80% of L1 tickets auto-resolved, review response rate from 20% to 95%, 4-minute average response time.
Your support inbox is a warzone. "Where is my order?" tickets make up 40-60% of the queue, and each one follows the same pattern: customer asks, agent looks up the tracking number, copies the status, pastes it into the reply. It is pure data entry masquerading as customer service.
Your support team spends its best hours on information retrieval instead of the complex, relationship-building interactions that actually matter. Meanwhile, negative reviews sit unanswered for days because your team prioritizes tickets over reputation management. Every unanswered one-star review is visible to thousands of potential customers making purchase decisions right now. Research shows responding to reviews increases conversion rates by 4-8% on product pages with active brand engagement, but who has time to draft thoughtful, on-brand responses to 50-200 reviews per week across Shopify, Trustpilot, Google, and Amazon?
And returns? Each return request triggers a manual chain: check eligibility, verify the order date, review the customer\u2019s history, decide whether to approve, generate a label, process the refund. At scale, this takes 48 hours end-to-end. The customer, already unhappy, waits through all of it. Customers who receive fast, hassle-free returns are 2.5x more likely to buy again.
Sarah is your AI Customer Experience Lead. She triages the overnight ticket queue at 7 AM, auto-resolves WISMO and policy questions instantly, processes straightforward returns with full customer history context, and drafts review responses across all platforms, all queued in Slack for your approval. You see a batch of 5 return decisions at noon, each with the customer\u2019s LTV, order history, return reason, and Sarah\u2019s recommendation. One tap per decision. Done.
That is why you need Sarah.
Each step is automated. Sarah only escalates when human judgment is required.
Sarah triages all tickets, auto-resolves L1 queries (WISMO, product info, policy questions) by pulling real-time data from Shopify and ShipStation, and queues complex tickets for human review with full context packages.
Sarah cross-references the customer’s LTV, order history, prior return history, and review history, validates eligibility against the return policy, and sends the founder a decision package: "Lisa M., 3rd order, $1,240 LTV, no prior returns, left 5-star review. Color mismatch claim. Recommendation: Approve free return label." [Approve] [Deny] [Offer Exchange]
Sarah drafts on-brand responses: genuine thank-you messages for positive reviews referencing the specific product, empathetic solution-oriented replies for negative reviews offering resolution. All drafts queued in a batch for founder approval.
Sarah escalates immediately with a full context package: complete conversation history, order details, shipment status, customer LTV, and a suggested resolution path. The founder sees exactly what happened and can respond in one message.
Sarah flags VIP status internally, triggers loyalty perks if configured, and ensures any future tickets from this customer receive priority handling and founder visibility.
Sarah sends a daily CX summary: total tickets handled, auto-resolution rate, average response time, escalations, serial returner flags, review response stats, and CSAT trend. The founder reads it in 60 seconds.
Clear boundaries. Sarah works autonomously within defined limits and escalates everything else.
Sarah connects to the platforms you already use. No new software to learn.
Sarah is deployed gradually with measurable checkpoints at every stage.
Monitoring mode first, then gradual rollout.
Pilot starts with the simplest ticket type: single-shipment domestic WISMO queries. Week 1-2 Sarah auto-resolves only "where is my order" tickets for standard ground shipping, with human agents reviewing every response.
Full validation before production deployment.
These AI employees share data and coordinate with Sarah to cover your full operation.