Make.com vs Zapier for Solopreneur Automation (2026): Honest Cost Math
Most “Make vs Zapier” articles on the internet open with the same line: “Make is cheaper, Zapier is easier.” They quote headline prices, wave at the “operations vs tasks” thing, and call it a comparison.
The actual story is more interesting and a lot more useful. Both platforms are excellent automation tools, they just count usage in fundamentally different ways, and the right pick depends on the shape of your specific workflows rather than a universal “X is better.” Context is the whole game here.
I’m a solo operator running a content business. I built six real automations, the kind a one-person business actually needs, on both platforms over 60 days. I tracked the real cost, the real time to build, and the real failure modes.
This is what I found.
The pricing tiers (June 2026, verified directly)
Make.com
- Free: $0, 1,000 credits/month
- Core: $9/month annual ($12/month monthly billing), 10,000 credits/month
- Pro: $16/month annual ($21/month monthly), 10,000 credits + priority execution + custom variables
- Teams: $29/month, multi-seat
- Enterprise: custom
Zapier
- Free: $0, 100 tasks/month, 2-step Zaps only
- Professional: $19.99/month annual ($29.99 monthly), 750 tasks/month, unlimited multi-step
- Team: $69/month annual ($103.50 monthly), 2,000 tasks/month, up to 25 users
- Enterprise: custom
At a glance: Make’s Core plan is less than half the price of Zapier’s Professional plan and gives you 13x more usage credits. Strong story for Make on the box.
But the headline numbers aren’t quite apples-to-apples, because Make and Zapier count usage differently. Once you understand how each one bills, the actual cost depends heavily on the shape of your automations.
The “credits vs tasks” distinction (this is the most useful frame)
Zapier charges per completed action. Triggers, filters, paths, polling, formatter steps, these are free. You only pay when an action actually runs successfully (an email is sent, a row is created, a Slack message is posted).
Make charges per operation (credit). Every step in a scenario counts toward the credit total: trigger, filters, router branches, iterator passes, aggregators, and retries. A 5-step Make scenario can consume 7–10 credits per run once filters and retries are included (the 7 Friday-admin Make scenarios I run weekly show this credit math in practice). The same outcome on Zapier maps to ~3 tasks, because Zapier only counts completed actions.
A real example I ran on both:
Workflow: “When a new Stripe payment comes in, check if it’s over $500, find the customer in HubSpot, create a project in ClickUp, send a Slack notification.”
- On Zapier: 3 tasks per run (HubSpot find, ClickUp create, Slack send, the Stripe trigger and the filter don’t count).
- On Make: 5–6 credits per run (trigger + filter + HubSpot search + ClickUp create + Slack, and Make often counts the filter as 1 credit each time).
Run it 200 times a month: Zapier eats 600 tasks. Make eats 1,000–1,200 credits.
Now do the math on the cheapest paid tier of each:
- Zapier Professional ($19.99/mo) gives you 750 tasks. 600 used. Comfortable headroom.
- Make Core ($9/mo) gives you 10,000 credits. 1,000–1,200 used. Significantly more headroom remaining.
So at low complexity and moderate volume, Make’s headline price advantage holds up nicely. The interesting question is what happens as workflows get richer.
How I tested
I built six real solopreneur automations on both platforms. Same goal, identical setup. Tracked credit/task burn over 30 days of actual use, plus the build experience.
The six:
- New lead → CRM → Slack notify (5-step)
- Stripe payment → bookkeeping spreadsheet + invoice file (4-step with branching)
- Calendly booking → kickoff doc + email + project setup (8-step)
- Form submission → enrich data → score → route by score (7-step with router)
- Daily summary email of yesterday’s metrics (multi-source aggregation, 12+ steps)
- RSS feed → AI summary → social posts (5-step with AI module)
Test 1: Simple lead → CRM → Slack (low complexity)
Build time on Zapier: 4 minutes. Pick trigger, pick CRM action, pick Slack action. Save. Done.
Build time on Make: 9 minutes. Drag modules onto canvas, connect them, configure each, test. The visual canvas is more capable but takes more setup.
Burn per run: Zapier = 2 tasks. Make = 3 credits.
Reliability over 30 days: Both 99%+ uptime. No issues.
Best fit: Zapier. For simple linear automations, Zapier’s step-by-step builder is the fastest path from idea to running automation, and the cost difference between the two is negligible at this scale.
Test 2: Stripe payment with branching (medium complexity)
Build time: Zapier 11 minutes (using Paths). Make 7 minutes (using a Router, Make’s branching visualization is a standout here).
Burn per run: Zapier = 4 tasks (only the executed branch counts). Make = 6–8 credits (the router and each filter inside it count as steps).
Best fit: Make for the build experience, Zapier for the per-run cost. Both are good answers depending on which side of that trade-off matters more to you.
Test 3: Calendly → kickoff doc → email → project (medium)
Build time: Zapier 14 minutes. Make 12 minutes.
Burn per run: Zapier = 5 tasks. Make = 9–10 credits.
Best fit: Even match. Both worked reliably. Make’s visual canvas helped me see the whole flow at a glance; Zapier’s step-by-step helped me ship the build faster.
Test 4: Form → enrich → score → route (medium-high)
This is where the data enrichment step matters. I used Clearbit on both.
Burn per run: Zapier = 4–5 tasks (Clearbit enrichment, scoring formula, route action, output). Make = 11–13 credits (router branches each count toward the total).
Build experience: Make’s router is genuinely excellent for “if this, elif this, else” logic with 3+ branches. Zapier’s Paths handle the same job with a different mental model.
Best fit: Make for the canvas and the branching UX, Zapier for the per-run efficiency. Real “depends on your priority” call.
Test 5: Daily metrics aggregation (high complexity)
The automation: pull yesterday’s data from Google Analytics, Stripe, Mailchimp, and Plausible. Aggregate into one summary. Email it to me at 8am.
Build time: Zapier 25 minutes (chained zaps). Make 18 minutes (single scenario with multiple modules).
Burn per run: Zapier = 6 tasks (one task per completed action). Make = 24+ credits (each module, iteration, and aggregator step is counted).
Monthly cost at 30 runs (daily for a month):
- Zapier: 180 tasks. Sits comfortably in the 750-task Professional plan.
- Make: 720+ credits. Sits comfortably in the 10,000-credit Core plan.
At this complexity, Make’s headline price keeps it cheaper end-to-end, but the gap narrows considerably compared to simple workflows, credits accumulate faster on heavy multi-source builds, so the headroom feels different than the headline numbers suggest.
Best fit: Make for the visual workflow design (which really shines on aggregations), Zapier for the predictable cost ceiling when usage spikes.
Test 6: RSS → AI summary → social posts (high)
The AI step is where the platforms’ pricing models behave most differently.
Build time: Make 8 minutes (AI modules are first-class citizens in their canvas). Zapier 14 minutes (chains the AI call across steps).
Burn per run: Make = 12+ credits (AI modules can consume multiple credits per call depending on context). Zapier = 4–5 tasks.
Best fit: Make for the build experience and AI module integration, Zapier for the per-run predictability on heavy AI usage. If you’re running a lot of AI-in-workflow scenarios, modeling out the credit cost on Make is worth the 10 minutes, same goes for modeling Zapier’s task overage tiers.
How each maps to the work
| Workflow type | Best fit (build) | Best fit (run cost) |
|---|---|---|
| Simple linear (3–4 steps) | Zapier | Even at this scale |
| Branching (path/router) | Make | Zapier |
| Multi-service aggregation | Make | Make |
| AI-heavy workflows | Make | Zapier |
| Long-tail app integrations | , | Zapier (broadest catalog) |
| Complex enterprise scenarios | Make | Make |
Both platforms are excellent, they just optimize for different shapes of work. For simpler, linear automations, Zapier’s onboarding speed and per-task billing tend to feel friendlier. For richer, multi-branch or aggregation-heavy scenarios, Make’s visual canvas and credit headroom shine. The choice is less “which is better” and more “which is shaped like your actual workflows.”
Real-world cost projection for a typical solopreneur
Most one-person businesses run 8–15 automations total, mostly simple. Math at that scale:
- Zapier Professional ($19.99/month annual): 750 tasks/month. 10 automations averaging 200 runs each at 3 tasks per run = ~6,000 tasks. You’d exceed the plan within a week. This is the catch.
- Make Core ($9/month annual): 10,000 credits/month. Same 10 automations at ~6 credits per run × 2,000 total runs = 12,000 credits. You’d ALSO exceed the plan, but only slightly, and you can buy a credit pack ($9 for 5,000 extra).
So at any real scale beyond hobby use, BOTH plans get expensive. The realistic monthly cost for a solopreneur running ~10 active automations is:
- Zapier: $19.99 Pro + likely 1 task overage tier upgrade ≈ $25–35/month
- Make: $9 Core + 1 credit pack ≈ $18–25/month
Make often ends up the cheaper of the two at real solopreneur scale, especially if you take advantage of its credit packs. The trade-off is in planning style: Make rewards thinking through each scenario’s credit footprint upfront, while Zapier’s “1 task = 1 completed action” model is easier to estimate at a glance. Two valid approaches, one favors flexibility, the other favors predictability.
Which one should you actually start with?
Start with Zapier Professional ($19.99/month) if:
- You’re newer to automation. Zapier’s onboarding is 3x better.
- Your workflows are linear (“when X, do Y, then Z”). Filters/branching aren’t critical.
- You use a lot of long-tail apps (Zapier has 6,000+ integrations to Make’s 2,000+).
- You want predictable monthly cost.
Start with Make Core ($9/month) if:
- You’re comfortable with technical tools. You’ll spend more time learning Make but get more flexibility.
- Your workflows have branching, loops, or aggregation. Make’s visual canvas earns its complexity here.
- You’re a heavy webhook/API user. Make handles raw HTTP modules more elegantly.
- You want the cheapest entry point and don’t mind buying credit packs as you scale.
The practical default for most solo readers of this site: Start where your week’s automations actually live. If you’re a “when X happens, do Y, then Z” kind of operator, Zapier gets you to value fastest. If you’re already comfortable with technical tools and your automations branch, loop, or merge data from multiple sources, Make rewards the slightly steeper learning curve with a more powerful canvas.
A reasonable test: try the free tier of each for a week with one real workflow. Whichever one you finish first is the one shaped like your brain.
What’s NOT in this comparison (and why)
- n8n, self-hosted, open-source. A different category entirely; requires you to run a server, which is its own commitment.
- Pipedream, developer-leaning workflow tool. Excellent if you’re comfortable writing code in your automations.
- IFTTT, focused on simple 1-trigger-1-action consumer automations. Different problem space than Make or Zapier.
- Lindy / Bardeen / others, AI-native automation tools. Newer category, increasingly capable, but different design philosophy. Worth a dedicated article.
The bigger point
The Make-vs-Zapier question is often framed as a cost optimization. The more useful frame is a complexity match.
If your automations are simple and linear, you want the tool that gets out of the way the fastest, that’s where Zapier’s straightforward builder shines.
If your automations involve branching logic, iterators, or multi-source aggregation, you want a tool that gives you a canvas to design with, that’s where Make’s visual workflow editor pays back the slightly steeper learning curve.
Both tools are excellent. Both have generous free tiers. The smartest move for a solo operator is to spin up a real workflow on each in their free plans, ship it, and let your hands tell you which mental model fits.
Match the tool to the shape of the work, then look at the price.
Want more honest comparisons? Next up: ChatGPT vs Claude vs Gemini for research tasks specifically. Subscribe to the blog so you don’t miss it.
