Kicking things off with @AshwinSreenivas on where customer experience is headed as AI becomes the primary interface between brands and customers. “Every company will need an AI concierge.”

We're announcing the most significant new strategic development since the start of the Customer Agent category: Fin now has specialized roles. And starting today anyone can sign up for and deploy the Fin Sales Role in minutes. Fin is now by far the very best sales agent on the market, and it's been live with some of the most innovative digital brands for months, conversing with thousands of prospects, aiding discovery, building pipeline, booking meetings and starting trials. We started the Customer Agent category with a focus on service by launching Fin three months after the launch of ChatGPT. Since then Fin has continued to lead the space, today delivering over 2 million resolutions a week for over 8k customers, including Anthropic, DoorDash, Snowflake, Asana, Mercury, Polymarket and many more exceptional brands. But our vision for Fin has always stretched far beyond service. And for the past 6 months we’ve been building Fin as a single Customer Agent, delivering a seamless experience across all stages of the customer lifecycle. We do not believe customers or businesses will want multiple agents for different parts of the lifecycle—because the agents won’t have shared memory and goals, and will have to compete with each other, delivering a poor customer experience and sub-optimal business results. We’ve more roles to come, including another dropping in two weeks. For now please watch our launch video or visit our launch page to learn more: fin DOT ai SLASH sales

The checkout is no longer just a payment moment. It's where customer experience, business growth and digital transformation converge. Patricia Brolly and Ciaran Walsh discuss how merchants can reduce friction, localize experiences and scale across diverse markets.

Google Cloud x The Home Depot: advancing interconnected retail through new agentic AI tools. With Gemini models and Gemini Enterprise for Customer Experience, The Home Depot is using AI to make the entire home improvement journey easier.

Google Cloud 🧰 @HomeDepot: advancing interconnected retail through new agentic AI tools. With Gemini models and Gemini Enterprise for Customer Experience, The Home Depot is using AI to make the entire home improvement journey easier.

ICYMI: Ask Mike is a new AI-powered shopping assistant from Michaels, built with Gemini Enterprise for Customer Experience. Learn how this new AI agent will enhance product discovery—from inspiration to purchase →

Just launched: Ask Mike is a new AI-powered shopping assistant from Michaels, built with Gemini Enterprise for Customer Experience. Learn how this new AI agent will enhance product discovery—from inspiration to purchase ↓

Benchmark performance does not guarantee business value. Organizations should evaluate LLMs within actual workflows such as measuring customer experience, employee well-being, productivity, and skill development. (2/6)

Bringing brand and performance closer requires some changes in the AI era: Treating brand and analytics as equal. Integrators are more likely to inject creativity in analytic functions and vice versa, especially when it comes to consumer insights and customer experience. In the AI era, this means leveraging predictive AI to turn raw consumer data into proactive creative briefs. Linking teams with an agile marketing operating model. This means having brand and digital marketers work from the brief through all execution. By integrating GenAI workflows, teams can rapidly co-create, test, and scale asset variations while maintaining strict brand guardrails. Defining clear, unified KPIs linked across the funnel. This includes analyzing and quantifying the impact of non-conversion events such as points of awareness, increased and qualified traffic generation. Investing in an AI-powered measurement ecosystem. Moving beyond traditional 'brand lift' studies to regular read-and-react geo-specific attribution, utilizing machine learning to run continuous, automated cross-channel simulations. An updated media mix model (MMM) for integrated spending. Including a pressure-tested, AI-driven MMM based on real-time incrementality tests in market to dynamically reallocate budget between brand and performance. Before undertaking all of the above, marketers should try a few AI-assisted pilot tests to quickly demonstrate the power and increased effectiveness when these muscles work together.