An automated revenue recovery system for e-commerce brands. It uses a voice AI like Vapi.ai to make personalized outbound calls to customers who trigger specific events (e.g., abandoned checkout). The system uses n8n for automation logic, GPT to generate dynamic scripts, and displays results in a no-code dashboard.
Revenue leaks out of an online store in several places at once: abandoned checkouts, failed subscription payments, declined cards on high-value orders and customers who stop reordering. Email and SMS flows in Klaviyo handle some of this, but each leak is managed separately, and nobody can see in one place what was attempted, what worked and what was left untouched. Owners of growing Shopify stores often know money is slipping away without knowing how much or where.
Adding voice calls to the mix is appealing, but most voice tools are set up as one-off campaigns with a fixed script. They do not know the customer's order history, whether they already received three emails, or whether they have unsubscribed. The result is awkward calls that repeat what the customer already ignored. Without logging outcomes centrally, the store cannot compare voice against other channels or improve the approach over time.
Shopify or the payment provider fires a webhook for a defined event, such as abandoned checkout or failed renewal, into an n8n workflow.
n8n gathers context from Shopify and Klaviyo, including cart contents, past orders, recent messages sent and consent status, and stops if the customer has opted out or already converted.
An LLM generates a short call brief and opening lines tailored to the event and customer history, within a fixed script structure and approved offer limits.
Vapi places the call, handles the conversation and returns a transcript, outcome and any follow-up request, such as an updated payment link by SMS.
Outcomes are written to Supabase and displayed in a Glide or Softr dashboard showing calls, conversions, opt-outs and reasons by event type.
An online store's Shopify setup triggers a webhook to an n8n workflow when a cart is abandoned. n8n fetches the cart details, uses OpenAI to generate a conversational script, and initiates a call via Vapi.ai. The voice agent offers a discount to the customer, and the call outcome is logged in a Glide dashboard.
Vapi.ai, n8n, OpenAI GPT models, Shopify API, Klaviyo API, Glide/Softr, Supabase
Recovery calls that promote a sale are telemarketing, so check the Do Not Call Register Act 2006 and the telemarketing industry standard for calling hours and identification, and record express consent where you rely on it. Follow-up SMS with offers must meet the Spam Act 2003 requirements for consent, sender identity and unsubscribe. Payment reminder calls should be factual and courteous; pressuring customers can breach the Australian Consumer Law. Call transcripts and recordings are personal information under the Privacy Act 1988, so check where Vapi, Supabase and your LLM provider store data and choose Australian regions where offered.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
It covers several revenue events, not just carts, and checks Klaviyo history and consent before calling so it does not repeat messages the customer already ignored. Every outcome lands in a shared database and dashboard, which lets you see which events and offers are worth a call and which should stay with email.
Yes, for a store with clean Shopify and Klaviyo data and one or two recovery events to start. The time goes into building the n8n workflow, writing and testing call briefs and setting up the dashboard. Adding more events later is quicker because the suppression and logging logic is already in place.
Day-to-day changes such as editing offers, call hours or dashboard views can be handled by a confident operations person. Changes to webhooks, database structure or new integrations are easier with someone who knows n8n and APIs. Many stores keep a small support arrangement for those occasional changes.
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