AI agents are reshaping commerce, but brand-owned experiences still matter. Explore how brands can use context, personalization, and engaging experiences to stay relevant.
Learn how to audit your eCommerce store for AI discovery, measure brand visibility and accuracy, fix content gaps, and improve your chances of being recommended.
Learn how to build an AI marketing stack for eCommerce with clean data, connected tools, reliable measurement, governance, and a practical migration plan.
Use Storyly Banners and Stories to run faster product discovery experiments, build pre-sale wishlists, and turn interactions into measurable intent signals.
Discover how agentic AI moves marketing beyond rule-based automation. Learn how adaptive, goal-driven systems enable real-time personalization, faster optimization, and smarter decision-making.
OpenAI, TikTok, Google and Meta are all testing the same idea: an ad click that opens a conversation with the brand instead of sending someone away. This piece walks through what each platform is building, why peak season is the real test of the format, and why the knowledge base a brand has written about itself is quietly becoming the creative.
AI agents are changing how people discover and buy products, but they may be making brand-owned experiences more important, not less. This article explores the two jobs brands still need to own: shaping the shortlist before an agent is involved and using customer context to create experiences that give people a reason to engage.
ChatGPT Ads are becoming a new channel for eCommerce, but limited reporting and no query-level data make measurement critical. This article breaks down what brands need to know about campaign setup, tracking, benchmarks, and deciding where ChatGPT Ads fit in the media mix.
Learn how to audit your eCommerce store for AI discovery across platforms like ChatGPT, Gemini, Perplexity, and Google AI Overviews. This guide covers how to measure visibility and accuracy, identify gaps, prioritize fixes, and build a repeatable monthly audit process.
Building an effective AI marketing stack for eCommerce is less about adding more tools and more about connecting data, decisioning, activation, and measurement into one reliable system. This guide breaks down the architecture, governance, migration steps, and measurement principles teams need to turn AI into measurable growth rather than more complexity.
Choosing AI tools for eCommerce is less about adopting the latest technology and more about finding use cases that improve revenue, retention, or operational efficiency. This guide covers the most valuable AI categories, data and integration requirements, ROI evaluation, and a practical 30/60/90-day rollout plan.