AI That Actually Helps: What Support Teams Can Learn from Best Buy and Leading QSRs
AI in customer support is moving from experiments to practical tools. Best Buy is rolling out an AI assistant for customers, agent-assist tools for phone support, and an internal assistant for store staff. Meanwhile, top quick-service restaurants (QSRs) are using AI to predict demand, reduce downtime, and streamline operations. The common thread: use data to shorten time-to-resolution and prevent repeat issues.
What Best Buy Is Shipping
- Customer-facing AI assistant to troubleshoot product issues, change delivery and scheduling, and manage subscriptions and memberships.
- Agent-assist tools that give real-time recommendations, summarize calls, detect sentiment, and capture data to reduce repeat problems.
- Internal assistant for frontline employees to quickly find resources and product guides, so service is faster and more consistent.
Translation for support leaders: deflect simple requests, supercharge agents during live calls, and make knowledge findable in seconds.
QSR Playbook: Predict, Don't React
McDonald's is deploying sensors and predictive analytics at scale to keep kitchens running and ease crew stress. Restaurant Brands International is unifying data across brands to power staffing, inventory, and promotions from one backbone.
Pizza leaders are using AI to forecast and listen. Papa John's is using Google Cloud models to predict what customers will order and when, improving timing and logistics. Domino's built pipelines to classify sentiment and surface themes from social channels, so they can respond to what people actually say, faster.
Others are bringing AI into operations. CAVA is piloting vision systems to track ingredient levels and robotics to automate digital makelines. Sweetgreen's automated "Infinite Kitchen" generates data that feeds smarter planning and less waste. The takeaway for support: forecast contact volume, staff to that forecast, and use feedback signals to prevent issues before they spike.
Why This Matters for Support
- Higher containment: route common questions to self-service that actually resolves them.
- Lower handle time: real-time summaries and suggestions reduce searching and after-call work.
- Better CX: proactive outreach and fewer repeat problems raise CSAT and loyalty.
- Happier agents: less swivel-chair work, clearer next steps, and fewer angry escalations.
A Simple Rollout Plan
- Start with high-volume intents: Order status, returns, appointment changes, password issues. Build guided flows with clear handoff to a human when confidence is low.
- Agent assist first: Real-time call transcription, suggested replies, and auto-summaries posted to the ticket. Plug into your CRM/ITSM so nothing is lost.
- Predict the work: Use historical tickets and order data to forecast contact drivers by day and channel. Adjust staffing, and send proactive messages to deflect known spikes.
- Tighten your knowledge loop: Centralize articles. Track which snippets agents use. Promote the best to self-service. Archive stale content.
- Put guardrails in place: Keep a human-in-the-loop for decisions that affect money, access, or safety. Redact PII. Log prompts, outputs, and outcomes for audits.
- Contracts and testing: As attorney Charles Nerko advises, supervise AI like your team, and use contracts that set accuracy, legality, and recourse. Attorney Craig Smith adds: insist on transparency about training and testing so you can validate reliability.
- Train and incent: Teach agents how to use suggestions without over-relying on them. Reward quality outcomes, not just speed.
KPIs to Track
- Containment rate (resolved by bot without human)
- Average handle time (AHT) and after-call work (ACW)
- First contact resolution (FCR) and reopen rate
- CSAT/NPS and sentiment by channel
- Transfer and escalation rate
- Issue recurrence rate (by driver and cohort)
Tech Stack Checklist
- Virtual agent and agent assist (for example, Google Cloud Contact Center AI)
- Real-time transcription and QA
- Searchable knowledge base with snippet-level analytics
- Data warehouse and streaming (contact events, orders, logistics)
- PII redaction, access controls, and audit logs
Quick Wins You Can Ship in 30 Days
- Auto-summaries for every call and chat, posted to the ticket, trimming ACW.
- Suggested replies for top five intents, reviewed by QA weekly.
- FAQ chat for order changes and appointment rescheduling with safe human handoff.
- Proactive notifications for delayed orders to reduce "where is my order" contacts.
- Sentiment tagging to prioritize callbacks and coach agents with real examples.
What This Means for Your Team
Steal the blueprint: combine self-service for the simple stuff, agent assist for live conversations, and prediction to head off problems. Keep humans in control, measure relentlessly, and turn every interaction into a learning signal. That's how AI moves the numbers that matter.
If you want structured help building these skills for support roles, see our curated paths at Complete AI Training.
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