AI app for marketing · no coding needed
Purchase Follow-up Agent
Messages that remember what each customer bought and why, trained on the brand's voice, for every single order.
Made for: E-commerce managers at small direct-to-consumer brands
What it does for you
The problem
One-size-fits-all thank-you emails miss the chance to turn one-time buyers into repeat customers.
What it gives you
Personalised follow-up messages and managed reply conversations
What you give it
Order dataproduct descriptionscustomer historybrand voice examples
How it works, step by step
- Read each new order with product and customer details
- Draft a personalised follow-up message per order
- Offer tone options trained on the brand's voice
- Let users review drafts or set auto-send rules
- Handle replies with suggested responses for approval
- Track open, reply and repeat purchase rates
What you see on screen
- Order feed
- message drafts
- reply inbox
- performance dashboard
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Purchase Follow-up Agent with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Purchase Follow-up Agent with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links1 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare20 KB
- prompt-vps.mdThe same build on your own server (Docker)20 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria10 KB
- demo/index.htmlThe working demo on sample data195 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
For e-commerce managers at small direct-to-consumer brands, turn order data, product descriptions and customer history into personalised follow-up messages that ask the right question at the right time. Address the recurring problem: one-size-fits-all thank-you emails miss the chance to turn one-time buyers into repeat customers. The value hypothesis is higher reply and repeat purchase rates without extra staff time; the pilot must establish whether that benefit is real.
Connect the store, sync new orders, review drafts, set auto-send rules, send messages, handle replies, and review performance. Start with order data, product descriptions and customer history and finish with personalised follow-up messages and reply handling.
How the AI works
Use language models to draft messages based on order details, product descriptions and customer history. Train on the brand's voice using past emails and style guides. A store owner or manager reviews drafts before auto-send is enabled, and checks suggested replies before they go out. The agent learns from open and reply rates to improve tone and timing.
Safeguards
Store owners approve drafts before auto-send, set limits on message frequency, restrict replies to approved topics, and the agent must not send promotional content without explicit approval or share customer data outside the store's systems.
What to build first
One buyer: e-commerce managers at small DTC brands. One use case: follow-up email per order. First two modules: order feed and message drafts. Manual review of every draft before sending.
What it can connect to
Start with Shopify and WooCommerce order systems, then add email platforms like Gmail or Outlook, and later connect to loyalty and subscription tools.
The screens in detail
Use a list of recent orders on the left, a central preview of the drafted message, and a right-hand panel showing customer history and product details. Let users approve, edit or set auto-send rules per brand. Display draft, sent and replied states. Provide a reply inbox where the agent handles incoming messages. In this product, the first view is order feed, followed by message drafts and reply inbox.
