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    <title>InfoQ - Marketing</title>
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    <description>InfoQ Marketing feed</description>
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      <title>Instacart Scales Personalized Marketing via Configuration-Driven Multi-Tenant Platform</title>
      <link>https://www.infoq.com/news/2026/07/instacart-multi-tenant-marketing/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Marketing</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Instacart redesigned its personalized marketing system using a configuration-driven multi-tenant architecture on Storefront Pro. The system replaces retailer-specific implementations with a shared execution engine, enabling scalable personalization, faster configuration propagation in under a minute, and 99.9% delivery success across hundreds of retail banners through a unified campaign platform.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>SMS</category>
      <category>Marketing</category>
      <category>Distributed Systems</category>
      <category>Multi-Tenant Data</category>
      <category>Observability</category>
      <category>Configuration Management Tools</category>
      <category>Event Driven Architecture</category>
      <category>Multi-tenancy</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>news</category>
      <pubDate>Wed, 01 Jul 2026 14:05:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/07/instacart-multi-tenant-marketing/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Marketing</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-07-01T14:05:00Z</dc:date>
      <dc:identifier>/news/2026/07/instacart-multi-tenant-marketing/en</dc:identifier>
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    <item>
      <title>Inside Target’s LLM-Based System for Semantic Matching in Marketing Forecast Pipelines</title>
      <link>https://www.infoq.com/news/2026/06/target-ai-campaign-forecasting/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Marketing</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/06/target-ai-campaign-forecasting/en/headerimage/generatedHeaderImage-1780529558601.jpg"/&gt;&lt;p&gt;Target built a generative AI system to improve marketing campaign forecasting by retrieving and ranking similar historical campaigns. Using embeddings, vector search, and LLM ranking, it replaces rule-based workflows. Evaluation shows 75% top-1 and 100% top-3 coverage. The system reduces manual effort, improves consistency, and uses feedback loops to refine retrieval using campaign outcomes.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Systems Thinking</category>
      <category>Retrieval-Augmented Generation</category>
      <category>Large Concept Models</category>
      <category>Data Analytics</category>
      <category>vector databases</category>
      <category>Observability</category>
      <category>Evolutionary Architecture</category>
      <category>MLOps</category>
      <category>Machine Learning</category>
      <category>Marketing</category>
      <category>Generative AI</category>
      <category>Model Fine Tuning</category>
      <category>Business Analytics</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 29 Jun 2026 14:26:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/06/target-ai-campaign-forecasting/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Marketing</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-06-29T14:26:00Z</dc:date>
      <dc:identifier>/news/2026/06/target-ai-campaign-forecasting/en</dc:identifier>
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