Advertising effectiveness is measured through several lenses: modeled return on ad spend (ROAS), incremental sales, brand recall, reach, and the quality of the signals used for attribution. The statistics below span Southeast Asian consumer packaged goods, U.S. video advertising, global privacy and data practices, and retail media. Measurement periods and study scopes matter because these figures are estimates, survey results, or case-study outcomes rather than universal benchmarks.
Contents
- Campaign return and sales lift
- Brand lift and recall
- Video channel reach and buying priorities
- Measurement obstacles
- Privacy, signal loss, and attribution
- Budget allocation and retail media
Campaign return and sales lift
Nielsen’s Southeast Asia CPG Marketing Mix Modeling meta-analysis provides a campaign-level view of effectiveness for TikTok. The analysis modeled two years of historical data in 2023. It reported a modeled short-term return of $1.70 for every advertising dollar, and said TikTok’s short-term result was 2.0 times better than the other measured media channels in the study. The result is a modeled estimate for the study’s market and category scope, not a guarantee for every advertiser. (Southeast Asia: CPG Marketing Mix Modeling meta analysis)
The same analysis separated immediate sales from the longer-term effect of brand equity. TikTok advertising delivered 2.2 times more modeled long-term sales through brand-equity impact than the other measured channels. When short-term return and long-term brand equity were combined, TikTok outperformed the other measured channels by 1.4 times. The combined model produced total ROAS of $2.30 per advertising dollar. These comparisons depend on the modeling approach and the channels included in the study.
The study also reported a sales-lift result for channel coordination. Running TikTok ads with television ads for at least four weeks generated 9.4% incremental sales in Southeast Asia. This figure describes the reported incremental outcome of that combined schedule and period; it does not establish that every TikTok-and-TV plan will produce the same lift.
TikTok format-level modeled ROAS
The format results show why a single platform average can hide meaningful differences. TikTok In-Feed ads produced modeled short-term ROAS of $2.00 per dollar and modeled long-term ROAS of $2.80 per dollar. Branded Effect ads produced modeled short-term ROAS of $2.30 per dollar and modeled long-term ROAS of $3.00 per dollar. Brand ads produced modeled short-term ROAS of $1.50 per dollar, while creator ads produced modeled short-term ROAS of $2.00 per dollar.
| TikTok format | Modeled short-term ROAS | Modeled long-term ROAS |
|---|---|---|
| In-Feed ads | $2.00 | $2.80 |
| Branded Effect ads | $2.30 | $3.00 |
| Brand ads | $1.50 | Not reported |
| Creator ads | $2.00 | Not reported |
All figures in this table come from Nielsen’s Southeast Asia study, using two-year historical data modeled in 2023. “Not reported” means the supplied study result did not provide a long-term figure for that format, not that the long-term return was zero.
Brand lift and recall
Brand metrics capture effects that a short-term sales calculation may miss. Google’s Measuring the Impact of Online Video on Brand Metrics study, published in March 2015, analyzed campaigns completed before publication. Among about 50 Google Preferred campaigns, 94% produced a statistically significant lift in ad recall. The campaigns that lifted ad recall had an average ad-recall lift of 80%. (Measuring the Impact of Online Video on Brand Metrics)
The same study reported that 65% of the Google Preferred ads analyzed increased brand awareness. The ads that increased awareness had an average brand-awareness lift of 17%. These are study findings from the analyzed campaign group and measurement period; they should not be read as a current universal rate for online video.
A larger set of YouTube TrueView Brand Lift studies showed a related pattern. Of more than 800 studies, 65% showed a statistically significant lift in brand interest. The YouTube TrueView campaigns that lifted brand interest had an average lift of 13%. The percentage describes the share of studies with a significant result, while the 13% describes the average lift among campaigns that lifted brand interest.
Creative execution also mattered in the study’s Trident Unlimited case. In a Mondelez creative test, the version showing the actor already chewing produced a recall rate 5% higher than the comparison version. After Mondelez optimized budget toward the higher-recall creative, campaign recall reached 97%. This is a case-study outcome from the Trident Unlimited campaign published in 2015, so it is best used as an example of creative optimization rather than a general forecast.
Video channel reach and buying priorities
The 2024 IAB Video Ad Spend Report surveyed U.S. advertisers with at least $50 million in annual media spend. In that large-spender group, 70% considered social video a must-buy for their media plan and 69% considered connected TV (CTV) a must-buy. National broadcast or cable TV was a must-buy for 46%, while local broadcast or cable TV was a must-buy for 34%. Audience-addressable TV and online video each were considered a must-buy by 28%.
Across video advertisers, reach or scale was among the top three investment criteria for 79%. Ad quality ranked in the top three for 70%, measurement for 66%, and brand safety or suitability for 60%. Audience personalization capabilities were a crucial criterion when selecting an advertising partner for 66% of buyers. (2024 IAB Video Ad Spend Report)
These results suggest that effectiveness is not evaluated only after a campaign runs. Buyers also use expected reach, the quality of the ad experience, measurement capability, safety, and personalization to decide where spending belongs. The survey’s population is important: the must-buy figures describe large U.S. advertisers, while the investment-criteria figures describe video advertisers more broadly within the report.
Measurement obstacles
The IAB report also documented why reported effectiveness can be difficult to compare across TV and video campaigns. Co-viewing was very much or somewhat an issue for 70% of buyers measuring campaign effectiveness. Placement transparency was an issue for 69%, brand safety or suitability for 68%, and viewability for 67%.
Other reported obstacles affected the quality and comparability of delivery data. Ads served on made-for-advertising sites were an issue for 66% of buyers, as were ads served on televisions that were turned off. Obtaining sell-side data was an issue for 65%, and using multiple currencies was also an issue for 65%. Standardized sell-side targets were an issue for 64%.
| Measurement issue | Buyers reporting it as an issue |
|---|---|
| Co-viewing | 70% |
| Placement transparency | 69% |
| Brand safety or suitability | 68% |
| Viewability | 67% |
| Made-for-advertising sites | 66% |
| TVs that were turned off | 66% |
| Sell-side data access | 65% |
| Multiple currencies | 65% |
| Standardized sell-side targets | 64% |
Because these figures are survey responses, they measure buyer-reported difficulty rather than the frequency of an objectively verified defect. Still, they show why a high delivery number or platform-reported conversion total may not be enough to establish incremental business impact.
Privacy, signal loss, and attribution
The IAB State of Data 2024 report examined how privacy changes and signal loss were affecting data practices. Its survey was conducted from November 2023 through February 2024. Sixty-one percent of respondents expected it to become harder to collect demographic, preference, and behavior data from third parties. Seventy-two percent expected reduced access to browser history, real-time signals, personally identifiable information, and location data. (IAB State of Data 2024)
Respondents also reported lower confidence in data accuracy from several sources. Fifty-nine percent reported lower confidence in data received from social platforms because of legislation and signal loss. The corresponding figures were 57% for programmatic platforms and 52% for ad servers. These findings concern confidence in received data, not a measured percentage error in any one platform’s reporting.
Attribution and optimization were expected to become harder as well. Seventy-three percent expected reduced ability to attribute campaign or channel performance, measure ROI, track conversions, and optimize campaigns. Fifty-seven percent expected it to become harder to capture advertising reach and frequency.
The reported response was investment in owned and measurement capabilities. Seventy-one percent of brands, agencies, and publishers said they were increasing their first-party data sets to support media efforts. Those increasing first-party data sets anticipated average growth of 35% within the following 12 months. In addition, 87% of data decision-makers were investing or planning to invest in website analytics tools because of legislation and signal loss. These are expectations and planned actions from the November 2023–February 2024 survey period, not guarantees about subsequent implementation or performance.
Budget allocation and retail media
Retail media was another area where marketers reported shifting priorities. Nielsen’s 2025 marketer survey found that 65% of global marketers said retail media networks would play a bigger role in their media mix in 2025. Regionally, 74% of North American marketers said retail media networks were more important than the prior year, compared with 69% in Latin America and 68% in Asia-Pacific. (The future of retail media)
Europe showed a different direction in the supplied comparison: 48% of European marketers planned to increase retail-media-network use, compared with 59% in 2024. The comparison is between the 2025 survey result and the prior reported 2024 figure, so it indicates a lower planned-increase share rather than a quantified decline in retail-media sales or ROAS.
Nielsen Ad Intel data in the 2025 report also described how global Amazon retail-media budgets were distributed. Sponsored products accounted for 40%, sponsored brands for 24%, display ads for 20%, and video ads for 16%.
| Amazon retail-media format | Share of global budget |
|---|---|
| Sponsored products | 40% |
| Sponsored brands | 24% |
| Display ads | 20% |
| Video ads | 16% |
These budget shares are allocation indicators, not effectiveness scores. A larger share shows where reported spending was concentrated; it does not by itself prove that a format generated higher incremental sales or better ROAS. For that reason, retail-media planning should keep budget distribution separate from outcome measurement and make the measurement scope explicit.