Chatbots are helping airlines communicate effectively with passengers and provide phenomenal experiences.

Virtual Assistants / Conversational Bots in Airline Industry Today

Virtual assistants help airlines improve their pilots’ productivity and efficiency by reducing repetitive tasks, such as changing radio channels, reading wind forecasts, and providing on-demand position information. Virtual assistants handle these repetitive tasks. Companies such as Garmin (USA) offer AI-enabled audio panels that are useful for pilots.

Airlines also use these assistants to improve customer service. For example – Virtual assistance with AI provides quick responses to simple questions (FAQs). These FAQs include flight status or services/offers (audio, video, Wi-Fi), reservations, baggage queries, seat availability, etc. This allows customer service representatives to attend to and respond to more critical questions than simple and recurring FAQs. These virtual assistants help passengers book tickets and plan trips, too. Almost all airlines have created apps to help customers across various travel-related tasks.

Conversational Bots in Customer Service and Retention:

Today, AI is helping airlines to optimize pricing strategies, raise customer satisfaction rates, customer retention & engagement, and improve the overall flight experience. Below is a list of potential AI use cases for the Airline industry:

Chatbot software and customer service automation: Kayak, a famous American travel booking agency, lets you plan your next trip directly from your Facebook Messenger app. The Chatbot understands simple questions and responds conversationally like human agents.

Conversational IVR: Enables calls for automation or semi-automation of the contact center’s processes, thereby increasing the agents’ efficiency.

According to Gartner, Advanced Virtual Assistants (AVA) are the next big step in today’s chatbots. AVAs are powered by natural language processing (NLP), generating conversational and intuitive sessions and semantic and deep learning techniques such as deep neural networks (DNNs).

Benefits of Conversational Bots in the Airline Industry:

AI chatbots are an innovative technological breakthrough that is gaining popularity worldwide. Userlike conducted a survey where 80% of the respondents confirmed that they had interacted with chatbots. Airlines are investing in chatbot development to address their critical operational and service-related issues. Below are some ways chatbots are making airlines smarter, better, and more efficient.

Improved customer service: Chatbots can handle customer inquiries 24/7 and provide real-time information in an emergency to the customer. At the same time, chatbots don’t have time zone and language barriers as they can be programmed to work according to your customer’s needs.

When customers have a chatbot that answers all their questions, it results in a better customer experience that strengthens the brand image.

Higher engagement: Chatbots can improve customer engagement by providing information, helping customers book airline tickets, fulfilling customer requests, and gathering all the information in one place. This engages the customer better than waiting a long time to contact an airline representative over the phone.

Revenue growth opportunities: Chatbots are increasingly evolving from customer support intermediaries to flexible solutions that can take advantage of sales opportunities. Airlines have increased conversion rates and sales by adding payment gateways, offers, and transaction capabilities to chatbots.

According to Juniper, 47% of consumers are open to using a chatbot to make a purchase, and chatbots will account for $112 billion in retail sales by 2023. This creates a tremendous opportunity to sell more in-flight services/other services to airlines.

Streamlined and integrated data access: Chatbots can collect all flight-related information and data and make it available on the platform that customers can access from anywhere and anytime. Chatbots can record all customer conversations and provide airlines with helpful information about their preferences, booking history, issues, etc. Optimized data access for end customers and airlines can make the industry more efficient.

Saves time and efforts: By integrating an omnichannel conversational bot, airlines can save time and effort handling customer inquiries. Because chatbots can continuously respond to simple and recurring requests 24/7, businesses can hire staff for more valuable tasks, activities, and issues. This saves time and energy and ultimately leads to efficiencies in customer service and engagement processes.

Economical query resolution solution for airlines: Developing a chatbot that works 24/7 is a much more cost-effective option for airlines than hiring and paying staff. Once set and implemented, chatbots can automate the request resolution process. This reduces the need to refer customer inquiries to a maintenance center, which reduces operational costs.

Conclusion

With the increasing investments by airlines in conversational AI, IGT Solutions has partnered with platform providers, such as Uniphore, and LivePerson, amongst others, that provide chatbot platforms along with intelligent insights and analytical capabilities, which IGT can further offer to their clients. These partnerships help IGT Solutions to create a base conversational platform for all existing and opportunistic clients and offer better and customized solutions. IGT has developed 12 different chatbots for a leading American Airline, improving customer satisfaction for the client. If you want similar results for your business, contact us today!

Author:

Apurva Sale is a Lead Business Consultant at IGT Solutions’ Intelligent Automation and Conversational Analytics Practice. She is an Analytics expert with 8 years of experience across Travel, Telecom and Retail domain. With a strong background of Business & Data Analytics, Apurva has extensively worked on elevating customer experience with Insights & sentiment analysis, Social Media Analysis & Insights. She can be reached at Apurva.sale@igtsolutions.azurewebsites.net

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Continuous refinement of technology has redefined and enabled the user to harness various benefits of digital transformation, on the other hand, it has also provided the same advancement to a hacker who has been sharpening hacking attempts and malware attacks.

In the year 2022, it has become prudent for individuals and companies to be well prepared for tackling ever increasing cyber threats and continue to fine-tune and upgrade security strategies and benchmarks.

One of the solutions is to timely invest in security testing but it would be important to know about the trends to expect this year.

Artificial Intelligence: The key use cases of artificial intelligence are seen in the fraud detection on financial portals and intrusion detection systems. It is very useful in analyzing the data and finding unusual patterns of cyber-attacks on the systems. Artificial intelligence by its core is capable of analyzing humongous amount of data from network traffic to assess possibility of cyber threat on the system.

Given the fact that hackers are trying to utilize machine learning methodologies to automate and implement malicious events in organizations, it is prudent for the organizations to enhance their cyber defense systems by harnessing the power of artificial intelligence.

Ransomware Threat: The year 2021 had seen a spike in ransomware attacks. The UK National Cyber Security Centre reported the number of ransomware attacks increased by three folds in the first quarter of 2021 compared to the whole of 2019. The various reasons attributed to these spikes are due to the increase in financial activities on digital platforms due to the pandemic, enhanced usage of e-commerce and enough controls not in place for employees working from home.

Many companies and governments are still using outdated technologies, processes, protocols, and procedures, which ultimately increases the vulnerability of getting attacked by ransomware. We have to fix these issues with proper budgeting and management alignment, in addition to other measures such as improved security, better monitoring and reporting.

Cloud Security: With the popularity of cloud implementation and moving organizational sensitive data to the cloud, it becomes very important to secure cloud infrastructure. Cloud though is very secure and has several layers of security from user management, network management, to secure key management. It has its own challenges in terms of security, as any security issues on cloud hosted applications will impact the authenticity, integrity and availability of the data.

One trend of year 2022 would be a possible growth in terms of cloud adaptation, it will also mark for newer ways of cyber-attacks on the cloud infrastructure.

Cybersecurity Talent Shortage: Cybersecurity talent is scarce in the market and there is no doubt about it.  The increased number of cyber-attacks in the year 2021 has further fueled the demand for trained cybersecurity professionals across the globe. It is unlikely that this gap will be filled in a timely manner, respite may come from artificial intelligence, where it will be used to detect malware in the network by analyzing a vast amount of data more quickly than humans, detecting issues such as phishing attacks, privilege escalations, and insider threats.

Internet of Things: Statista, a market research company, projects global spending of 1.1 Trillion USD by 2023 and consumer spending on smart home systems worldwide in the tune of 123 bn USD by 2021. The risk of cyberthreat is going to increase in the year 2022 with more proliferation of IoT devices. As we all are aware of the high vulnerability of IoT devices owing to different communication protocols, operating systems, integrations and lack of any standardization in space.

Conclusion

IGT with its Security Testing COE is well positioned to achieve shift-left of security testing and thereby finding security vulnerabilities earlier in the lifecycle, and working with all stakeholders to ensure these vulnerabilities are taken care of before releasing the software on production. IGT cyber assurance covers OWASP, PCI-DSS, HIPPA, ISO 27001 and other standards of cyber security.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

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What are No-Code and Low-Code platforms?

These are the development environments that are used to rapidly develop and deploy custom applications by minimizing coding and using drag & drop for pre-build libraries and components for creating user interfaces, business logic, and data services.

 Main challenges in the traditional approach of application development:

• Key technology skills are in shortage: There is a shortage of skills in key technologies these days, making it difficult to deliver the application development project on time, with the agreed quality and scope.
• Time to market is the key: In today’s hyper-demanding market, the expected delivery time is in days and weeks and not in These kinds of timelines are not feasible in the legacy ways of working.
• Technological complexity: The technology is changing very rapidly and staying on top of all related areas of GUI, interfaces, security, scalability is an ardent task and quite time-consuming.
• Business innovations: By the time the technical team develops and is ready with an application, there is already a demand for new changes.

These challenges of traditional approach on software development are the key enablers of no-code- and low-code platforms as these very challenges are resolved with a new approach.

How to finalize low-code and no-code platforms for your development team?

Usually we need to perform comparative assessments of available platforms with respect to the organization’s budget, business needs and team composition. Gartner’s magic quadrants are a good starting point. We can  get information on vendors from other industry forums and publications as well.

Gartner’s Magic Quadrant for Enterprise Low-Code Application platforms:

As per Gartner, the low-code development technologies space is expected to reach $29 billion in revenue by 2025 (with a compound annual growth rate of more than 20%).

Key reasons for the rapid growth of low code platforms are:

• Business users get the opportunity to develop their use cases and features and dependence on core techies is reduced
• Automation and hyper-automation initiatives are very well supported by low-code applications, as pre-built components are available to integrate with other 3^rd party APIs and systems
• It provides greater composability of application services, functionality and capabilities, which enable teams to implement applications across different technologies

Key features of low-code applications:

A low-code platform can be used to create applications with the below features:

Low-code and no-code development in the Travel and Transportation industry:

Travel and transportation organizations can develop user–facing and self-services applications for customer registration, flight booking, baggage claim, cargo management, payment and loyalty programs using low-code and no-code platforms.

The Travel and Transportation applications have longer development cycles and have various interfaces with payment gateways, loyalty management systems, booking engines, reservation systems, and industry bodies such as IATA, HFTP, HTNG, GSTC and local Government authorities. The use of low-code and no-code platforms can help create these applications faster, and help achieve scalability, maintainability, and security.

The built-in libraries and components in low-code and no-code applications make it easier to exchange data among various functions of internal and external 3rd party systems, thereby enabling the development of the internet of things (IoT), artificial intelligence (AI) and machine learning (ML) applications.

Conclusion

IGT has partnered with various no-code and low-code platforms, we offer end-to-end digital solutions and services to Travel and Transportation customers. IGT’s no-code application digital assurance services employ an in-house developed digital assurance framework with pre-built use cases and are faster, and easier to deploy, manage, and optimize ensuring a higher ROI for our customers.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

Sources: Gartner

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The proliferation of Agile and DevOps adaptation in order to improve efficiency, agility, customer experience, and profitability is the need of the hour to remain relevant and thrive in the current market dynamics.

Faster, Faster, and Faster is the mantra of digital strategies which leads to faster development, faster deployment, and faster delivery. This means shorter testing cycles while still covering all the risk areas.

The existing ways of performing quality assurance of the products are no longer adequate in today’s time, where software applications are supposed to be available anywhere, on any device, on every screen size, on every browser, and provide amazing customer experience to its users.

Sharpen Digital Assurance further with AI

We all know that finding and fixing a defect in the software comes at an undesirable cost which we all want to minimize. Having said that, if defects remain undetected and are passed onto the production stage, it might cause a severe impact on the project delivery cost, not to mention a dent in brand image leading to customer attrition. The problem at hand is to optimize the testing process to achieve a balance of risk mitigation and cost/efforts/timeline incurred.

Tremendous improvements have been seen in the software quality assurance domain in the last decade, such as automation testing, shift-left, lean testing, and so on. At the same time, the application complexity, devices supported, and speed of delivery have also increased manifold. The gap has become wider between the current state and target state in the software quality assurance domain.

The Key approach here will be the utilization of AI/ML in software testing. The AI/ML based algorithm will train the model to predict the areas of maximum risk so efforts are optimally aligned to achieve maximum ROI.

The AI / ML model training itself is tricky, as it needs a large volume of data to train the model on, and any error in data if not identified at right time, would amplify the outcome of AI thus doing more wrong than good. Careful calibration of the model and availability of correct test data is going to be useful to enable AI in the Testing process.

The To Be state is when the model will provide a probability of defects in the area of the code, so automation testing (static and dynamic) is focused on a specific area, thus helping achieve results in a shorter time.

Why Digital Assurance function is best suited for AI modelling

Everyone is fascinated by the results promised by Artificial Intelligence (AI) and there is a lot of buzz in the media too. Let’s go a bit deeper and take a look at the four fundamental elements of AI:

Categorization: Categorization involves creating metrics specific to the problem, for example:

• There is a huge rework cost of defect identification, fixing, and revalidation post-deployment to production. Example metric: rework cost is 20% of overall project delivery cost
• Customers are finding it difficult to use the application and finding the right section on the browser / WebApp; this is driving the customer to move to a competitor product. Example metric: Customer Satisfaction surveys mention 3.1 (which is lower) on a scale of 1 to 5
• The delivery cycle of the organization is 4 weeks while several companies within the same domain/market have started adopting a two-week delivery cycle, thus having the advantage of delivering faster to market. Example metric: SDLC cycle takes 4 weeks from planning to production deployment.

Quality Assurance: Quality Assurance provides the data needed to create foundations of AI/ML applications, such as historical defect data categorized into modules, impacted code area, releases, developers, type of issues, etc.  QA also provides details on test cases executed/pass/fail, first-pass rate, etc. It helps join the dots and create problem statements.

Classification: Once a problem is categorized into various areas, the next step is to identify classifiers for each category to direct the user for analysis and conclusion. For example, in the airline travel domain, if the problem identified has to do with making a booking, the team needs to start classifying the possible causes of the problem: Web Application, Mobile App, Authentication, Authorization, Calendar, Pricing, Payment, and Reservation Factors and so on

Machine Learning: Now the problem is categorized and classified for domain-specific terms, the team can start feeding this data to machine learning.  There are various algorithms and techniques broadly divided into supervised learning and unsupervised learning. Supervised machine learning with neural networks is becoming popular. Few other applications of machine learning are feature discovery, event correlation, and time series anomaly detection.

As the quality assurance function is generating a huge volume of data such as test cases, code reviews, defects data, test execution data, etc. it is pertinent to use this huge volume of data related to code quality, testing results etc. in order to train the model.

Collaborative Filtering: It is used to sort through large volumes of data and starts using AI based solutions. This helps in turning data collection and analysis into meaningful insight or action.

Challenges of using AI/ML into Quality Assurance

The key requirements for an AI system are:

• Enormous sets of data
• Validity of testing data collected from various source
• Integrity of data

The challenge is with the availability of a large amount of verifiable data. If there are outliers in test data, those should be taken care of while massaging.

Another challenge is the non-availability of a continuous stream of data, as most testing is done on a discrete basis. In such a scenario, it would be difficult to find patterns in the QA data of one release and other releases.

Since there are various attributes involved in training ML models, and QA data of different types of industry/programs may have different outcomes, it becomes a bit difficult to have a single ML model for all projects.

Conclusion

Future belongs to AI/ML and we should be ready to embrace the changes. At the same time, we also need to ensure authenticity, integrity, and availability of correct data. If the above-mentioned challenges are taken care of, AI can be very beneficial if used along with digital assurance to work and deliver solutions, thereby achieving predictive threat modeling. This will provide benefits such as shorter delivery cycles, improved risk management, and cost optimization.

Author:

Yatender has 20+ years of experience in software test engineering. As the head of Testing Practice at IGT Solutions, Yatender is actively involved in innovations related to test engineering covering new tools, technologies, and solutions, and enabling IGT’s clients to achieve faster time to market quality improvement, and optimization of developer efforts in overall SDLC. A result-oriented leader, proficient in delivering high customer value and achieving excellence in service delivery management with proven skills in consulting and managing large and complex test programs. When away from work, he enjoys reading on a variety of topics and spending time with kids.

The post Deliver Insightful Results with AI and Digital Assurance appeared first on IGT Solutions.

As robots don’t have intelligence of their own, it severely limits the extent to which automation is possible, as there may be a lot of varied inputs and processes that require decision-making at different stages. To bring in some intelligence to automation, we must look at Artificial Intelligence technologies. AI has the ability to use its own logic and understanding to perform tasks. AI can learn to take decisions on its own, based on rules created by humans, and can learn by failing too, which is popularly known as machine learning.

AI includes multiple technologies that study the different facets of intelligence, including Natural Language Processing (NLP) and Machine Learning (ML). NLP and ML are more advanced than RPA. Other technologies used in AI include Virtual Agents, Biometrics, and Image Recognition. Virtual agents make use of chatbots that are programmed in a way that it can respond to human queries. A lot of applications use a virtual agent as the first point of contact for interaction with customers. Biometrics are used for identification and analysis of the human body e.g.; fingerprint can be used for entering the in-time or login time of an employee. Image Recognition is used for identifying and distinguishing an object in a video.

To explain in layman terms, RPA depicts human actions whereas AI depicts the intelligence of a human. RPA does not have the ability to learn from its mistakes whereas AI can keep learning from its own actions. RPA performs tasks that are clearly defined and where no thinking is involved. However, AI is a step further from RPA as it can learn and analyze and can give improved output to the user through training. AI differs from RPA as it can include voice and facial recognition.

Intelligent Automation (IA) combines RPA with AI technologies as per business needs to maximize the value of automation. Organizations can use IA to provide virtual assistants to their customers across chat and voice channels. The organizations that use IA can surely see an increase in their productivity, accuracy and understand the needs of their customers better by directly connecting with them. It also leads to a reduction in costs.

The ideal combo is one where RPA is combined with AI where AI helps yield better results. Which directly results in the expansion of the scope of automation within the enterprise.

As we already learned, to maximize value from automation and expand its scope, a blend of RPA with AI technologies will result in Intelligent Automation to empower rapid end-to-end business processes and considerably more.

IA offers many advantages that can be incorporated by organizations so that efficient solutions can be provided to the clients. The advantages are as follows:

• Increased productivity that enable automated applications and processes to run faster.
• Reduced costs – Automation ensures increased productivity leading to decreased manpower costs.
• Improved accuracy – Work done by an automated bot has less errors than done by humans.

Let’s look at one of the use cases where IGT incorporated RPA technology for a leading airline. This technology helped the airline cabin crew staff update their status of flying with the help of chatbots. The chatbot that interacts with the attendants shares updates about last minute changes in the staff on a particular flight.

IGT has deployed IA solutions in multiple domains like travel, hospitality and healthcare. With IA, IGT has improved its customer experience by optimizing back-office operations and increasing process efficiencies. By incorporating IA in contact center processes, it has further been able to handle surges in call center volumes, provide proactive customer service, and automated personalized messages for many of its clients.

Author:

Ayushi Jain is a Module Lead in RPA at IGT Solutions. She has 8.5 years of experience in the IT industry and has rich work experience in the Travel and HealthCare domains. Ayushi has obtained various certifications in UiPath and Automation Anywhere. She loves to travel and explore the untouched beauty of nature and enjoys reading fiction in her free time.

The post Progressing from Robotic Process Automation to Intelligent Automation appeared first on IGT Solutions.

The Business Intelligence analysis technology has been present since the 1980s when the ‘Gen One’ BI was first introduced in the market. It could generate business reports but heavily relied on IT professionals and was inaccessible to those with no IT background. However, the reports generated by ‘Gen One’ BI were beneficial for enterprises, and hence it sparked the interest of many business analysts.

A few years later, the ‘Gen two’ BI was introduced as an updated version of its predecessor. The second-generation BI made the data more accessible and consumable to business owners. Overall, the ‘Gen two’ BI made the analytical tasks easier for businesses, but there were still many flaws when used for Big Data Analysis. According to a report by Business Wire, the adoption of Big Data is still an issue for 73.4% of enterprises. Another problem with the ‘Gen two’ BI was its high cost and time-intensive nature.

To solve these problems, a couple of years ago, the third generation of BI, which is commonly referred to as ‘Next-gen BI’, was introduced, and its prospects reflect the visions of CXOs across the world. The ‘Next-gen BI’ utilized Artificial Intelligence (AI) for providing real-time insights and predictive analytics from Big Data through visualization.

As the third generation of Business Intelligence came into the picture, many enterprises have been adopting it. As of 2021, the BI software segment is expected to generate a revenue of 22,845.99 million U.S dollars.

The following article will discuss different aspects of Next gen-BI, like how data visualization is done in BI, how it can add value to businesses, and many more.

How Is Data Visualized In BI?

Data visualization is a process of presenting raw data in eye-catching and graphical formats such as bar graphs, pie charts, bar graphs, etc. The purpose of visualization is to recognize trends and patterns among the different units.  Traditionally it was done manually on software like Microsoft PowerPoint, excel sheets, and photo-shops.

The modern and more efficient way of doing visualization is by using BI tools. But before we can see the visualization of the data, there is a long process involved that raw data has to go through.

Here is how visualization is done in BI,

• Initially, the types of data and data sources that are going to be visualized are defined.
• After the first step, the transformation methods and database qualities are identified.
• Then, the data is sourced by BI from its initial stages. Here the data is cleansed, mapped, and standardized to a unified format.
• With the help of APIs, data is moved to the staging area.
• The cleaned data is finally moved into the storage, and this data is then visualized.

What Can The Next-gen BI Offer To Businesses?
There are numerous benefits that organizations can gain by opting for Next-gen BI. All the tedious and repetitive tasks can be automated with Next-gen BI. It can help businesses to perform better because of its following capabilities:

Data Is More Accessible, And The User Interface Is Intuitive: According to Dataversity, the customs data visualization offered by the next-gen BI has significantly upgraded the outcomes of BI. By opting for Next-gen BI, many steps in the enterprise workflow can be automated, improving the overall efficiency of the workflow.

The automation of processes allows employees to focus more on their primary tasks rather than looking into data for hours every day for insights. This reduces the friction throughout the entire data lifecycle.

Next-gen BI has allowed businesses and customers to access data from their fingertips. Nowadays, there are AI chatbots created especially to answer all the data-related queries. These bots analyze the data and put forward the best visual representation for the users.

It means that companies now don’t have to invest their time creating pie charts or bar graphs anymore.  Anybody can generate relevant information in a matter of seconds just by asking some set of questions.

This is a considerable improvement in the data analysis field as earlier businesses required human resources to extract, analyze, and visually represent the data. With the constant development of technology, next-gen BI is no longer just a tool for companies, and it has become more conversational and intuitive.

Real-time insights: In today’s world, companies need to act on real-time data. The next-gen BI provides real-time numbers that enable businesses to analyze live data and gain real-time insights. A report by Forrester shows that insight-driven companies are growing at the rate of 30% per year.

The Next-gen BI is incorporated with Artificial Intelligence (AI) and Machine Learning (ML) technologies. ML algorithm makes next-gen BI a self-learner and allows it to learn which insights are helpful for the business making the presented data more refined without any human feedback. AI assists it in automating the process and producing actionable valuable real-time insights in an increasingly timely manner.

Better Predictive Analytics: As Next-gen BI performs Big Data Analysis, it can offer predictive analytics. Predictive analytics enables top executives to lay out a plan of action for their business’s further development and expansion.

Assist Companies To Make Better Decisions: Another way the ‘Next-gen BI’ adds value to the business is by allowing them to make better decisions through its insights and hence decreasing the risk factor. According to TechCrunch, a company with the help of next-gen BI software witnessed an increase of $100,000 revenue per year.

The ‘Next-gen BI’ also offers insights into customers’ behavior, which can also assist in delivering a better customer experience.

Who Can Benefit From The Next-gen BI?

All the types of enterprises can benefit from the next-gen BI:

MNCs: As MNCs have to deal with massive amounts of data, they can benefit from next-gen BI for Big Data Analysis. Automation of monotonous business tasks and access to real-time insights that are very difficult to generate manually can be handy for MNCs or any business in general.

Mid-sized Businesses: As Mid-sized companies don’t have the budget for hiring a data analytics team, ‘Next-gen BI’ can help them with data visualization and exportation that can cut costs across the board. Therefore, it becomes more beneficial for businesses to utilize this software technology.

For Small and Medium-sized businesses utilizing BI-as-a-service is a great way to integrate this technology. By using BI-as-a-service, companies don’t have to invest in creating an on-premise infrastructure, making it a viable option. We will discuss more on BI-as-a-service in the further section.

Small-sized Businesses:

• BI’s desktop tools like Tableau and Microsoft Power BI are a more popular choice among small-sized businesses. Along with these desktop tools, many small-sized companies and startups go with the option of SaaS and cloud services.One of the reasons small-sized businesses opt for these tools is because of their simplicity. They work very similar to Excel and PowerPoint, applications in which most analysts already have high proficiency. Today’s BI tools also utilize AI-ML algorithms along with natural language for generating visual data.
• Microsoft Power BI is now integrated with Siri shortcuts. It means business owners will only have to say, ‘Hey Siri, open my reports,’ and the tool will present the user with all the relevant data. Power BI offers centralized reporting capabilities so that enterprises can make most of the self-service analytics.
• Tableau is another tool that is similar to Power BI.  It adds AI to the workflow and makes data more accessible by sharing the reports on Slack. Tableau has gifted its user with the ability to converse with the data. It offers suitable visuals and interactive explanations to all the data-related queries of business users. Tableau also provides AI-based predictions for Salesforce reports and sends them to Slack.
• Qlik Insight Bot is a conversational BI tool that provides automated insights and allows business owners to make data-driven decisions. The data and reports can be accessed via Qlik Sense and also through other platforms like Slack, Skype, Salesforce, and Microsoft Teams.  All the insights are driven by Natural Language Generation (NLG).
• Microsoft Power BI is now integrated with Siri shortcuts. It means business owners will only have to say, ‘Hey Siri, open my reports,’ and the tool will present the user with all the relevant data. Power BI offers centralized reporting capabilities so that enterprises can make most of the self-service analytics.
• Tableau is another tool that is similar to Power BI.  It adds AI to the workflow and makes data more accessible by sharing the reports on Slack. Tableau has gifted its user with the ability to converse with the data. It offers suitable visuals and interactive explanations to all the data-related queries of business users. Tableau also provides AI-based predictions for Salesforce reports and sends them to Slack.
• Qlik Insight Bot is a conversational BI tool that provides automated insights and allows business owners to make data-driven decisions. The data and reports can be accessed via Qlik Sense and also through other platforms like Slack, Skype, Salesforce, and Microsoft Teams.  All the insights are driven by Natural Language Generation (NLG).

Future of Business Intelligence

• According to Statista, the revenue of the BI software market is going to reach 32,652.95 million U.S dollars by 2026.
• In the future, the BI tools will get better at providing collaboration among the team. The current BI tools don’t have the feature to connect it with a broad network, but many researchers are working on it so that colleagues can work side-by-side, according to
• Third-party integration will also be introduced. It will simplify data processing and allow businesses to take appropriate action on the generated insights. The BI software and tools would become more accessible as they will send real-time insights to users via emails, text messages, and notifications.
• The ever-improving AI and ML technology will make it an even better self-learner. The coming generation of BI software is expected to become more intuitive and predictive in nature. Also, the AI/ML-based are good at learning from their past experience, making BI software more efficient with time.
• It will have Data Proactivity. This means that only relevant data will be provided to business owners, and all human efforts required to do this job would be omitted. This concept of Data Proactivity is co-related to third-party integration. Users don’t necessarily have to engage with the tools; instead, all the business data would be brought to users without any engagement.
• There will be an advancement in the network. A solid network is needed for any software. Many Computer Engineers are looking for a way to develop hardware networks and automatically increase the volume of data of BI tools.

Business Intelligence-As-A-Service

As discussed earlier, BI-as-a-service is another ingenious way to use BI technology if a company has limited IT resources at its disposal. Traditionally Business Intelligent solutions require extraction of the relevant data, organizing the data in the data warehouse, and then deriving insights from them by applying various algorithms.

But things have changed drastically ever since cloud computing came into the picture. It has made BI solutions more scalable and cost-effective for SMEs. Businesses can employ an end-to-end business intelligence-as-a-service solution instead of investing money in a data warehouse and maintaining it. Companies that already have incorporated BI solutions can also utilize BI-as-a-service for more streamlined and agile solutions which have better accessibility of data.

Sometimes people think BI-as-a-service is the same as Software-as-a-service. The SaaS providers only offer the part of what BI-as-a-service brings to the table. SaaS companies deliver an optimized user interface for interacting with data. But BI-as-a-service providers, along with intuitive UI, also do the job of extraction, organization and offer real-time insights into your data.

If you are also looking to hire a BI-as-a-service company, you must choose one that caters to all your business needs. As a BI-as-a-service company will do most of the heavy lifting, it becomes essential for you to choose the right Business Intelligence solution provider.

The question that comes to mind is how to choose the right Business intelligence solution.

Here are some criteria based on which you can make the right decision:

Reporting Abilities: The BI-as-a-service company should have the ability to provide dynamic reports that can be customized as per your insights requirements. By looking at these reports, you will be making important business decisions; therefore, the service provider must offer dynamic reports that perfectly fit your purpose.

Seamless Integration: The solutions that the service provider would deploy should be able to work in harmony with any other existing solution that you might have deployed in the past.

Accessibility of Data: You should be able to access data anytime, anywhere, and from any device you want. Look if the BI-as-a-service company has the ability to offer real-time insights and reports on any mobile application.  It will save a lot of time and increase the efficiency of the business.

Company’s Expertise: The employees of the service provider should have the relevant industry knowledge and experience. A BI-as-a-service company with a highly skilled team can let you gain a competitive advantage through their above-par BI services.

From the above article, we can see that the future of Business Intelligence and visualization is looking very bright. To ensure that the BI models are integrated seamlessly and working without any troubles, outsourcing this job to a BI-as-a-service company with a team of skilled and experienced professionals is another effective way to adopt this technology.

Sources: Statista, Gartner, Techcrunch, Dataversity, Deloitte, Businesswire, Blugranite, Forrester, ComputerWeekly

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Today, influential megatrends are reshaping the industry adoption of Conversational AI, reimagining value delivery in unforeseen ways. It includes the emergence of voice commerce, data-driven chatbot design, customer sentiment analysis, multi-lingual support, M2M conversations, voice assistants, and much more.

With proven benefits, enterprises are increasingly putting Conversational AI into action for enriching customer experience, improving bottom-line performance in the process. As per Deloitte’s Beyond Touch: Voice Commerce 2030 study, voice commerce will increase online sales. The decisive factor here is unimagined convenience for the customer, with the study predicting that over 30% of e-commerce sales will be driven via voice commerce by 2030.

Applications of Conversational AI

Businesses leveraging Conversational AI can become an emphatic organization that is more responsive to the customer’s needs. Chatbots depicts one of the most popular forms of Conversational AI. However, there are diverse applications of this emerging technology across business verticals, some of which include:

Online Customer Support: Conversational AI is being implemented by many companies for providing 24/7 customer service support at an optimized cost and much greater reliability.  E-commerce platforms use virtual assistance for product selection and customer service, which helps the business achieve higher customer satisfaction and service relevance.

HR Processes: Most of the time, employees call HR managers to know the information they can look up themselves. To maximize the HR department’s efficiency, a 24/7 employee service AI chatbot can be implemented to answer all the employees’ FAQs.  The HR chatbot is also helpful in passing any relevant information and real-time updates related to any changes in the company’s policy.

Retail & Ecommerce: According to Statista, worldwide e-commerce retail sales are expected to reach 5.4 trillion USD by 2022. At this growth rate, e-commerce platforms often struggle with manual sales and support systems that have their limits to delivering a seamless customer experience. As a respite, e-commerce and retail platforms are shifting towards Conversational AI to increase engagement, elevate the customer’s purchase journey, and offer personalized communication for the buyers.

Gaming: Gamers are usually engrossed and if there is a challenging level to complete, and they happen to face a technical glitch, they want it resolved immediately so that the momentum is not lost. Nowadays, many gaming companies have set up service centers to assist gamers whenever they feel stuck at a level. To help resolve common issues, an AI chatbot is set up to answer these queries. With this help, there is a high chance that the slump faced by gamers will end, and they are less likely to end the game mid-way.

Travel & Hospitality: The traveling customers expect to have their queries resolved on demand. It is where an AI-based chatbot can come in handy for companies that provide travel & hospitality services. Conversational AI is used to keep track of customers booking details, room preferences, opted traveling packages, travel dates, and many other details.

How Does Conversational AI Add Value to A Business?

Conversational AI is a technology that guarantees optimized ROI for growth-oriented enterprises. It brings value for both the customer and the employees and promises exceptional benefits for businesses, some of which include:

Substantial Cost-Savings: About 15 -70% of cost reduction opportunities are available for businesses with Conversational AI depending on customer channel interactions. The algorithm powering the Conversational AI bot can be trained to answer repetitive questions, allowing valuable human resources to focus on more strategic roles like customer relationship development and grievance redressal.

Increased Sales & Customer Engagement: Conversational AI allows customers to engage more frequently with the brand, creating a sense of trust among the target audience and ultimately increasing revenue.

The personalization feature can keep track of customer activity and recommend products or services depending upon their previous preferences.  

Deep Customer Insights: The customer’s interaction with the Conversational AI-based bot provides companies with data on what problems customers face and which issues need to be targeted and resolved on priority.

How Are Enterprises Implementing Conversational AI?

Let’s take a look at some real-life instances of some world-class organizations using Conversational AI to improve value delivery.

A Leading Airline Company Applies AI Chatbots

Germany’s largest airline company implements Conversational AI to update passengers on canceled or missed connection flights. The AI chatbots can answer all the FAQs that a passenger can have while boarding the plane.  If passengers are not satisfied with the answers of Chatbot, then they also interact with human agents without any waiting period. This way, customer service executives can spend more time answering complex and specific queries.

A Mental Healthcare Chatbot

A mental healthcare company makes use of a conversational AI-powered mental health chatbot that has made mental healthcare services more accessible for patients. It breaks all the barriers of mental therapy and allows people to have real-time interaction with the bot. Researchers developed the AI chatbot in collaboration with Stanford University to deliver behavioral therapy to patients at their convenience. It provides psychoeducation to the users and offers insights to deal with their mental issues by conversing with them.

Implementing Conversational AI:

• Making A Smart Adoption Strategy: While making the adoption strategy, businesses should figure out detailed customer persona, narrow down the scope, and use the data that is already available to set up the scene.
• Conversation Design: A lousy conversation design can lead to a bad customer experience. Conversation design plays a massive role in delivering a superior customer experience. A suitable conversation design must be sought out earlier in the development stage as it is easy to change.
• Choose The Right Channels for Integration: Before jumping into the development of Conversational AI, you should figure out which key channel and existing software you are to integrate with it, for example, company website, social media channels, CRM, emails, etc.

Even though Conversational AI has many applications today, there is still much room left for its development. Chatbots will become more personalized with time. According to a survey carried out by Deloitte, personalization is one of the significant fields of innovation and is responsible for 16 % of patents filed today.

Sources: Deloitte, Statista, Juniperresearch,

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Artificial Intelligence and Digitalization are creating new waves of change across industries and empowering them to meet customers’ ever-changing expectations. Customer 360 – an Artificial Intelligence (AI) enabled analytic framework, aids companies to efficiently create a workflow best-suited for their customer requirements, facilitating enriched customer experience.

Market Scenario

The market landscape of each segment, from retail, travel to hospitality, showcases significant disparities. While the retail market is booming, the travel and hospitality sector is yet to embark on growth.

Industries like: travel and hospitality are still facing the brunt of the pandemic, and there’s significant disruption in ensuing safety measures in international and domestic travel. Also, hotels, resorts, home-shaping platforms like Airbnb have faced a considerable jolt.  While these industries are recuperating, polishing their work structure will help them build greater resilience and stability, putting them on the growth path.

According to recent studies, about the retail sector, in 2019, the global sales generated by the retail market were approximately $25 trillion, with a forecast to reach $27 trillion by 2022. The retail market is flourishing – whether it is physical, in-store retail, or online retailing/e-commerce channels. One of the core reasons is that retailers are constantly fine-tuning their daily operations using digitalization and new-age technologies. Gaining insights and analytics helped them drive a better consumer experience which opened up new business opportunities.

Customer 360

The advent of intelligent technologies like Customer 360 caters to the needs of the modern-day customer, enabling them to connect with brands and have instant access to informative content through multiple channels. These channels include mobile apps, customer support, online communities, social media marketing, and many more. Such customer-relevant data can be processed and analyzed to personalize the customer experience in real-time.

The success driver for any service organization is the customer happiness index. Service providers in retail, travel, and hospitality can stand out by combining customer interaction footprints through all channels. With a 360-degree view of customers, service providers can offer personalized services best suited for their customers, augmenting their overall experience.

Customer 360 Benefits

Today, it has become challenging for most industries to meet the demands of the widely scattered customers -geographically and demographically. While most companies have opted for digitalization into their workflow, how to drive value from it still remains the big question. It is important for companies to understand their digitization capabilities, and implementing the same in their operations shall empower them with better analytical tools, reduce their costs, and expand their businesses.

Companies now have huge customer interaction with them, thanks to digitalization. With customer 360, it’s easier for companies to segregate their customers into different categories by analyzing their patterns, purchase behavior, social media interactions, interests and geographies, and ancillary sales.

Customer 360  in Retail Sector:

Retail brands are constantly looking to boost their marketing KPIs and enrich customer experiences. However, they face challenges like dealing with various data sources and disparate systems, making it difficult to create and manage a centralized index of records.

With customer 360, brands are now able to connect with external systems for new analytics and have access to master customer product data. Brands are enabled with a clear and single view of the customer. Customer 360 allows an automated combination of integrated workflow capabilities, and companies can now improve cross-team collaboration and understand relevant data to use. Useful information such as customers’ profiles, preferences, different transactions, and their relationships with other suppliers empowers them to develop innovative marketing and advertising strategies enabling growth. For example:

Customer 360 enhances FMCG retail’s merchandising and marketing activities and provides a single view of the product, pricing, and promotions. A digital analytic assistant offers customers with latest trends in aspects of grocery and hard goods. It also provides predictive analytics, which proves beneficial for future actions to be taken. With alerts and notifications about the latest events and customer behavior patterns, retailers can scale their businesses.

Customer 360  Driving Business

Customer 360 also provides the Next Best Offer analytics, which uses predictive analytics to identify the product or services that the customer needs. This data helps to add an extra dash of personalization to the customer’s experience. Customer 360 helps retain the loyalty of customers and stitches together an offer that meets their requirements.

IGT Solutions provides Customer 360- Artificial Intelligence (AI) enabled analytics that aids companies to understand their customer profiles, purchase behavior, customer engagements, and preferences with Customer 360 intelligence. This technology’s vast suite of features facilitates the unique identification of customers, situations, and decision-making propensities, enabling contextual and actionable recommendations to drive the subsequent optimal outcome.

Companies can leverage IGT’s Customer 360 to deliver hyper-personalized services to their customers. The framework identifies and segregates different areas of personalization under ‘NORC’, ensuring that valuable insights are extracted from the enormous data volumes NORC is related to the travel sector.

Customer 360 in Travel:

Travel companies can now eliminate silos with the help of Customer 360 and effectively manage their online and offline interactions. These companies are now capable of interacting seamlessly with their customers using real-time communication. For example:

Airline companies are now enabling customers to interact with them across multiple channels, providing them with ease of use and flexibility. Customers can directly call or use apps and social media to make reservations and raise queries or complaints. In case of any disruptions, travel companies can respond to their customer queries faster with the right message and the right channel.

Ticket bookings from all touchpoints are integrated into the cloud. Airline Company’s reservation and customer experience teams now have access to a unified view of customer interactions. During Covid-19, customers’ calls and queries were handled effectively by airline companies using Customer 360. Also, companies were successful in transitioning their teams from the workplace to work from home successfully.

Other Added Benefits:

• If travel plans have been changed or cancelled, eligible customers can now receive their compensations in less than 24 hours which traditionally used to take four to six weeks.
• Today, people simply don’t wish to buy a ticket but also want to be informed on various hotel options, events to attend while on stay, commute, and others.
• Airline ticket systems can now compare pricing with more accurate data from the cloud using Customer 360 predictive analytics and data discovery capabilities.

Personalization –Key Driver for Success

Industries’ complete range of ancillary services is often neglected, leading to poor customer experience. The cause can be primarily because of the lack or incomplete customer behaviour profile. Even through OTA or any other channel, the seller cannot anticipate the right ancillary service for the customer and therefore misses out on a great revenue generation opportunity.

By analyzing past behavior, social media activities, and customers’ online behavior, travel service firms can target the right cross-sell and up-sell opportunities and use the right channel. Customer 360 view provides ease of operations by providing a dynamic view of tested data. Customer 360’s data discovery capabilities help get accurate data from the cloud, which can be later applied across all verticals enabling them to grab the attention of more customers and retain the present ones.

Customer 360 Personalization in Hospitality

Hospitality industries are now proactive in analyzing revenue generation by collecting information from various venues and understanding customer activities. They can now make enhanced data-based operational decisions that will benefit both- the hotels and customers. For example:

• Hospitality segments can now update or inform customers or prospective customers in real-time using the marketing cloud over email, SMS, and Push notifications.
• Hotels can now segment customers by demographics, age, preference; and change their offerings dynamically. It can now add a personalization touch and create a WOW factor for its customers.

Customer 360 can amplify business operations with deeper analytics and customer data widening the scope for business scalability.

Sources: Statista

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The primary function of chatbots is to act like a virtual assistant and provide answers. In the current scenario, conversational automation which includes chatbots and voicebots are able to regulate tasks and promises an exceptional conversational and digital user experience.

Sharing critical information

Chatbots have the ability to serve the most pressing updates without spamming people. With a crisis on one hand and changing customer needs on the other, chatbots are in high demand from several industries because of their capability and functionality. Brands can share information updates through push notifications during a crisis instead of waiting for users to get in touch with them. They play a critical role in helping people receive crucial news and updates and are becoming increasing important and relevant during the novel coronavirus.

Chatbot capabilities:

• Interpretation Skills

Customers can ask questions using their own words and chatbots can deliver intuitive and intelligent online experiences. They are able to process the user’s query and respond according to an algorithm that infers the message and shares a suitable response. With NLP (Natural Language Processing) algorithms, chatbots can interpret, determine and define a series of appropriate actions based on the user’s query. For e.g, classifying your query as urgent/non-urgent.

• Long-term memory

Before responding, chatbots follow a series of algorithms to process the intent of the question, these algorithms are stored in the memory. A chatbot’s job is to remember you as a user and store your details intelligently so as to refer to them whenever you revisit. It is thus able to answer most questions in a smart way by remembering you and evolving over time to be able to answer questions that are off-topic as well. For e.g., remembering your postponed flight tickets.

• Emotionally Aware

With the use of psychology, chatbots are able to use customer insights from the chat contexts to provide them with better service. They are also able to detect instances that need human intervention so as to prevent any unwanted situation. It is not just the words used by the user that helps chatbots determine the level of urgency or the type of response, but also the tone in voice and the context. For e.g., a user using words with negative connotations would help the chatbots categorize them as negative reactions.

• Playing different roles

Chatbots can be classified depending on the purpose they solve. Either they help you collect information or help you complete a task. As intelligent agents, they play many roles such as; processing, collecting, storing and eventually converting data. They take ownership of all roles and identify the problem and present a solution to the end customer. A chatbot offers strong potential for curated updates and information. Many companies are using chatbots to provide information on COVID-19.

Conversational automation in times of crisis

B2B and B2C brands are switching to chatbot technology for sales support, customer services, as booking agents and more. When a crisis such as the one we are currently facing occurs, it becomes difficult to accurately gauge where affected members will seek out information. To attend to your customers, there is a need for proper tools that can manage several tasks at once. Chatbots help in evaluating customer’s needs, can handle high traffic on multiple platforms and help funnel information to users as per their requirement.

IGT’s conversational automation features are equipped with the right tools, partners, procedures, frameworks and experts who have experience in solving travel business problems thus not only bringing operational efficiencies but also enhancing end user experience.

Our cognitive capabilities include:

• Natural Language Processing (NLP)
• Optical Character Recognition (OCR)
• Speech Recognition & Transcription
• Machine Learning

Companies have started looking at chatbots as an important part of the COVID-19 crisis situation as opposed to just an addition. They only enhance the efforts of humans and in times of a crisis, it’s important we leverage its features so that we are there for our customers in times like these.

Author :

Gurmeet Oberoi is a researcher and writer of change tactics and technologies in travel and other verticals, she frequently posts across the digital ecosystem. With 9-yrs of experience in communications and marketing, Gurmeet has a passion for travel and reading among other things. She can be reached at gurmeet.oberoi@igtsolutions.azurewebsites.net

The post Why are chatbots gaining traction amidst COVID-19? appeared first on IGT Solutions.

Why are they important?

According to a research done by Adobe, 50% of travel and hospitality companies today are gathering and using real-time data; 47% are using automated personalization.

A study by AIIOT states, 73% of retailers plan to introduce AI to optimize their pricing by 2021.

Automation makes life easier, tasks faster and efficiency better. Some of the benefits that automation brings in are, quality, consistency, cost reduction, faster turnaround time and improved operational efficiency to name a few. AI on the other hand can bring the human element to information exchange, for e.g. bots can be simulated to engage with a user, send emojis based on the sentiment and even share stickers. However, let’s do a break down and look at how automation and AI can enhance the landscape of businesses

Visible metrics

Real-time tracking and reporting through automation helps businesses pinpoint trends like spending patterns of the consumer pricing strategies of your competitor and monitoring other excessive costs. Automation also gives light to unforeseen business opportunities and helps in the overall governance of your operations. These metrics can be picked up by AI and help predict and recommend destinations and even suggest services in hotels.

Enhanced customer experience

Consumers of today demand an interesting experience. With the help of automation and AI technology, brands today are able to stay in touch with the consumer before and after their journey. It allows them to deliver personalized communication and experiences at the right time. Automation and AI assist in creating an intuitive experience for the consumer who is looking to learn and experience new things.

A study by Gartner reveals 40% of all customer interactions will be automated through AI and machine learning by 2023.

Increased responsiveness

Time spent on administrative tasks such as searching, checking, collation etc. can be time consuming, however, with automation, this can be a very quick process. Automation can carry out high-volume tasks with greater accuracy while avoiding any manual errors. AI on the other hand can draw patterns and provide additional insights about the customer to help employees with more personalized responses to their customers.

Price tracking

Many customers use price comparison websites to make purchase decisions. Using automation to understand your competitor’s behaviour and gain market intelligence should be high on a brands’ priority if they want to stay in the competition. Automated pricing with the help of AI can help feed accurate data and set dynamic pricing for your business through offers and promotions and can also help fix those abandoned shopping carts.

Expense management

What was previously a painstaking task of inputting manual codes, has become a smooth painless process. With automation and AI, employees are able to track real-time spending and access reports from a centralized location, which traditional systems could not handle. Automated self-booking systems have freed up time in other areas of a business. Stacks of statements and invoices can now be swiftly processed even after modifications are made at the customer’s end.

Customer Retention

The automation approach has far-reaching benefits, for e.g.; conversations with your customers don’t have to end once their purchase is complete. Even post travel, businesses can stay in touch with the customer through emailers and digital ads. Brands can use automation and artificial intelligence to send relevant offers to customers based on their purchase history. Even customers who browsed on your platform but did not check out can be targeted with the help of automation and AI.

Brands that take business priorities and objectives seriously should automate their business processes to maximize results.

But for many, the million dollar question is, how and where to get started?

IGT’s automation centre of excellence is an all-inclusive shop for  several brands. Equipped with the right tools and experts, IGT has successfully implemented automated solutions like Chatbots and RPAs for multiple large airlines, hotels and  Internet companies By leveraging automation with AI, we are able to generate models for solving complex business problems with the right mix of robotics and humans.

Businesses looking to scale have to answer a simple question, do they want to reap the above benefits? If yes, then getting started is easy with IGT’s Automation Consultative Services and Artificial Intelligence offerings, where a team of experienced travel SMEs and business consultants can help you with the following sub-services:

• Automation maturity assessment
• Speech and text analytics
• Financial and technical feasibility
• Natural Language Processing (NLP) and Robotics
• ROI and Business Case Development
• Automation Centre of Excellence Roadmap

Automation and AI are shaping the future of  business management; not only do they lead to efficient operations for a brand, but also increase employee satisfaction. Employees are able to make best choices with the help of the decision support provided by these technologies, due to which, they are able to maintain compliance, engage with the customer and feel a sense of loyalty for the brand they represent.

Learn how IGT’s Automation CoE (Center of Excellence)has helped the travel and hospitality industry achieve great heights!

Author:

Gurmeet Oberoi is a researcher and writer of change tactics and technologies in travel and other verticals, she frequently posts across the digital ecosystem. With 9-yrs of experience in communications and marketing, Gurmeet has a passion for travel and reading among other things. She can be reached at gurmeet.oberoi@igtsolutions.azurewebsites.net

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