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Things to Consider Before Leveraging ChatBots for Your Business!

By Guest Contributor on March 29, 2019

Today’s smart world is filled with virtual assistants everywhere. Be it an app or a chatbot, we have this digital support wherever we go and with whatever we experience. Chatbots are a huge hit in the present day’s digital marketing. Offering a plethora of advantages, Chatbots are often viewed as a great source for building trust in customers.

If you are someone who’s planning to increase your online sales, then building a chatbot for your business is indeed the right choice. Even though you have a top-notch customer service team, you still need a chatbot for increasing efficiency in your business.

This is because we are living in a fast-paced world where consumers expect an instant reply to their queries. When they are asking a question or an inquiry via email, they want immediate responses. They even evaluate and review a company based on these swift replies. It is evident that chatbots are mandatory for retaining and increasing customer base in business.

Chatbots can efficiently help you to increase your customer traction through the following ways such as,

Faster Complaint Resolution

A great business is all about satisfying customers’ needs and resolving their queries immediately. Providing support to customers’ queries with a chatbot is a simple yet powerful cost-effective solution.

With advancement in AI, chatbots can now even detect human feelings and emotions such as anger, irritation, joy, and satisfaction. If a chatbot can sense any such emotions as mentioned above, it is programmed to have a seamless interaction to solve queries at the earliest.

Saves Money and Time

It has been found in a survey that, about 265 billion customer requests are made in a year and it costs around a staggering $1.3 trillion for servicing them. A Chatbot is designed in such a way that it doesn’t require any financial resource or workforce. As per a report from Chatbot magazine, it has been found that employing a chatbot can help people to save upto 30% profit in their business.

Unlike humans, you don’t need to provide sick leave or medical coverage to chatbots and you don’t have to undergo the trouble of recruiting the right people for your business.  Chatbots can attend to customer queries 24/7 and there is no limit for geographical locations as well.

Instant Customer Gratification

Unlike humans who may get distracted by emotions, chatbots are programmed and they follow rules without any bewilderment. This results in perfection in work and improves the efficacy in business operations.

Chatbots are extremely good at comparing, analysing and providing relevant product details, thus helping customers to avoid the voluminous search for products. Chatbots can even address multiple users’ needs in real time.

Building a Chatbot

Now you know how Chatbots are disrupting the future of marketing with their countless advantages. Are you interested in building a chatbot for your business? If so, then these are the things you should consider while developing a flawless chatbot for your business.

Know Your Audience/ Customer First!

Even Though it’s been a decade, Chatbots are still at their infancy stage of AI. We can’t say that chatbots can be utilised for all sorts of businesses. If you’re starting a business with a small audience, you can very well go with live chat applications.

Generally in a business with a limited audience, people prefer to hear response from a human rather than a machine. The primary key is to know your audience and customers before designing a chatbot.

Examine the Goals in Your Business

A chatbot should be useful in solving actual problems. For that, you should have knowledge of your customers’ likes and dislikes. You have to stand in your customers’ shoes literally, then only you can get a better understanding of how chatbots can enhance your business journey of success. For instance, how you’re planning to use the chatbot? Is it for answering basic queries? Or Helping your customers in choosing and buying products? And so on.

Human Supervision Should be there!

We live in a world with technical wonders and advancements, still, human supervision is needed as a deciding authority. Therefore in your business, you must always make sure to include a human’s support besides a chatbot, for help at times of complications or questions. If not, it may result in losing leads in business.

Consistency in optimization

Chatbots should be evaluated and tracked regularly. You should check whether the links are working properly or not. You should try asking weird phrases and check how your bots are responding.

It is clear that the rise of chatbots is here to stay forever and this snowballing technology shows no signs of a slowdown. Some enterprises encounter problems in devising chatbots for their business operations. This is because the technology behind developing a chatbot is complex and it requires professional developers’ guidance.

What’s so intriguing about Customized Bots?

Getting a customized bot from a reputed company will benefit you in so many ways such as

  • It is affordable
  • A fair level of customization can be deployed
  • Faster and smoother launch

It is true that already existing platforms are less expensive and easy to customize when compared to developing a new one from the ground-up.

If you’re planning to launch a customized bot for your business, then you should get it done with the professionals in the field.

Summing Up

Although Chatbots seem to be a great fit for marketing, you still have to decide with due diligence whether it is suitable for your business or not. You should properly weigh the assets and liabilities in joining the future race with chatbots.

This article is contributed by Brenda Darlene, Content writer at Appdupe– clone app development company.

7 Powerful Ways AI Can Be the Key to An Improved Customer Shopping Experience

By Guest Contributor on March 27, 2019

In the modern world, consumers live in an Omnichannel globe. But many companies still force clients on appointment course that are abrupt in legacy and instantaneously experience rationalized. However, this problem is solved by Artificial Intelligence (AI).

It is one of the latest techniques that are used to convert a large number of retail data into actionable highlights that help management to make a decision fast. It helps customers to easily find the latest fashions that look attractive and are within their budget.

Artificial intelligence (AI) can be effectively engaged to offer an intellectual, suitable and knowledgeable customer practice at any point besides the client journey. This will result in re-imagined customer experiences and end-to-end customer journeys that are included and more individual so that they experience more likely to shoppers.

Call for Artificial Intelligence in CX

Customer Experience is considered as a competitive driver of development while having success and greatest source of risk when gets fails in business. Data insights are one of the main tools used in the improvement of CX.

Data sets of CX are disorganized and customer reaction towards this is confused. The rules are not properly clear and success criteria are indefinite. Therefore, CX is a dreadful dataset for an AI developer.

Simultaneously, this complication is specifically the cause why AI can unleash so much importance in CX.

Conveying a logical experience from corner to corner in all project touch points requires verdict patterns across an overpowering number of data points. This is chief clump viewable for AI.

Let us have a look at seven powerful ways that benefits in improving Customer Shopping Experience

1. Virtual Assistants for Automated Customer Service

Virtual assistants are very commonly used in providing customer service. In addition to that chatbots, bots or digital assistants help to interact directly with clients and provide knowledge, solve simple issues and process support inquiries. They vary in technical complexity and range from simple scripted experience to leveraging Natural Language processing (NLP) as well as understanding technologies.

When the customer request is complex, bots are unable to handle potential customer request in the market. Therefore, most companies choose a cooperative model in which human agents, as well as bots, work in tandem.

2. Helps to recognize outstanding targets viewpoints

Latest Artificial Intelligence (AI) technology supports e-commerce businesses with suitable intelligence necessary, to resolve their business confronts such as lead generation. Marketing businesses like Mintigo offer AI solutions for CRM, marketing and sales system.

With the help of Mintigo software, you will get Getty images with productively generated important recent leads. These images are made from confining data that shows business websites having featuring images from Getty.

Moreover, it will help you to identify best quality scenarios and provides sales team an aggressive benefit to winning new business. But without the use of Machine learning and AI, you will not able to use as large-scale data.

3. Agent Facing Bots for the quicker Human Service

Chatbots are not just used for enraged shoppers. But it can also be used to organize virtual assistants for providing support to your team. You can provide quick reply templates, performing earlier searches of inner knowledge bases or support for other operating steps.

However, these bots do not interact directly with customers but can significantly improve customer experience by lessening the average resolution time for your customer service team. Microsoft AI proposes agent-facing bots as a branch of its Dynamics 365 solution. in-house departments of Microsoft such as HP and Macy’s, are previously using AI technology to advance the overall client happiness and to hold more applications in a short period of time.

4. Chatbots for Conversational Commerce

Virtual agents are also helpful in sales and marketing.They help to change laid-back browsers into paying buyers. There are many brands like Facebook Messenger, Amazon Echo, or other interactive platforms that have to organize chat- or voice-based retail experiences on.

For instance, Domino’s chatbots receive your pizza order and conditionally you type “pizza” in Facebook Messenger; although it’s Alexa proficiency even follow your order when asked! One More detailed illustration comprises eBay’s ShopBot, which will find definite items if you give a name or upload a photo, or you can talk to Hipmunkon Facebook Messenger, Slack, or Skype while scheduling and booking your subsequent trip.

5. Sentiment Analysis for your client approaching

How do purchasers, in reality, think about your trademark and your products? Sentiment analysis helps to evaluate textual data like emails, social media posts, review responses or chats and call logs, for exciting information.

However, sentiment analysis has been used for decades, but AI-powered methods can now change understated gradations in textual data into precise insights about a shopper’s feeling, requirements, and requests.

You will easily get to know when customers are having a definite problem with your product that will help you to take more paying attention action in an appropriate way.For illustration, IBM Watson’s Tone Analyzer can parse from side to side online customer opinion and find out the common attitude of users evaluating a product.

6. Recommender Systems for Cross Selling& Up Selling

Recommender systems help to personalize product position and seek results for every end user. Recommending products or content that consumers are more probable to buy gives the buyer an enhanced sales experience while lashing more income for businesses in the course of cross-selling and up-selling.

There are a number of algorithms that presently influence the mainstream of these systems. Let us discuss that-

– Collaborative filtering

It depends on the supposition that public with same uniqueness and interests are more likely to prefer the same items. This approach was measured by state-of-the-art in 2009.

However, it is most commonly used in business situations. It needs some information about a user before it can make good suggestions, which is a severe drawback for newfangled businesses.

– Clustering

These algorithms groups are used together users who have the same interests. This approach works sound when business requires enough customer information.

Moreover, it is used when there is a first step for recommender systems when shared filtering can’t be functional unswervingly due to the complete number of users or items.

–  Deep learning

This type of algorithm uses neural networks to help in the sorting of things and then provides the ranking according to a history of users and contextual circumstances. Deep neural networks are presently the state-of-the-art loom for recommender systems.

7.     Emotion AI for increasing customer satisfaction

Emotion AI or affective computing is used for providing training to machines so that they can easily distinguish, understand, and react to human emotion in the form of text, voice, facial expressions, or body language.

For illustration envision that a client has been chatting with a customer service representative who is not able to understand the problem, then emotion AI would on time shoot up the customer to an administrator based on the disappointment that it noticed through word choice or pitch.  In addition to that, it can also benefit physical sellers.

A retail technology called Cloverleaf has integrated Affectiva’s Emotion AI technology into its shelf Point resolution. It helps to demonstrate digital advertising in high-definition LCD display strips that are enveloped around shelf faces in a store. These help to detain customer engagement and sentiment data at the time of buy.

Key Takeaways

Although the term artificial means a little depressing or dehumanized, artificial intelligence (AI) permits businesses to offer an additional personalized experience for their clients.

It helps to revolve many-siloed, multi-channel projects into particular personas that in turn help to memorize, recognize, and react to their customers’ success and setbacks in a significant way.

This article is contributed by Ankit Patel, Project/Marketing Manager at XongoLab Technologies LLP – mobile apps development services company

Understanding the Impact of Machine Learning on Business Performance

By Guest Contributor on March 25, 2019

Machine learning is a robust technology that gives systems the ability to learn and optimize user experience without being explicitly programmed.

The advent of machine learning has significantly transformed the face of business marketing. Its ever-growing impact has made it evident that the future of marketing will encompass savvy marketers working together with machine learning-based automation entities to create tailored and effective business strategies.

The Expanding Force

Machine Learning focuses on identifying and interpreting both, structured and unstructured data and enables companies to use the gathered knowledge and insights to plan and build strategies. Knowing what the customers want and delivering the same is the only way to sustain in this highly competitive marketplace.

Machine learning assists companies to identify the customers’ changing demand and develop a plan to efficiently respond to these dynamic behaviours. Evidently, businesses across the globe are increasingly adopting ML technologies and obtaining its benefits.

Automated Data Visualization

90% of the world’s data was collected in the last two years. The potential to visualize relevant relationships between data not only helps companies make profitable decisions, but also boosts the credibility of their processes.

With advancements in machine learning, the business landscape can expect the invention of more user-centric data automated visualization platforms and widgets. This will allow real-time analysis and interpretation of data, thereby offering a wealth of valuable insights and increased productivity.

Content Management and Analysis

Ensuring a strong connection with the targeted audience is one of the constructive ways to generate brand loyalty, drive engagement, and build long lasting customer relationships.

With companies trying to engage in valuable conversation with their customers, machine learning plays a critical role in analyzing specific words, phrase, sentences, idioms, etc., that resonate with their audience members.

For instance, Pinterest processes 150 million images each month and it has leveraged ML to filter out content that aligns with the users’ needs, preferences, and behaviours. Evidently, machine learning is encouraging lexical analysis that allows marketers to customize their content to improve engagement.

Paving Way for Better Future Prospects

With the potentials it holds, machine learning is creating a serious momentum. It is the responsibility of company executives to ensure each member of the team understands the benefits of ML for the organization.

It is an innovative technology that helps the company become more productive, predictive, intelligent, and efficient.

And the advantages are not just restricted to the companies; machine learning is equally beneficial for employees as well. ML is in great demand in the market, therefore, acquiring a deep understanding and knowledge of ML can significantly boost career opportunities for a lot of job seekers in the market.

Obtaining a masters in machine learning can help them gain all the relevant and practical knowledge of this innovative technology, thereby providing a competitive edge in the market over their peers.

Machine Learning – Leading to the Future

Presently, we are heading towards a world where people and technology are working together to connect and market products and services in a more comprehensive, efficient, and personal manner than ever before.

By harnessing the powerful potentials of ML and helping the team incorporate it effectively, companies stand a chance to develop an influential position for themselves in the marketplace.

This article is contributed by Sid Rawat, Marketing Manager of TalentEdge – Advance Machine Learning Online Course Company.

How Cloud Computing Can Change Web App Development

By Guest Contributor on March 23, 2019

With the advancements in technology and with the increasing number of Web apps, the need to improve efficiency has increased. Developers are looking forward towards such tools that not only enable them to work efficiently but can also automate certain tasks. Automation at effective cost is becoming the need of the hour to tackle the ever-growing demand. With such a need in hand, cloud computing has gained appreciable popularity in recent years.

Before we dig deep into our central concept, let’s first understand what cloud computing is.

What is Cloud Computing?

According to Wikipedia:

“Cloud computing is shared pools of configurable computer system resources and higher-level services that can be rapidly provisioned with minimal management effort, often over the Internet.”

In simple words, cloud computing harnesses the power of computers connected over the Internet to do the computation. Cloud computing, in recent years, has shown great improvement. A number of vendors have come up with their platforms to provide cloud computing services.

With high competition in the market, cloud services are now available at budget-friendly rates with surprising uptime. With the increasing availability and reliability, corporates are moving most of their business process to the cloud. From development to marketing, cloud services are proving their benefits over conventional methods. Here we’ll discuss one such area, i.e., web application development.

What is a Web App?

A Web App is basically an application program that resides on remote servers and is accessed by users over the Internet, through a web browser. To access a web app, it is not necessary to download it, rather it can be accessed through the network.

As the trend for digitization is increasing, so is increasing for web application development that provides a direct connection between the clients and the hosts. Instant messaging services, online image editing, and online word processing are some of the examples of web apps that operate from remote servers. But what about those servers where they are installed? Are they manually set up or are provided by third-party vendors?

This is where the role of cloud-based services come into effect.

Cloud computing in web app development

For any web app development, you need to provide an environment which is usually a server-based application where the programmers can launch and test their code. Well, everybody knows that handling a server is not an easy job. One needs to constantly monitor it to eliminate any chance of issue creeping in. What if this task is outsourced to the cloud?

Many tech giants have already bid goodbye to the traditional methods of web app development. With the advent of cloud computing service providers like Amazon Web Services (AWS), Google Cloud Platform, Microsoft Azure, etc., the procedure for shifting to the cloud has simplified to a great extent. Now the programmers can focus properly on their work with the guarantee of the services that the cloud service providers provide. IT sector has seen astounding benefits out of this.

Benefits of cloud computing in web app development

Cloud computing is proving to be a boon to web app development sector. With the benefits of cloud computing, a number of problems of developers were solved and they can now outreach to a greater section of the market. Some worth benefits are outlined below:

  • Scalability

Scalability helps a software adapt to the market changes whether it be in terms of user handling capability or speedy hardware utilization. With cloud services, as and when required, the user handling capability of the app can be increased easily. To handle the increasing number of requests, more servers with the choice of better hardware configuration can be deployed.

  • Cost-effectiveness

When you set up traditional on-premise data centers to connect to remote servers, you need an appreciable upfront investment and a team to continuously monitor it. But with cloud service, there no such requirement. With a wide variety of options, you can choose the plan that suits your need and pay only for what you use.

  • Continuous deployment

With continuous deployment, developers can easily and quickly release new features in front of users. Tools like Amazon EC2 and GitHub allows teams to continuously deploy software without dependencies as there are redundant servers that can compensate at the time of failure. This helps companies flow with the market.

  • Immediate availability of resources

Cloud services provide you with lots of pre-stored resources and allow you to use them as and when required. Even in urgent cases, you have full support from the service provider. With this, you don’t have resources that lay unused and also you don’t need to care about wear and tear of the hardware being utilized.

  • Global Reach

As the cloud services are delivered through the Internet and are not limited to local scope, developers are able to connect to the global audience. This has another benefit that if a team consists of developers from different geographical locations, then each can work collaboratively with others. This enhances productivity as the web app will receive inputs from different developers from different locations thus making the app more versatile.

While cloud technology comes up with a number of advantages, its infrastructures draw more attention when sensitive data is to be shared.

Sometimes conditions like vendor lock-in period, compliance requirements, and extra transparency requirement while debugging may limit your choice. But, if your requirements pass out of some of the hurdles like these, then cloud computing has all the necessary capabilities to power your web app development process.

The modern business process demands more productivity with less resource utilization and cloud computing has the necessary potential for it.

This article is contributed by Shubhanshu Agrawal, Sr. Content Writer at Appventurez – mobile app development company .

How is Hadoop helping companies deal with Big Data challenges?

By Guest Contributor on March 21, 2019

Today’s world runs on data. Almost every rideshare application, food order app, retail or shopping site, and even all e-commerce sites require consumer data to provide an optimally satisfying customer experience. As every aspect of the web and applications are becoming experience-driven, every corporation and company are thinking about monetizing their data. Unfortunately, with the rise of mobile computing and multi-device access, gargantuan volumes of data keep flowing in from all directions. The traditional database architecture is no longer sufficient to hold enormous amounts of data or organize it appropriately.

Why is dealing with Big Data a significant challenge?

Big Data usually flow into a heterogeneous environment that data scientists typically refer to as a data lake. They are different from data warehouses. The traditional warehouses of data have a comparatively uniform architecture that is either wholly definite or rigid. Some companies define their data lakes as modern data warehouses, primarily since they use Hadoop. Hadoop makes data collection, storage, and management quite straightforward even for the small businesses that are new to the world of Big Data.

Here are the currently available technologies that deal with Big Data technologies –

  • Traditional RDBMS including SQL databases
  • NoSQL database systems
  • Hadoop and other massively parallel computing technology

What are SQL databases?

RDBMS or relational database management system has been the standard response to all data storage and collection challenges people have faced in the near past. However, SQL databases are usually appropriate for a definite volume of data that has defined structure. Relational databases have been losing popularity in recent times as the age of Big Data dawns upon us. Big Data has massive volume, and it flows in at a tremendous velocity. It is highly variable that a traditional RDBMS database cannot tackle. It is not the primary scalable solution that meets every need for Big Data.

What are NoSQL databases?

NoSQL databases are taking over the data management landscape thanks to the rise of Big Data. Nonetheless, the much popular and time-tested structures are not enough to either store or analyze the ever-evolving nature of Big Data. Database admins now require something dynamic yet robust to tackle the management and analytical problems the new generation of data throws their way.

Unlike traditional SQL technology, NoSQL is flexible, and it is highly scalable. Most NoSQL database leaves room for the DBA to define and redefine data types and database structures. NoSQL allows the database admin to trade off rigid structures for agility and speed. It is the ideal requirement for Big Data management where the primary necessity is speed and not accuracy. Some of the most significant data warehouses including Google and Amazon now leverage the power of NoSQL to manage their unmeasurable bulk of data. Due to its incredible scalability, the users can continue to add more hardware as the data continues to explode.

What is Hadoop?

On the other hand, the state-of-the-art technological solutions that are capable of handling Big Data include the likes of Hadoop. It is not a database. It is a software ecosystem or framework of multiple software programs that support parallel computing. It does enable certain NoSQL database types to store and collect Big Data, like the HBase. It allows the expansion of data across multiple servers with little to no redundancy.

What is the role of MapReduce in the Hadoop framework?

MapReduce is a stable computational model of the Hadoop ecosystem. It plays a critical role in the determination of the intensive data processes from the ecosystem and spreads the computation throughout thousands (potentially endless) of servers. DBAs refer to this as a Hadoop cluster. Hadoop has standardized models that make data management a breeze for new companies and long-time running corporations. It comes with inherent fault tolerance. The data processing enjoys protection against hardware failure. Therefore, in case of a node malfunction, the job automatically goes to another node to ensure that the distribution computing remains continuous. In short, no matter how massive your data-load is, Hadoop has the solution.

Most companies that use Hadoop enjoy high flexibility of data types and scalable storage options at a low cost. Thanks to remote database management services the maintenance and updating of Hadoop enabled NoSQL databases has become a lot easier than it used to be. Users no longer require the presence of on-site DBAs for the optimization of database performance. Off-site database administration services can take care of updating, managing, caching and maintaining complete databases from remote locations. To know more about remote database management.

What are the most prominent uses of Hadoop right now?

Data analytics and predictive analytics – Most corporations and SMBs use Hadoop for analytics purposes. When there is a massive volume of data that require analysis, Hadoop is the primary choice for data scientists. It has the ability to store and process multiple data types simultaneously. That makes Hadoop the perfect fit for Big Data analytics and predictive analytics. Big Data environments are highly heterogeneous, and that consists of various information in structured, semi-structured and unstructured forms. Whether it is social media posts, social networking activities, clickstream records or customer emails, Hadoop has the agility and potential to store and sort it all.

Customer analytics – As a result, most companies use Hadoop for customer analytics purposes exclusively. One of its top functions is to predict customer behavior including conversion rates and track consumer emotions. Analysis like these utilizes information from social media activities of individual users and responses to corporate or promotional emails. E-commerce companies, healthcare organizations, and insurers often use Hadoop for analyzing promotional offers, treatment opportunities, and policy pricing respectively.

Predictive maintenance – Several manufacturers are now leveraging Hadoop in the maintenance of operations to determine equipment failure as they are about to happen. They are running real-time analytics applications including Apache Spark and Apache Flink along with Hadoop for improving their accuracy during prediction. The emergence of Hadoop as a robust and reliable prediction analytics tool has enabled the detection of online fraud, and cybercrime. It has also improved aspects of website and user interface (UI) design by gauging signs of customer satisfaction.

Hadoop has made its mark in the data management realm by attracting prominent IT vendors including Hortonworks, MapR, Cloudera and AWS. The Hadoop framework is attracting users and vendors from all across the globe. Its popularity is soaring along with the increasing importance of Big Data.

This article is contributed by Jack Dsouja, noted data analyst at RemoteDBA.com

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