Inside Yum's AI factory: 200M personalized messages, 5x lift, and Taco Bell's record digital mix

How Yum's AI factory supercharges marketing at Taco Bell - and how you can apply it

Taco Bell hit a record 41% digital sales mix in Q2 2025. Across Yum Brands, AI-generated communications topped 200 million and have performed up to 5x better than traditional tactics on frequency and return on ad spend.

The engine behind that lift: an "AI factory" built on years of first-party data work, centralized in a consumer data program called Red360. It now contains over 140 million permissioned profiles with transaction histories - roughly half from Taco Bell.

The foundation: first-party data that actually moves

Red360 isn't just a warehouse. It's a living system that feeds personalization across channels and brands. With that scale and permission set, Yum can model behaviors, test messages, and push updates into live campaigns at speed.

If you don't have a clean, consented data spine, AI will amplify noise. Yum solved the inputs first, then scaled the outputs.

Where AI shows up: three practical pillars

• Consumer interactions: CRM, in-app recommendations, kiosks, and drive-thru experiences.
• Operations software: Yum's Byte suite for inventory and scheduling, improving availability and staffing so promos don't outpace ops.
• Above-store use: executive and corporate productivity, analysis, and decision support.

The takeaway: AI isn't a side project. It lives in the customer experience, the tools that run the stores, and the decisions leaders make every day.

Taco Bell's play: use AI to strengthen fan relationships

AI efforts at Taco Bell lifted CRM frequency and in-app recommendations by focusing on one-to-one relevance. The brand pushes learnings across surfaces - app, kiosk, and drive-thru - instead of treating each as a silo.

Importantly, the team isn't chasing hype. AI is plugged into the daily work of marketers and creatives: content workflows, message generation, and rapid iteration.

Experimentation at scale: the real unlock

Assumptions get tested, not debated. Taco Bell and Yum run structured experiments across data sets, fold insights back into models, then roll the winners across brands. That shared learning system compounds results.

Marketers who systematize experimentation - not one-off tests - will pull ahead. The proof: broad gains in frequency and ROAS, with AI messages hitting up to 5x effectiveness.

Build vs. buy: a clear decision filter

• Is there existing tech that does it better than we can?
• Are we doing something unique that warrants building?
• Who can execute faster and cheaper without sacrificing results?

Example: upsell personalization on kiosks was cheaper and faster to build in-house using Red360. For email and SMS personalization, Yum partnered with OfferFit (now part of Braze) to skip years of internal development and deploy a reinforcement engine immediately. See details from Braze here: Braze acquires OfferFit.

A practical operating system for AI-first marketing

• Data: centralize permissioned identities and transactions; enforce governance and freshness.
• Models: start simple (propensity, next-best-action), then evolve to reinforcement learning.
• Experiences: wire models into real surfaces (app, site, kiosk, drive-thru, outbound).
• Feedback: capture engagement and conversion signals to retrain continuously.
• Scale: templatize tests, share learnings across teams and brands, and automate rollout.

Metrics that matter

• Engagement lift vs. control (open, click, view-through).
• Frequency and incremental orders per user.
• ROAS and contribution margin, not just conversion rate.
• Offer relevance: acceptance rate and time-to-accept.
• Operational readiness: item availability, staffing alignment with promos.

Your 30/60/90-day action plan

• Days 1-30: Audit data assets and consent; define 3 core KPIs; pick one high-volume channel (e.g., CRM) and one surface (e.g., app) for pilots.
• Days 31-60: Ship a next-best-message test; connect creative workflows to AI copy/image generation with human QA; implement a test library.
• Days 61-90: Add reinforcement learning for send time and offer; expand to a second surface (kiosk or web); automate win rollout and reporting.

Key lessons you can use this quarter

• Data first. Bad inputs waste budget at scale.
• Think portfolio. Share models and learnings across brands or business units.
• Tie AI to operations. Promos fail if the store can't fulfill them.
• Be tool-agnostic. Build where it's core, partner where speed and expertise win.
• Systematize experiments. Make testing the default, not an event.

Level up your team

If you're building similar capabilities, upskill your marketers on practical AI and experimentation frameworks. Start here: AI Certification for Marketing Specialists and AI courses by job.

Yum's message is simple: AI works when it runs on quality data, plugs into real experiences, and learns faster than your organization can guess. Do that, and the results compound.