How Digital Technologies are booming the Real Estate

Digital disruptions are impacting all the industries and pushing organizations to change or die. 

The residential real estate industry was built upon personal relations and contacts. Knowing the trustworthy estate agent personally, was more comfortable for buyers to make investments.

Today the scenario is changing. Several online estate agencies have been set up, which allow owners to buy and sell properties digitally.

At every step in the process of finding, visiting and buying a home, property managers are now focused on enhancing the customer experience with help of digital technologies.

Digital technologies are used for real estate portals, to find a trusted agent, view potential properties and invest as required.

Some property managers allow their agents to shoot, edit and upload video footage of their properties using their mobile devices. This resulted in the increase in reach and quick selling.

Digitization can help you increase your reach from a bunch of agents and investors to thousands of individuals who have interests in purchase and sale of Real Estate.

Digital has come into real estate as well:

·      In searching the properties – Buyers can go online on MagicBricks.com, 99Acres.com to rent or check out the property before buying.

·      Virtual tours of the property – commonfloor.com gives you live-in tours saying see your next home from every angle. This reduces time and expense for owners and creates convenience for the buyers.

·      All the Frequently asked questions about the proposed project can be answered in a direct chat with use of emerging technologies like chatbot powered with artificial intelligence

·      Old fashioned hardcopy of blueprints are now replaced by Building Information Modeling (BIM) which uses 3-D computer modeling. This helps architects and contractors to collaborate more easily and make on-the-fly alterations to existing designs. Maintenance becomes very easy as the BIM model contains all construction data in a single plan.

·      With Social media presence, buyers can get multiple reviews and comments on the properties and even ask the agents to take them on a video tour of the property through WhatsApp, FaceTime, Skype etc.

From the buying or selling when we come to occupied properties, digital technologies are used for the betterment of occupants.

·      Smart Buildings: Facilities including power management, lighting, physical security, fire safety and IT infrastructure.

·      Smart Energy: Automatic lighting control, may vary from obvious night-time auto-activation to dimming based on crowd density and weather conditions. Nest offers a number of innovations like motion detectors to adjust the heat settings when the family has left for the office or schools.

·      Smart Meters - Every home will have a smart meter to control the power usage and report in real time.

·      Smart Water System: IoT sensor enabled water systems which measure the flow, pressure, level and chemical content of the water to improve quality and usability

·      Smart Access: Users can open home doors or office doors by just touch of a finger or even with IoT enabled sensors ensuring garage doors are opened when users are approaching

From living rooms to the yard, we are embracing the digital technologies which are helping the booming real estate industry.

Artificial Intelligence in Financial Lending

I remember the 90s when I wanted to get a home loan and it took me 3 months to complete the process from providing all the hard copies of my income, tax returns, identity proofs then bank checked my creditworthiness & provided the approval.

Today everybody has some kind of loans like home loan, auto loan, education loan, two wheeler loan or even loan to buy appliances like HD TV and Refrigerator.

How do they assess your creditworthiness? There are so many cases of defaulters, which keeps increasing and hence established banks or lenders constantly looking for ways to improve the returns or proactively identify risks.

Lenders traditionally make decisions based on a loan applicant’s credit score, a three-digit number obtained from credit bureaus such as the TransUnion, Experian, and Equifax.  But these credit scores are based solely on credit-history and do not take into account rich data available, which can potentially give lenders access to data points as varied as online purchases, the strength of social connections and travel patterns. When viewed this data holistically, lenders can get a complete picture of potential borrowers & can significantly improve their ability to predict loan defaults.

Today digital transformation has changed everything. While the interest rate and closing costs on loans are still primary considerations, the speed, simplicity, transparency and customer service of the entire process is important.

As the purchasing power among millennials & gen Z continues to increase, they tend to purchase property and acquire assets that will provide stability & generate wealth.

The ability to cross-sell to these customers on loan products drives a significant portion of new loans. The difference for a digital-first customer is that they do their shopping online and may select an alternative provider based on the right combination of cost and ease of process.

Artificial Intelligence is used today, to determine the creditworthiness of those who don’t have any credit history like students or immigrants etc. It also helps to improve customer experience, e.g. by showing pre-approved loan amount. AI makes loan approvals quick and easy, reduce operational costs and these savings can then be extended to customers in the form of lower rates. Artificial Intelligence can process large amounts of data that human underwriters would simply not be able to make sense of.

Machine learning streamlines the process, drastically reduces the likelihood of errors and significantly cuts down the time it takes to approve a loan and disburse funds to the borrower, thereby enhancing the customer experience.

AI & Machine learning also helps to detect fraud by comparing customer behavior with the baseline data of normal customers and removing outliers.

Today apart from credit score and income, lenders are also looking at the digital footprint, payment data from other sources, purchase history, professional reputation from LinkedIn and other sources.

This is called alternative data sourcing. The use of machine learning to analyze this alternative data in loans and credit rating is going to raise some privacy, ethical, and legal concerns.

The future of digital lending will reduce the friction associated with the borrowing process, eliminating paperwork and moving all of the steps of the customer journey to an online and mobile capability. AI and Machine learning will become an inherent part of financial lending.

Machine Learning - The brain of Digital Transformation

We are all familiar with machine learning in our everyday lives. Both Amazon and Netflix use machine learning to learn our preferences and provide a better shopping and movie experience.

Artificial intelligence (AI) has stormed the world today. It is an umbrella term that includes multiple technologies, such as machine learning, deep learning, and computer vision, natural language processing (NLP), machine reasoning, and strong AI.

Organizations are using machine learning for various insights they want to know about consumers, products, vendors and take actions which will help grow the business, increase the consumer satisfaction or decrease the costs.

Here are some top use cases for machine learning:

·     Predicting & preventing cyber-attacks: With WannaCry making havoc in many organizations, machine learning algorithms have become extremely important to look for patterns in how the data is accessed, and report anomalies that could predict security breaches.

·     Algorithmic Trading: Today many of financial trading decisions are made using algorithmic trading at higher speed, to make huge profits.

·     Fraud Detection: This is still one of the key issues in all the financial transactions. With the help of deep learning/artificial intelligence, the identification and prediction of frauds have become more accurate.

·     Recommendation Engines: In this digital age, every business is trying hyper-personalization using recommendation engines to give you a right offer at right time.

·     Predictive Maintenance: With embedded sensors as the Internet of Things, many of the heavy industrial machinery manufacturers are applying machine learning to predict the failures in advance, to avoid the costly downtime and improve efficiency.

·     Text Classification: Machine Learning with NLP is used to detect spam, define the topic of a news article or document categorization.

·     Predict patient’s readmission rates: By taking into consideration patient’s history, length of stay in hospitals, lab results, doctor’s notes, hospitals now can predict readmission to avoid penalties and improve patient care.

·     Imaging Analytics: Machine learning can supplement the skills of doctors by identifying subtle changes in imaging scans more quickly, which can lead to earlier and more accurate diagnoses.

·     Sentiment Analysis: Today, it is important to know consumer emotions while they are interacting with your business and use that for improving customer satisfaction. Nestle, Toyota is spending huge money and efforts on keeping their customer’s happy.

·     Detecting drug reactions: With Association analysis on healthcare data like-the drugs taken by patients, history & vitals of each patient, good or bad drug effects etc; drug manufacturers identify the combination of patient characteristics and medications that lead to adverse side effects of the drugs.

·     Credit Scoring & Risk Analytics: Using machine learning to score the creditworthiness of cardholders, defaulters, and risk analytics.

·     Recruitment for Clinical Trials: Patients are identified to enroll into clinical trials based on history, drug effects

With today’s advanced cognitive computing capabilities, image/speech recognition, language translation using NLP has become a reality which is used in very innovative use cases.

Machine learning is nothing new to us but today it has become the brain of digital transformation. In future, machine learning will be like air and water as an essential part of our lives.

How Customer Analytics has evolved...

Customer analytics has been one of hottest buzzwords for years. Few years back it was only marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza.

SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services.

In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics.

By the late 2000s, Facebook, Twitter and all the other social channels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant.

With the digital age things have changed drastically. Customer is superman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience.

This tsunami of data has changed the customer analytics forever.

Today customer analytics is not only restricted to marketing for churn and retention but more focus is going on how to improve the customer experience and is done by every department of the organization.

A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics.

From the technology perspective, the biggest change is the introduction of big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation.

Then came Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure.

Predictive models of customer churn, Retention, Cross-Sell do exist today as well, but they run against more data than ever before.

Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical.

There are various ways customer analytics is carried out:

·       Acquiring all the customer data

·       Understanding the customer journey

·       Applying big data concepts to customer relationships

·       Finding high propensity prospects

·       Upselling by identifying related products and interests

·       Generating customer loyalty by discovering response patterns

·       Predicting customer lifetime value (CLV)

·       Identifying dissatisfied customers & churn patterns

·       Applying predictive analytics

·       Implementing continuous improvement

Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time

Now via Cognitive computing and Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their deep learning neural network algorithms provide a game changing aspect.

Tomorrow there may not be just plain simple customer sentiment analytics based on feedbacks or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time.

There’s no doubt that customer analytics is absolutely essential for brand survival.

How Augmented Reality is improving Digital Age!!

Augmented reality (AR) means amplified reality with graphics, sounds, haptic feedback and smell to the natural world as it exists. Virtual objects and information are displayed on top of the physical world, will make its way to our phones.

Just like the Internet ofThings & Big data, Analytics, augmented reality is going mainstream. Search engines are already expanding on image search, allowing you to point your camera at something and search for information based on what the lens takes in.

Both video games and cell phones are driving & exploiting the development of augmented reality. Everyone from tourists to someone looking for the closest McDonalds can now benefit from the ability to place computer-generated graphics in their field of vision.

Unlike Virtual Reality, which creates a totally artificial environment like you are on the top of Eiffel tower or looking at Taj Mahal right now from your living room couch, augmented reality uses the existing environment and overlays new information on top of it.

Pokemon Go released in 2016 was the most successful game to use AR to superimpose Pokemon on physical background and all children and adults were mad chasing them in real world.

Recent innovation, Heads-Up Display (HUDs) glass with AR superimpose crystal-clear driving directions on top of the real world so you can easily navigate without taking your eyes off the road. It’s like Pokemon Go but all the adorable monsters have been replaced by driving directions.

Digital Marketing will get a boost with AR.  A new augmented reality campaign from Pepsi Max have stunned people in London, giving experiences like a prowling tiger, a meteor crashing, an alien tentacle grabbing people on the street, the bus stop window serves as a scarily realistic screen to bring these scenarios to life.

With AR, you can view your living room on a smartphone and see how virtual furniture would fit into the real world and decide what is good to buy.

Artificial Intelligence has brought virtual assistants like Siri, Alexa, Cortana, Google to life but AR can put a face to it and beef up the experience. Microsoft Hololens is currently leading the AR headset race. 

There are several industries that will benefit from AR applications, including healthcare, tourism and entertainment. However, it is retailers who are the ones to use it more. With AR, your retail website is brought to life with a 360° online presentation of your store. In-store, augmented reality can easily display information and other visuals on packaged items with a simple image scan.

Lego’s “Digital Box” Provides Customers with an Interactive 3D Digital Experience. Aside from kiosks in stores, soon they will have mobile devices to be equipped with the capability to instantly bring up relevant information about any product in real-time.

Fashion retailer Forever 21 had put up a giant billboard which features a model walking in front of an image of the crowd below. The model occasionally leans over, and pluck someone out of the crowd. Sometimes, she drops them in her bag and happily walks off.

French cosmetic super chain Sephora is one of the leaders in AR marketing area. Their mobile apps & AR mirrors allow people to see how clothing, jewelry, and accessories look on them.

Augmented Reality cleverly blurs the line between the digital and the real by way of specially designed apps and unique visual ‘markers’ to intuitively visualise 3D virtual forms in physical realms.

We are still in the very early days of AR, and all of the future possibilities are difficult to imagine at this point. As this technology advances and gets more affordable, it will be easier for businesses to take advantage of it. AR helps to bridge the divide between the digital and offline world.

Terminator or Iron Man – What will AI bring in future?

In the age of Digital Transformation, Artificial Intelligence has come a long way from Siri to driverless cars.

If you have used a GPS on Google Maps to navigate in your car, purchased a book recommended to you by  Amazon or watched a movie suggested to you by Netflix, then you have interacted with artificial intelligence.

Artificial Intelligence is the capability of a machine to imitate intelligent human behavior which relies on the processing and comparison of vast amounts of data in volumes with help of big data analytics, no human being could ever absorb.

Stephen Hawking, Elon Musk, Bill Gates have recently expressed concern in the media about the risks posed by AI.

According to them, AI will soon replace all kinds of manual tasks and make humans redundant. This could be true in some sense but still this is a far cry from the current maturity levels of AI, which is still at the stage of figuring out real-world use cases.

Today machines can carry out complex actions but without a mind or thinking for themselves. Smartphones are smart because they are responding to your specific inputs.

The world’s top tech companies are in a race to build the best AI and capture that massive market, which means the technology will get better fast, and come at us at faster speed. IBM is investing billions in its Watson, Apple improving Siri, Amazon is banking on Alexa;  Google, Facebook and Microsoft are devoting their research labs to AI and robotics.

Together, they will swirl into that roaring twister, blowing down the industries and businesses in its path.

Within maybe few years, AI will be better than humans at diagnosing medical images and converting speech to emotions. But it can also be stealing millions of records from a government agency to identify targets vulnerable to extortion.

Soon you’ll be able to contact an AI doctor on your smartphone, talk to it about your symptoms, use your camera to show it anything it wants to see and get a diagnosis that tells you to either take a couple of Tylenols or see a specialist.

In all the fairy tales we have seen so far, good almost always wins over evil.

This is what we have seen in the movies like I, Robot or Avengers: Age of Ultron.  But Will Smith or team of avengers does not know that till end of the story. That’s where we are now: face to face with the demon for the first time, doing everything we can to get through the scary plot alive.

Today many companies are using AI for improving their business:

·         Geico is using Watson based cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite

·         Google Translate applies AI in not only translating words, but in understanding the meaning of sentences to provide a true translation.

·         IBM Watson is the most prominent example of AI based question answering via petabytes of data retrieval that helps in various areas like finance, healthcare & insurance.

As Humans we are programmed from childhood either by nurture or nature to do things the way we do. All the nine emotions we have learned since then are the inseparable part of our lives.

Currently we are in the control of the planet because we are smartest species compared to all the animals.

But when, and if machines learns to love or hate, work in peace or retaliate in anger, then it’s not too far that, with the ability to consume & digest the vast amount of data, they will become more smarter & start taking control of the planet.

Only then we will be able to know that AI is helping us like Iron Man's Jarvis or planning to eradicate us like Terminator!!

Beginner's guide to Chatbots - a driver for Digital Transformation

We are living in a century where technology dominates lifestyle; Digital Transformation with Big Data, IoT, Artificial Intelligence (AI) are such examples.

Over the past six months, Chatbots have dominated much of the tech conversation, the next big gold rush in the field of online marketing.

Chatbots are built to mimic human interaction, making them seem like an actual individual existing digitally. It could live in any major chat product (Facebook Messenger, Slack, Telegram, Text Messages, etc.), powered by basic rules engine or NLP and AI.

Chatbots have helped in conversation commerce in real time such as booking a cab or ordering a bouquet of flowers or pizza. Consumers will benefit from chatbots through personalization, and this is where social media plays a big part.

Here are a couple of other examples:

·       Weather bot: Get the weather whenever you ask like Poncho

·       Grocery bot:  Help me pick out and order groceries for the week like Yana, MagicX

·       News bot:  Ask it to tell you whenever something interesting happens like TechCrunch, CNN

·       Personal finance bot: It helps me manage my money better like Abe

A chatbot for an airline will function fundamentally differently from a banking bot.

People are now spending more time in messaging apps than in social media and that is a huge turning point. Messaging apps are the platforms of the future and bots as over 90% of our time on mobile is spent on messaging platforms like Facebook messenger, Whatsapp, Wechat, Viber etc.

Typically business need to answer following questions to create a bot:

·       Do you need a constant communication back and forth with the consumer?

·       What are customers’ expectations for the interaction?

·       How will the bot act?

·       What happens when the bot fails?

Chat bots have to be great at answering questions, this is usually how they are challenged, and IBM’s Watson is probably the best question and answer system.

There are several advantage of Chatbots:

·       24×7 availability – A bot exists digitally unlike a human being, and can thus be pressed into service continuously without any interference

·       Faster response time than humans, coupled with an AI, chatbot’s machine learning and multi-tasking abilities make it a highly efficient virtual assistant

·       Bots allow for a two-way, personalized interaction between the consumer and a brand

·       Saves Resources – Employing a chatbot to handle basic customer interactions can free up valuable human resources without a decline in productivity

Tacobot Allows to order Taco Bell even more quickly.

KLM has a customer service bot that's able to check your flight status and let you know if it's been delayed.

Interacting with software at a human level is becoming more mainstream from digital assistants like Google Home, Google Now, Apple Siri. 

Going forward people will not be able to tell the difference between human and machine.