How AI is transforming the way brands evaluate advertising value: we analyze verified data and market context, plus actionable insights for brands, agencies, and the advertising industry.

AI in media planning has moved the industry from an experimental phase into a period of proving measurable effectiveness. Briefs now demand not AI tests, but concrete incrementality metrics—the lift in results that would remain unachievable without the new channel or tool. The challenge is that there are no unified standards for measuring incrementality: each brand, agency, and platform uses its own baseline and definition of effectiveness.

How is AI transforming the way brands evaluate advertising value?

Two decades of programmatic infrastructure evolution have created a paradox: media plans are populated not by the most valuable audiences, but by those most accessible for transaction. If inventory can be easily purchased through familiar DSPs and SSPs, it enters the strategy. If it requires separate integration, direct contracts with device manufacturers, or work through privacy-first browsers—the platform drops out of consideration, even when it demonstrates measurable business results.

This logic is especially apparent when working with OEM inventory (native device advertising), CTV platforms outside major ecosystems, and native environments of smart devices. These touchpoints capture a significant share of consumer attention, but historically lie outside standard programmatic workflows. The result is a structural gap between where budgets flow and where untapped sales growth potential resides.

CPMshows the cost per thousand impressions, but not their value for business
Incrementalitythe most requested metric in the industry amid the absence of unified audit standards
OEM, CTV, smart devicessignificant touchpoints historically difficult to access through programmatic channels

In the Russian market, this challenge is amplified by the fragmentation of measurement systems following the exit of Western analytics platforms. Brands are forced to build evidence from scattered sources: proprietary CRM, retail partner data, pixel analytics, and post-view conversions. When each channel is measured differently, comparing effectiveness becomes subjective interpretation rather than objective ranking.

The difference between performance and business value

AI does boost performance: reports that used to take a day are generated in ten minutes, campaign deployment time is cut in half, routine operations are automated. These changes are visible to clients and easily measurable within the agency. But performance is not value.

Value is determined by whether the business economics have changed: whether new demand has emerged that would otherwise go uncaptured, whether incremental sales have grown, whether the unit economics of customer acquisition have improved

These outcomes are harder to measure than creative production time, but they're what ultimately justify technology adoption. As AI becomes foundational infrastructure—embedded in planning, creative development, and operational workflows—the technology itself ceases to be a competitive advantage. The real differentiator becomes the ability to prove with concrete data that AI-informed decisions actually moved the needle on final results, rather than simply accelerating the workflow.

How to measure true campaign incrementality

Incrementality requires comparing two scenarios: what happened when a channel or tool was activated, and what would have happened without it. In practice, this means setting up control groups, hold-out tests, or geo-experiments where part of your audience intentionally doesn't see the ads, then comparing group behavior afterward.

Checklist for evaluating channel or campaign incrementality:

  • Isolate your control group before launch: 10–20% of your audience, matched as closely as possible to your test group on demographics and behavior, who won't see the ads.
  • Establish your baseline: conversion rate, average order value, and purchase frequency in both control and test groups should be equal before the campaign starts.
  • Measure the difference in key actions: after the campaign ends, compare conversions, sales, or other KPIs between groups. That difference is your incremental lift.
  • Account for external factors: if your test period coincided with a sale, holiday, or supply chain disruption, adjust your conclusions to account for these events.
  • Replicate the test in another region or segment: a single experiment isn't enough to justify scaling—validate results in at least two independent conditions.

For the Russian market, access to transaction data remains a key challenge. Not all categories can link ad placements with bloggers or in CTV apps to offline purchases. Promo codes, unique UTM tags, loyalty program integration, and device identifier matching with user consent help bridge this gap.

What's happening with CPM as a value metric

CPM shows the cost per thousand impressions, but it doesn't explain what those impressions were worth to your business. The industry continues using this metric because it's universal and understood by all players in the chain—not because it accurately reflects value. The gap between price and value becomes critical when AI makes it possible to optimize not just cost per contact, but also conversion probability, customer LTV, and channel margins.

Shifting from CPM to incremental metrics requires changing contract models: instead of paying for impressions, you pay for sales growth, for new customer acquisition, or for retention of existing customers. These models are already being tested in the performance segment: paying per qualified lead, per first purchase, per repeat order within 30 days. AI makes such calculations technically possible in real time, but implementing them requires transparent data and trust between advertiser and platform.

Frequently Asked Questions

How is incrementality different from ROMI

Incrementality measures the lift in results that occurred solely because of a specific channel or campaign, using control groups. ROMI (return on marketing investment) shows the overall return on all marketing investments without breaking down by channel and doesn't account for which portion of sales would have happened anyway without advertising. Incrementality is a more precise tool for evaluating the effectiveness of an individual channel.

How to measure incrementality of blogger advertising

Use unique promo codes or UTM tags for each blogger to track direct clicks and purchases. Additionally, set up a hold-out test: part of your target audience won't see the blogger's ad, then compare conversion rates between both groups. The difference will show the actual lift generated by the integration, minus organic demand.

Why CPM doesn't reflect true advertising effectiveness

CPM only reflects the cost of reaching an audience, but doesn't account for the quality of that contact or its impact on sales. Two campaigns with the same CPM can deliver different revenue lift, different customer quality, and different margins. To evaluate effectiveness, you need metrics tied to business results: incremental sales, customer acquisition cost adjusted for LTV, and lift in repeat purchases.

In brief

  • Campaign briefs now require proven incrementality, but there are no unified industry standards for measuring it — each platform uses its own definitions and baselines.
  • The ease of buying inventory is displacing platforms with measurable results but complex integration from media plans: OEM, CTV outside major ecosystems, and privacy-first environments remain underutilized sources of growth.
  • AI performance (report speed, planning automation) does not equal business value — value is determined by sales uplift, improved unit economics, and access to audiences that would otherwise remain unreached.
  • CPM shows the cost per thousand impressions, but not their impact on revenue — the gap between price and value becomes critical when optimizing for conversion and LTV.
  • Measuring incrementality requires control groups, hold-out tests, and baseline fixation before launch — on the Russian market, the key challenge is access to transaction data and linking impressions to offline purchases.
  • As AI becomes basic infrastructure, competitive advantage will come not from the technology itself, but from the ability to prove with real data that decisions made with its help changed the final outcome.

CEO comment

Leonid Naumtsev CEO, ETC AGENCY

We're witnessing a significant shift in how brands evaluate advertising performance. Previously, channel selection was driven by convenience of purchasing through familiar DSP and SSP platforms, but now proven incrementality—the sales lift that wouldn't have happened without that specific channel—has become the decisive factor. The paradox is that there are still no unified standards for measuring incrementality, which creates a real problem: valuable media placements with measurable results get excluded from media plans simply because they're harder to integrate. Our role as an agency is to stop confusing AI productivity with its actual business value. Speed of reporting and planning automation don't equal genuine revenue growth. We need to set up control groups, run hold-out tests, and establish baseline metrics before campaign launch to prove our clients real results, not the sophistication of our tools.

ETC AGENCY

ETC helps brands build media strategies focused on incremental results: we identify high-value placements beyond walled gardens, implement real business-value measurement, and demonstrate which solutions drive actual demand rather than just accelerate processes.

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