Close Menu
  • Home
  • AI Models
    • DeepSeek
    • xAI
    • OpenAI
    • Meta AI Llama
    • Google DeepMind
    • Amazon AWS AI
    • Microsoft AI
    • Anthropic (Claude)
    • NVIDIA AI
    • IBM WatsonX Granite 3.1
    • Adobe Sensi
    • Hugging Face
    • Alibaba Cloud (Qwen)
    • Baidu (ERNIE)
    • C3 AI
    • DataRobot
    • Mistral AI
    • Moonshot AI (Kimi)
    • Google Gemma
    • xAI
    • Stability AI
    • H20.ai
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Microsoft Research
    • Meta AI Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding & Startups
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • Expert Insights & Videos
    • Google DeepMind
    • Lex Fridman
    • Matt Wolfe AI
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • Matt Wolfe AI
    • The TechLead
    • Andrew Ng
    • OpenAI
  • Expert Blogs
    • François Chollet
    • Gary Marcus
    • IBM
    • Jack Clark
    • Jeremy Howard
    • Melanie Mitchell
    • Andrew Ng
    • Andrej Karpathy
    • Sebastian Ruder
    • Rachel Thomas
    • IBM
  • AI Policy & Ethics
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
    • EFF AI
    • European Commission AI
    • Partnership on AI
    • Stanford HAI Policy
    • Mozilla Foundation AI
    • Future of Life Institute
    • Center for AI Safety
    • World Economic Forum AI
  • AI Tools & Product Releases
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
    • Image Generation
    • Video Generation
    • Writing Tools
    • AI for Recruitment
    • Voice/Audio Generation
  • Industry Applications
    • Finance AI
    • Healthcare AI
    • Legal AI
    • Manufacturing AI
    • Media & Entertainment
    • Transportation AI
    • Education AI
    • Retail AI
    • Agriculture AI
    • Energy AI
  • AI Art & Entertainment
    • AI Art News Blog
    • Artvy Blog » AI Art Blog
    • Weird Wonderful AI Art Blog
    • The Chainsaw » AI Art
    • Artvy Blog » AI Art Blog
What's Hot

European Commission Outlines New Strategies for AI and Science – Fintech Schweiz Digital Finance News

Operator Bell begins Cohere AI rollout

Lucio, Lightbringer, Harvey, Jus Mundi, SpotDraft, LI UK + NY – Artificial Lawyer

Facebook X (Twitter) Instagram
Advanced AI News
  • Home
  • AI Models
    • OpenAI (GPT-4 / GPT-4o)
    • Anthropic (Claude 3)
    • Google DeepMind (Gemini)
    • Meta (LLaMA)
    • Cohere (Command R)
    • Amazon (Titan)
    • IBM (Watsonx)
    • Inflection AI (Pi)
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Meta AI Research
    • Microsoft Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • AI Experts
    • Google DeepMind
    • Lex Fridman
    • Meta AI Llama
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • The TechLead
    • Matt Wolfe AI
    • Andrew Ng
    • OpenAI
    • Expert Blogs
      • François Chollet
      • Gary Marcus
      • IBM
      • Jack Clark
      • Jeremy Howard
      • Melanie Mitchell
      • Andrew Ng
      • Andrej Karpathy
      • Sebastian Ruder
      • Rachel Thomas
      • IBM
  • AI Tools
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
  • AI Policy
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
  • Business AI
    • Advanced AI News Features
    • Finance AI
    • Healthcare AI
    • Education AI
    • Energy AI
    • Legal AI
LinkedIn Instagram YouTube Threads X (Twitter)
Advanced AI News
Retail AI

Marketing that thinks for itself: Why agentic AI is the new cornerstone of growth

By Advanced AI EditorJune 23, 2025No Comments4 Mins Read
Share Facebook Twitter Pinterest Copy Link Telegram LinkedIn Tumblr Email
Share
Facebook Twitter LinkedIn Pinterest Email


Let’s face it, if your marketing strategy still needs a team of humans to babysit every campaign, you’re burning hours you don’t have and missing revenue you can’t afford to leave on the table. Retail moves fast—inventory shifts by the hour, customers disappear in seconds and margins get squeezed from every direction, yet too many marketing stacks are still stuck in the past, bogged down by rigid workflows, delayed decisions and non-stop manual effort. That’s a recipe for irrelevance.

Today’s most effective retail leaders are letting go of control, and growing faster because of it. They’re handing the reins to a smarter system: Agentic AI, and rapidly scaling AI-driven performance marketing across their stack.

Retail needs more than optimization. It needs intelligence that acts

Marketers have heard the AI pitch before, quicker A/B tests, tidier segments, a sprinkle of personalization. Most are dabbling with generative tools, using AI to write subject lines or suggest content tweaks. But that’s just scratching the surface.

Agentic AI isn’t here to patch broken processes, it’s built to make thousands of smart, real-time decisions on your behalf, automatically and continuously. What makes it “agentic”? It perceives what’s happening in the moment, whether a customer is viewing a product, abandoning a cart, or returning after weeks and takes the best next action. Not suggestions, not prompts. Action.

It might suppress an email because the shopper is already active on-site. Or trigger a text minutes after a key behavior. Or update messaging for a logged-in customer who’s been price-checking. Whatever the move, the system does it, autonomously, intelligently and across every channel.

This is marketing that thinks for itself. And that shift, from rule-based workflows to autonomous, context-aware execution, is what retail leaders are building into the core of their growth strategies.

Decisioning that moves as fast as your customers

Shoppers don’t wait for your campaign calendar. They scroll, click, bounce and convert on their own terms, and they expect every interaction to feel relevant in the moment. Meeting that expectation takes more than connected data. It requires systems that can think and act faster than any human team.

Agentic decisioning makes that possible. It responds instantly to behavior, deciding whether to send, suppress, or adapt a message in real time, not hours later, and not based on a rigid flowchart. With every interaction, it learns and improves.

This isn’t about message volume. It’s about precision: the right content, for the right customer, at exactly the right moment. Consistently.

Build smarter, not bigger

Of course, none of that works if you bolt smart tech onto a brittle stack. Agentic platforms that actually deliver are built to flex. Some teams use lightweight SDKs to control data collection. Others plug into APIs that work with existing ESPs, CDPs, or internal systems. Many drop behavior-triggered decisions into the platforms they already use, without giving up creative control.

The best systems don’t force a tradeoff between speed and flexibility—they give you both. Seamless integration. Clean data. No extra strain on your engineering team.

In retail, where agility is survival, that kind of flexibility is essential. Performance marketing is no longer just a media tactic, it’s a system for growing revenue across every touchpoint, powered by AI that adapts on its own.

The message from Wunderkind’s playbook on how to integrate AI-driven performance marketing across your stack is clear—retail marketers are tying identity, behavior and results together with agentic decisioning. It’s not hype. It’s what comes next.

Most marketers are still doing the heavy lifting themselves. The leaders are letting their systems think for them. In a world where the next conversion, or drop-off, is one click away, that’s the edge that matters. Start with marketing that decides for itself. The rest follows.



Source link

Follow on Google News Follow on Flipboard
Share. Facebook Twitter Pinterest LinkedIn Tumblr Email Copy Link
Previous ArticleDigital Creatures Learn to Navigate in 3D | Two Minute Papers #153
Next Article Why global markets are brushing off U.S. strikes on Iran
Advanced AI Editor
  • Website

Related Posts

Dollar Tree to open 1.25M-square-foot Arizona distribution center

October 9, 2025

Ikea operator acquires AI logistics platform

October 8, 2025

Gap Inc. recruits micro-influencers for new affiliate program

October 8, 2025
Leave A Reply

Latest Posts

Frieze to Launch Abu Dhabi Fair in November 2026

Jeff Koons Returns to Gagosian with First New York Show in Seven Years

$45 M. Basquait Painting to Headline Sotheby’s Fall Sales in New York

Guggenheim’s 2026 Shows Include Carol Bove Survey, Taryn Simon Project

Latest Posts

European Commission Outlines New Strategies for AI and Science – Fintech Schweiz Digital Finance News

October 10, 2025

Operator Bell begins Cohere AI rollout

October 10, 2025

Lucio, Lightbringer, Harvey, Jus Mundi, SpotDraft, LI UK + NY – Artificial Lawyer

October 10, 2025

Subscribe to News

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

Recent Posts

  • European Commission Outlines New Strategies for AI and Science – Fintech Schweiz Digital Finance News
  • Operator Bell begins Cohere AI rollout
  • Lucio, Lightbringer, Harvey, Jus Mundi, SpotDraft, LI UK + NY – Artificial Lawyer
  • SciVideoBench: Benchmarking Scientific Video Reasoning in Large Multimodal Models – Takara TLDR
  • Alibaba’s Qwen Team Takes Off! Lin Junyang Leads the Charge as a Major Player Joins the Embodied Intelligence Arena_known_team_models

Recent Comments

  1. nuwobtCheab on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  2. Jasonboili on [2405.19874] Is In-Context Learning Sufficient for Instruction Following in LLMs?
  3. Thomaswam on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10
  4. metall-115 on C3 AI and Arcfield Announce Partnership to Accelerate AI Capabilities to Serve U.S. Defense and Intelligence Communities
  5. viagra stock on Building a foundation with AI to jumpstart your journalism

Welcome to Advanced AI News—your ultimate destination for the latest advancements, insights, and breakthroughs in artificial intelligence.

At Advanced AI News, we are passionate about keeping you informed on the cutting edge of AI technology, from groundbreaking research to emerging startups, expert insights, and real-world applications. Our mission is to deliver high-quality, up-to-date, and insightful content that empowers AI enthusiasts, professionals, and businesses to stay ahead in this fast-evolving field.

Subscribe to Updates

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

LinkedIn Instagram YouTube Threads X (Twitter)
  • Home
  • About Us
  • Advertise With Us
  • Contact Us
  • DMCA
  • Privacy Policy
  • Terms & Conditions
© 2025 advancedainews. Designed by advancedainews.

Type above and press Enter to search. Press Esc to cancel.