{"id":58541,"date":"2026-05-21T23:11:44","date_gmt":"2026-05-21T20:11:44","guid":{"rendered":"https:\/\/affisemmp.com\/?post_type=glossary-term&#038;p=58541"},"modified":"2026-06-03T14:33:57","modified_gmt":"2026-06-03T11:33:57","slug":"incrementality-testing","status":"publish","type":"glossary-term","link":"https:\/\/affisemmp.com\/ru\/glossary-term\/incrementality-testing\/","title":{"rendered":"Incrementality Testing"},"content":{"rendered":"<h2 id=\"What-is-incrementality-testing\" tabindex=\"-1\" data-local-id=\"ee40567e-776f-403e-b2fd-0dd74dcf2d75\" data-renderer-start-pos=\"18381\">What is incrementality testing<\/h2>\n<p data-renderer-start-pos=\"18413\" data-local-id=\"dd45561b-7289-4e99-9e4b-95d5010620b1\">Incrementality testing is designed to answer one critical question: <em data-renderer-mark=\"true\">\u201cHow much of our observed results would not have occurred without this marketing campaign?\u201d<\/em> For example, some users might purchase a product or install an app even without seeing an ad, due to brand recognition, word of mouth, or other external influences. Incrementality testing separates these naturally occurring actions from those truly driven by marketing, providing a <strong data-renderer-mark=\"true\">clear picture of the campaign\u2019s causal impact<\/strong>.<\/p>\n<p data-renderer-start-pos=\"18903\" data-local-id=\"9a0cd46fbbc8\">By measuring true incremental lift, advertisers can evaluate the efficiency and effectiveness of their marketing channels, identify which campaigns are genuinely contributing to business growth, and avoid overvaluing efforts that appear successful only because of baseline activity.<\/p>\n<h2 id=\"How-incrementality-testing-works\" tabindex=\"-1\" data-local-id=\"e923befd-be0c-411f-acc9-60f426a64e75\" data-renderer-start-pos=\"19187\">How incrementality testing works<\/h2>\n<p data-renderer-start-pos=\"19221\" data-local-id=\"b4e3a841-98eb-4568-91e0-4fd003ecef63\">Incrementality testing typically relies on <strong data-renderer-mark=\"true\">controlled experiments<\/strong> that divide the audience into two distinct groups: a test group and a control group. The test group is exposed to the marketing activity, such as an ad campaign, promotion, or email, while the control group receives no exposure. After a defined period, outcomes from both groups are compared to determine the <strong data-renderer-mark=\"true\">incremental impact<\/strong> generated specifically by the campaign.<\/p>\n<p data-renderer-start-pos=\"19656\" data-local-id=\"b8836eabbabd\">This methodology can be applied to various marketing channels, including digital ads, email campaigns, push notifications, or in-app promotions. By carefully structuring the experiment, marketers can minimize bias and external influences, making incrementality testing one of the most reliable ways to measure the <strong data-renderer-mark=\"true\">true effectiveness of marketing efforts<\/strong>.<\/p>\n<h2 id=\"Why-it-matters\" tabindex=\"-1\" data-local-id=\"0a2c4914-36c9-4d02-844d-a9c2d1473256\" data-renderer-start-pos=\"20012\">Why it matters<\/h2>\n<ul class=\"ak-ul\" data-local-id=\"217b46b46d05\" data-indent-level=\"1\">\n<li>\n<p data-renderer-start-pos=\"20030\" data-local-id=\"2296598024c6\">Ensures marketers measure the <strong data-renderer-mark=\"true\">true causal impact<\/strong> of campaigns rather than relying on surface-level metrics<\/p>\n<\/li>\n<li>\n<p data-renderer-start-pos=\"20140\" data-local-id=\"4e06164db8aa\">Helps avoid <strong data-renderer-mark=\"true\">overestimating ROI<\/strong> and wasting ad spend on campaigns that would have performed organically<\/p>\n<\/li>\n<li>\n<p data-renderer-start-pos=\"20246\" data-local-id=\"e14da93dce1d\">Provides insight into <strong data-renderer-mark=\"true\">which campaigns genuinely drive conversions, purchases, or user actions<\/strong><\/p>\n<\/li>\n<li>\n<p data-renderer-start-pos=\"20343\" data-local-id=\"c24ab9d875b7\">Supports smarter <strong data-renderer-mark=\"true\">budget allocation<\/strong> by focusing on marketing initiatives that deliver measurable growth<\/p>\n<\/li>\n<li>\n<p data-renderer-start-pos=\"20449\" data-local-id=\"976feda86102\">Enables optimization of targeting, creative strategies, and media spend based on <strong data-renderer-mark=\"true\">data-driven results<\/strong><\/p>\n<\/li>\n<\/ul>\n","protected":false},"template":"","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false},"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.1 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Incrementality Testing &#8212; Affise<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/affisemmp.com\/ru\/glossary-term\/incrementality-testing\/\" \/>\n<meta property=\"og:locale\" content=\"ru_RU\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Incrementality Testing &#8212; Affise\" \/>\n<meta property=\"og:description\" content=\"What is incrementality testing Incrementality testing is designed to answer one critical question: \u201cHow much of our observed results would not have occurred without this marketing campaign?\u201d For example, some users might purchase a product or install an app even without seeing an ad, due to brand recognition, word of mouth, or other external influences. 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