I started using Make for a specific use case because I needed to create a workflow to upload videos using the API from YouTube. I decided to create an automation workflow to upload a new video every day without manual intervention.

My main use case for Make is to create a workflow where I connect to Gemini to generate ideas, then trigger a video API to create a video from this prompt, and afterwards, use the Gemini API to create a title for the video.

Basically, I have a scheduler that starts every evening to facilitate how this automation works.

My main goal was to create an automation workflow without manual intervention, and this workflow creates and uploads a video to YouTube. From the same idea, there are different videos and different titles, and I do not write them down in Excel; everything is inside Make within this workflow. I was trying to reduce my manual effort.

The best features Make offers include its very visual interface, which stands out for me.

The visual interface provided by Make is valuable because it gives a global view and a global understanding of what comes after what.

My experience with Make has been a sour point because I thought it would be much easier to create, but I found it really tricky.

What made it challenging for me was dealing with the API keys and navigating between different locations; it should be from one platform, and for example, creating an API key should be one action instead of having to investigate where it is located.

I wish the connection to the API was much easier and smoother for how Make can be improved.

I chose a rating of seven out of ten because when you are trying to handle a complex workflow, the visual builder is great but very hard to manage. When I was trying to build a complex automation, I needed error handling, and it is really difficult to handle, which made it messy.

Actually, I did not finish this project with Make; I could not manage to finish the full workflow, and I decided to leave it as it is, implementing it a different way because it is very tricky.

Make has not been stable for me, and I did not appreciate it as much, mostly because of the problems I mentioned.

As CTO at MyDubai.io, I have been working for about a year, but with application development, I have worked for over a decade.

Make has not been stable for me, and I did not appreciate it as much, mostly because of the problems I mentioned.

When it comes to Make's scalability, I find that when you create a huge workflow, it is very difficult because it is very complex to create a complex workflow, and when you have an error, it is very hard to do error handling and debugging.

I did not reach out to any customer support team regarding Make.

I used a traditional solution like Python before using Make, which essentially created the same ideas that I wanted, just using traditional programming.

The idea to use Make came to me when I met it the first time, and after not finishing it successfully, the idea remained, but I ended up implementing it using traditional programs.

I downloaded the Docker and installed Make on-premises in my organization.

I think the price is fair, but I found myself paying too much for every subscription; that is a different story. I found a solution that allows me to use Make almost for free, just using the Docker on-premises, making pricing a consideration since it was free for me.

My advice to others looking into using Make is to start with a very simple workflow and not try to overcomplicate it; when you finish the simple workflow, you can add more to it, otherwise it will become messy very quickly, making it very difficult to handle errors.

I think overall Make is a really powerful tool, but there are definitely a few areas it could be improved based on my experience. My overall rating for Make is seven out of ten.

In automating any kind of user workflow or business process workflow, everything leads back to how data is being transferred, modified, or saved across systems while using Make automations. For example, if we have our CRM systems on monday.com and we are using a Google Form to collect responses for a particular item, we use Make to understand the responses and pass it properly into the monday CRM and send relevant communications using email or text.

In our current organization, we have automated well over 600 processes including all the major workflows of student onboarding, student discontinuation, team member handling, tickets, and CRM manipulation. We have across 2,000 to 3,000 scenarios in the system, with over 500 to 600 workflows automated.

In terms of communicating between systems and between platforms, Make would be the primary tool of choice because instead of going about creating or writing API codes for multiple platforms, Make creates a seamless connection where modules come in and take care of most of the heavy lifting of code.

The visual workflow builder is something that stands out prominently, providing a no-code platform which connects across multiple different integrations and platforms. This means that even making changes to a particular platform can trigger a different functionality on a separate platform, so integrations definitely come into the picture. Additionally, the ability to create webhooks on the go is another particular feature that stands out.

Having an in-built or in-house data store to manipulate data and store it across multiple different scenarios is one more feature which particularly makes it stand out. The new work grid feature makes it visually very appealing to see how the automation workflow works.

Make has positively impacted my organization by reducing the number of hours that go into validating and verifying the flow of a particular repetitive process, which would otherwise take multiple hours, to just a few minutes to review for more than 1,000 or 2,000 case scenarios. Any fallback cases also go seamlessly into the incomplete executions DLQ for me to analyze and resolve.

The ability to have further customizations to certain functions and modules that are pre-existing may be something that could be improved. Regular updates to cover up any bugs or issues or proper repeated community asks is also essential.

Pricing is definitely something that is on a higher tier where we are consuming around 1.5 to 2 million operations per month, which makes the bill quite substantial. Keeping that in mind, there can be instances where the scenarios can be optimized properly to reduce operation count. One other thing that probably needs improvement is proper documentation of internal automations, which could be a tool that queries all the current scenarios and acts as a chatbot or helper to find certain values or parameters used across scenarios.

I have been using Make for about three to four years.

My advice to others looking into using Make is to go through the documentation first and go through the training and certification courses. Those are pretty detailed and almost cover all aspects that you would need to implement in an automation scenario. I would rate this product an 8 out of 10.

I have been using Make for almost five to six months. My main use case for Make is to automate certain tasks like social media posting and article posting on WordPress. As I work in FitPyo, we need to post blogs or articles on our website regularly, so rather than doing it manually, I created an automation workflow that fetches the posts and automatically publishes them to Facebook, Instagram, and other social media websites. Article posting is one of the major use cases for Make.

I decided to automate social media and article posting first due to the need to post tons of articles daily and to make the process really fast and effective. We use Make because we are a startup where many tasks need to be done on the go. I created an entire automation workflow so that articles can be fetched, rewritten with GenAI models, and posted on our website. The same applies to social media posting as we need to post frequently on Instagram and LinkedIn.

Regarding my main use case with Make, I am trying to automate WhatsApp messaging through Make for client interactions to facilitate direct replies. I am still figuring out how to do that. I am also considering posting a YouTube video through Make, although I feel Make is too complicated for that. I am also looking into using n8n to see if it might be a better option.

The best features Make offers are its ease of use with drag and drop functionality. Compared to other automation tools like n8n, which is complicated, I find that Make is very simple. The standout features include ease of navigation and error checking, and I really enjoy the drag and drop feature personally.

I feel that if you are a beginner looking to get into automation, you should start with Make because it provides an environment where you can practice automation more flexibly, although integration and API can be a hindrance.

Make has positively impacted my organization by reducing our manual workflow and workload by almost twenty to thirty percent, which I feel is great. Many tasks that previously took time, such as article posting and writing, have seen a reduction of almost forty to forty-five percent in time. This allows our team to focus on innovating and developing our wearable products.

I feel that Make can be improved in terms of API handling and integrations. While n8n provides many integrations, Make has a limited set that can be enhanced for better performance.

I think error handling can also be improved, and the turnaround time should be addressed to enhance the user experience further.

I have been working with Make for almost six to seven months. To be precise, it would be almost seven months and ten to twenty days. I am very versed with Make and automation.

Make is stable, and I can confidently say that.

Make's scalability depends on the use case, but I find that it is scalable, especially for my needs.

Customer support for Make is good. I get responses and replies when I need assistance.

I have already shared a lot of information with you.

Make is deployed in my organization as a hybrid cloud solution.

I have seen a return on investment with Make, as the manual workflow is reduced by about ten to twelve people. Our turnaround time has improved by thirty to forty percent, which highlights the operational efficiency gained through automation.

My experience with pricing, setup cost, and licensing is that pricing is fine and not that expensive. I need to consider effectiveness in automation, and I feel everything is good to go without much to add.

I previously tested with Zapier, but I am not a fan of it. Make is a win for me.

Before choosing Make, I evaluated other options such as Zapier, but I found that Zapier was more suited for social media posting alone. I needed something in a broader format, and I feel Make can be trusted for that.

I am using the time saved through Make automation to develop my own line of products because, at the end of the day, product matters. A specific project arising from that extra capacity is the ability to brainstorm many ideas that can lead to long-term profits.

My advice for others looking into using Make is to tailor automation based on the use case rather than an organization's needs, focusing on effectiveness in automation. I would rate this review a seven out of ten.

I have been working in my current field for the last three years and have been using Make for two months.

I have used Make for two projects. The first project is medical case analysis, where if a patient uploads any case details, we handle that and provide solutions in three fields of a hospital: allopathy, homeopathy, and Ayurveda. Ayurveda is in Indian medical sciences, and from these three options, the patient can decide which one to choose and what tests are included.

In this medical case analysis project, I took five case studies of five different patients and translated the manual data using API to shift it to Google AI Studio. I made it there and used Make's JSON response from the output.

In my second project, which is about the UPSC exam, I converted PDFs given in manual format into HTML. I used data manipulations along with Make's built-in data parsers and regular expressions modules to analyze each question and integrate the options by iterators, making the process sequential.

The best features Make offers, in my experience, include the infrastructure of hosting and error handling, which I have found reduces many errors during projects. Additionally, it allows for secure and reliable API integration with Google AI Studio and provides visual debugging for the mock test data.

During my projects, the visual debugging helped me connect to AI Studio. JSON represents large data, which is converted into a shorter image that I can explain easily to patients.

I have two to three drawbacks I would like to add.

There is a file size constraint, as when I try to upload a PDF question bank of 200 pages, it shows an error and the file cannot process the data. The second drawback is the complex native app modules, as every single API does not integrate properly. I have tested some other API integrations, and they have not worked as expected. The third issue is that if I encounter one error, it halts the execution, which causes a delay.

These drawbacks impact my workflow as I have to separate the PDF into two or three parts due to the file constraints. For native app API integration, I use standard APIs like Google AI Studio, and for error handling, checking manually works better if just one error occurs. Additionally, I notice Make is heavily dependent on regular expressions. For example, if a question is written as 1Q, it sees it as one question.

I feel I have covered most of the points regarding improvements needed. I choose a rating of eight out of ten because I feel the file constraint part and native modules for API integration should be improved while making the workflow process. I do not have any other improvements needed for Make apart from the file constraint issue, which must be looked into, and the visual clutter issues when uploading more than three to five patients at once.

Make is stable in my experience.

Make's scalability is good.

When I had a problem during the pricing payment, the customer support handled it very well. I also received good responses when posting in the community forum while doing the project.

Previously, I have tried to use Zapier, which was very simple and linear, but I switched to Make because it provides visual representations that I find beneficial.

I have seen a return on investment, particularly in my second project where I converted PDFs into HTML format, saving costs on paper for approximately ten thousand questions and reducing time by about fifty percent. For patient case studies, I was able to present options in allopathy, homeopathy, and Ayurveda clearly and more quickly.

I have used the free version of Make and I find the pricing reasonable, especially with discounts available.

Before choosing Make, I evaluated Zapier, but after a friend's recommendation to use Make, the workflow has been very smooth for me.

Make saves me roughly forty-five percent to sixty percent of time since the analysis part and solution are provided below the question.

My advice to others looking into using Make is that you can create a very smooth workflow compared to others, and the visual representation is excellent for presenting data or any complex problems, especially for complex systems such as the neural, respiratory, and reproductive systems. The built-in modules make it easy to convert PDFs without needing to search for other modules to integrate.

I'm using Make for integration with GoHighLevel, which is a CRM tool. I integrate data from Google Sheets or the GHL CRM to automate repetitive tasks. I use Make nearly every day for whatever task comes my way, including reconciliation of bills and transaction tracking in Google Sheets, as well as GoHighLevel work. When I receive leads from Meta, I integrate those as well.

I have created an Airbnb scraper that extracts all details from Airbnb, including reviews and pinned locations, which are not very easy to obtain. I used Claude to create Python code, integrated it through Make, and used Apify. Make sends the command and prompt to Apify, which runs the code and scrapes all the details from Airbnb, then updates them in Google Sheets. Once any row is updated, Make automatically sends all details to every user. For example, when my name is entered in the Google Sheet, Make takes the name, email ID, company, and everything based on the flow I have configured, and sends the email automatically to that person. We have a company called Rental Abode, which is similar to Airbnb and we are building it now. I target them by scraping all details from Airbnb and sending it to them using Make.

Creating scenarios and sending them is really straightforward. I was doing manual tasks in the sheet before, and now Make makes everything easy for me. I can write the interior logic, whatever loops or anything I want, and whatever I was doing manually, Make now does it automatically. I only need to write one code and create a scenario, and based on that, it executes everything. This scenario is essentially a webhook, allowing integration from one site to any other site, which is quite interesting.

The data storage feature is also excellent. Whenever I'm using data, I can store all of it in Make, and whenever I need it, I can access it. The templates that Make provides are good, with everything built-in. I can use the data structure smoothly, and the custom app feature is also one of the best, as it's a good option for anyone who wants to explore.

The outcome is far better than before. Every employee used to work manually, and I also used to do manual tasks. Now Make does everything automatically. Whenever any task comes up, I'm always thinking about how to automate it with Make, which is something positive.

Sometimes the platform is too laggy and loads slowly. The credits are also getting used up too quickly, which takes too much credit. If the credits could be reduced, that would be more efficient.

The lagging problem needs to be solved. Sometimes it lags a lot with long workflows, taking too much time or giving errors like not running.

I have been working in my current field for more than two to three years.

As of now, Make is stable for me.

Make has scalability. Whenever a new task comes to mind, I think about automating it with Make, which is good. However, I see many cheaper competitors emerging, so understanding their features could help.

I have not reached out to customer support because I haven't encountered any issues that I couldn't solve.

I was doing a manual approach completely before Make.

The setup was easy. I completed everything related to pricing, setup costs, and licensing within two or three hours.

I was supposed to hire a business analyst, but due to Make, I realized it has this much capacity. I can do multiple tasks as a founder, but I don't have time. So I created automations, saving me around 7 to 8 lakh INR.

Earlier I used to spend too much time understanding the insights from my projects. Now I only spend four to five hours, but I can get everything in one hour or even 30 seconds. It's easy. After one click, it's pulling data from my database, updating in ChatGPT, and then analyzing and updating in the document. I can understand within five minutes what exactly is going on in the business and its direction.

I looked into Zapier, but it was more costly, so I chose Make.

If you want to automate everything, Make is the only thing you can use to integrate and automate all the platforms, especially if you don't want to work manually.

I is primarily use Make for automations in companies and businesses, specifically for report generation and similar tasks.

I recently built a workflow for a recruiting company called NSL that needed to conduct a test for candidates and generate a report. The entire process, including test preparation, result generation, and sending the 40-page report to the candidates, was fully automated.

Automating this process with Make saved considerable time for NSL and my team because generating one report manually could take nearly one day for each candidate. Automation reduced that time to approximately 14 minutes per candidate, allowing the entire process to be completed within 15 minutes from start to finish.

My main use case for Make currently involves small automations, although I believe Make has introduced new features such as agent mode, which I haven't tested extensively but seem promising.

Make offers great features, including extensive tool connectivities and a simple user interface, which makes it excellent for beginners and enhances ease of use.

Regarding tool connectivities, I find the RSS feed straightforward and user-friendly, and the Airtable node is similarly easy to use. Make has asset-type reactor nodes that automatically begin actions when data is entered, which is something that other apps typically require webhook integrations to achieve.

The user interface is straightforward and always presents data in schema format, enabling an easy drag-and-drop experience.

Make has positively impacted my organization by enabling me to generate numerous leads because it is easy to implement, which allowed me to drastically reduce the time needed to create and present a minimum viable product to clients.

To improve Make, I would suggest increasing the token limit, possibly allowing each run to cost only one token, which would be beneficial as no-code tools require significant testing. Additionally, implementing a pin feature for each result would facilitate reusing outputs easily.

I give Make a rating of seven because it is not open-sourced and there are many hidden charges, which can affect a beginner's workflow when trying it out. I recommend making testing free initially, then requiring a premium subscription for publishing. Additionally, there are not enough nodes for internal tasks such as adding Python code, which requires third-party tools.

I have been using Make for the past two years.

My advice for others looking into using Make is to start as a beginner, understand the concepts, explore relevant artificial intelligence for automations, and begin with templates, as there are many resources available within the community and on YouTube. I also believe the flow in Make could improve by allowing multiple nodes to be executed synchronously.

I believe Make can still improve to compete better with the open-source automation platform n8n. I rate Make a seven overall.

My main use case for Make is mostly for marketing automation, including lead generation, lead integration, routing to sales agents, and for personal uses.

I had a client who wanted me to retrieve every post being posted on a specific subreddit so that he could use that conversation or specific post and comment on it organically. This gives him a chance to warm up the client and sell his CRM product. I set up the automation by using the Reddit API to connect to Make and used the Google Gemini flash AI agent to summarize the post and the replies.

One of our clients uses HubSpot as a CRM, so I connected WhatsApp automation and everything on Make. Whenever the lead status is changed on HubSpot, the automation triggers on Make, and a certain type of template that I have created on WhatsApp is automatically sent to the lead. An internal notification is also sent to the sales team.

The best features Make offers are unlimited workflows that can be created, and the pricing is quite affordable.

The unlimited workflows have helped me and my clients get more done because sometimes I need to create a temporary workflow for my personal use cases. With another version like Zapier, I would not be able to quickly add multiple workflows with complex routing. With Make, I could pause the active scenarios and resume my temporary one, which is beneficial.

I really appreciate the drag and drop interface. I am not good at coding, so if I had to create automation for my marketing purposes and CRM integration, I would have to code it manually using Python or JavaScript and rely on another developer or someone who knows code. With Make, it is much easier for me.

Make has positively impacted my organization by helping me save around 10 plus hours per month to automate reporting and social media posting.

Since I am not using Make extensively for other purposes, my use is fulfilled enough, and I do not see anything that needs improvement.

I have not faced any needed improvements or challenges while using Make. I chose a nine out of ten because sometimes my browser gets crashed while working on Make, and I do not know why. For this reason, I have to save every couple of minutes so I do not lose any progress.

I have been using Make for around seven to eight months.

Make is stable in my experience.

In terms of scalability, I think Make is capable of handling complex workflows. The workflows that I have created are pretty simple and not too difficult.

I have not contacted customer support yet for any issues because I am not a regular user.

I previously used N8n, which had a self-hosted version, so I could create as many workflows as I wanted. N8n is much better than Make, and I used N8n much more than Make, so I do not know all the features Make has.

My experience with pricing, setup cost, and licensing is that it is quite affordable for my use case. I could get the return on investment from the work that I have done using Make, so the setup is not difficult and is pretty simple for me.

I have seen a return on investment because I could avoid hiring a new team to do reporting and social media posting. Everything is done through Make.

With that extra time each month, I could focus more on sales and upscaling my business, so it is really worth it.

My experience with pricing, setup cost, and licensing is that it is quite affordable for my use case. I could get the return on investment from the work that I have done using Make, so the setup is not difficult and is pretty simple for me.

Before choosing Make, I evaluated other options including N8n due to the self-hosted version.

I would advise others looking into using Make to consider it if they want to get a starting point of automation for something pretty simple. I would rate Make a nine out of ten.

My main use case for Make involves automating WhatsApp messages, website visits, and how to reply to them. I'm not using it very frequently, but it is a helpful tool.

I once automated a few things with Make. If a client is onboarding and that person has some questions, I had submitted a few things, and accordingly, it was giving them a reply, and it was finally redirecting them towards my website.

I chose to automate that particular process ideally just to save my time because I was getting so many leads and needed to filter them out, determining which lead is a warm lead, which lead is a hot lead, or something similar.

I don't have anything else to add about my main use case or how it's helped me manage my leads. I think I have covered most of it. I will be using Make in the future, but as of now, I am using a lot of other tools as well.

The templates available on Make are really interesting, and they can really help a person who is starting a new company. But I think for my current situation, I can only leave this kind of review for now.

Make has helped me save time positively. The templates available on Make are really interesting and can genuinely help people who are starting new companies.

I cannot give you any particular metric, but overall, Make has helped me save my time.

Make has helped me save my time, and time is money, so obviously, eventually it has helped me save my money as well.

Make has helped me save time positively, but I think there is room for improvement in Make as well. I believe there were a lot of features related to Make that I was not able to use because of a lack of knowledge. If you could add some kind of tool or something which could help people who are laymen in terms of tech, that would be helpful.

As of now, I don't think I have a lot of things in my mind about how Make can be improved.

I have been using the solution since September 2025.

I did not previously use a different solution for automation. Make was my first automation tool, so this was my very first experience with any kind of automation.

I don't have any connections with this vendor other than being a customer. I just completed my course from Make, received my certifications, and used a few tools and templates.

Make has helped me save my time, and time is money, so obviously, eventually it has helped me save my money as well.

I don't think I paid anything for Make. I just completed the course and got my certifications after I had passed the test.

My advice to others looking into using Make is to use it and explore a few things. You will be able to learn a few things which you will be needing in the future. Make is a helpful tool. But I think you should do a bit of marketing because I don't know many people who know about Make in person.

I have not explored Make a lot, but it's decent.

I chose eight out of ten because I haven't used any tool which is related to automation. This was my first experience with an automation tool, and it was helpful for me. Obviously, I don't have any other tool in my mind which can help me automate a few things. There is always room for improvement for things, so that's why I'm giving an eight, not a perfect ten.

I'm not using Make very frequently as of now, but there was a time in the past few months when I was actually using it on a daily basis to automate some things.

When I was using Make regularly, it was deployed just through the make.com website.

My primary reason for using Make is workflow automation. When it comes to scraping data from portals like LinkedIn or any other website and then storing it on a Google Sheet, that is the most time-consuming task. I was able to create a workflow and automate it through agentic AI, which was a significant achievement for me.

Make could possibly provide scenarios on their homepage. The moment I log in to my account, Make could ask me what I really want to do in a visual way and not in text form. When I see visuals indicating that I'm going to scrape data, I would click on a thumbnail, or if I'm going to create a workflow, I might look for something like an always-on agentic AI. These can be put onto a thumbnail which can further make my work faster on make.com.

There is still a lot of difference when it comes to how the credits come into use and how to monetize what is being offered by Make. For me to be able to monetize what Make offers is equally important as using it. If my clients are going to pay me in a span of 60 to 90 days for a service that is consumed, I need to understand that within that 90-day timeframe, whether using free credits or otherwise, I have to justify the cost. Can I give it more work than the ones I'm currently doing? The ultimate factor is that there are many tasks that an executive does in a recruitment consultancy. Within a recruitment consultancy, being on the agency side of the business where I do business development, prospecting, and lead generation, I document information for each candidate, and then create a business model canvas for each lead I prospect. When presented with 10 different requirements from a Fortune 500 client, I need to quickly close those. Can those free credits be really worthy at that point in time? My commitment needs to be based on the inventory I have.

Without really looking at many things, I feel that Make is a space where I can automate a lot of my work, and that says a lot.

When I think about automating my work with Make, I would say that the credits given on a monthly basis are useful for me to use them. The integration of webhooks and understanding how which particular tool can be integrated and how it can be played further is a significant achievement.

Make is a space which can be explored further. If I have to scrape data and if that consumes five to six hours, the fatigue that comes after doing repetitive tasks does not allow me to do any other work for another three or four hours. This means the task that I would complete in a span of one day is completed in a matter of minutes by using Make.

Make is the reason why I feel confident about taking up newer and newer assignments.

Make could possibly provide scenarios on their homepage. The moment I log in to my account, Make could ask me what I really want to do in a visual way and not in text form. When I see visuals indicating that I'm going to scrape data, I would click on a thumbnail, or if I'm going to create a workflow, I might look for something like an always-on agentic AI. These can be put onto a thumbnail which can further make my work faster on make.com. There is still a lot of difference when it comes to how the credits come into use and how to monetize what is being offered by Make. For me to be able to monetize what Make offers is equally important as using it.

If my clients are going to pay me in a span of 60 to 90 days for a service that is consumed, I need to understand that within that 90-day timeframe, whether using free credits or otherwise, I have to justify the cost. Can I give it more work than the ones I'm currently doing? The ultimate factor is that there are many tasks that an executive does in a recruitment consultancy. Within a recruitment consultancy, being on the agency side of the business where I do business development, prospecting, and lead generation, I document information for each candidate, and then create a business model canvas for each lead I prospect. When presented with 10 different requirements from a Fortune 500 client, I need to quickly close those. Can those free credits be really worthy at that point in time? My commitment needs to be based on the inventory I have.

I have been using Make for close to about three to six months.

My rating for Make is 90 out of 100. I give it 90 because there is always scope for improvement, but I feel that this product is exceptional. I have not seen anything like Make so far.

A perfect 10 would mean there is nothing more to improve. A nine probably means there is scope for improvement, changes to be made, and relevance to be established. Even with the world's best service, I question whether the world really recognizes it or if it can be utilized economically. Giving me a thousand credits per month can be consumed quickly, but none of those things accumulates, nor is there an unlimited version that can wait until I become profitable before offering me the first paid plan. I give commitments based on the number of credits being offered.

Make is deployed in my organization on a public cloud. I use the make.com website itself. I signed up directly through the Make website.

I would say to make your first use case and understand what the product is. Each entrepreneur or executive must understand what inventory they add by taking a subscription to Make. When you realize you have a machine that can save you time, it still needs to be understood that it can save you time based on the credits. If the credits get exhausted quickly, then you cannot save any further time.

I am neither a partner nor a reseller. I am just a customer.

I think it is a wonderful product, and if the aspect of giving time-based or quarterly credits instead of monthly credits comes into play, it could allow an entrepreneur or executive at any designation in an organization to make one or two full cycles over a quarter, which could be a significant achievement. I rate Make at 90 out of 100.

I use Make for my personal use only as of now, and I am learning Make and automating things with it.

Recently, I have created a scenario wherein I can automate the process to find me a topic, and based on that topic, it makes me a LinkedIn post and shares it with me on my email.

That was a scenario I had created, but the only challenge is that this scenario is not yet perfect, so I am not yet posting those posts.

I already shared one example of Make, where I have prepared a scenario wherein I spoke about the LinkedIn post. That is the only task I have prepared, and I think if I could give the perfect prompt, if I can enhance the prompt, it can give me a better output. Once that is successful, I will not have to search or hunt down for a topic every day to post on LinkedIn; Make will automatically help me research the topic and get me a scenario to post on LinkedIn.

I use Make for my private use only; I have not used it for my organization.

The process that Make offers is very easy and easily understandable.

Everything about Make, including the interface, is easy to understand, eye-pleasing, and there are enough tutorials on Make that help me learn new scenarios.

Initially, I was not aware of automation, but now I can do plenty of automations. I can try out various things and can make it interact with one application to another, which is very helpful. This has made a very positive impact on my life because initially I was not able to do things quickly and efficiently, but now with the help of Make, I can plan many things that help my work become efficient.

I think I have a Teams plan, which is helpful for me, but once that plan is over, as a learner, I will not be able to afford this Teams plan further. Make can enhance the credit limit for free use because what is happening now is that most of the credits have been used during testing only.

The thing I missed, which kept it from being a perfect ten, was the free usage limit because whenever a free user runs out of their credit, they have to wait for a long time, and most of the credits have been used during testing only.

I have been using Make for around six to seven months.

As of now, I have not experienced any downtime or issues with Make; it is quite a stable application for me.

Previously, I have used n8n, but the only thing that I found was that n8n's plans are costlier than Make, which is why I switched to Make, and even the Make interface is easy.

I have already used n8n before choosing Make.

I have definitely seen a return on investment, but I cannot share an example because I have not made many scenarios with Make.

I will definitely ask others to use Make more often because it helps a lot; it improves efficiency, and that is the biggest thing I found about Make.