The real game-changer in ecommerce came with the recent rise in artificial intelligence (AI). AI has progressed to a point where it has become an essential part of this industry. AI technologies have the ability to demonstrate intelligence that involves emotions and consciousness. With the combination of machine learning (ML), businesses can use algorithms to find patterns in large amounts of data and improve the recommendation system on their website and thus, strengthen the customer experience.

Hyper-personalization with predictive AI based analytics

According to a study by Adobe, although 83% of marketers said that they were familiar with machine-learning solutions, the application remains low, with only 14% of respondents saying they were using them.

In general terms, personalization is another name for recommendations, however, there are a lot of possibilities in personalization. For example, an ecommerce website showing simply the customer’s name after login is one form of personalization. Another example is showing separate landing pages for men and women. While personalization might include a customer’s name in emails or online ads, hyper-personalization involves more parameters like browsing and purchase history and other real-time behavioural data which is more complex as it goes beyond basic customer data. For example, hyper-personalization would include ads showing trekking gear based on the exact location where it was last purchased including payment method, applied coupons, social media activity and more. AI based predictive analytics play a huge role in a customer’s interactive buying process, it also is the driving force behind relevant and lead-generating campaigns.

Let’s take a look at some other important uses of artificial intelligence (AI), and machine learning (ML) in ecommerce and their role in improving growth and personalization:

Drive product recommendations

The use of recommendation engines has become a significant part of ecommerce businesses; the best examples of a recommendation would be ‘customers also bought’ on Amazon or ‘people you may know’ on Facebook. This is possible with the help of a recommendation engine or system. A recommendation system is a tool used by companies to foresee a customer’s choice of product amongst a long list of suggested items. AI can deliver suitable suggestions based on a customer’s preference. AI, along with ML uses vast amounts of data to offer products they would be interested in, and data here encompasses a lot of things: images, clicks, numbers, words etc. Once all this data is stored digitally, it can be fed into a machine learning algorithm to generate suitable recommendations to the customer.

AI based chatbots for customer service

In an age of conversational commerce, any successful ecommerce business will most likely have AI based chatbots and voicebots on their online platform for driving sales and customer service. AI based chatbots and voicebots, which are powered by natural language processing (NLP), help in assisting customers at different stages of the sales and marketing funnel. To ensure a seamless customer experience, the integration of these assistants is essential for engaging customers. As per a report by Gartner, by 2021, more than 50% of enterprises will spend more per annum on bots and chatbot creation than traditional mobile app development. AI is capable of reducing the workload of customer service agents, as chatbots and voicebots can answer a majority of standard questions and increase the response time. They additionally aid in following a customer-focused approach. With accurate data and insights at their disposal, ecommerce businesses can understand the trends in sales and tackle issues such as abandoned shopping carts, collect first-party data, and notify about promotions and deals which help in humanizing the brand. From making initial contact to answering simple script based FAQs, these AI based agents add to the company’s credibility.

AI visual search and image recognition

A picture is worth a thousand words; an ecommerce product picture is perhaps worth millions to any ecommerce company. Many a time customers see a new product, however, when it comes to describing it they get stuck. Ecommerce websites have improved their interface with accurate text-based search, but many customers might not be aware of the vocabulary that adequately describes a product; we as humans are visual beings after all. It is for this reason that voice and image based search has picked up and will transform the customer experience of a company radically. According to a report by Gartner, ecommerce businesses that implement visual and voice search will increase their digital commerce revenue by 30%. With AI based visual search, customers can simply take a snapshot of the product and search online. The AI powered ecommerce platform can quickly identify the product and line up a list of similar products, turning the virtual world into a shopping catalogue. Visual search is capturing the customer’s attention slowly, as AI based visual search gains maturity, companies have started putting together a gallery of images to be at the forefront of the search engine results. Many ecommerce websites are using a customer’s product preference and with the help of AI, they are able to show a product the way a customer wants, with ease.

Catalog classification using AI and ML

Customer experience is the ultimate factor that separates successful companies. Having a simple ecommerce website will just not suffice. To ensure superior customer experience, ecommerce companies must provide an exceptional shopping experience. To accomplish this, the creation of optimized catalogs that cater to the exact needs of the customer is imperative. Buyers today research online, browse offline and purchase on a website that offers a seamless shopping journey. AI and ML advancements in retail cataloging help in the classification of catalogs based on-demand analysis, local preferences, buying habits and new trends. AI based product catalog management takes care of automating workflows such as product listing, product identifications, and price competition checks. By looking at historical sales, promotions, weather patterns and season, AI can help businesses create an optimized catalog by predicting future demand. The goal is to unify in-store and online.

The buzzword is AI. Soon, personalized online experiences powered by AI will become a basic expectation. Hyper-personalization is here and will remain. IGT has been helping top companies to drive success to their business by delivering a super personalized customer experience.

We have been creating opportunities by leveraging AI/ML to generate models to solve complex business problems with the right mix of robotics and humans. By augmenting decision-making based on vast and complex datasets, millions of variables/unstructured data and enormous distributed computational capacity, AI/ML plays a key role in providing new business outcomes. These technologies have disrupted the traditional way of marketing, customer insights and engagement.

Source:

• https://www.gartner.com/smarterwithgartner/gartner-top-strategic-predictions-for-2018-and-beyond/
• https://blog.adobe.com/en/2018/07/19/5-trends-transforming-ecommerce-personalization.html#gs.qlu224

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 Revolutionize your ecommerce CX with AI enabled hyper-personalization appeared first on IGT Solutions.

So how is the travel industry coping with this shock? Airlines that are functioning have reduced capacity by 90% on international flights. Many have freezed their hiring as well; steps are being taken to cut costs. This extreme response that is generally expected in war like situations is making the travel industry rebuild a framework that addresses short-term triage for the situation we face, and also balances long-term planning.

While it is too early to tell how things will pan out in the future, the only way to combat the challenges is to follow a phase-wise strategy.

Phase 1 (Reaction and response) – In the initial phase, organizations were occupied in reacting and responding to the challenges that COVID-19 brought with itself. By implementing work from home, this phase resulted in companies assuring their customers of the steps they are taking to ensure business continuity.

Phase 2 (Redirection) – In this phase we see a dip in customer demand. Markets slow down and companies are focused on providing business opportunities to its existing and new customers. This is a crucial time where competition is high, as businesses reach out to new customers or other businesses.

Phase 3 (Recover) – While this phase can last a few months or quarters, business however, starts to recover and so does the economy. Overall, this phase will see new demands, and businesses must be prepared to offer new solutions to its customers.

Phase 4 (Opportunity) – The decisions taken in phase two will have an impact in phase four; there will be scope for strong investments and collaborations as companies start to rebound. The world will recover and the market will be better equipped to handle future disruptions from its learning.

The first phase is over, the impact has been acknowledged and decisions taken from now will have a long-term impact on a business. At this stage, any decision that paints a company in a corner must be avoided. Creating a multiple solution plan and having two-way options is the key. While consumers are in survival mode, their appetite for things will change. They will be more skeptical, which is why, offering new solutions and building resiliency is highly imperative at this point. The travel industry needs to maintain focus on demand simulation without compromising on customer satisfaction.

Areas that the travel industry must be equipped with post COVID-19:

• Analytics

The use of technology has been amplified because of COVID-19. Technology is being adopted by most businesses so they can sustain and this might even push the society towards a different future. This is the time for an organization to deploy analytics to deliver real-time information that aids in decision making. It’s time to acquire and analyze data based on travel and customer sentiment so that it can be integrated with predictive and other forms of analytics to take realistic measures. Analytics will help you examine lead indicators that can help you measure your customer’s comfort level and their plans of resuming travel. Analysis of a user’s spending activity for example can help you build a solution plan.

• Conversational Automation

A crucial learning from COVID-19 is that having a self-service capability is very important. For travel customer, having to wait in a queue for getting their queries addressed can add to the stress. With the help of conversational automation, which involves the integration of chatbots and voicebots; brands can assign large chat and call volumes and also ease the pressure off your team members.  This allows customers to cancel, refund or re-schedule their tickets or hotel stays on their own and also gives them control.

• Back office Automation

The COVID-19 pandemic has made the travel industry look at business from new angles. It’s time to accommodate adjustments and even creativity if we want to make it to phase three. While the world is able to keep in touch with updates through social platforms, organizations need to take it up a notch if they want to rebuild customer confidence during phase 3 of recovery. Investing in centralized applications by using back office automation, powered by Artificial Intelligence and Machine Learning, can show significant cost benefit. Automation can help process congested back end queues and help speed up the claims and other processes.

Preparing for the future

While work from home is not new to many of us, the new way of working amidst the pandemic has given us the ability to adapt and deliver our responsibilities from our homes. Companies have restructured the way they work, thanks to technology.  It has equipped us to function in this shutdown scenario and target new customers through various online communication tools.

While we will return to good health and so will our economy, competition will intensify and new disrupters can emerge. Businesses need to keep an open mind and should be willing to infuse innovation into their ecosystem.

IGT Solutions is helping organizations get through the current scenario with its technical capabilities. With cutting edge technologies that can provide custom advanced analytics solutions, we are helping businesses transform their digital journeys at this time.

To prepare for this new way of working, brands need an operating model that can ensure business continuity and pave the way to new ideation. IGT is equipped with the right tools, partners, procedures, framework and experts that can bring operational efficiency to your business through RPA. Our technical solutions help you stay connected with your customer and optimizes business processes which can help you retain your customer’s trust.

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 How can travel industry build business resilience post COVID-19? appeared first on IGT Solutions.

Frequent flyer programs were one of the first methods airlines used to gather customer data. To stand out from the crowd and gain a loyal customer base, they offered special services like lounge access, duty free shopping etc. to their frequent flyers. When customers signed up for a frequent flyer program, airlines got access to their data. As technology advanced, airlines were able to gather large amounts of data such as the location of the purchase, frequency of travel etc. Once considered key elements of a retention strategy, is now recognized as an efficient way of gathering user data.

While there are certain laws where airlines belonging to a certain geographical boundary (European region) are not permitted to use personal data from historical bookings available within the airline reservation system, other regions who don’t have such strict rules, started building profiles for their customers to market tailored messages to them. Over time airlines started integrating data analytics with loyalty program information to segregate customers based on the number of times they flew and money spent on auxiliary services. Data analytics helped airlines gain insights on customer behavior and preferences by looking at their travel history and spending patterns. By applying predictive analytics to this information, airlines were able to predict customer needs for the future by analyzing when they are likely to plan their next trip. With the help of predictive analysis, airlines can now shoot out customized offers on flight tickets, in-flight services, non-stop flights etc. The more the data, the more the analysis and more the opportunity to target their audience at the right moment.

As time progressed, analytics got integrated with customer data to cater to the ever evolving traveler. To diversify themselves, airlines partnered with other airlines, hotels, car rentals and credit card companies to not just gain further insight on their spending habits, but to offer customized catalogues and services based on the behaviour and preference of the user in terms of food, shopping and other interests.  Many airlines offer unique and useful purchasing options; Qantas frequent flyer members for example can use their miles to pay for their healthcare insurance or even buy a Jaguar!

Airlines don’t just want to be known for their air rewards but a brand that offers an assortment of rewards. It’s not just the airlines that have to gain, customers equally benefit from the information they submit; when their data is integrated with analytics, they are kept up-to-date on new offers, they receive alerts about flight delays or gate changes and their custom needs can also be addressed.

Frequent flyer analytics enable win-win partnerships for coalition partners and customers. In a highly competitive market, service providers in many industries have discovered the importance of customer retention. Airlines are investing and focusing more on frequent flyer programs to increase revenue while adding value to the customer’s overall experience by using the data received from different sources and by gaining insights on the customer’s future needs.

IGT’s analytics services offers significant business insights by integrating multiple data sources using a proven methodology, established frameworks, automated tools, and pre-configured data models for the travel industry

The post How can you reap benefits of frequent flyer programs with integrated analytics appeared first on IGT Solutions.

Techniques involved in the execution of the VOC

A traditional form of VOC which many brands have been using, is customer feedback in the form of emails, over the phone or even in person. Other forms include on-site surveys, recorded call-data, and the usage of management tools like Net Promoter Score etc. While these are great tools and having all kinds of techniques is only beneficial, one form of VOC that can’t be ignored in today’s age are the ones available on social media and the internet.

Using social media to evaluate your customer’s intent

According to Global Web Index, people spend 2 hours and 23 minutes daily on social media browsing and messaging. Additionally, 98.55% of people use at least four social media platforms daily.

Social media platforms like Facebook, Twitter, LinkedIn, Instagram, YouTube, WhatsApp etc have been an important part of all our lives, thanks to them, people of all ages are able to connect with each other, express their opinions on trending topics and share experiences, good or bad, in the form of messages, comments, views etc. Customers share sentiments and unfiltered views directly on a brand’s social media platform, they leave messages through features like online chat, social media groups and online reviews and expect a brand to respond directly to them.

According to PwC, 17% of customers will walk away from a brand they love if they have even a single bad experience with it. On the other hand, 59% of them will abandon it after several bad experiences.

These sentiments can be turned into hard data and analyzed to take corrective measures, this is where sentiment analysis comes into place. Sentiment analysis is the process of determining whether any feedback (review, comment etc) is positive, negative or neutral. It helps in understanding a customer’s behavioural pattern by assessing their tone, context and emotion. Brands can use sentiment analysis to research on the public’s opinion of them. It also helps in competitor analysis and evaluate their own performance.

A few ways brands can leverage social media sentiments:

1. Run targeted social media marketing campaigns.

By staying on top of the game in analyzing data, as a brand, targeting the right audience with messaging they are looking for becomes easier. The idea is to have a holistic approach to run campaigns that address the customer’s needs at the right time.

89% of marketers use Facebook in their brand marketing efforts as per a study by SproutSocial.

2. Detect early signs of potential critical periods.

People like to share their experiences of travel, stay and journey with their friends, family members, and followers on social media. They also alert other users about any instance like delay, security breach, and natural calamities etc which impact their natural course of life. These sentiments become a vital source for the service provider to investigate and take necessary action in case measures are not being taken as per operational standards.

3. Strategize and evaluate new concepts and solutions.

For travel and hospitality service providers, social media is an essential tool to keep a tab of events around the globe and take immediate action required to turn a negative sentiment into a positive or a neutral one.

4. Possibility of adding new features to meet the customer’s needs.

From enabling chatbots to upping their game with virtual tours, the travel and hospitality sector has as much competition as any other sector. To stay in the game, brands have to not just also provide what their competitor is providing, but also do one better.

Social media sentiment analysis has helped organisations convert emotions into actionable data points. It helps gain insight on the target audience and helps organisations take a customer centric approach just by capturing and analyzing feedback on social media channels.

In a time where using social media is almost a habit, it has shaped the way we look at it and the numbers are only increasing.

Social Media Sentiment Analysis platform by IGT

IGT’s Analytics framework is designed to cater to the requirements of the travel and hospitality sector. The platform plays a key role in classifying problems into relevant buckets and derive upward or downward trends. The segmented data buckets of market behaviour, sentiments and patterns help gain clarity from a brand perception standpoint. Prior to social media prominence, traditional tools like CRM, reservation systems and loyalty were used to extract relevant data. With the addition of social media comes buying patterns, likes, and dislikes, interactions and opinions.

How IGT’s Analytics platform assesses this data

1. List out customer’s key issues
2. Overall positioning of the brand vs. competitors
3. Focus on improvement areas such as:
   1. Operations
   2. Pricing
   3. Customer Service
   4. Product/Service type offered
   5. Campaign idea formation
   6. Analysis of campaigns run and its re-evaluation

 How IGT’s Analytics Platform can help your Social Media Strategy

• Discover unique market insights
• Develop a customized digital marketing strategy for your brand
• Develop digital marketing campaigns that resonate with your target audience
• Evaluate the performance of your campaigns

IGT’s analytics platform combines traditional data and customer sentiments to provide a 360 degree understanding of customer’s behaviour and offers a larger, more reliable analysis of the customer’s mindset. Social media is always evolving and so is technology. Our advanced analytics framework is enabled to analyze vast amounts of data and seamlessly provide insights that can help your brand manage, maintain and develop new relationships with your customers.

Know more about IGT’s Analytics Services and the customer-specific solutions we have developed to improve operational performances for the travel and hospitality sector.

Author :

Taj Mohammad is a Senior Project Manager at IGT Solutions’s Digital Travel Analytics Division. Carrying with him over 16 years of experience in IT delivery across various domains. In his 12 years at IGT solutions Taj has worked extensively on application development in Microsoft technologies before moving into fulltime project management. He has worked on various projects in Travel and Technologies including Datawarehousing, Reservation systems for Airlines, Alliance & Hotels. He can be reached out at taj.mohammad@igtsolutions.azurewebsites.net

The post Social Media Sentiment Analysis – To identify true pulse of your customer appeared first on IGT Solutions.

Consumers use various mediums like email, chatting mediums, and social media platforms to raise their concerns and expect real time resolution to their issues thus it becomes time-consuming and taxing for an entity who is working behind the scene to process and respond in-situ, to the real-time data that is being generated rapidly across these various platforms.

Henceforth, it becomes the responsibility of the organization to identify the problem and provide a solution to the consumer in real time, after following the adequate process.

WHY WE NEED AUTOMATED RESPONSE GENERATORS?

In the current scenario where customers’ expectations are changing and organizations want to maintain a reputation in the industry where they are seen as a brand that respects the needs of its consumers, it has become imperative to automate the process of Real Time Response generation.

For a business entity to respond in real-time, it needs to develop a model that is capable of apprehending, filtering and analyzing data to make useful business decisions. The model should be capable of determining that a response is required and at the same time should also be able to intelligently identify what, when & how of the responses or reactions.

IGT’s NLP SOLUTION FRAMEWORK:

The fast-growing human-generated content, which includes text, email, speech voice recordings, videos, social media post, etc. are almost unstructured. And customers expect organizations to uncover the deep insights from these unstructured data and transform them into actionable insights, accelerating the speed of the outcome.

Developing a machine learning pipeline is generally a complicated process. Text analysis is about leveraging tools, techniques, and algorithms to process and understand linguistic data, which is usually in unstructured forms like text, speech, etc. Within this pipeline, we use the tested and well-experimented strategies, techniques and workflows to gain useful insights by leveraging our travel and hospitality expertise.

At IGT, we developed an NLP solution framework with the capabilities to mine the incoming query text, parse that text and do text preprocessing, extract relevant information and classify them into various entities to evaluate the intent/sentiment of the query.

Having all this in place, a tailor-made response is generated and shared with the concern.

The process starts at the data ingestion point which can be from multiple sources like email, chatbox or social media/forums.

The framework is capable of recognizing who the customer is by checking the information of the query sender against the customer database. This enables us to provide improved tailor-made responses for that customer based on his/her historical data regarding queries if it exists.

The incoming query text is ingested by the NLP solution framework where the text is analyzed based on text processing rules that the machine learning model has. Then, an appropriate response is generated and is provided to the customer instantaneously.

This framework has not only reduced human effort, but also has improved efficiency and accuracy. And because of a set framework in place, it has become easy to recognize the pattern and types of queries of the concern which has significantly also reduced the turnaround time.

With the help of this Machine Learning based automated response generation system, the task has become less taxing because of its capability to analyze and respond in real-time. Along with this, the instantaneous generation of responses with accuracy and efficiency has also lead to customer satisfaction, trust and loyalty.

Let’s understand with an example of a customer email to a leading US carrier about baggage query:

At the core of our system, whenever a customer sends an email to the carrier enquiring about his baggage, the system gets triggered and starts handling the incoming message, it does the required preprocessing on the text corpus and feeds it into the feedforward Neural Network (NLP Layer), which in turn predicts the most likely response and provides the information related to the baggage like its current location, why it’s being delayed, etc. to the customer.

The NLP framework also extracts the relevant information so that the response is curated to match the customer’s question. The system aims at understanding the customer email and then starts to action based on that understanding and convey meaningful information.

About the Authors:

Ambuj Mittal is a Data Science Engineer at IGT Solutions’ Travel Analytics group. As a Machine Learning practitioner, he loves challenging real-life travel problems which can be solved using the power of Data Science and ML. He is skilled in Python, Machine Learning, Deep Learning, and Data Engineering. He is involved in development of AI and ML solution for our Travel and Hospitality customers. For further information he can be reached at ambuj.mittal@igtsolutions.azurewebsites.net

Qurratulain Saleem is a Data Engineer at IGT Solutions. He is skilled in Python, Data Structures, Algorithms, Machine Learning and Deep Learning. He is a Statistics and Math enthusiast. He is a passionate programmer and like solving algorithm problems and philosophizing about AI, algorithms, machine learning and their effects on our world and real life problems. He can be reached at Qurratulain.Saleem@igt.in

The post Real-Time Automated Response Analytics appeared first on IGT Solutions.