Need for AI in Travel Industry

NEED FOR AI  IN TRAVEL INDUSTRY, WITH REFERENCE TO COVID-19

Every sector is anticipating a dismal future. Even in these gloomy times, AI can help us float the boat. In Wuhan, where the virus originated, China facial recognition software linked to a mandatory phone app that color-coded people based on their contagion risk, decided who could enter public spaces. Even before such technology was implemented, BlueDot, A Canadian AI start-up, alerted about unusual pneumonia around a market in Wuhan in the month of December.

With the growing middle class and an increase in disposable income as a result of easy credit availability, the travel and leisure industry has benefited the most. However, The COVID  pandemic has affected the regular lifestyle of many. This sector stands most affected. In China, international travel was suspended even for those holding a valid visa.

Travel is a consumer-oriented service. AI can help understand customer needs in order to enhance loyalty as well as profitability. Conversational AI can be employed on social media platforms where the customers provide their feedback.  Chatbots can also be used to handle customer queries to make the process hassle-free. online customer service could also be enhanced by the same.

Traveler’s behavior and needs (most traveled regions, age group, gender, etc) can be understood with the use of heat mapping and travel service providers can target their marketing accordingly.  Facial recognition can ensure that tiresome paperwork is gotten rid of.  This way people can easily move through airports and other transport centers.

Machine learning can use external data and customer behavior to provide suggestions to the customer based on the same. For instance,  a change in climatic conditions can result in a change in travel plans. This can be managed by AI for the customer.

Travel is not only about customer satisfaction but also sustaining in the market.  When Jet Airways quit the market, the vault created for customers had to be filled by other airline service providers. In such a situation predictive analysis plays a key role In understanding competition and customer churn rates. Each airline could have predicted market conditions earlier and developed itself to serve the situation.

India was having slow economic growth even before the pandemic. To tackle the fall in aggregate demand, artificial demand had been created in various sectors. However, at this moment supply is stagnant due to the virus outbreak. Such a situation could also be tackled with predictive analysis.  Even when the virus began to spread earlier this year, reduction in travel was certainly foreseeable. Ways to sustain employment could be discovered beforehand by predicting customer trends with AI.

(Source: https://www.statista.com/)

AI/ML approaches to aid COVID-19 combat

As the total number of COVID-19 reported cases reaches 1,358,469 as of 7 April 2020. And countries like Spain & Iran reported 3835 & 2089 number of reported in one day, countries across the globe are trying their best to combat this crisis. Several countries including The US, China, South Korea, Taiwan are implementing AI-based solutions to combat COVID-19.

AI can not only predict the start of an epidemic but can also forecast how it will spread. Quick response, prediction, and prevention help stalling outbreaks of epidemics such as the COVID-19.  Natural Language Processing, Machine Learning, and genetic applied science can successfully study travel patterns, traveler data, health organizations data, climate data from satellites and more to provide new insights to address the outbreak and help contain the devastating effects.

The role of AI becomes more relevant to contain the spread of the disease COVID-19 because of its technological developments and innovative techniques.  AI helps in predicting the flow of the virus by drilling deep into the data collected.

So, what kind of data is needed for AI to predict the flow and pattern of COVID-19 across the countries? Data such as clinical and travel data helps the researchers to a great extent to predict the pattern of COVID-19 flow. There are also personal data that will be of help to analyze the affected status from social media channels such as their lifestyle, eating habits, family history and more.

From early detection of coronavirus to tracing the contacts, providing analytics on collected data from various sources, developing vaccines, AI plays an important role in fighting COVID-19 globally. Doctors and Governments are now using AI to trace the people who came in contact with the infected patients, to isolate and monitor them for symptoms to help stop the spread. There are various analytics techniques that are available to generate actionable insights to better study COVID-19 & fight against it. A few of them are described below:

  1. Path analysis – It helps to visualize the flow of coronavirus in infected patients. It projects in detail how the disease is progressing across a particular demography. Medical data of a region like daily reported cases, active cases, number of deaths & recovery are taken into account to do path analysis.
  2. Graph analysis – This analysis generates insights on the COVID-19 outbreak to predict the spread among the local population. A detailed analysis further identifies the super spreaders’ or events where the infection was super-spreading among the people. In the graph, analysis forms a network map that projects the degree of interconnectedness between infected cases & the contacts. Each junction represents an infected person wherein the edge represents the channeling of the infection through contact.
  3. Telco analytics – This refers to the analytics done with the data gathered from a person’s electronic devices such as mobiles, tabs, smartwatch & other electronic accessories. The electronic devices not only possess the personal data right from the name, age, gender, to GPS data collected both present & previous locations, to browsing patterns and much more. A lot can be analyzed with the GPS data including travel history & mobility patterns. The best thing about telco analytics is it is capable of providing real-time insights about an infected person’s activities who are referred to isolation or the suspects who are advised for home quarantine.

The applications of AI/analytics does not stop here. Researchers & therapeutics are betting on AI to discover potential COVID-19 medicines. AI is used to identify molecular compounds in the test data that can be as promising as to go for detailed testing in the labs within a few weeks of its discovery, unlike the conventional way where a team of scientists takes years of several experiments testing the chemical compounds in an effort to develop a new drug. Neural networks are used to accelerate the drug discovery process as they can run through the huge molecular data set & identify the required attributes to develop a new drug. NLP is being used to remove the texts from thousands & thousands of sources to cleanse news & statements made by representatives about the health of living beings.

Countries are broadly relying on AI applications to combat this infection because of their fast learning cycle, generating key insights & accuracy in forecasting from the collected data. AI is capable of learning both structured and unstructured datasets available anywhere in the sources. But one of the main challenges here is the availability of appropriate data by the government. A lot of manipulation happens in the data before it makes public in order to control the panic rising among the citizens. There are lots of open sources from where the data on coronavirus cases can be reaped using AI. Many AI-based firms are now developing a deep-learning-based model for automated detection COVID-19. The model is trained with chest CT scans images of COVID-19 infected patients from several hospitals treating COVID patients.

AI-powered chatbots are now widely being used to provide information about COVID-19 symptoms, do’s & don’ts during quarantine period & many more. Organizations like Facebook in association with the Indian government and national governments around the world are building chatbots to help people get accurate and timely information about COVID-19. They have also tied up with the World Health Organization (WHO) to get authoritative information about coronavirus directly in the WhatsApp inbox to help fight misinformation amid crisis. Real-time insights on daily reports about COVID-19 cases are being sent using this chatbot. Many healthcare tech industries are developing chatbots for people to go through self-assessment about COVID-19 symptoms. There are a set of parameters given if selected accurately the chatbot further guides the user if it requires to get admitted in hospital or home quarantine is applicable. The primary objective of a chatbot is to provide real-time information of COVID-19 cases, fight the fake information over social media handles & other sites, creating awareness & self-assessment of COVID symptoms.

Singapore hospital & public health facility are performing real-time temperature checks using smartphone & thermal sensors. China is using an AI system that uses sensor & AI to predict people’s temperature, this system can check the temperature of around 200 people per minute. The systems send an alarm if it detects a person with a temperature above 99.1 degrees Fahrenheit. Drones are being used to supervise people under home quarantine, thermal sensing & spraying disinfectant. As soon as South Korea’s government permitted private sector companies to begin developing coronavirus testing kits, a Seoul-based molecular biotech company used AI to accelerate the development of testing kits.

There is a race to find medicines and treatments not only in various AI tech companies & but also in between various countries like the US, China, South Korea, and Israel. Although every country in the world has adopted personalized approaches to end the disease, they are extensively using AI, Big Data & Data Science among various other technologies to combat COVID-19.

You can also help your country in this fight against coronavirus by regularly washing, sanitizing your hands, avoiding contact with any parts of your face and most importantly by maintaining social-distancing & avoid going out unless it is really necessary.

India Analysis of COVID

COVID-19 is a bio-war against humanity that has its origin in Wuhan, China that started way back in December 2019, declared as “Pandemic” on 11 March 2020 after it infected approximately 1,118,245 people across the world as on 3 April 2020. India is also grappling to combat this virus spread by adopting various measures from time to time including lockdowns and border shutdowns.

A major outbreak in the country is likely to have a far-reaching effect if not contained at this stage.  As the nation gets ready to combat the outbreak, let us have a look at what the data reveals on the pandemic in relation to the Indian geography.

A graphical representation of Date wise COVID-19 cumulative reported cases

source:www.covid19india.org

India reported its first COVID-19 case on 30th January 2020. As of 3rd April 2020, the Ministry of Health and Family Welfare has confirmed a total of 2902 reported cases (Source:https://www.covid19india.org/). Although the testing rates are comparatively lower as compared to other countries in the world. As per reports, the COVID-19 infection rate in India is reported to be 1.7, lower than the rate in the worst affected countries.

India is witnessing a steady increase in the number of cumulative reported cases.  From 3 March 2020 (6 reported cases) to 4th March 2020, there has been a sudden spike in the numbers from a single-digit 6 to double-digit 28. India continued reporting 2-3 cases per day which is much lower than the daily reports of other countries. On 14th March 2020, India COVID-19 reports crossed 100 when the union government declared the pandemic as a “notified disaster” under the Disaster Management Act, 2005.

Indian Prime Minister Narendra Modi imposed a ‘Janata curfew’ on 19th March, during a 30-minute live telecast, asking all citizens to observe “Janta Curfew” on 22 March from 7 AM to 9 PM post the steep increase in the reported cases. Following this one-day lockdown, many states & union territories started implementing state-wise lockdown till 31 March. A 21-day nationwide lockdown was announced on 24th March by Prime Minister Narendra Modi as a preventive measure for combating the outbreak.  The outbreak has been declared an epidemic considering the growing number of reported cases and when the transmission escalated from 24th March to 3rd April 2020. Ever since then, the numbers are alarmingly increasing in the country.

State/UT wise cumulative reported cases

Inspite of the lockdown in place, the total number of reported cases is increasing almost every day. Maharashtra, Tamil Nadu & Delhi are witnessing the worst COVID-19 reported cases 490, 411 & 386 respectively as on 3rd April 2020. New Delhi is expected to get affected by more numbers in the next 1-2 days. The surge in the numbers is due to participation by the people in a religious congregation in Delhi in early March.

About. 1830 people across India attended this event which included 281 foreigners who stayed put there till 8 March. Many people who attended the event started showing symptoms in late March which is when the news of this event came into light. In Delhi, around 53 people have tested COVID-19 whereas Tamil Nadu reported more than 190 cases in a single day followed by Assam, Arunachal Pradesh that has reported 5 & 1 new cases each.  Telangana government has declared 6 deaths and all of them have been to this event.

Date wise death reports

State/UT wise death reports

India has confirmed 68 deaths as of 3 April 2020. The number of deaths increased two-folds in the last 4 days crossing 40 plus. Maharashtra has witnessed the highest death counts among all other states/UTs touching 26 as of 3 April 2020. People who died of COVID-19 in India had other underlying chronic diseases along with coronavirus. A total number of 229 patients have recovered so far which brings the total active cases to 2673.

Two of the major challenges for the government is trying to overcome is the scope of tracking people with international, national travel history and the supply of medical essentials like ventilators, masks,hand-sanitizers, ventilators, COVID specialized ICU units, etc.

In a study earlier this week of data from 332 reported cases and population statistics from data.un.org, the majority of infections were in the 20-29-year age category amounting to 28.9%. This group had imported cases, carrying from the infection from traveling abroad.

The 30-39-year category amounted to 20.5% that also had a lot of imported cases.

While the central government has improved the health indicators, immunizations, etc, and some states like Tamil Nadu, Kerala and Karnataka have a comparatively better health system than the other states, it is important to contain the spread and impose diligent measures for the same.  While social distancing, stay home are imposed, it becomes equally important for citizens of all age groups to take responsibility to provide support to the nation in terms of combating the outbreak by following the same while healthcare workers are enhancing their approaches to contain the virus spread.

Cracking Corona – What the numbers are revealing?

As per statistics on 31st March 2020, the global coronavirus cases have touched 884,921 (worldometers.info). It all started on 31st December 2019 when WHO China was informed of cases of pneumonia because of an unknown cause. The total number of reported cases reached 44 on 3rd January 2020 and on 7th January 2020, Chinese authorities identified a new type of virus, the coronavirus. On 20th January 2020, China reported 278 confirmed cases and 6 deaths from the city of Wuhan, the epicenter of the pandemic, home to 11 million inhabitants. The evacuation process spread the virus to many people from China to various countries.

A look at date wise charts to show the spread of Coronavirus in China, Italy, Iran & the US, the top countries of the major outbreak is represented in the charts below

The article throws light on the jump from stage 1 of the virus spread where the cases are imported from affected countries to stage 2 where local transmission happens to stage 3 of community transmission.  Stage 4 has clusters of infection, China has been in stage 4.

The graphs represent the spread of the virus since its first outbreak in the respective countries. While the first outbreak in China happened on 31st December 2019, Italy reported its 1st on 31st January 2020 & Iran on 19th February 2020. The outburst in the four countries is much more compared to the other countries. While in China the spread was increasing twofold every second day, Italy faced a rise in almost 2 weeks of the outbreak. If the dates are to be analyzed, the outbreak in Italy happened very late after the outbreak in China but the increase in the number of cases reported is similar to China. Even in the US, the number of reported coronavirus cases is shockingly huge in two months of its outbreak currently standing at 189,612.  But the majority of the countries reported as low as 2 positive cases in stage 1 of coronavirus pandemic. Stage 1 indicates the stage where the infection is only limited to those who have traveled to virus hit countries and have tested positive.

As China grappled with the pandemic outbreak that seemed out of control, it seems to be leveling off in a matter of 2 months. 15th March 2020 marked a statistical milestone date when confirmed cases of COVID-19 outside of China surpassed the Chinese total.

A detailed day-wise study for 2 months, of the number of reported cases, in a few selected countries including India, shown below to better understand how countries are fighting against the virus spread:

The table above describes the spread recorded in a timeline of 5 days to do a comparative study to better understand the flow of the virus. For each of the countries, day 1 may vary depending on the date of the outbreak.

China reported the highest number of cases on the very first day of the coronavirus outbreak whereas other countries reported a maximum of 1-2 cases each. Other than China, where it all started, the rest of the cases were imported into the countries through an already infected carrier. Iran shows the highest rise in the number of reported cases in 10 days to 388 as compared to any other country.  China the epicenter of the pandemic shows a rise in the number of cases to 278 after 20 days.

Italy saw a steady increase in the number of cases but after a month the numbers jumped to a whopping 2000. Since then the number has been alarmingly increasing in the country and stood at 10149 at day 40. Reason?? No early measures to contain the spread or isolate the virus or limit the movement of the people. After China, Iran is the most affected as the numbers increased to an exploding 14991 on day 50 from 4747 on day 40.

Almost a month after Iran got hit by the pandemic, the number of reported cases reached 24811, almost touching the US’ number at day 60. Even after observing Italy’s situation, Iran failed to take early steps to control the virus spread. The number of officially reported cases has doubled almost daily and at least 3,036 people have now died, according to the latest official figures. As per sources, the officials tried to hide the outbreak of the virus to the country by stating that it’s like normal flu.

While the impact of the novel coronavirus has been the most in China and Italy, India also is within its grasp.  India reported the first case on 30th January 2020 in Kerala. The government has announced a 21-day lockdown until April 14, 2020, identified 20 existing and 22 potential hotspots to prevent the widespread transmission. The epidemic has expanded its footprint in the country, affecting 1,347 people till 31st March 2020 and the trajectory of the disease is going to be unclear.

Table below depicts states & union territories wise reported cases in India

Maharashtra and Kerala reported the highest numbers of coronavirus cases with 325 & 241 respectively. Even before the Government announced the complete lockdown, many states in India have already implemented a state-level lockdown to curb the numbers, sealing their borders from their neighboring states to ban all kinds of transportations. As per reports, India is at stage 2 of the COVID-19 outbreak even after two months of its first case reported.

In the US, where the numbers are overwhelmingly increasing at the rate of 1000s every 5th day, reported cases as of 31st March 2020 stood at 140640. President Donal Trump is endorsing the end to coronavirus social distancing soon and announced in a news conference that “America will again — and soon — be open for business,”. In developed countries like the US which has 2.8 hospital beds per 1,000 people, at a 10% hospitalization rate, all hospital beds in the U.S. are predicted to be filled by 10th May 2020. If 20% of cases require hospitalization, there are chances that the US might run out of beds by May 4. Deaths have been in devastating numbers mostly because of unpreparedness for the pandemic followed by a limited number of doctors operating per infected person & lack of medical treatments.

Because of the inverse relationship between the number of infectees & medical facilities including the number of doctors, nurses, medicines the death rates are also increasing globally. The graph below is a comparative death analysis among several countries like China, Japan, The US, Italy, Canada, Iran & India.

China has seen great losses in human lives right from the beginning of the outbreak by approx. 3,287. Italy surpassed the death rates of China in two months of the outbreak in the country by 7,503. The US has also crossed 2000 deaths as on 31st March 2020 followed by Iran witnessing 222 deaths as on the same date. Countries like Canada & India have experienced 58 & 33 deaths respectively. In China, where the population is approx 1,427,647,786 the death rate is comparatively invincible than the countries like the US, Italy & Iran which has a population of 327,096,265, 60,627,291 & 81,800,188 respectively. Whereas India whose population is 1,352,642,280 almost equivalent to China, the death rate is considerably lower than all the countries listed above (Source: https://en.wikipedia.org/wiki/World_population).

 

What is interesting here is China, the epicenter of the pandemic is experiencing a sudden dip in the number of deaths in China. If one can compare the number of new deaths on 20th March 2020, China stands at 8 new deaths compared to what was observed on 5th March 2020 (31 new deaths) wherein countries like Italy touched 625 highest number compared to what was recorded as on 5th march 2020 (27 new deaths). 

 

This leads to a very interesting question. Was China already prepared for this pandemic ever since its reporting in Wuhan? Or China is internally fighting this virus without letting the information come out of the country? 

As China prepared itself as the virus started rolling, they started constructing makeshift medical facilities on 24th January 2020 with 1,000 beds that became operational on 3rd February 2020. There are a lot of speculations building around this sudden fall in the death rate in China while the numbers are increasing rigorously in other countries.

 

The mishandling by the government of China on the coronavirus outbreak that began in Wuhan province by initially trying to cover it up. They started detaining the doctors who raised early alarm bells to make other countries aware of the spread of the pandemic. But now, as cases within its own borders begin to rise, Beijing is shipping sorely needed medical supplies and their doctors worldwide, including to Italy and Iran, two of the countries hit hardest by the virus outside of China. 

 

In these three months since the virus began its deadly spread, China, Europe, and the United States have all set off at a sprint to become the first country to produce a coronavirus vaccine. The World Health Organization officials say they are working with scientists across the globe on at least 20 different coronavirus vaccines with some already in clinical trials in record time.

 

Countries like China & the US are using advanced AI to help diagnose the disease and accelerate the development of a vaccine. AI is also being used as a surveillance system to keep a tab on infected individuals and enforce quarantines. Tech companies across the globe are implementing AI to track the virus & predict the outbreaks to process healthcare claims. AI-powered chatbots are also being used to deliver real-time information about the coronavirus pandemic. AI is learning every implementation during this hard time to aid research and vaccination.

Note: The numbers of reported cases & the number of deaths are subject to variation depending on the numbers reported.

Future of AI and Conversational AI in the eCommerce sector

Artificial intelligence provides a quicker, engaging and seamless experience in increasing operational efficiencies thereby leading to the transmutation of businesses across industries.  A source from Statista. com says AI will grow into a $118.6 billion industry by 2025.

Evolving AI not only includes search, facial/ voice recognition but also self-driving cars and chatbots.  Chatbots are computer programs that conduct a conversation with a human. Companies like Amazon, eBay; Sephora are already deriving a greater ROI from AI technologies.

 Some interesting facts of Artificial Intelligence from allied market research.com are:

  • 55.6% is the forecasted compound annual growth rate of the AI market.

  • Asia Pacific is expected to hold the largest AI market share.

  • Manufacturing is expected to experience the highest AI growth.

  • The scarcity of AI experts is seen to be a major obstacle to the AI market’s growth.

AI in eCommerce Industry

eCommerce

eCommerce sector is experiencing a major impact with AI with data showing that of all the industries, eCommerce is the one most ripe for AI investment. AI has been modeled to understand the customer, learn from the experience, provide customer satisfaction and generate leads.

Conversational Artificial intelligence in eCommerce is used to improve and develop business growth with a greater ROI with technologies such as Machine learning, NLP and data mining. These work together to learn about the user and provide the relevant information on time. Recommendations based on customer searches and previous purchases are also provided eventually becoming their virtual assistant.

Some of the key features of AI in the eCommerce sector are:

Predictive sales: AI derives deep insights about the customer and helps develop the sales by predicting the customer purchase using current data. As per Forbes, “87 percent of current AI adopters said they were using or considering using AI for sales forecasting and for improving email marketing”.

Product recommendations: Just like how we ask for recommendations from friends/ family before buying a product and the salesperson at the store recommends the product based on our preferences, conversational AI makes this an online engagement with the help of a smart search. The recommendation engine analyzes customer behavior and provides all similar products with different versions.

Warehouse automation: AI automates the warehouse and distribution operations to achieve greater outcomes. Warehouse automation reduces the operating expenses and minimizes the manual process. A survey conducted for Zebra’s Warehouse Vision Report found that 59% of IT and operations personnel in manufacturing, retail, transportation, and wholesale market segments planned to expand process automation between 2017 and 2022.

Inventory Management: With AI, the demand forecast becomes more precise and allows to control of the supply chain with ease thereby saving time and cost.

Chatbots: Chatbots are computer programs that simulate human conversation through voice commands or text chats or both based on a set of a predefined algorithm. They respond to most of the rudimentary queries raised by customers, resolve their issues and infer customer preferences to create a customized shopping experience.

Conversational AI: Amazon’s Alexa, Microsoft’s Cortana, Google Assistant, and other voice-enabled applications have been contributing to a rapid spread of voice-driven user experience in the last few years.

Conversational AI is not only redefining the way people shop but also establishing deeper connections with customers resulting in better customer experience and higher engagement rates.  This results in higher retention, conversion rates and thereby revenue. Voice-enabled AI is impacting the emotional connect of the customers and in their decision-making process.

Voice-enabled AI enhances customer experiences, builds brand reputation and leads to higher revenue earning capability in the eCommerce sector.

Gartner foresees that by the year 2020, 30% of all web-browsing sessions will be managed without a screen.

Through conversational AI is still in the nascent stage, it is anticipated to grow manifold in the next 1 to 5 years thereby making a paradigm shift in the way we communicate with the world around us.

Check out our product, Flash, AI-powered business intelligence suite for today’s business.

Conversational AI – Making your platforms more intelligent

Analytics

Chatbots are an integral part of most websites and used by many marketers to interact with their customers on a regular basis in the digital space.  There has been a paradigm shift from web browsers in the late ’90s to chatbots in 2008 to the much-advanced voice-enabled artificial intelligence using the most intuitive interface- natural language.  Businesses and millennials today are already using conversational artificial intelligence (AI) platforms as they are easier, less intrusive and quicker.

“There has been a paradigm shift from web browsers in the late ’90s to chatbots in 2008 to the much-advanced voice-enabled artificial intelligence using the most intuitive interface- natural language”

Technology research company, Gartner, has predicted that 85 percent of all customer interactions will be automated by 2020, and consultancy Servion believes that artificial intelligence will power 95 percent of all customer interactions by 2025.

So what is the difference between a chatbot and conversational AI? Though both may sound similar, there is a huge difference in the customer engagement to customer satisfaction levels of both. This blog covers the differences between the two, how conversational AI surpasses chatbots with its features & performance and makes platforms more intelligent.

In conventional chatbots, the interactions are based on a set of predefined conditions, statements and/or queries. These chatbots require human intervention if the queries asked by the users are beyond the rudimentary questions. Chatbots have inherent rules with which they operate, to provide consistent and uncustomized responses.  They also fail to continue the long human conversation as they lack language processing skills. They are programmed to converse only in one language and pick only certain words from the user query and answer it according to the predefined statements.

Conversational AI is a wider term that covers chatbots, text assistants and more has a much advanced interactive platform. Artificial intelligence enables the learning by classifying the models in data. Without training, conversational AI can apply the model to new & varied queries. This ability enhances their task performance and problem-solving skills without human intervention. Unlike chatbots, conversational artificial intelligence is more user-oriented. It engages in long human conversations with users and also provides recommendations based on previous interactions. Machine learning helps to learn from the experience without any mediation and then utilize the learning in their next user conversation.  Natural Language Processing (NLP) used in conversational artificial intelligence helps to learn and imitate the methods of human conversation which lessens human intervention helping business transformation, customer engagement, and growth in the organization’s Return on Investment.

Conversational AI is a boon for businesses that involve tasks that are monotonous and tedious in industries such as e-commerce, retail, travel, tourism, banking, business processing and more. Where the customer interactions are more frequent, it is customizable according to the customer requirements, inquiries, complaints or orders.

We, at geniSIGHTS, as an emerging leader in this space, aid organizations adopt scalable advanced analytics with pre-canned advanced solutions with conversational AI capabilities that fit common business needs and provisions to build, integrate customized analytical solutions.

Conversational AI – can this really become your Data Assistant?

The previous article explained the benefits of Conversational AI over traditional BI, how the static dashboards are getting obsolete due to their inability to provide new insights. Going a step ahead, in this article, we will dig deeper into understanding how conversational AI can evolve as “data assistant” for the decision makers. Many successful organizations are switching from traditional BI to conversational AI. Have you ever thought why this transition is happening?

Traditional BI generates insights from the data! But are these insights actionable? What understanding the business owners will get from these insights? The reports & dashboards generated from traditional BI are restricted and often fail to paint the bigger picture and draw insights for their business.

Conversational AI is driven by powerful AI that continuously learns from the user’s behavior (i.e. from their past queries), gives recommendations during the next query based on the learning. Further to this, the conversational AI has NLP engine which helps it to understand the user’s language & engage with them in a conversation to drill down the data & provide relevant insights. It doesn’t only generate the reports & dashboards, also tells the user the performances & forecasting of each segment in the dashboard. According to IDC, worldwide spending on cognitive & AI forecast to reach $77.6 Billion in 2022.

Alexa, Google Assistant is becoming popular and conversational AI is definitely going to impact our lives in a very significant way.  Imagine…. One fine morning you wake up to your conversational AI’s greeting message telling you about the future trends in the market, current business performance and finally assisting you with tasks that get a priority based on previous day performance. Amazing, isn’t it?

Join us!! For a CXO Breakfast Session on 15th June 2019 conducted by geniSIGHTS, an IIT Madras Research Park established company & a member of NASSCOM. The focus of the session would be on Conversational AI & its benefits to decision makers.

 

Bye Bye BI!! Welcome Conversational AI

Gone are the days when decision-makers have to be dependent on static reports & dashboards to make business decisions. Static dashboards are often restricted to certain “filters” and “drills”, eventually lose their significance over a period of time for not providing new insights. It takes approx. 3-4 months for the IT to develop these dashboards once the requirements are given by the business heads/owners. By the time the reports & dashboards reach the business owners, it becomes obsolete as it doesn’t deliver new insights but rather present scenarios thought of a few months ago!

The shortcomings of the traditional dashboards impel the business owners to shift to conversational AI. Conversational AI is emerging at a fast pace which helps businesses with better ROI when compared to static dashboards because of its novel features like:

  1. Provides real-time insights.

  2. Increases user engagement by delivering a more accurate response to queries.

  3. Learns from user behavior & give recommendations based on it.

  4. Bury IT dependency & development complexities.

  5. Engage with user’s customized preferences and satisfaction.

Are you ready to embrace this new innovation to increase your organization’s ROI?

It’s time to evolve from the traditional BI to conversational AI. With this vision geniSIGHTS, an IIT Madras Research Park established company & a member of NASSCOM have developed a tool called Flash. Flash is first-of-a-kind AI-powered dashboards with voice support for decision makers.

To know more… Join us!! For a CXO Breakfast Session on 15th June 2019 conducted by geniSIGHTS, an IIT Madras Research Park established company & a member of NASSCOM. The focus of the session would be on Conversational AI & its benefits to decision makers.

Conversational AI

Have you adopted “Conversational AI” – the big innovation happening in the field of AI/Analytics?

Conversational AI is emerging at a fast pace which helps businesses bring real-time insights by engaging in conversation with their databases with the help of a powerful AI program. The technology has become more value adding enterprise marketing than being more futuristic.

Voice interactions, chatbots, AI-supported human assistants and digital assistants dominantly make up the conversation AI in India. The complexities of data analytics, data modeling, ETL layer are buried deeper and the business is exposed to a simpler interface for conversation. The business now just must “Speak to the tool and get your insights.” the algorithms became intelligent over a period and truly become “data assistant” to address their day to day problems- prediction for future scenarios, etc.

According to Gartner, close to about 40% of Indian entities have already adopted or are in the process of adopting the conversational artificial intelligence.

This has been gaining a lot of support from financial services for sales and marketing but industries like hospitality and travel are in the process of embracing it into business to gain its benefits and keep consumers engaged and satisfied.

It is important that businesses invest in a tool which can help the businesses grow. GeniSIGHTS, a NASSCOM warehouse has established a BI/ Analytics tool for decision making known as Flash. It helps businesses in many ways such as; helps in gaining business insights, real-time interactions, helps user command using voice/text, learns user behavior and responds with relevant recommendations and many more.

Make your IoT more intelligent

Have you built Analytics on your IoT? Analytics implementation on the IoT helps the organization to perform

  • aggregations on the data from various devices and provide periodic schedule reports (e.g.: Hourly / Daily / Weekly / Monthly)

  • machine learning, advanced analytical model to predict the likely failure time of the devices, expected service maintenance time, etc.

  • historical data analytics and gather data-driven insights from the past

  • real-time data analytics

  • and many more

Interested to develop Analytics on your IoT? Collaborate with Us.

Our Things team would be your one-stop solution to help you build your own IoT analytics.

Want to see a demo? Go to http://things.genisights.com/

Click on “Things Demo

Request for the demo: contact@things.genisights.com

 

Demo Description: The demo consists of a data simulator which simulates the live factory environment and provides a live feed. There is an external data aggregator to get the external data from various other sites/sources. These inputs are then processed in an analytical engine where appropriate transformation, aggregation, and machine learning models are run to arrive at the desired business objective. The outputs are facilitated as streams and the stream could be visually seen in the dashboard.