice granular control over individual bidding decisions. The automation benefits highlighted in the study must be weighed against reduced oversight capabilities and potential conflicts between measurement objectivity and optimization performance.

The research comes at a strategic moment as DoubleVerify seeks to expand Scibids' market presence beyond the open web into social channels and streaming platforms. CEO Mark Zagorski has indicated plans to apply the bidding technology across Meta, TikTok, and Netflix environments, representing significant growth opportunities for the acquired platform. The study's findings provide market validation for these expansion plans while simultaneously educating potential customers about AI adoption benefits.

DoubleVerify's transition from pure verification services to activation solutions reflects broader industry shifts toward comprehensive advertising technology platforms. Activation solutions now account for approximately half of DoubleVerify's business, with the Scibids acquisition representing a strategic investment in capturing additional market share within the growing automation segment. The timing of this research report aligns with the company's positioning as both measurement provider and optimization solution vendor.

Campaign managers increasingly function as facilitators managing reactive workflows rather than strategic planners developing innovative approaches. AI implementation aims to reverse this dynamic by automating routine decisions and enabling strategic focus on higher-value activities including creative testing and audience strategy development.

The future of AI in advertising extends beyond simple optimization toward comprehensive campaign intelligence. Systems will likely evolve to handle complete campaign lifecycles from initial planning through performance analysis, requiring new skill sets focused on strategy development and AI system management rather than manual execution.

Integration challenges remain as organizations balance automation benefits with control requirements and measurement independence concerns. Successful implementations must address advertiser reluctance to consolidate optimization and verification functions within single vendors. The balance between efficiency gains and strategic control will likely shape AI adoption patterns across different organization types, with some preferring separation between measurement and optimization providers to maintain objectivity in performance evaluation.

The advertising industry faces fundamental questions about the appropriate boundaries between measurement and optimization services. DoubleVerify's expansion into bidding automation represents one approach to integrated advertising technology, though advertiser acceptance may vary based on comfort levels with consolidated vendor relationships. Alternative market structures might preserve measurement independence while still capturing automation benefits through specialized provider partnerships.

Timeline

• January 1, 2025: A new model for AI advertising emerges as agents could replace human attention - Perplexity AI founder outlines vision where AI agents become target audience for digital advertising
• January 26, 2025: DV360: New tools for privacy-focused advertising - Google introduces PAIR and AI tools for enhanced privacy and audience targeting
• March 17, 2025: Adform launches new campaign planning tool for digital advertisers - AI-powered Campaign Planner addresses workflow fragmentation in programmatic advertising
• June 15, 2025: DoubleVerify unveils AI-powered solution for video advertising optimization - DV Authentic AdVantage combines media quality verification with campaign optimization
• June 22, 2025: Meta launches opportunity score globally for all advertisers - AI-driven tool provides campaign optimization guidance while maintaining advertiser control
• July 8, 2025: Google Ads Editor 2.10 brings AI features and enhanced targeting control - Update addresses advertiser demands for precision targeting within automated campaigns
• July 9, 2025: StackAdapt launches AI assistant Ivy for programmatic advertising - Natural language processing capabilities support optimization across multiple programmatic channels
• July 21, 2025: Agentic AI threatens traditional DSP business models says industry veteran - Analysis suggests AI could disrupt programmatic advertising technology stack
• June 2023: DoubleVerify and Scibids announce partnership launching DoubleVerify Algorithmic Optimizer, combining attention metrics with AI-powered decision-making
• August 2023: DoubleVerify completes $125 million acquisition of Scibids, AI-powered bidding optimization startup, adding 70 employees including 20+ AI engineers to its workforce
• August 13, 2025: DoubleVerify releases 2025 Global Insights report examining AI adoption across digital advertising workflows
• October 13, 2024: TikTok launches Smart+: AI-powered ad optimization - End-to-end performance solution leverages machine learning for automated campaign management
• March 2025: McKinsey: AI agents reshape advertising landscape - Industry adoption of AI-powered marketing automation platforms accelerates

Summary

Who: DoubleVerify, a leading software platform for media quality verification and ad performance optimization, conducted research involving 1,970 marketing and advertising decision-makers across APAC, EMEA, LATAM, and North America.

What: Release of the 2025 Global Insights report revealing that marketers spend 26% of their time (over 10 hours weekly) on manual campaign optimizations, costing North American agencies $17,000+ annually per employee. The study shows 42% of marketers already use third-party AI solutions with 49% planning adoption.

When: The report was released on August 13, 2025, based on survey data collected in March 2025 and platform intelligence from DoubleVerify's global operations throughout 2024.

Where: The research encompasses global markets including Asia-Pacific, Europe-Middle East-Africa, Latin America, and North America, with data derived from online partner panels and DoubleVerify's advertising verification platform.

Why: The study addresses growing operational burdens on marketing teams and examines how artificial intelligence can automate routine tasks, reduce costs, and enable strategic focus on campaign innovation and performance optimization in an increasingly complex digital advertising landscape.

PPC Land explains

Campaign Optimization Campaign optimization encompasses the systematic process of adjusting advertising parameters to improve performance metrics and achieve specific marketing objectives. This includes modifications to targeting criteria, bid amounts, budget allocation, creative elements, and timing strategies based on real-time performance data. Modern optimization requires continuous monitoring and adjustment across multiple variables simultaneously, creating complexity that increasingly favors automated solutions over manual management approaches.

Artificial Intelligence (AI) Artificial intelligence in advertising refers to machine learning systems that can analyze data patterns, make predictions, and execute decisions with minimal human intervention. These systems process vast amounts of campaign data to identify optimization opportunities, predict audience behavior, and automatically adjust campaign parameters. AI applications in advertising range from simple automated bidding to complex multi-variable optimization across entire campaign portfolios.

Programmatic Advertising Programmatic advertising represents the automated buying and selling of digital ad inventory through software platforms rather than traditional manual negotiations. This technology enables real-time bidding on ad placements, audience targeting based on data insights, and campaign optimization at scale. Programmatic systems handle millions of transactions per second, making human-speed decision making obsolete for many advertising functions.

Demand-Side Platform (DSP) A demand-side platform serves as the technological infrastructure that enables advertisers to purchase digital ad inventory across multiple sources through automated systems. DSPs provide tools for audience targeting, bid management, campaign tracking, and performance optimization. These platforms integrate with various ad exchanges and supply-side platforms to access diverse inventory sources and enable sophisticated campaign management capabilities.

Manual Optimization Manual optimization involves human marketers directly adjusting campaign parameters based on performance analysis and strategic judgment. This approach typically includes reviewing performance reports, identifying improvement opportunities, and implementing changes through platform interfaces. While manual optimization allows for nuanced strategic decisions, it becomes increasingly inefficient as campaign complexity and scale expand beyond human processing capabilities.

Cost Per Action (CPA) Cost per action measures the average cost required to generate a specific desired outcome from advertising campaigns, such as purchases, registrations, or downloads. CPA calculations divide total campaign costs by the number of completed actions, providing a key metric for evaluating campaign efficiency and return on investment. Lower CPA values generally indicate more effective campaigns, making CPA optimization a primary focus for performance-driven advertising strategies.

Upper-Funnel Campaigns Upper-funnel campaigns focus on building brand awareness and reaching broad audiences early in the customer journey, before specific purchase intent develops. These campaigns typically emphasize reach, frequency, and brand message delivery rather than immediate conversion actions. Upper-funnel strategies require different optimization approaches compared to lower-funnel campaigns, often prioritizing audience quality, brand safety, and message resonance over direct response metrics.

Bid Management Bid management involves setting and adjusting the amounts advertisers are willing to pay for specific ad placements, audiences, or performance outcomes. Effective bid management requires understanding market dynamics, competition levels, audience value, and campaign objectives to optimize spending efficiency. Automated bid management systems use machine learning algorithms to adjust bids in real-time based on performance data and market conditions.

Performance Metrics Performance metrics encompass the various measurements used to evaluate advertising campaign effectiveness, including click-through rates, conversion rates, cost per acquisition, return on ad spend, and viewability rates. These metrics provide quantitative feedback on campaign performance and guide optimization decisions. Modern advertising platforms track hundreds of performance indicators, requiring sophisticated analysis to identify meaningful patterns and optimization opportunities.

Workflow Automation Workflow automation streamlines advertising operations by eliminating manual steps in campaign setup, management, and optimization processes. This includes automated rule-based adjustments, template-driven campaign creation, and integrated reporting systems. Automation reduces human error, increases operational efficiency, and enables marketers to focus on strategic activities rather than routine execution tasks that can be handled by software systems.