Make.com is the automation tool I recommend most often to D2C founders who want power without complexity. It's visual, it connects natively to almost every app your store runs on, and the learning curve is a fraction of n8n's.
But most guides to Make.com automation are either too basic ("connect Shopify to Gmail!") or too abstract ("automate your business!"). Neither helps you actually build anything.
This post is different. Below are 10 real Make.com recipes that we use or have built for clients. For each one, I'll give you the trigger, the action, the approximate operation count (which matters for your Make plan), and the business outcome. I'll also tell you honestly where Make.com has limits — and where n8n might be the smarter call.
How Make.com Pricing Works (Before You Build Anything)
Make charges by operations, not by the number of scenarios you run. Every module that executes in a scenario counts as one operation. A scenario with 5 modules that runs 100 times uses 500 operations.
The free plan gives you 1,000 operations/month. The Core plan (Rs 850/month) gives you 10,000. Pro gives 150,000.
For most D2C brands doing 200–500 orders/month, the Core plan is enough to start. If you're running the full set of 10 recipes below with good volume, budget for Pro.
Now, the recipes.
Pre-Purchase Recipes
Recipe 1: Lead Capture → Welcome Sequence Trigger
Name: New Lead → Klaviyo Enroll
Trigger: Webhook (from your landing page or quiz form tool)
Action: 1) Validate email via Kickbox or ZeroBounce module → 2) Create/update contact in Klaviyo → 3) Add to "Welcome" flow → 4) Slack notification to marketing team
Operations per run: ~4
Business outcome: Every lead hits your welcome sequence within seconds, not the next batch sync. Klaviyo's native forms do this already — but if you're capturing leads from TypeForm, Webflow, or a quiz tool, Make is the bridge.
Honest take: For Klaviyo-to-Shopify, the native integration is often enough. Use Make here when your lead source isn't a Shopify-native form.
Recipe 2: Abandoned Checkout Recovery Alert
Name: Abandoned Cart → Slack Alert + CRM Tag
Trigger: Shopify — Watch Abandoned Checkouts (polls every 15 minutes)
Action: 1) Filter: cart value > Rs 2,000 → 2) Search for contact in HubSpot or Pipedrive → 3) If found: add tag "High-Value Abandon" + create follow-up task → 4) Post to Slack #sales-alerts with customer name, cart contents, cart value
Operations per run: ~4–6 depending on CRM branch
Business outcome: Your sales team knows within 15 minutes when a high-value cart is abandoned. This pairs with your email automation — the email goes out automatically, the sales call is now a human decision informed by real data.
Watch out: The Shopify "Watch Abandoned Checkouts" module polls on a schedule (not instant). If you need real-time triggers, use a Shopify webhook + Make's custom webhook receiver instead — it's faster and uses fewer operations.
Recipe 3: Back-in-Stock Notification
Name: Inventory Restored → Notify Waitlist
Trigger: Shopify — Watch Inventory Levels (schedule: every 30 min)
Action: 1) Filter: inventory level changes from 0 to >0 → 2) Search Airtable or Google Sheets for customers who requested notification → 3) Send email via Klaviyo or Mailchimp → 4) Log notification sent in your sheet
Operations per run: ~5
Business outcome: Customers who wanted a product and didn't buy are converted when the product returns. This is money sitting on the table for most D2C brands that SKU out frequently.
Purchase Recipes
Recipe 4: Order Confirmation + Internal Fulfilment Alert
Name: New Order → Ops Dashboard Update
Trigger: Shopify — Watch New Orders
Action: 1) Extract order data (SKUs, quantities, shipping address, customer tags) → 2) Append row to Google Sheets ops dashboard → 3) If order contains a specific SKU or tag (e.g., "custom" or "pre-order"): send Slack message to fulfilment team with order link → 4) If order is COD: create task in ClickUp or Asana for confirmation call
Operations per run: ~5–7
Business outcome: Your ops team has a live dashboard of today's orders without anyone manually logging anything. The COD branch alone saves 30–45 minutes per day for brands doing significant COD volume.
Note: Make.com's Google Sheets module is excellent — no authentication headaches, native integration, and the "Add a Row" module is fast and reliable.
Recipe 5: High-Value Order → VIP Treatment Trigger
Name: Big Order → VIP Tag + Personal Email
Trigger: Shopify — Watch New Orders (filter: order value > Rs 10,000)
Action: 1) Add customer tag "VIP" in Shopify → 2) Enroll in Klaviyo VIP flow → 3) Create draft personal email in Gmail with customer name, order details, and a note from the founder → 4) Notify founder via Slack with one-click send option
Operations per run: ~4
Business outcome: High-value customers feel seen. The personal email from the founder doesn't have to be sent — just knowing it's drafted and waiting takes 2 minutes instead of 20. This is the recipe that generates the most "wow" replies.
Recipe 6: Fulfillment Alert + Shipping Update Sync
Name: Order Fulfilled → Tracking Push
Trigger: Shopify — Watch Updated Orders (filter: fulfilment_status = "fulfilled")
Action: 1) Extract tracking number and carrier → 2) Update contact in your CRM with tracking info → 3) Send branded tracking email via Klaviyo (or trigger an existing flow) → 4) Log fulfilment timestamp in your analytics sheet
Operations per run: ~4
Business outcome: Customers get tracking info faster, and your ops analytics are clean. This reduces WISMO ("Where is my order?") tickets significantly.
Post-Purchase Recipes
Recipe 7: Review Request Sequence
Name: Delivered → Review Ask (Timed)
Trigger: Shopify — Watch Updated Orders (filter: fulfilment_status = "delivered") OR a scheduled scenario 7 days after fulfilment
Action: 1) Check customer's purchase history — first-time or repeat? → 2) Branch: first-time → send "How was your first order?" flow in Klaviyo → repeat → send shorter "Leave us a review" direct ask → 3) Log segment in Airtable
Operations per run: ~5
Business outcome: Review ask timing is everything. Sending to a first-time buyer too early feels pushy. This recipe ensures the message matches the relationship.
Make.com advantage here: The conditional routing is visual and easy to update. In n8n, the same branch logic is faster to write in JSON — but harder for a non-technical team member to maintain.
Recipe 8: Loyalty Trigger — Repeat Purchase Milestone
Name: 3rd Order → Loyalty Reward
Trigger: Shopify — Watch New Orders
Action: 1) Count customer's total completed orders via Shopify "Search Orders" → 2) If order count = 3: add tag "loyal-3x" to customer → 3) Enroll in Klaviyo loyalty flow → 4) Create discount code via Shopify and attach to email
Operations per run: ~6
Business outcome: Customers who hit their 3rd order are your most likely to become brand advocates. Catching this moment automatically — with a personalised reward — is a high-ROI touchpoint that almost no small brand does consistently.
Operations watch: The "Search Orders" call adds 1–2 operations per run. If your order volume is high, this adds up. Consider caching the count in a Shopify customer tag (updated on each order) to skip the search step.
Recipe 9: Churn Risk Detection
Name: Lapsed Customer → Win-Back Trigger
Trigger: Scheduled scenario — runs daily
Action: 1) Query Shopify for customers whose last order was 60–90 days ago AND who have not ordered since → 2) Filter: customer has made at least 2 previous orders → 3) Tag customer "churn-risk" in Shopify → 4) Enroll in Klaviyo win-back flow → 5) Log in Airtable for review
Operations per run: Scales with customer count — expect 3–8 operations per customer checked
Business outcome: You identify and act on churn risk before the customer is gone. Most brands discover a lapsed customer only when they manually check their CRM — which is never.
n8n is better here: If you have 5,000+ customers, this scenario gets expensive fast on Make.com due to operations cost. n8n's self-hosted version runs this for free. This is where Make.com's pricing model breaks down at scale.
Recipe 10: Post-Purchase Upsell Intelligence
Name: Product Bought → Smart Upsell Trigger
Trigger: Shopify — Watch New Orders
Action: 1) Extract products purchased → 2) Match against a product pairing table in Google Sheets (e.g., "bought X → recommend Y") → 3) If match found: enroll in Klaviyo upsell flow with product Y pre-populated → 4) Log in analytics sheet
Operations per run: ~5
Business outcome: A customer who buys a face wash is shown a toner 3 days later. Not via a generic "you might also like" email — but one that references what they actually bought. This is personalisation at scale without a complex CDP.
Make.com vs n8n: When to Use Each
I use both. Here's the honest breakdown:
Make.com wins when:
- Your team is non-technical and needs to maintain the workflows
- You need native integrations that just work (Klaviyo, HubSpot, Shopify, Notion, Airtable)
- You're building Recipes 1–7 above with moderate order volume
- You want a scenario to be understandable to someone who didn't build it
n8n wins when:
- You have high-volume scenarios where operation costs become significant
- You need custom code inside a workflow (n8n's Function nodes are far more powerful)
- You're running workflows that touch sensitive data and want self-hosted control
- You're building the churn/lapsed detection recipes above at scale
The hybrid approach that we run for several clients: Make.com handles all real-time order-triggered flows (Recipes 4–8), n8n handles the bulk scheduled jobs (Recipes 9 and analytics pipelines). Best of both worlds.
Where to Start
If you're new to Make.com automation, don't try to build all 10 at once.
Start with Recipe 4 (Order → Ops Dashboard). It delivers immediate, visible value and teaches you the core Make.com pattern: trigger → filter → action → log. Once that's running, add Recipe 2 (Abandoned Cart) and Recipe 8 (Loyalty Trigger).
Those three alone, built properly, will meaningfully impact your revenue within 30 days.
If you want us to build and maintain these for you — or audit what you've already built — book a discovery call and we'll scope it in the first 30 minutes.
FAQ
What Make.com plan do I need for these recipes? For a D2C brand doing 200–500 orders/month running 5–6 of these scenarios, the Core plan (10,000 operations/month) is usually sufficient. Add up your operations per run × monthly run frequency to estimate.
Can I use these with WooCommerce instead of Shopify? Yes. Make.com has a WooCommerce module. The trigger names differ slightly but the logic is identical.
Do I need a developer to set these up? Not for most of these. Make.com is genuinely no-code. Recipes 9 and 10 (the ones involving product matching and bulk queries) are intermediate — you'll need to understand Make's iterator and aggregator modules.
How do I handle errors in Make.com? Enable "Error handlers" on each scenario. Make.com lets you add a dedicated error route that sends a Slack notification or logs the failure to a sheet. Don't skip this.
What's the difference between a Make.com scenario and a Zapier Zap? Make scenarios can be multi-step, branching, and iterative — closer to a real workflow than Zapier's linear "if this, then that" model. For D2C use cases with conditional logic (like Recipe 7 and 8), Make is significantly more capable.
Can Make.com replace a dedicated email platform like Klaviyo? No. Make.com is a workflow orchestrator — it tells Klaviyo what to do, it doesn't replace it. Keep your email flows in Klaviyo. Use Make.com to trigger them at the right moment with the right data.