Make Reviews

Some of the very simple use cases that people use Make for is AI-powered content creation. That is where we help them out with different kinds of content creation and social media posting, different business process automations such as HR recruitment processes. Several of these cases have been implemented using Make.

Make's front-end interface, the modular interface that it has, drag-and-drop interface, is very easy to understand, use, and integrate. It has definitely helped us and in terms of efficiency, it reduces the time that is required to complete any sort of automations.

Make's key features are very flexible when compared to Zapier. Because of that flexibility and the features it provides when using a particular module within Make, as well as using an HTTP module directly accessing any API, it is very flexible compared to Zapier.

Make's front-end or the low-code interface provides you with a very efficient way of creating these integrations and automations, which saves your time to market or creation time of these automations.

We utilize Make's drag-and-drop interface all the time. We use that low-code interface for creating automations.

We have utilized them and used them with different sorts of AI decision making. As advanced users of Make, we have handled many complex scenarios within Make.

Make needs to put some focus on or clarify the security aspect in its documentation or website. When creating automation through these modules between two different applications, there should be clarity about whether the data is secure while passing through these automations or integrations created within Make.

The pricing of Make at this point is through operations consumption, and it becomes really expensive in certain scenarios when iterations are involved. The operation consumption is too high and sometimes becomes a burden on the client. Make needs to review its pricing strategy since they have tough competition from n8n.

Make sometimes has issues with user logins and data saving when simultaneously working on two different PCs or when two developers are working on something or some blueprint. It can lose saved data from one interface to the other, and when logging on with the same user on another workstation, it occasionally misbehaves.

We were unaware that Make had its own local implementation module. They need to advertise this feature more effectively as we are developing many projects in Make and working with various clients.

We have been working on Make for the last two to two and a half years. Before Make, it was called Integromat. We have been working with it since before it was acquired and rebranded.

In terms of scalability, Make has no limitation or issues.

We have escalated a few issues that we faced during some integrations, and we received reasonable responses from Make support.

Positive

The initial setup for Make and getting a project ready and starting off with the project is very easy. Usability is not an issue.

n8n provides the same kind of flexibility and is much cheaper than Make. Once we install and get the local implementation ready for n8n, it becomes free for users.

Zapier is less flexible, and with the evolution coming through n8n and Make's new features, it is becoming a primitive tool. The main comparison in terms of features between Make and n8n shows that n8n, apart from pricing, is evolving into user interface based automations as other tools UIPath or Automation Anywhere.

In the last three months, many new customers are requesting n8n because of this pricing strategy.

Make is very flexible, easy to use, and has a whole universe of modules readily available within its offering and portfolio. People should feel comfortable using it even if they are citizen developers or not hardcore developers. They should be able to use Make by watching one or two tutorials and by dragging and dropping things and connecting the different modules and adding conditions. I highly recommend Make with a rating of 8 out of 10.

I'm working on multiple Make, n8n, and a lot of tools. For sending some proposals and login systems, I use a tool called Bubble. Some of the workflows that are complex on Bubble, we used to do with Make. For Google Docs, AI automations, and content creation, I have a couple of things, and email commenting and replies for that are some examples.

When I'm trying to build some workflows, there's a chatbot component. When I ask for something like this, it helps me in that. Or if I get a bug that I'm finding difficult to debug or understand the use case or the log, it clearly explains it to me and sometimes it advises me to do this or that, so that it's easy for me to fix it.

Real-time functionality is really needed in most cases. For example, in AI automations, when a customer signs up into my portal and I try to send them a reply, the data would synchronize so then I can send them accurate data. There are a couple of use cases which are complex that I cannot explain on the call.

Most of what I learned about Make is mainly from the templates only. Anything that I tried to do, I try to see who has done it already and try to understand and rebuild it.

The new AI feature that Make has launched is really amazing. The UI is pretty clear for me compared to Zapier. In terms of features, the flexibility of adding the code and doing all of that is the best thing that I appreciate about Make.

It's complicated to give good feedback, but it's helping me in saving a lot of time in terms of manual input. There's a huge cost cutting in my application when I'm using Make.

Most of what I learned about Make is mainly from the templates only. Anything that I tried to do, I try to see who has done it already and try to understand and rebuild it.

When I'm trying to build some workflows, there's a chatbot component. When I ask for something, it helps me in that. Or if I get a bug that I'm finding difficult to debug or understand the use case or the log, it clearly explains it to me and sometimes it advises me to do certain things, so that it's easy for me to fix it.

One area for improvement is an auto-building feature. Another is how n8n has a chatbot completion where you can bring some LLMs into the workflow and integrating Ollama and all of that is something I felt is really needed for Make also.

I have been using Make for three years.

I don't have any issues; it's as smooth as the other platforms, not very complex or hard to understand, but it's fine for me. It's working fine, and I don't have any major concerns about it, but my purpose and my use case is getting done. So I don't have many additional points there.

It's scalable. I don't feel that for my requirement, I'm getting the best out of it.

I haven't taken very much advantage of the services, but what I had earlier, they were doing the best job for my use cases and my problems. So they helped me. However, I'm not very extensively reliant on the customer support. I used to talk to the developers or the forum that Make was having. I used to go there and figure it out by myself. So very rarely I used to get in touch with the support team.

Neutral

Something like n8n is an alternative. Recently I started learning to use n8n a lot, which has AI agent features, and it is open source. Right now, n8n is an open source platform. So I would be more interested in learning more and exploring more if Make is also an open source option. Because a lot of experiments can be done if it's an open source.

It's straightforward and easy for me because I come from a tech background. It's quite easy for me. I don't know if a person from a non-tech background would find it a bit difficult, but for me it's very comfortable.

I also referred to a couple of my internal team members and some of my clients to use Make for their business processes as well.

I've achieved a lot. The return is approximately 300%, and that you can think about, with an approximate range of around 500 to 600%.

It's perfect. It's cost-effective and it's pocket-friendly. I don't have many issues with the pricing part. Pricing is quite comfortable for me.

Something like n8n is an alternative. Recently I started learning to use n8n a lot, which has AI agent features, and it is open source. Right now, n8n is an open source platform. So I would be more interested in learning more and exploring more if Make is also an open source option. Because a lot of experiments can be done if it's an open source.

Each platform has its own keen usage and keen requirement. I feel that Make is doing the best of its use case. Each platform has its own specialty in terms of UI, workflow, or customer support in terms of building the tool more reliable to customers and accessible to people when issues come. For now I feel that it's doing good. I would rate this review a 9 out of 10.

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.

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.

A specific example of how I use Make for API connections in my environment is integrating our CRM with a marketing application for data transmission and unity, GDPR compliance, and synchronization has been excellent through Make. Building scenarios for each specific language or location action has been beneficial. Managing certain actions and triggers based on links, some of the workflow solutions were not present in marketing tools, and we needed to create more complex processing in Make to meet our needs. Make is also a great tool that we use to build various automations, and it is excellent for connecting multiple tools together to send data. For example, at our company, we use Make to send new orders notifications from Shopify to Slack and also add the customer's shipping information to a Google Sheet for the fulfillment team. The best feature about Make that competitors lack is the option to connect rare and available apps via their API. It also allows us to get data from anywhere on the internet via GET requests.

I have additional use cases for Make, as we use it to support a variety of internal and client integration projects. Everything from automating invoices from CRM orders to running recurring data pools from our database to client platform API connections for reporting has been excellent. It also helped us to connect platforms that otherwise would not connect while giving us the opportunity to code and customize these integrations for our specific use cases.

Make has been used in my organization to start an automation process in the sales and marketing departments, closely followed by operations and human resources departments. Sales and marketing are automating all their initial contacts with clients from the first contact until the client is up and running independently. Operations are automating the tickets and follow-up to pending reports that clients submit. Human resources benefit from Make because they are integrating information streams from some of their departments using Make.

Make has positively impacted my organization by enabling us to solve use cases for hundreds of clients across hundreds of different platforms, providing the customization capabilities to automate accounting and invoicing processes that save dozens of man-hours a month, and allowing us to build custom churn, retention, and engagement costs that have driven a 30% reduction in churn.

Furthermore, providing more thorough support documentation on connecting various platforms and troubleshooting errors would be very beneficial, especially for junior team members.

Negative

I switched from Zapier to Make because Make has a different pricing schema than Zapier. Almost all the apps that I create on Make can be done in Zapier. The only difference is that Make is more accessible in terms of cost. In my opinion, Make is bigger than Zapier and has more robust features, and it is very cost-effective and easy to use for anyone.

My advice for others looking into using Make is that it is a great tool if you want to automate boring tasks such as sending welcome messages to people and automating repetitive tasks that do not generate value for the person doing them, thus saving their time and allowing them to focus on more strategic tasks. Additionally, it effectively automates the creation of complex interactions between applications in order to streamline completely internal processes, thus saving a lot of cost and time. I would rate my overall experience with Make an 8 out of 10, as it is a very recommendable tool.

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.

In that project, I used Make to build a real-time monitoring dashboard for internet of things devices using React for the front end and a FastAPI for the back end and MQTT for handling data streams. I used Make to automate workflows between the back end and external services, such as email notification systems and data storage endpoints. When specific events occurred, such as device data updates or threshold alerts, Make triggered actions such as sending notifications, forwarding processed data to other APIs, and synchronizing data for further analysis.

Regarding the use case, Make helped us avoid writing custom integration logic in the back end and kept our system more modular.

The best features Make offers are that it helps automate repetitive back end tasks, which is very helpful. You save a lot of time and money. It also helps connect multiple services quickly so you do not spend time writing integration code or reviewing back end documentation. Thus, it saves a significant amount of development time.

Make positively impacts our organization by helping us save a significant amount of time, especially for the back end where we needed many integrations to our API. We had third-party storages where we saved our data and needed notifications sent. When we had threshold data and emergencies when we hit limitations, we did not want to spend time on integration, which is a very repetitive task that requires learning specific documentation details. For that part, I think Make saved money and time, which is very important in the initial phase of development.

Instead of spending several days implementing and testing API integrations inside our FastAPI back end, I was able to build the workflows in a few hours using Make. I saved multiple development days and it also reduced the engineering effort, lowering maintenance costs since changes to integrations could be handled directly in Make without modifying back end code. As a result, I could focus more on core features such as real-time data processing and the React dashboard, rather than managing integrations. Overall, I saved around a week, which translates to approximately a thousand euros, so it was a very significant amount.

One area that needs improvement is the debugging and monitoring. When a workflow fails and you have different places where the problem might be, it can be very difficult to identify which step caused the issue, especially in multi-step scenarios. When handling event-driven workflows from a FastAPI back end triggered by MQTT data, it is sometimes not clear whether the issue is in the API response, in the transformation step, or in the final action. I would love to have more detailed logs, step-by-step error tracing, and better visualization of failed executions, as I think it would improve the user experience significantly.

My advice for others looking into using Make is that it is a great tool for quickly automating workflows and integrating APIs. However, it is important to keep workflows organized as complexity grows.

The most valuable feature is the time saving, especially in startups when you want to release the first version of your product quickly and want other parts to be smooth. Sometimes back end tasks take more time, sometimes front end, but if you have services such as Make, it can make the development time faster. You develop faster, check your features faster, and make integrations faster, so overall it helps to go to market quicker. I would rate this product an 8 out of 10.

My main use case for Make involves automating social media content creation and personalized content creation for my social profile like Instagram.

Make offers a very simple and easy to understand user interface. The best feature Make offers is a simple process because as a beginner, when I started with Make, it was very easy to understand how to connect the nodes and how to create them.

I would add that there are more features available. Initially, I was working on a free version offered by Make, but I was unable to use more than two nodes active at a time. This is why I shifted to the Core plan where I can keep more than two scenarios active anytime. My automations include four to five automations active at any time.

I have seen a return on investment from using Make because it saves my time. I am using Make for content creation, and it saves time in content creation for me and helps with tasks by creating content for me even without writing a single word. I completely agree and strongly agree with this point and will rate it a ten out of ten for Make.

Make is stable and has been reliable for me during my automations and workflow tasks.

I think there are improvements needed for Make. They could add a guide roadmap for beginners to make it more accessible. While Make is easy to use, there is always room for improvement.

There are many useful features available. We can work on MCP, and we can also work on MCP from Make. Currently, I do not have an idea about major improvements, but it would be helpful for users if they could add something like an AI assistant, which would give users more clarity on what they can achieve with Make. I am talking about beginner users because if someone is experienced in automations and workflows, they will not have any issues, but a beginner might face a lack of knowledge. I suggest adding something like an AI assistant, as most companies and websites are adding this feature for user assistance. Make could implement this for user support.

Make is good enough, but there is also a scope for improvement. Their peer companies provide features that Make could consider. I was talking about dark mode because it feels irritating when working in dark places. This directly impacts user satisfaction, so they need to focus on it. I come from a technical background, so it is not that difficult of a task, but it greatly improves user experience.

I have been working in automation or workflow management for the last six to eight months.

Make is stable and has been reliable for me during my automations and workflow tasks.

Make's scalability is good. It can handle increasing workloads or more complex automations easily, but I need to set up each and every component carefully.

The customer support for Make has not been necessary for me as I did not interact with the Make support team.

I did not use any other solution for automation or content creation before Make, but I was working simultaneously on Make as well as N8N. I did not switch, so I cannot justify it further.

Make is not deployed in my organization as I got in touch with Make through my online classes. When I learned about Make from my peers, I started to use it.

I was offered a link from my classes to sign up for Make directly through the website.

I do not have a business relationship with this vendor other than being a customer because I do not work in any company, so I do not have any connection with Make or any partnership with them.

I have seen a return on investment from using Make because it saves my time. I am using Make because it saves time in content creation for me and helps with tasks by creating content for me even without writing a single word. I completely agree and strongly agree with this point and will rate it a ten out of ten for Make.

Regarding my experience with pricing, setup costs, and licensing for Make, I would add that they need to provide a dark mode because the UI is in light mode. I remember that when I was working late at night, it was feeling irritating to me.

Before choosing Make, I would have gone with N8N.

I will probably advise others looking into using Make that it is easy to start and explore automations because when I started, I also found it straightforward. I would rate this review an eight out of ten overall.

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.