LiveOps Analysis

Ad Campaign Analysis

A full quantitative analysis of ad campaign performance on the AE analytics platform: channel efficiency, conversion funnel, attribution analysis, retention quality, and ROI accounting.

IndustriesGamesE-commerce

Agent · Skills Live

skill · loadedindustry+100

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Ad Campaign Analysis is a campaign-performance quantification capability in ThinkingAI's industry Skill library. It helps growth and operations teams complete end-to-end ad-campaign analysis in one place, from channel efficiency, conversion funnel, and attribution contribution to retention quality and ROI accounting, packaging the complex work of combining multiple models into a standardized process. This is ThinkingAI's decade of industry experience, packaged into ready-to-use Skills.

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June's user-acquisition push had 5 active campaigns, and the CTR on paper looks fine across the board, but overall payback just won't come up. Pull every campaign's performance metrics side by side and, above all, find out who's burning money.

Metadata query: confirm the channel and campaign fields

Matched media_source + campaign_id, 5 active campaigns

Event analysis: break down impressions / clicks / activations / payment by campaign

43,265 new users entered the cohort in the last 30 days

Funnel analysis: activation-to-first-payment conversion window set to 7 days

P1 activation→first-payment conversion 8%, P3 at 22%

Retention analysis: D3 retention and 7-day LTV by campaign

ROI accounting: LTV vs CAC to judge payback

Overall ROI 1.28, P1 / P5 below the break-even line

The comparison is done. The real money-burners are the two biggest spenders: P1 'Hype-Cut Montage,' high CTR and low retention, and P5 'Legacy Creative Rerun,' already in decline, together they eat 58% of the budget, yet both sit below the break-even line. Last-30-day per-campaign data for a sample anime card game (demo) follows.

1. Six-metric data by campaign

Campaign	Spend share	CTR	CPI	D3 retention	Payment rate	ROI
P1 Hype-Cut Montage	28%	4.2%	$6.8	11%	0.6%	0.71
P2 Story-Driven Creative	18%	2.8%	$9.5	21%	1.6%	1.9
P3 Creator Live-Action	9%	2.1%	$10.4	26%	2.4%	2.6
P4 Search Keywords	15%	3.1%	$8.2	19%	1.4%	1.5
P5 Legacy Creative Rerun	30%	2.4%	$7.6	17%	1.1%	0.94

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Three signals: (1) P1 has the highest CTR of the lot (4.2%), but only 11% D3 retention (19% overall) and just 8% activation→first-payment: the creative maxes out the urge to click, but it pulls in the wrong players; (2) P5's CTR has fallen 21% cumulatively over the last 10 days, yet daily spend is still above $8,000: there's no stop mechanism for creative in decline; (3) P3 Creator Live-Action has only 2.1% CTR but a 7-day LTV 46% above the overall: held down at 9% of spend by the 'budget by CTR' logic.

2. ROI comparison by campaign

Last-30-day ROI comparison by campaign

Rank by CTR versus rank by ROI and the order flips completely: P1, the highest CTR, is the worst ROI campaign, and P3, the lowest CTR, is the ROI champion. Each metric alone has a reasonable explanation, but put together the conclusion reverses: the problem isn't that the creative is bad, it's that budget follows CTR instead of payback.

Conclusion

Three moves: (1) cut P1 spend from 28% to 10%, keeping a small amount as an audience control; (2) retire and refresh P5's declining creative this week to stop the $8,000+ daily burn first; (3) scale P3 budget from 9% to 24% to test whether its LTV advantage holds. On this plan, overall ROI should recover from 1.28 to above 1.7; after scaling, watch P3's marginal CPI weekly.

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The problem

Ad campaign analysis involves several models, event analysis, funnel analysis, attribution analysis, retention analysis, and ROI accounting, and a complete analysis needs at least 4 to 5 of them combined. Analysts build reports one by one, with many parameters like channel field names, attribution windows, and funnel steps, and a full campaign analysis usually takes 2 to 3 days. Definitions are inconsistent across analysts, and about 40% of campaign assessments reach opposite conclusions on the same channel, leading to budget misjudgment.

What it does

Full coverage of five core scenarios: channel-performance overview, ad conversion funnel, attribution analysis, retention-quality assessment, and ROI accounting

Automatically adapts to each project's channel field name (channel / utm_source / media_source), checking metadata before configuring

Attribution analysis supports first-touch, last-touch, and linear models, recommending the right one for the business scenario

ROI accounting uses simultaneously-displayed metrics in the retention model to automatically compute LTV and compare against CAC to output a payback verdict

Funnel analysis provides reasonable conversion-window suggestions, such as click to install, install to registration, and registration to first payment

When to use it

Quickly assessing each channel's efficiency and quality after acquiring a new batch of users

A clear drop-off in the ad conversion chain that needs the biggest problem step located

Unclear contribution of multiple ad touchpoints to the final conversion that needs attribution analysis

Low retention quality for a channel's users that needs comparison of retention rate and LTV across channels

Computing each channel's ROI to decide which channels can pay back and which should be paused

In the field

Case

A game project · June campaign performance assessment

The project ran 3 channels. The Skill first used event analysis to break down impressions, clicks, installs, registrations, and payment amount by channel, finding channel A had the most registrations but a low payment rate; funnel analysis then found channel A's registration-to-payment conversion was only 8% versus channel C's 22%; attribution analysis showed channel A's touchpoint contribution was only 15% versus channel C's 45%; and the final verdict was that channel A was not expected to pay back while channel C would pay back by D60.

FAQ

Which attribution model should ad attribution use?

First-touch attribution for brand-awareness campaigns, last-touch attribution for performance-driven campaigns, and linear attribution for multi-channel long chains.

How long should the attribution window be?

Usually 7 to 30 days on mobile, longer for games and shorter for e-commerce, depending on the product decision cycle.

What is the difference between ROI accounting and LTV analysis?

ROI accounting specifically means ad-campaign payback analysis, computing LTV in the retention model and comparing it against CAC, while LTV analysis is more general.