Kapnova provides advertising analytics, simulation, measurement, and decision-support services for brands running paid media across Amazon Ads, retail media, Google Ads, TikTok Ads, Meta, Klaviyo, Shopify, and marketplace channels.
Kapnova helps advertising teams evaluate what happened, what is likely to happen next, and which media decision has the best risk-adjusted outcome.
Review spend, impressions, clicks, conversions, attributed revenue, ROAS, CAC, and SKU-level advertising performance across connected platforms.
Simulate budget shifts across Amazon Ads, retail media, Google, TikTok, Meta, influencer campaigns, and marketplace channels before changing spend.
Evaluate creative fatigue, campaign timing, influencer portfolio risk, sentiment response, engagement lift, and audience reaction before scaling a campaign.
Connect advertising performance with marketplace context: SKU velocity, product launches, inventory availability, promotion windows, and competitor response.
Back-test prior campaigns, build a current decision simulation, design a test plan, and deliver advertiser-ready reporting for leadership review.
Translate advertising data into CEO, CMO, CFO, and growth-team recommendations with confidence bands, assumptions, downside risk, and dissenting views.
Kapnova helps brands evaluate Amazon Ads and retail media decisions before budget is committed. Services include sponsored ads performance analysis, campaign back-testing, spend reallocation simulations, marketplace demand context, SKU-level advertising readouts, and executive-ready recommendations.
Kapnova supports consumer brands, retail media advertisers, DTC and marketplace sellers, and marketing, growth, and performance teams that need defensible advertising decisions before they move spend.
Kapnova supports advertising and marketplace analysis across Amazon Ads, Google Ads, TikTok Ads, Meta, Klaviyo, Shopify, Triple Whale, Impact, retail media, and marketplace data sources.
Start with your URL and Kapnova will surface what it can find from public data alone. Then connect your own data to measure what past decisions actually caused and where the next revenue or profit opportunity may be.