# Make Buyer's Checklist: 8 Questions to Ask Before You Commit > A 7-point buyer's checklist for evaluating Make.com — process fit, learning curve, cost at scale, integrations, AI, data export and support — with our honest verdict on each. _Source: https://professionalstoolkit.com/articles/make-checklist — The Professional's Toolkit · updated 2026-07-29_ --- > **TL;DR —** Before you commit to Make — or any automation platform — run it through a short buyer's checklist so you don't discover a dealbreaker three months in. Here's the eight-point framework we use, applied to Make, so you can see exactly where it clears the bar and where you need to look twice. **8 checks** — Run Make through these before you commit — two are pass/fail, the rest are trade-offs to weigh against your own situation. - **$9/mo** — Core — 10,000 credits - **3,000+** — apps + HTTP for the rest - **All paid tiers** — include AI Agents ## How to use this checklist Automation tools are easy to adopt and painful to migrate off, so the questions worth asking are the ones that surface a mismatch *before* you've built your operation on top of the wrong platform. Work down these eight checks in order — the first two are pass/fail, the rest are trade-offs to weigh — and score honestly against your own situation, not the marketing page. > 💡 **Score against YOUR situation:** A 'con' that never touches your workflow isn't a con for you. Weigh each check by whether it actually binds your team, not in the abstract. ## 1. Does your process actually fit? The single biggest predictor of success. Make rewards **recurring, multi-step, multi-app processes** — "when X happens, check Y, then do Z or W." If you can describe your job that way, it fits. Concrete signs it's a fit: the task runs at least a few times a week, touches two or more tools that don't talk natively, and follows rules you could hand to a new hire in a sentence. Signs it *isn't*: a single two-app handoff with no branching (a one-click tool is faster), or a task that only runs occasionally (the setup never pays back). The sharper your process description, the more obvious the answer — vagueness here is usually a sign the process itself isn't ready to automate yet, not that Make is wrong. **Make verdict: strong pass — if your process is genuinely multi-step.** ## 2. Can you live with the learning curve? Make is more powerful and more demanding than one-click rivals. Budget a few hours for your first real scenario and expect the depth to take a little study. Be specific about what's actually hard, because it's a short list: **data mapping** (wiring one module's output into the next — the concept that clicks after your first working scenario), and the three power features — **routers** (branching), **iterators/aggregators** (handling lists), and **error handling**. None of them are conceptually difficult; they're just unfamiliar, and they're front-loaded — the first scenario is the steep part, after which your tenth takes an afternoon. The honest blocker isn't difficulty, it's *appetite*: if nobody on the team can spare the couple of hours to get over the first hump, that's a real signal a simpler tool fits better today. **Make verdict: pass with effort — front-loaded, pays back after the first build.** ## 3. Will the cost scale the way you need? Make bills by **operations/credits**, not seats — Core is $9/mo for 10,000 credits,[1] and all paid tiers include the same allowance (you buy credit packs for more). That's cheap and predictable *if* you model your volume, but three specific things burn credits fast, and they're worth naming so you can design around them: **polling triggers** (a scenario that wakes every few minutes spends credits even when there's nothing new — a webhook fires only on a real event), **iterators/loops** (each item runs every downstream module, so a 12-item order multiplies your operation count), and **AI steps** (which cost more than plain data moves). A quick way to sanity-check: estimate *runs × modules per run* for your busiest scenario against the 10,000-credit Core allowance — if one scenario alone eats the budget, redesign it before you blame the price. Run your numbers against our [pricing guide](/articles/make-pricing) before committing. **Make verdict: pass — excellent value at scale, provided you design scenarios with cost in mind.** ## 4. Does it integrate with your actual stack? List the specific apps you need connected, then confirm each. Make covers **3,000+ apps** plus a generic HTTP/webhook module for anything with an API, so coverage is rarely the issue — but check your niche or in-house tools specifically rather than assuming. One non-obvious trap worth a minute: a connector *existing* isn't the same as it being *deep*. Open the connector and check it actually exposes the specific triggers and actions you need (some cover only a handful of the underlying app's endpoints); if the native module is shallow, you may still need the HTTP module to reach the exact API call your workflow depends on. **Make verdict: pass — very broad, with an HTTP escape hatch for the long tail.** > ⚠ **The exit question people skip:** Always confirm data export before you build an operation on any tool. With Make most data lives in your connected apps — but verify you can export scenarios (as a JSON blueprint) too. ## 5. How real is the AI — and what does it cost? If AI matters, check two things: capability and price. Make includes **AI Agents across all paid plans** (from $9), and you connect your own model (Claude, GPT), so you're not locked to one vendor's bundled AI. Credit cost for AI steps is the thing to model — count how many AI calls each run makes and how often the scenario fires, since AI operations cost more than plain data moves and are the likeliest to surprise you at volume. **Make verdict: strong pass — genuine AI on every paid tier; see the [AI Playbook](/articles/make-ai-playbook) for how to use it well.** ## 6. Can you get your data out? The exit question everyone skips. Confirm you can export scenarios and the data they touch, so you're never trapped. Make handles this better than most: you can export any scenario as a **blueprint (a JSON file)** that captures its whole structure, so your automation logic is portable rather than locked in a proprietary black box. And because your actual *data* largely lives in the connected apps (Sheets, your CRM, your database) rather than being warehoused inside Make, leaving is a rebuild of the wiring, not a data-rescue operation. The practical test takes two minutes — clone a scenario, export the blueprint, and confirm the connected apps hold the records you'd need — but it's the difference between "we can switch if we must" and "we're stuck." **Make verdict: pass — low lock-in; your logic exports and your data stays in your own tools.** ## 7. Is the support level right for you? Support and onboarding are thinner on Make's entry tiers, offset by a deep community and template library. If you need hand-holding or guaranteed response times, price in a higher tier or Enterprise (which carries a defined support SLA). If you're comfortable self-serving with docs and community, the entry tiers are fine. **Make verdict: conditional — great self-serve resources; buy up if you need managed support.** ## 8. Does it clear your security & compliance bar? For any B2B buyer touching customer or regulated data, this is non-negotiable — and it's where a lot of cheaper tools quietly fail. Make holds up well: its information-security program is **ISO 27001 certified**, and it has completed **SOC 2 Type II and SOC 3** audits, with infrastructure running in private AWS (VPC) instances.[2] It has implemented GDPR safeguards, which matters given our own EU-facing stance.[2] Two caveats to check against your own needs: **data residency** — if you handle HIPAA/GDPR/PCI-regulated data, confirm the Make region aligns with your policy — and **SLAs/uptime**, where the guaranteed 99.5% uptime and defined support SLA sit on the **Enterprise** plan, not the self-serve tiers.[2] **Make verdict: strong pass for most; regulated-data teams should confirm region + go Enterprise for the SLA.** *How to test it:* pull Make's security page and DPA, match its certifications and data-residency options to your compliance checklist, and if you're regulated, get the region and SLA commitments in writing before you build. ## The 60-minute due-diligence, in order Reading the checks is one thing; pressure-testing them takes an hour and saves months. Do this before you commit, in this order: 1. **Write your process as one sentence** ("when X happens, check Y, then do Z"). If you can't, you're not ready to pick a tool yet — go define the process. 2. **Build it on the free tier.** Make's free plan runs real scenarios (1,000 credits, 2 active), so build your actual first workflow, not a toy. This single step answers checks 1 and 2 honestly — does it fit, and can your team handle the canvas? 3. **Check your three must-have integrations by name.** Don't assume — search each in Make's catalog, and for anything missing confirm it has an API you can hit with the HTTP module. 4. **Model a month of credits.** Estimate runs × modules × how AI-heavy each is, against the 10,000-credit Core allowance, using our [pricing guide](/articles/make-pricing). If a single scenario looks scary, redesign it (webhook over polling) before blaming the tool. 5. **Test an export.** Clone a scenario and confirm you can get your data out of the connected apps — the exit door you hope never to use. 6. **Time-box the learning.** Give the first build a hard two-hour window. If nobody can spare it, that's your honest signal that a simpler tool fits your team better right now. If Make clears all six in an hour of real use, it will clear them at scale. ## Red flags that should stop you A checklist is as much about knowing when *not* to buy. Walk away — or pause until you've resolved the issue — if any of these are true: - **Nobody can invest the learning time.** Make punishes teams that want automation to be invisible; if check 2 is a hard no, force-fitting it wastes money and morale. A one-click tool is the honest answer. - **Your "process" isn't actually repeatable.** If the task runs a handful of times, ever, the setup overhead never pays back — automation is for the recurring, not the occasional. - **You need a guaranteed uptime SLA but won't budget Enterprise.** The 99.5% SLA lives on Enterprise; if a self-serve tier's best-effort reliability isn't enough for a revenue-critical flow, that's a real gap to price in, not ignore. - **You handle regulated data and can't confirm region alignment.** For HIPAA/GDPR/PCI workloads, an unconfirmed data-residency region is a blocker until it's resolved in writing — don't build first and ask later. - **Your one must-have integration is missing and has no API.** The HTTP module covers anything with an API, but a critical tool that offers neither a native connector nor an API is a genuine dealbreaker. Confirm this before, not after. If none of these fire, you've cleared the real risks — the rest is preference, and Make is a strong default. ## The scorecard Against this framework, Make clears every pass/fail check and wins most of the trade-offs — the two to weigh honestly for your team are the **learning curve** (check 2) and **support level** (check 7). If those two are acceptable for you, Make is very hard to beat on capability and price. If either is a hard blocker, that's your signal to look at the [alternatives](/articles/make-alternatives) — the right tool is the one that clears *your* non-negotiables, not the one with the longest feature list. ## FAQ **How do I decide if Make is the right automation tool for me?** Weigh four things: whether your workflows are multi-step enough to need Make's visual logic (vs a simpler tool), whether your monthly operations volume fits its pricing, whether your team can invest in the modest learning curve, and whether cloud-only hosting is acceptable (if not, look at n8n). If most line up, Make is a strong fit. **How do I estimate my Make operations usage before committing?** Count the modules in each scenario and multiply by how often it runs per month, then sum across scenarios. A 6-module scenario running 500 times is ~3,000 operations. Do this for your real workflows and you'll know which plan you need — and you can validate it on the free 1,000-operation tier first. **What should I test in Make's free plan before paying?** Build your hardest real workflow end to end: confirm the apps you need have modules (or work via the HTTP module), that the logic (filters, routers) does what you expect, and watch how many operations a typical run consumes. That tells you both feasibility and cost before you commit a cent. **How do I avoid runaway operation costs in Make?** Filter early so modules don't run on data you'll discard, widen polling intervals on triggers, avoid unbounded iterators, and add error handling so failures don't retry endlessly. Then monitor your operations dashboard — most cost surprises come from one inefficient, frequently-running scenario you can quickly optimize. **Is Make secure enough for sensitive business data?** Make encrypts data in transit and offers team permissions and connection controls suitable for most business use. For regulated data (health, finance) confirm the specific compliance and data-residency guarantees you need directly on Make's site, since requirements vary — and consider a self-hosted option like n8n if data can't leave your infrastructure. ## Sources 1. Make — official pricing — https://www.make.com/en/pricing 2. Make — security & compliance — https://www.make.com/en/security 3. Make — GDPR — https://www.make.com/en/privacy-and-gdpr ## References [1] Make — official pricing — https://www.make.com/en/pricing (2026-07) [2] Make — security & compliance (ISO 27001, SOC 2 Type II, GDPR) — https://www.make.com/en/security (2026-07)