## Why Your Business Needs a Chatbot

As the competition has intensified nowadays it becomes significant for companies to work harder and level up the services, they offer to customers goal will be to brand, secure, and sustain customer loyalty. Chatbots are a unique and progressive tool for companies, especially in the current fast and digital world. They are an instrument to satisfy all these needs and business development.

There is great potential for the size and growth of the market of chatbots in the future years. Therefore, if you need to focus on your clients, offer each of them an individual treatment, be helpful and reliable, or even draw the attention of some potential consumers, your enterprise will require a chatbot in the future.

## Save Time and Money

![Image by redgreystock on FreePik](img/flat-woman-chatting-with-chatbot-communicating-ai-robot-assistant_88138-959.jpg "Image by redgreystock on FreePik")

Image by redgreystock on FreePik\
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Today, chatbots are truly effective and can provide great assistance in managing time and resources for companies. Not only the large volume of inquiries can be answered in less time but the quality of the services provided remains high.

Though their use implies a certain level of investment, chatbots are becoming increasingly inexpensive. Compared to an employee, their cost is relatively low since you have to buy or provide them with a salary, train them, buy equipment and so on. Second, there will be no more human mistakes which can be quite expensive.

## Expand Your Business

It is a way of integrating and enabling your business to attend to more customers‘ queries as compared to in the past. This means you can draw their attention towards your products as well as improve their satisfaction levels with our services. It is not only that you can write back to your clients 24/7 but you can also handle numerous messages at once.

## Build Trust with Customers

Chatbots help you in a way that you can offer your customers with 24/7 instant responses to their inquiries. This makes them loyal and trusting since they feel that they are getting something provided by a firm that is receptive to realizing their needs. Reducing calls to such inquiries, you give your employees more time and opportunities to do their job more effectively and concentrate on more important situations.

## Strengthen Your Brand Authority

The widely spread use of chatbots proves that you are using modern solutions and caring about your clients. This enhances your brand image and makes you an informed company embraced by technology in all its operations.

## Increase Sales

Through the assistance of chatbots, users are able to generate leads, find recommended products, and even carry out the transaction process. They can enhance your sales and conversion by offering custom assistance and instant answers due to the high level of interaction provided by chatbot applications.

## Implement in Any Industry

![Image by pch.vector on FreePik](img/modern-cute-chatbot-different-poses-flat-set_74855-15475.jpg "Image by pch.vector on FreePik")

Image by pch.vector on FreePik\
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It would be pertinent to also know that chatbots are very flexible when utilized in an organization hence can be implemented in different organizations ranging from retail and e-commerce to health and banking industries. Whether it is in the service sector, retail, manufacturing, or financial sector, a chatbot can help to automate processes and enhance customer engagements.

## Attract More Potential Clients

Through a modern and efficient approach that involves using a chatbot to deal with your customers, you are likely to attract more potential customers than you could anticipate by using the traditional and conventional methods that are used by your competitors.

The fundamental importance of organization to engage chatbots in the modern business world that is full of changes can be stated as follows.

## Conclusion

When it comes to the benefits of implementing a chatbot, the advantages that can be gained are evident: From minimal costs and time consumption to increased brand credibility and sales figures. The use of chatbots is advantageous to the business since it allows for customer support service at any time, boosting customer relations, market prospects, and ensuring the accomplishment of organizational tasks effectively.

Furthermore, the usefulness of chatbots can be easily implemented and applied across numerous fields as an efficient tool for businesses, as well as enhancing their performance and providing only the best solutions according to the specific characteristics of the company.

The fact that traditional customer relations is one of the primary areas that are affected by the advent of chatbots, means that, very soon, businesses that are too conservative, to incorporate the new way of doing things may soon be left behind. It is crucial to remember that businesses must continually adapt to consumers’ expectations of digital solutions.

Feeling overwhelmed by the demands of running your business? Enter the world of chatbots – intelligent, conversational assistants that are poised to become your company's new best friend!

The Key to Enhance Customer Experience and Business Profits with Chatbots

## Introduction:

Meta has made a milestone breakthrough it will present as its next generation large language model: a state-of-the-art open-source tool – Llama 3. This year, Meta has declared officially the start of a new phase. In this phase, they will be using the latest AI technology that is meant to empower both individuals and businesses of all kinds.

## Meta AI: An Admirable Quest to Personalize Your Everyday Life 

Lying at the core of this development Meta AI, a powerful and competent AI assistant, is made from the basis of Llama 3 technology, Meta AI, powered by Artificial Intelligence, is your constant companion. It allows you to increase your intelligence and make your life easy, and the interface is adaptable, and it works across all Meta’s apps.

Whether it is a dinner menu from the food products you have in your fridge, or seeking for the answers for an exam to come, or looking for an inspiration for your creative art, AI is there ready to assist you. Because of its impressive features, this AI assistant can come up with the band band album art, offer decor ideas for your apartment or even generate GIF animations – just name what do you need.

## Llama 3: Shoe Horn for or Release Image Depicting Rising of Bar for Open-Source LLMs. 

![Image from frimufilms](img/llama-3-shoe-horn-for-or-release-image-depicting-rising-of-bar-for-open-source-llms.jpg "Image from frimufilms")

Image from frimufilms\
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Meta's initiative on Llama3 lies at the heart of the open and collaborative AI ecosystem, which has been at the core of its developmental drive. Through this official transfer of the leading-edge models to a global community, Meta will set the stage for a spiraling catapult of next-gen breakthroughs: a blizzard of applications and tools for developers, a storm of iterative advancements in model evaluations, generation, and optimization.

State-of-the-Art Performance Llama 3 is the golden egg of all LLMs, demonstrating an exceptional level of performance on 8B and 70B parameter scenarios. Meta's model, on the other hand, is trained in advance and then via post-training technique, and it is capable of outperforming other solutions that are available in the industry, along with the demonstrated ability to improve reasoning, high performance when generating code, as well as superior instruction following.

Innovative Architecture and the Develoment of Training Approach Mane of the model challenging issues, the heart of Llama 3's success lies with its novel model architecture design and training. In spite of involving the classic decoder-only transformer architecture Meta still introduces substantial advancements illustrated by utilizing a particularly large 128K vocabulary tokenizer for more efficient encoder and training as well as by employing GQA for higher inference efficiency of the process.

On top of that, Llama 3 has been trained on a dataset (including 15T tokens) that is way too large to be imagined, thus it is made up of more than 50% of publicly available data sources, most of which is the high quality non-English multilingual data. Shengli is a super fast filtering pipeline and tough incubator. As a result, technical scientists using Llama 3 efficiently and effectively will achieve a wide range of objectives on different subjects from trivia questions, stem subjects to computer programming and historical knowledge.

## Scale-Up: Pretraining Enhanced and Instruction Fine-Tuning Modality 

Meta's AI limit expansion by Scale Project is well demonstrated as Llama 3. Through conducting meticulous scaling laws, having downstream benchmark evaluations, Meta can be confident in predicting the performance of the largest models on code generation and such other tasks before the actual training takes place. Consequently, such approach provides a strong performance in complex situations where a higher level of cognition is needed.

Furthermore, Meta has recognized the progress in the field of best practice fine-tuning (SFT) by combining SFT, rejection sampling, PPO, and DPO. Meta has done that by designing numerous prompts differently and optimizing the human preference ranking. Consequently, Llama 3 is able to learn to choose correct reasoning traces and produce truthful solutions.

## Building with Llama 3: 

Enhancement of developer's power and guarantee of responsible usage of it. Meta's ambition with Llama 3 is to achieve more than frameworks; it convinces experts to boost their actions and utilize optimal way of utilizing the model's potential. For this purpose, the company has implemented new trust and safety tools, for example, Llama Guard 2, CyberSec Eval 2 and the cutting-edge Code Shield, a safeguard protecting from insecure code that came out of LLMs inference cycle.

Meta has also been partnered with torchtune, which created pyTorch-native library to simplify the process of building, fine-tuning and experimenting in the style of large language models. The library is compatible with well-known environments, including Hugging Face, Weights and Biases, and EleutherAI, also including delagation for Executorch to run inference on mobile and edge devices.

## A System Level Approach: An Ethic System for AI. 

![Image from rawpixel.com](img/a-system-level-approach-an-ethic-system-for-ai..jpg "Image from rawpixel.com")

Image from rawpixel.com\
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Also as MA recognizes the role of responsible AI in AI construct, it has taken a holistic approach to ensure secure and ethical use of Llama 3 technology. Hence, it is conceived here in the models that Llama will serve as the basic parts of the entire system. And with this, developers can now easily make the systems catering to their areas of expertise while meeting the industry-level standards.

Instruction fine-tuning plaes a critical part in the security of Llama 3 models by fine-tuneing greatly. Meta makes efforts which are really tough to secure those technologies and other critical areas by human experts and automated method such as red-teaming which helps to assess and mitigate the risks related to misuse, chemical, biological, cybersecurity and more.

Moreover, Meta has revised the Responsible Use Guide (RUG) presenting a whole new foundation for the unrefined LLM use. This guide focus on the importance of categorization and distribution of propaganda, vigilance with regard to content guidelines and cloud providers AIs and the other content moderation tools.

## Deploying Llama 3 at Scale: 

They aggravate the problem of overexploitation and elevated consumption, due to harvesting to fulfill demand once this resources become easily available and efficient. Llama 3 AI democratization is of the same Standard with the other Meta vision of letting the tool used by the people without expense and low-cost deployment challenges. This outstanding model is going to be available on all main delivery platforms that include the cloud providers and API providers among others in the coming days making it actually ubiquitous.

It was revealed that the new Llama 3's tokenising system was more efficient than the previous generation, Llama 2, resulting in a token reduction of maximum 15%. Besides that, GQA inclusion in 8B and 70B attentions has been instrumental in achievement of the similar inference efficiency as the Llama 2 7B one, in spite of the increased model size.

Meta is able to provide an extensive collection of source code open-source for developers with its support in order to facilitate Llama 3 adoption rate. Rather than just a collection, it is neatly called "Llama Recipes. " In this, the developers are provided with examples and guidance on things like fine-tuning, deployment, model evaluation and so on.

## The Future of Llama 3: Continuous Innovation and Advanced Technologies in the Aircraft Manufacturing Market 

![Image from upklyak](img/the-future-of-llama-3-continuous-innovation-and-advanced-technologies-in-the-aircraft-manufacturing-market.jpg "Image from upklyak")

Image from upklyak\
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Even 8B and 70B Llama 3 models are the first steps in the Meta project. However, this project is not about releasing the technology - it's only the beginning of realizing this revolutionary AI technology. During the upcoming several months the company will be taking its prowess to the next level by launching a variety of new models with breath-taking capabilities like multimodality, multilingual conversational abilities, significantly longer context windows and much stronger overall performance.

To give an insight into what’s in store, Meta Corporation has revealed screenshots of its biggest LLM model; but, still there are some areas where the model is in the process of training and therefore currently excels in other areas. These abilities may not be available even in the models released today, but they set them as a stage for the future effort to explore the high level of capabilities that AI is able to reach.

Obviously, Meta features as one of the major actors in the open AI ecosystem, with the company working towards open development of AI things, responsible release practices and rapid adaptation in the market. Spreading the community-first approach, Meta plans to transfer the know-how of Llama 3 to developers, researchers, and enthusiasts, launching the community to search for new horizons which this innovative technology has opened for the society.

## Conclusion: 

The debut of Llama 3 AI by Meta and also the adding of Meta AI assistant are definitely calling stages in artificial intelligence theme. The next breakthrough in AI is aimed at providing its users with unrivalled performance, highly advanced architecture and a strong responsible development which will ultimately bring about an art form of the future that will let us access and utilize new layers of productivity, creativity and intellectual exploration.

As Meta works towards making Llama 3 even more advanced and feature rich, the horizons have possibly the widest and most astonishing landscape. AI language models are no longer just a simulation of the human language. Instead, they continuously change and improve in real-time to form a seamless communication platform in any language. AI technology will move from now simple multilingual communication to ground-breaking multimodal experience that will reshape our understanding of capabilities. This will create a future in which human intelligence can merge with machine intelligence to produce fantastic achievements.

Together with Meta AI use its innovative Llama 3 model based on AI technologies to explore with your own eyes the contributions of this revolutionary approach to the future.

Hey there, AI enthusiasts! Get ready to be amazed by Meta's latest creation – Llama 3, a next-generation AI model that's about to change the way you interact with technology.

Everything You Need to Know About Meta AI Assistant: Major AI model, Llama 3, has arrived

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## The Goal

How about analyzing, which Collaboration Software Tool has the best sentiment (most mentiones with positive sentiment)?\
We’ve analyzed the mentions all over the web for a month, to check which of the following tools is used in the most positive, and negative contexts:

* [Jira](https://www.atlassian.com/software/jira)
* [Azure DevOps](https://azure.microsoft.com/en-us/products/devops/)
* [ServiceNow](https://www.servicenow.com/)
* [Asana](https://asana.com/)
* [Monday.com](https://Monday.com/)
* [ClickUp](https://clickup.com/)
* [Zendesk](https://www.zendesk.com/)

*Disclaimer: It’s not a professional research, done with sentiment analysis professionals, rather an analysis, an exercise, so some some small mistakes might have been made. We did our best to avoid them, by deleting all the noise (f.e. by setting out dedicated filters, improving the formulas from day to day based on the results we saw). But there is always a possibility, that we skipped something.  So take the results lightly. If the community will like it, we’ll prepare the next editions, trying to be better, and better.*

> There are a lot of rankings about software, G2, Capterra, Gartner, and probably many others. Most of them are focused on features, some on reviews, others on income and market share. But… none of them are about emotions, the sentiment.\
> *Jacek Wizmur, Co-Founder of [Getint.io](https://getint.io/)*

In a very competitive market, most of the available tools are very similar in terms of core functionalities.

So… what differentiates them?\
What makes people choose one over the other?

`UX? Is it really?`\
`Performance? Probably.`\
`Completeness? Maybe.`\
`Customization possibilities? Could be.`\
`Deployment option (SaaS vs OnPremise)? For enterprises, it’s one of the factors, sure.`\
`Pricing? At some point, yes.`

But… In the end, all the decisions are made by humans. It’s not B2B or B2C – it’s B2H (Business to Human). In the era of social media, and reviews (Capterra, Clutch, etc.) emotions and buzz are becoming more and more a decisive factor. Additionally, people want to work with a tool that has this positive vibe.

As getint.io, we are a platform that helps people integrate software (f.e. Jira – Jira, Jira – Azure DevOps, Asana – Azure DevOps, ServiceNow- ServiceNow, and so on), or migrate from one software to the other (f.e Monday to Jira). For us, there is no one mighty, go-to software that always is the best. We’re not biased. The practice taught us, that each is best for some scenarios, and the main goal is the Customer’s satisfaction.\
If it works, it’s good.

We did not want to prepare a report to state that one software is better than another, or more liked than the other. We wanted to see, which drives the conversation in the most positive, or negative context. In addition to that, we wanted to check the volume of mentions all over the web, to see which seems to be the most popular tool.

## A bit of history

What may affect the number of mentions, is the fact of how long each tool is on the market – how much time it had to build a customer base, willing to talk about a tool.

Let’s take a quick look.\
**Jira**: 2002\
**Azure DevOps**: 2018 (current version, its lineage can be traced back to Visual Studio Team System which was launched in 2006)\
**Monday.com**: 2012\
**ClickUp**: 2017\
**ServiceNow**: 2003\
**Zendesk**: 2007\
**Asana**: 2008

Jira is the oldest tool, it was the first to make the way for others. ServiceNow was launched just a year later. The most recent ones are ClickUp, and Monday.com – they could use the lessons learned from their predecessors.

## How we did it (**the Collaboration Software Tools, Sentiment Analysis report)**

Getint.io team was collecting data on Jira, Azure DevOps (including ADO keyword), ServiceNow (including keywords like “snow platform”, and “now platform”), Monday.com, Asana, ClickUp, and Zendesk for more than a month, but for this analysis, we will take the dates from 27.01 to 27.02.2022.

This report was possible thanks to our friends at [Brand24](https://brand24.com/?utm_source=Getint.io&utm_medium=blogpost&utm_campaign=BR24_Getint_SentimentAnalysis), the Social Media Monitoring tool, which was recognized as the best in business by f.e. Sujan Patel. The tool has great reviews all over the web (Capterra, G2, Software Advice). Brand24 was featured in TechCrunch, Entrepreneur, AdWeek, and Forbes.\
\
What does Brand24 do? The tool is collecting mentions about specified keywords, in blogs, news channels, social media (mostly Twitter, collecting the data from LinkedIn is not possible for now, and collecting data from Facebook, and Instagram is challenging, and limited only to the public mentions). Thanks to that, a brand can see what people are saying about it and can join the conversation.

We were collecting data based on keywords, topics, hashtags, and @mentions across blogs, news sites, and social networks (mostly Twitter). We analyzed more than 65,100 mentions concerning these Collaboration Software Tools to see, which have the most positive, and the most negative sentiment.

> I have to say, it wasn’t as easy, as I thought.

We had to make a lot of work to filter out the web mentions – it turned out that f.e. “Jira” is not that unique keyword, it means “wait”, and “Waxaa jira” means “there is” in some African languages (f.e. Hausa). What’s more “la jira con” means “the tour with” in Spanish. There are also a lot of Twitter users using “jira” in their username. 

On the other hand, “Asana” is a yoga position, and most of the mentions were about yoga, not the tool. Things were easier with “ServiceNow”, or “Azure DevOps” where mentions were usually about the software we wanted to analyze. In short, we needed to delete a lot of the mentions to keep the data as clean as possible.

Since it was challenging to make sure it’s done 100% correctly, I’ll present all of the data, but I’ll analyze only the ones from the following countries: United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Switzerland, Sweden, and Ukraine.

Here is an example how the data in Brand24 look like:

![clickup-infogr-countrires](https://getint.io/wp-content/uploads/2022/03/clickup-infogr-countrires.png "clickup-infogr-countrires")

## [Brand24 Sentiment Analysis](https://getint.io/collaboration-software-tools-sentiment-analysis-report/#:~:text=Brand24%20Sentiment%20Analysis)

As Tom from Brand24 writes:

> “Sentiment analysis, also known as opinion mining, or emotion AI, boils down to one thing: It’s the process of analyzing online pieces of writing to determine the emotional tone they carry, whether they’re positive, negative, or neutral.”

A sentiment analysis system for text analysis combines natural language processing (NLP) and machine learning techniques to assign weighted sentiment scores to the entities. The texts that make up the mentions are converted into numerical sequences that are much more understandable to the algorithm than pure text strings. The second neural network was based on embeddings, which we learned to distinguish between sentiments. The entire text in the found entry is analyzed.

### **First stage – Dictionary analysis.** 

Brand24 stores several thousand words related to emotions – both positive and negative. Each word has an assigned weight. In the first stage, Brand24 divides the content into sentences and analyzes each of them separately in terms of the presence of these words.

### **Stage two – Linguistic analysis.**

Implementation of language rules and context analysis is described in the first stage. The algorithm finding the word “good” should check if the word “morning” has not appeared before or after it, etc. The algorithm contains a lot of additional parameters, such as the distance of positive or negative words from the search subject. Only the qualified results (according to these parameters) are marked as positive or negative.

**So in this analysis/report, we are not stating, that Jira is better than Asana, or the other way around. We analyze the emotional tone of the posts of people writing them.**

## **TL: DR**

### **The most popular: Jira**

Undoubtedly Jira is the most popular Collaboration Software Tool. Almost 30% of all collected mentiones, were about Jira.

### **Most loved: ClickUp**

46% positive mentiones make ClickUp the most loved tool, second Asana has two times fewer positive mentiones. ClickUp has what it takes to make people love it.

### **The Controversial One: Jira**

Jira had 20.55% of negative mentiones which is the worst result, but… being the leader isn’t easy. There is a saying that “It doesn’t matter what they say about you, as long as they say it” or “there is no such thing as bad publicity”. 

## **Collaboration Software Tools, Sentiment Analysis Ranking**

### `The most-liked according to our sentiment analysis is….`

![Collaboration Software Tools, Sentiment Analysis: Summary](https://getint.io/wp-content/uploads/2022/04/Blog-post-summary.png "Collaboration Software Tools, Sentiment Analysis: Summary")

*\*Only for the following countries were taken into consideration: United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia,  Slovenia, Switzerland, Sweden, and Ukraine*

Now let’s dive more into details. Who is the most liked, and who has the most negative related mentiones? How many mentiones were there in total? Here is more in-depth comparison (again only some countries are taken into account here).

![Collaboration Software Tools, Sentiment Analysis: Selected countries](https://getint.io/wp-content/uploads/2022/04/Blog-post-1.png "Collaboration Software Tools, Sentiment Analysis: Selected countries")

Some of you may still wonder, how all the data looked like (even though they are less relevant). For those, here is the table below. As you can see, the volumes are much bigger. 

![Collaboration Software Tools, Sentiment Analysis Details (all countries)](https://getint.io/wp-content/uploads/2022/04/Blog-post-2.png "Collaboration Software Tools, Sentiment Analysis Details (all countries)")

### **ClickUp – the most positive mentiones**

The emotional tone of mentiones related to ClickUp was very positive: 46% when analyzing only some countries *(United States, Spain, United Kingdom, Germany, France, Argentina, Australia, Austria, Belgium, Brazil, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, Greece, Iceland, Ireland, Israel, Italy, Lithuania, Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Slovenia, Switzerland, Sweden, and Ukraine – we did it because we weren’t 100% sure we filtered out all the noise from Asian, and African countries, where the keywords we use for analysis also mean totally different things – as described in the first part of the blogpost)*, and 38% when taking into account all of them. That’s a very good result. At the same time, the volume of mentiones was one of the lowest (3rd from the bottom). 

ClickUp is a relatively fresh tool (founded just 5 years ago), gaining market share, generating positive vibes around the product. We will see how it evolves.

### **Jira – the most popular one**

The biggest volume of mentiones was about Atlassian’s Jira. It’s the product that generated a lot of comments – both good and bad. About 17% of mentiones had a positive sentiment, while about 20% negative. What’s worth mentioning, is the fact that the sentiment could be negative, while it wasn’t because of the Jira itself (f.e. “I had such a bad morning, I’m late for work, and I feel terrible. Time to start my day with the Jira board”). So we can say that Jira is generating emotions 🙂 45% of all mentiones had some emotional sentiment, different that neutral.

### **Azure DevOps – the technical one**

Azure DevOps was last in our ranking, with only 16,89% of positive mentiones, and 8,45% of negative. The volume was very low, just 438 (and 5 298 globally). The possible reason? While all those tools are helping teams collaborate, they are addressing different target groups. ClickUp, Monday.com, Asana are used by all departments and are often preferred by the business side (Marketing, Product Owners, Sales). Those are the groups that are more active on social media, than developers, who are targeted by more technical Azure DevOps.

### **ServiceNow – positive/neutral**

ServiceNow is a strong player somewhere in the middle. Most of the mentiones with ServiceNow brand were neutral, 17,11% positive, and just slightly more than 2% with the negative sentiment. ServiceNow is a very expensive tool, targeting enterprises, and still, the number of mentions was second biggest, just after Jira. 

### **Asana – always second**

Second best, and second… worst. 33% of mentions with the Asana brand, had any sentiment, out of which 23,93% were positive, and 9,48% were negative. In terms of volume, Asana was 4th after Jira, ServiceNow, and Zendesk. 

### **Monday.com**

3rd place on the podium of the most positive mentiones. 4th in the negative ones, and also 4th when analyzing the volume of mentiones. 

### **Zendesk – the… stock one?**

This was a tough one – there were a lot of mentiones featuring Zendesk in February, but… just some of them were actually about the product. There was a big volume of mentiones related to Zendesk’s stocks. 

### **Most Twitter mentiones**

The most mentiones on Twitter were regarding Jira, then ServiceNow, Zendesk, Asana, ClickUp, Azure DevOps, and Monday.com. 

[Check out our integrations here](https://getint.io/integrations/)😎

Discover which collaboration software tool generates the most positive sentiment and popularity on social media, as analyzed by Getint.io using Brand24's sentiment analysis. See how Jira, Azure DevOps, ServiceNow, Asana, Monday.com, ClickUp, and Zendesk fare in terms of emotional tone and volume of mentions in selected countries. Find out why ClickUp stands out as the most loved tool, while Jira remains the most popular but also controversial one.

Collaboration Software Tools, Sentiment Analysis Report

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