If a customer buys an item you don’t actually have, you’re on the clock. In dropshipping, stockouts can snowball into cancellations, refunds, and one‑star reviews unless your support team moves fast and follows a clear service‑level agreement (SLA). This guide gives SMB store owners and ops leads a practical, 24/7 playbook for measurable SLAs—anchored on first response, time to resolution, and first‑contact resolution—and a step‑by‑step workflow for supplier out‑of‑stock (OOS) events with instant replacement SKU communication.
Key takeaways
Aim for an aggressive but realistic chat first response time (FRT) with automation: ≤ 2 minutes, because satisfaction drops sharply after that window, and set a transitional baseline of ≤ 15 minutes if you’re not yet automated.
Define and track medians by issue type (e.g., OOS/backorder, shipping delay); publish internal medians and improve 10–20% per quarter instead of quoting unverified industry “averages.”
Standardize consent‑based replacements: never auto‑substitute; propose comparable SKUs, capture customer approval, and reroute the order.
Treat supplier communication like a two‑hop SLA: acknowledge OOS within 1–2 business hours and deliver replacement options or ETA within 4–24 hours.
Build a multilingual, multichannel plan: real‑time for urgent, ticket/email for non‑urgent, with canned messages to speed FCR.
What a strong dropshipping customer support SLA includes
A good dropshipping customer support SLA is specific, measurable, and aligned to channels and issue severity. It should define: first response time (FRT), time to resolution (median), first‑contact resolution (FCR), escalation rules, coverage hours, languages, and reporting cadence.
Why push chat first response ≤ 2 minutes
Customer satisfaction falls as seconds tick by in live chat. HubSpot reports that when customers get a response within five seconds, average CSAT is 85%, but when it takes longer than two minutes, CSAT drops to 60%—a stark decline that justifies aggressive chat SLAs for e‑commerce (HubSpot, 2024). See the evidence in the HubSpot analysis on response speed and satisfaction: “12 Customer Satisfaction Metrics Worth Monitoring in 2024”.
Set two tiers:
Aspirational (automation‑enabled): FRT ≤ 2 minutes on chat/WhatsApp during staffed hours; after‑hours, auto‑acknowledge with queue handoff.
Transitional baseline (manual): FRT ≤ 15 minutes until automation is in place.
For consistent measurement definitions, reference platform docs like Zendesk’s metrics for live chat.
Median time to resolution (MTTR) and FCR
Public ecommerce‑specific medians are thin. Instead of quoting generic numbers, segment your own data by issue class and track medians weekly. As a starting target, maintain a published median for OOS/backorder issues and aim to reduce it 10–20% per quarter.
For first‑contact resolution, define it clearly (customer‑confirmed resolution; no repeat contact within, say, 72 hours) and target ≥ 70% overall, with higher targets on chat for repeatable issues. Calibrate this based on your baseline and category complexity.
SLA cheat‑sheet (starting targets)
KPI | Channel/Scope | Starting Target | Notes |
|---|
First response time (FRT) | Chat/WhatsApp | ≤ 2 minutes (aspirational with automation); ≤ 15 minutes baseline | Anchored by HubSpot’s CSAT vs time finding (2024) and operational feasibility |
First response time (FRT) | Email/Ticket | 4–24 hours | Define by staffing; publish your tiered hours |
Supplier OOS acknowledge | Priority supplier ticket | 1–2 business hours | Starting point based on inventory platform guidance |
Replacement proposal or ETA | After OOS confirm | 4–24 hours | Depends on category/time zones; provide updates if delayed |
Median time to resolution | OOS/Backorder issues | Track internally; improve 10–20%/qtr | Publish by issue class |
First‑contact resolution (FCR) | All support | ≥ 70% overall | Define FCR precisely; verify via surveys/logs |
Sources: HubSpot 2025 CSAT metrics; definitions context from Zendesk live chat metrics; supplier timing targets synthesized from inventory best‑practice articles by Shopify, InventorySource, and Flxpoint.
The supplier OOS → replacement SKU workflow (with timings)
Let’s anchor this with a real scenario: it’s 10:00 pm in peak season. A top‑selling SKU goes OOS at your primary supplier right after a customer checks out. What happens next?
Detect and verify
Automation flags OOS at payment capture or pre‑fulfillment. Your system auto‑creates a “Priority: OOS” ticket with order ID and SKU attributes.
A human verifies within 60 minutes during staffed hours. If truly OOS, the ticket severity escalates to “Order at risk.”
Notify the supplier (set supplier‑side SLAs)
Prepare customer‑ready alternatives (replacement mapping)
Use a prebuilt mapping table to propose 2–3 comparable SKUs (price range, category, specs/compatibility, shipping speed). If you use a helpdesk integrated with your store, you can pull inventory and edit orders directly. For example, Gorgias documents AI‑assisted recommendations and Shopify order actions that support replacement flows: manage ecommerce orders in your helpdesk and AI Agent actions on Shopify orders.
Message the customer (consent is mandatory)
Within the same day—and ideally within hours—send a concise message offering: (a) replacement options, (b) backorder with ETA, or (c) full refund. DSers emphasizes fast, transparent stockout communication and offering alternatives/waitlists: stockout transparency best practices.
Capture approval and execute
On approval, update or duplicate the order with the chosen replacement. If declined, process refund or backorder. Confirm the change in writing and update tracking once shipped. Gorgias’s docs show practical steps to adjust Shopify orders from the helpdesk: AI Agent order actions.
Close the loop and learn
Tag and log: cause (supplier OOS), response times (supplier acknowledge, replacement proposal, customer decision), and final resolution time. Feed this data into your supplier scorecard and SLA review.
Recommended timing summary (starting points): detection instant via automation; supplier acknowledge 1–2 business hours; replacement proposal 4–24 hours; resolution 48–72 hours with updates near the upper bound. Treat these as starting targets and adjust by category and region.
Disclosure: ASG is our product. In practice, managed 24/7 teams and tooling like ASG can enforce SLAs, route after‑hours OOS tickets to on‑call agents, and coordinate supplier follow‑ups without promotional frills—use them when internal coverage is thin.
Channel and multilingual strategy (urgent vs. non‑urgent)
Real‑time channels for urgent order‑impacting issues: chat and WhatsApp for OOS, address corrections, and payment holds. Why? Live channels align with the steep satisfaction drop after slow responses noted by HubSpot’s CSAT analysis (2025), and Zendesk’s ecommerce service guidance underscores digital speed expectations.
Asynchronous channels for non‑urgent: email/tickets for general inquiries or warranty questions; publish clear SLA windows.
Multilingual coverage: prepare short, translated macros for OOS notices and approvals; route by agent language. Maintain legal copy consistency across languages.
Escalation matrix: if a supplier has not acknowledged an OOS within 60 minutes past the target window, escalate to a supervisor and add a backup supplier path.
Automation recipes you can actually build (Shopify‑centric, tool‑agnostic)
Pattern 1: Detect OOS at checkout/fulfillment
Trigger: Order created → Check line items against inventory API.
Action: If any SKU OOS, tag order “OOS‑at‑risk,” open a Priority ticket, send auto‑acknowledge to customer.
Optional: Call a replacement mapping endpoint to fetch 2–3 alternates.
Pattern 2: Supplier notification and chase
Trigger: Ticket tagged “OOS‑at‑risk.”
Action: Send supplier email/API request with order/SKU. If no reply in 90 minutes, auto‑remind and escalate.
Pattern 3: Consent‑based replacement
Trigger: Replacement list prepared.
Action: Send customer message with options; when approved, execute Shopify order update via helpdesk or API (cancel/refund/replace/duplicate). See Gorgias order management for an example of in‑helpdesk actions.
Caveat: We didn’t find a turnkey “replacement suggester” app to cite; treat these as buildable patterns via Shopify Flow, Zapier, or Make with HTTP steps and your own mapping table. Shopify community forums show partial flows and alerts, such as building a Flow for OOS orders.
Templates you can copy
Supplier scorecard (CSV fields)
supplier_name, oos_rate_percent, avg_ack_time_hours, replacement_proposal_time_hours, fulfillment_sla_adherence_percent, defect_return_rate_percent, csat_delta, notes
Canned customer message (chat/email/WhatsApp)
Subject/Opener: “Quick update about your order for {Product Name}”
Body: “Thanks for your order. The item is temporarily out of stock at our supplier. We can (A) ship a comparable alternative today, (B) hold your order with an ETA of {date}, or (C) issue a full refund now. Here are 2–3 close matches: {SKU list}. Reply with your preference and we’ll confirm in writing.”
Canned supplier message
Subject: “OOS confirm + alternates request for Order {#} – respond within 2 hours”
Body: “Please confirm OOS for SKU {X}. If OOS, send 2–3 in‑stock alternates (similar specs/price) or a restock ETA. This is a priority ticket; we target acknowledgement within 1–2 business hours.”
Escalation matrix (excerpt)
Replacement mapping template (columns)
sku, alt_sku_1, alt_sku_2, price_delta_allowed, key_attributes_match, shipping_speed, compatibility_notes, preapproved, last_reviewed
Monitor, learn, and improve
KPIs to track weekly: chat FRT (median), email FRT, OOS ticket volume, supplier acknowledge time, replacement proposal time, median resolution by issue class, FCR rate, refund rate, CSAT for OOS tickets.
Cadence: monthly supplier reviews using the scorecard; quarterly SLA reset based on trend lines.
Seasonal playbook: pre‑season backup SKUs, tighter thresholds on low‑stock alerts, and added after‑hours coverage. Why guess when you can plan?
Next steps
Publish your SLA table, wire up a minimal automation flow, and run a two‑week pilot on OOS replacements; then tune targets from actual medians. If internal coverage is thin, consider a managed 24/7 partner to enforce the playbook.
Sources and further reading
