Customer Support

How to process refund and return requests as CPG Founders

Customer SupportFor CPG Founders3 apps11 steps~22 min to set up

Refunds and returns are a constant headache when you're selling across Shopify, Amazon FBA, and wholesale distributors simultaneously. A customer emails about a damaged unit from a co-packer run, your DTC site shows the order, your 3PL has the return tracking, and your lot traceability sheet is in a separate Google Sheet. You're manually piecing together what happened, deciding whether to replace or refund, updating three systems by hand, and hoping the customer doesn't leave a review while you're still figuring it out. At 40 SKUs and $2M in revenue, this is eating two to three hours a week — without a dedicated support person to absorb it.

Build this on Starch → See the apps used

Customer SupportFor CPG Founders3 apps11 steps~22 min to set up

Outcome

What you'll set up

A centralized refund and return inbox that pulls customer emails and order data together so you're never hunting across tabs to figure out what happened

A decision workflow that applies your return policy automatically — replacement vs. refund vs. credit, based on order value, lot number, and reason code — and drafts the reply for you

A running log of return reasons by SKU and lot, so you can spot a bad co-packer run before it becomes a customer service crisis

The Starch recipe

Apps, data, and prompts

The combination of Starch apps, the data sources they pull from, and the prompts you use to drive them.

Apps used

CRM Customer Support Agent

Data sources & config

Starch connects directly to Gmail (scheduled sync) to pull inbound customer emails. Connect Shopify from Starch's integration catalog — the agent queries it live to pull order details, customer history, and shipment status when a return email arrives. Return case records live in Starch's CRM. For Amazon FBA returns, Starch automates the Amazon Seller Central returns dashboard through your browser — no additional API needed.

Prompts to copy

Build me an email triage workflow that flags any incoming message containing 'return', 'refund', 'damaged', or 'wrong product', summarizes the thread, pulls the associated Shopify order, and drafts a reply based on my return policy: full refund within 30 days if damaged, store credit otherwise, no returns on perishables past best-by date.

Create a CRM view that logs every refund and return as a case record linked to the customer contact, with fields for: order ID, SKU, lot number, reason code (damaged / wrong item / quality issue / changed mind), resolution (refund / replacement / credit), and resolution date. I want to be able to filter by SKU or lot number to spot patterns.

Build a weekly digest that shows me refund and return volume by SKU and reason code for the past 7 days, and flags any SKU with more than 3 quality-related returns in a rolling 30-day window.

Run these in Starch → or paste them into your favorite agent

Walkthrough

Step-by-step

1 Connect Gmail via Starch's scheduled sync — Starch will monitor your inbox and surface every incoming email that matches return or refund keywords, so nothing gets buried under co-packer invoices and broker emails.

2 Connect Shopify from Starch's integration catalog so the agent can query order details, customer purchase history, and shipment status live the moment a return email is flagged.

3 Set up browser automation against Amazon Seller Central so Starch can pull FBA return reports and customer messages from the returns dashboard — no Amazon SP-API setup required.

4 Start with the Email Triage app (live in the App Store as 'Email Triage') and describe your return policy in natural language: who qualifies for a full refund, when you offer store credit, what your lot-level quality escalation threshold is.

5 Build a CRM case view — tell Starch: 'Create a return case record for every flagged email, linked to the customer contact, with fields for SKU, lot number, reason code, and resolution.' Starch generates the schema and wires it to your email triage.

6 Configure auto-drafted replies: Starch reads the email, looks up the order in Shopify, checks against your policy logic, and prepares a draft — you review and send with one click, or approve an auto-send rule for clear-cut cases like confirmed damaged goods under $40.

7 For quality-related returns, add a step that flags the lot number in your case log — so if three customers in a week cite a texture issue on the same SKU from the same production run, you see it before your Amazon listing starts accumulating one-star reviews.

8 Set up a weekly return digest — tell Starch: 'Every Monday at 8am, send me a Slack summary of last week's returns by SKU and reason code, and flag any lot with more than 3 quality complaints in 30 days.' Starch pulls from the CRM case log and your Gmail data.

9 For wholesale distributor deductions related to returns, use browser automation to log into your distributor portals (UNFI, KeHE, or whichever you're on) and pull deduction detail reports — Starch automates the navigation and extracts the data, no API or EDI setup needed.

10 Once your case log has 60 days of data, ask Starch: 'Show me my top 5 return reasons by SKU and which ones are most correlated with specific lot numbers or fulfillment channels.' Use this to take the quality conversation back to your co-packer with receipts.

11 When Customer Support Agent launches (coming soon — request beta access to get notified), it will handle first-contact return emails 24/7 using your policy as the source of truth, escalating only the edge cases to you with full order context already loaded.

See this running on Starch

Connect your tools, describe what you want, and the agent builds it. Closed beta is free.

Try it on Starch →

Worked example

February 2026: Grass-fed beef jerky texture complaint cluster

Sample numbers from a real run

Shopify DTC refunds issued	340
Amazon FBA return credits	215
Replacement units shipped (COGS)	180
Total return-related spend, Feb 2026	735

In February, Starch flagged 11 inbound emails in two weeks containing 'chewy', 'rubbery', or 'texture' for the 4oz Original flavor SKU. The Email Triage app summarized each thread and pulled the associated Shopify order — 8 of the 11 were from the same lot number (LOT-2026-0112), produced in the January co-packer run. Starch drafted refund or replacement replies for all 11 within minutes of each email arriving; you reviewed and approved in a batch. The CRM case log flagged LOT-2026-0112 automatically, which gave you the documentation you needed to go back to the co-packer and request a credit on the defective run. Total out-of-pocket: $735 in refunds and replacements. Without the lot-level pattern detection, you likely would have processed these as one-offs across three separate weeks and never connected them to the production run.

Measurement

How you'll know it's working

Refund rate by SKU and fulfillment channel (DTC vs. FBA vs. wholesale) — target under 2% per SKU

Time-to-resolution per return case — from first customer email to refund issued or replacement shipped

Quality-related return rate by lot number — the signal that tells you a co-packer run went wrong

Return reason code breakdown — damaged / wrong item / quality issue / buyer's remorse, tracked monthly

Distributor deduction volume tied to returns — separate from consumer refunds but part of the same cost picture

Comparison

What this replaces

The other ways teams handle this today, and how the Starch version compares.

Gorgias

Strong helpdesk for DTC brands on Shopify, but it doesn't connect your lot traceability, your wholesale deduction portals, or your co-packer data — so the quality pattern detection you actually need still happens in a spreadsheet.

Zendesk

Enterprise-grade ticketing with deep customization, but at $50–$150 per agent per month it's priced for teams, not a two-person CPG operation — and it won't surface lot-level quality trends without significant custom build work.

Spreadsheet + Gmail labels

Free and flexible but entirely manual — every return is a copy-paste job, nothing is linked to order data or lot numbers, and pattern detection only happens if you remember to look at the sheet.

Amazon Seller Central native tools

Covers FBA returns only — gives you no view into DTC or wholesale returns, and can't correlate Amazon return reasons back to specific production lots or your co-packer.

On Starch RECOMMENDED

One platform — founder inbox, crm, customer support agent all running on connected data. Setup in plain English; numbers stay current via scheduled syncs and live agent queries.

Try it on Starch →

FAQ

Frequently asked questions

Can Starch connect to Shopify to pull order details automatically when a return email comes in?

Yes. Connect Shopify from Starch's integration catalog and the agent queries it live — order details, customer purchase history, line items, and shipment status are all available the moment a return email is flagged. You don't need to look up the order manually.

What about Amazon FBA returns — do I need to set up an Amazon API connection?

No API setup required. Starch automates your Amazon Seller Central returns dashboard through your browser — it logs in, navigates to the returns report, and extracts the data. If you can click through it yourself, Starch can automate it.

I sell through UNFI and KeHE — can Starch pull my distributor deduction data for return-related chargebacks?

Yes, through browser automation. If you can log into your UNFI or KeHE portal and navigate to the deduction detail reports, Starch can automate that process and extract the data — no EDI or API needed.

Is the Customer Support Agent available now?

Not yet — it's currently in development. You can request beta access to get notified when it launches. In the meantime, the Email Triage app (live today) handles the inbox monitoring and draft-reply workflow, and you approve before anything goes out.

Is Starch SOC 2 certified? I want to make sure customer order data is handled appropriately.

Starch is not currently SOC 2 Type II certified. If that's a hard requirement for your brand given your retail partners or investor expectations, that's worth knowing upfront. It's on the roadmap.

Can Starch track returns at the lot number level, not just by SKU?

Yes — you define the fields in your CRM case log. Tell Starch 'add a lot number field to every return case record' and it builds that into the schema. Once you have a few weeks of data, you can ask Starch to surface which lot numbers are generating disproportionate quality complaints — which is exactly the data you need when talking to your co-packer.

What if I have a custom return policy — for example, perishables past best-by date are final sale, but I'll still replace damaged units?

You describe your policy in plain language when you set up the triage workflow. Starch applies it when drafting replies. If your policy changes — say you add a new exception for a wholesale-only SKU — you update the description and Starch adjusts. No rules engine to configure, no dropdown menus.