{"id":1932,"date":"2025-09-18T11:29:00","date_gmt":"2025-09-18T09:29:00","guid":{"rendered":"https:\/\/brainsuite.ai\/?p=1932"},"modified":"2025-10-20T11:30:29","modified_gmt":"2025-10-20T09:30:29","slug":"rethinking-shelf-strategies-how-lavazza-uses-predictive-ai-to-elevate-shopper-perception","status":"publish","type":"post","link":"https:\/\/brainsuite.ai\/en\/resources\/rethinking-shelf-strategies-how-lavazza-uses-predictive-ai-to-elevate-shopper-perception\/","title":{"rendered":"Rethinking Shelf Strategies: How Lavazza Uses Predictive AI to Elevate Shopper Perception"},"content":{"rendered":"\n<p>In retail, shelf placement is more than logistics\u2014it\u2019s a key driver of brand visibility and decision-making. Shoppers make split-second judgments based on what they see. Yet, for years, shelf design has been shaped by convention rather than concrete data.<\/p>\n\n\n\n<p>Lavazza, a leading global coffee brand, took a new approach. By integrating Brainsuite\u2019s predictive AI into their category planning, they gained real-time insight into what shoppers actually notice\u2014transforming shelf strategy from a best-guess effort into a data-driven discipline.<\/p>\n\n\n\n<figure class=\"wp-block-embed is-type-video is-provider-vimeo wp-block-embed-vimeo\"><div class=\"wp-block-embed__wrapper\">\n<iframe loading=\"lazy\" title=\"Brainsuite &amp; Lavazza: Smarter Shelf Strategies with Shopper Insights\" src=\"https:\/\/player.vimeo.com\/video\/1115514103?dnt=1&amp;app_id=122963\" width=\"500\" height=\"281\" frameborder=\"0\" allow=\"autoplay; fullscreen; picture-in-picture; clipboard-write; encrypted-media; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\"><\/iframe>\n<\/div><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">From Gut Feel to Clear Vision: Challenging Old Shelf Norms<\/h3>\n\n\n\n<p>Traditionally, shelf placement decisions followed a familiar rulebook: lead SKUs go at eye level, products are grouped by sub-brand or segment, and design follows assumed shopper logic. But these rules often lacked validation.<\/p>\n\n\n\n<p>As Moritz Patzke, Director Digital Transformation &amp; Data Strategy at Lavazza noted:<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>\u201cWe always had a set of rules\u2014but no data showing which brand or SKU truly earned its shelf level.\u201d<\/p>\n<\/blockquote>\n\n\n\n<p>Without visibility into how shelf changes impacted shopper perception, optimizing layout remained a guessing game.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Predictive Attention: Understanding What Shoppers Actually See<\/h3>\n\n\n\n<p>With Brainsuite\u2019s Pack + Shelf AI app, Lavazza was able to test multiple shelf layouts virtually\u2014bypassing the cost and constraints of traditional eye-tracking studies. Powered by neuroscience-based algorithms, the platform simulates real shopper attention, providing instant, reliable predictions on what will catch the eye.<\/p>\n\n\n\n<p>One key learning: <strong>sub-brand color coding played a more decisive role in attention than previously assumed.<\/strong> Small shifts in color contrast or placement significantly influenced visual hierarchy and product recall\u2014often more than changes in SKU size or label design.<\/p>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>\u201cThe insight: It\u2019s not just about being seen. It\u2019s about being seen in the right sequence, by the right shopper, at the right moment.\u201d<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">Building Smarter Shelves: Scalable, Measurable, Repeatable<\/h3>\n\n\n\n<p>Lavazza embedded Brainsuite directly into their internal category workflows, enabling continuous iteration and faster decision-making. Teams now use the platform to:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Evaluate shelf layouts before rollout<\/li>\n\n\n\n<li>Quantify the visibility of SKUs and sub-brands<\/li>\n\n\n\n<li>Maximize use of high-attention shelf zones<\/li>\n\n\n\n<li>Strengthen data-based conversations with retail partners<\/li>\n<\/ul>\n\n\n\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>\u201cThis gave us a toolkit to move from static shelf plans to dynamic, evidence-based scenarios,\u201d says Moritz Patzke.<\/p>\n<\/blockquote>\n\n\n\n<h3 class=\"wp-block-heading\">Brainsuite: Your Platform for Smarter Shelf Strategies<\/h3>\n\n\n\n<p>Brainsuite\u2019s Pack + Shelf app empowers brands to evaluate shelf layout and product placement using predictive AI\u2014without needing consumer panels or in-store tests. It simulates shopper perception at scale, helping teams optimize attention, branding, and visual hierarchy in real retail environments.<\/p>\n\n\n\n<p><strong>What You Can Expect:<\/strong><br>\u2705 Predictive eyetracking with 98.7% accuracy<br>\u2705 Rapid feedback for iterative design cycles<br>\u2705 Configurable insights tailored to category and shelf objectives<\/p>\n\n\n\n<p><strong>The outcome?<\/strong> Smarter shelf placement, better brand standout, and measurable impact at the point of sale.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Unlock the Full Potential of Your Shelf Strategy<\/h3>\n\n\n\n<p>Brainsuite is more than a testing tool. It\u2019s a scalable platform that enables marketing and retail teams to build AI capabilities into their workflows\u2014simplifying decision-making while boosting ROI.<\/p>\n\n\n\n<p>Want to see how your brand performs on the shelf\u2014before it hits the store?<\/p>\n\n\n\n<p>\ud83d\udc49<a href=\"https:\/\/getbrainsuite.com\/pack-shelf\" target=\"_blank\" rel=\"noopener\">&nbsp;Discover Brainsuite Pack + Shelf<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In retail, shelf placement is more than logistics\u2014it\u2019s a key driver of brand visibility and decision-making. Shoppers make split-second judgments based on what they see. Yet, for years, shelf design has been shaped by convention rather than concrete data. Lavazza, a leading global coffee brand, took a new approach. By integrating Brainsuite\u2019s predictive AI into [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":1933,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_breakdance_hide_in_design_set":false,"_breakdance_tags":"","footnotes":""},"categories":[14,47],"tags":[],"class_list":["post-1932","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","category-pack-shelf"],"_links":{"self":[{"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/posts\/1932","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/comments?post=1932"}],"version-history":[{"count":1,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/posts\/1932\/revisions"}],"predecessor-version":[{"id":1934,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/posts\/1932\/revisions\/1934"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/media\/1933"}],"wp:attachment":[{"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/media?parent=1932"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/categories?post=1932"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/brainsuite.ai\/en\/wp-json\/wp\/v2\/tags?post=1932"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}