Need for a Meaningful
And Informed Dashboards In Uncertain Times
We live in a Volatile ,
Uncertain and Complex world where Crises of any kind create near term
challenges with some carry-forward implications. A contained crisis such as a
flood results, at minimum, in a pause in business activity in the short term ,
but a global pandemic such as COVID-19 is the kind of crisis that has the added
complications of many possible and seemingly indeterminate timelines and
Over the last 18
months this has been more relevant than ever before. Business leaders,
decision-making skills have been put to the test and individuals and teams that
have had real time information about the health of their business at multiple
levels have been able to make more precise decisions in this uncertain world.
Did you know that about
90% of companies increased their growth through previous downturns and
outperformed their competitors in profits on an average of 10% ?
What’s clear is the uncertainty around us isn’t
going away any time soon. But what can support decision making at every level
is having the tools to access knowledge and understanding within your world to
direct everything from strategy and innovation to day to day decisions at an
It is time to Turn your data into Smart Decisions
Reporting, analytics, BI, dashboards – there are so many terms to talk
about the tools needed to get access to data but ultimately, it’s about making
meaningful business decisions by means of a management dashboard that displays the
critical information needed to manage an organization in a single location—on
one page or one screen.
Could you imagine it? Driving along, not knowing
what speed you were doing, not knowing if you were indicating right or left,
wondering how much fuel you had left and if it would get you to your
destination. It might be an exhilarating thought to begin with, but it would be
nerve racking to drive like that long term. Similarly in a business environment
function of a dashboard is to provide real-time results by aggregating and
extracting value from all the data you collect.
Todays BI reports provides awesome reports but they
do not provide beyond basic insights and rather forces people to get into a routine.
geniSIGHTS first of its kind innovative Al and Analytics tool that generates
meaningful reports and dashboards for taking informed decisions. Powered
by geniSIGHTS Natural language processing (NLP) , FLASH allows you to ask
questions naturally. FLASH’s natural language query lets you have a conversation
with your data wherein FLASH understands and learns from a user’s behaviour to
innovate itself to add value to the user. With a scalable platform like
FLASH, you can jumpstart your Al journey in under 30 minutes.
The Joy of
Welcome to the
world of conversational insights , to schedule a meeting with
India : +91 875 457 7388 | US : +1 415 689 6970
US +1 917 410
4519 | UK +44 744 144 0327
Do you know what is the
most natural way to get things done ? TALK — We have over the last couple of
months been “talking” to a lot of people , and the one question that was asked repeatedly
was “Is FLASH just another reporting tool / dashboard
wrapped up with Voice/Text support or is there something more”? There is something more and in this post we
shall try to explain what FLASH which is
an AI driven decision enablement framework do for a Large Enterprise.
The Dashboard as we see
today is nearly 20 years old and as someone said “Using a dashboard is like
viewing your business through a straw” .Although dashboards will
never disappear, they will be transformed by artificial intelligence (AI).
Rather than looking at information from a handful of top-level indicators, AI
based dashboards will bring maximum
value to the business, to the managers and to the people who are taking decisions
Speed of decision making and availability of critical Insights to take a decision in real-time, is a dominant factor of any organisation’s success. Organisations today have tons of data, both structured and unstructured. The volume of these data keep growing every second by receiving new and new updates from different sources. While organisations search their data for insights and the ‘single source of truth’ at critical business moments, executives are often dependant on data analysts to provide that information. Unfortunately, data and analysts are always not available in tandem all the time. So how does one navigate through all these data , extract the right data sets to bring maximum value to the business to the managers and people who make the decision ?
Introducing FIELD (FLASH IN ENTERPRISES LOADED and DEPLOYED)
FIELD is geniSIGHTS first-of-its-kind innovative AI and analytics tool for enterprises that generates meaningful reports and dashboards for business decision-making. Powered by geniSIGHTS patented AI , FIELD empowers the clients to interact with the company data through voice or chat to provide actionable insights
Driven by powerful
machine learning and deep learning, FIELD understands and learns from an user’s
behaviour (their previous searches or commands) wherein FIELD becomes an users
“Personal” Data Assistant. With
significant reduction in development and deployment time, organisations
regardless of where they are in the analytics adoption stage can jump-start using
the platform within a week.
FIELD strives to innovate
itself through rigorous learning to add value to its consumers consistently and
is available in three different flavours namely Essentials , Expert and Elite.
The basic differences of these flavours are as below
Do it yourself Dashboards
Organisation Wide Learning
Welcome to the world of conversational insights , to schedule a meeting with
India : +91 875 457 7388 | US: +1 415 689 6970 US : +1 917 410 4519 | UK +44 744 144 0327
SME’s looking for a cloud based solution’s visit http://blog.genisights.com/conversational-ai-powered-business-intelligence-suite-fast-launch-event/
All organization use reports and dashboard for daily stand up
meetings, weekly reviews, board meetings, strategic decisions, and the like
wherein every department use their individual reporting and dashboarding
solutions. Every organizations identifies its
KPIs/metrics/chart which are made a part of their dashboarding solution.
The result – A bloated reporting system – several hundred reports, several
drill throughs, several charts and insights in each reports.
Are these reports actionable? Well, yes but you
need to spend time to infer – for each dashboard, each drill through, each
hour, each min, each second, etc. Don’t You wish you had a system that is
simple yet complete and guiding for actionable insights ? Don’t you wish you
had insights in a FLASH!
Well we at geniSIGHTS have developed FLASH a
first of a kind Artificial Intelligence powered dashboards with voice support developed specifically to help decision
makers. Just like a simple Google interface, FLASH, our AI driven
conversational dashboard waits for your command to open up actionable insights
from your data. The charts and insights are driven by your simple ask, FLASH’s
advanced self-learning AI understands your ask and customizes it specifically
for you. A simple system that that keeps the entire team productive
. Welcome to the world of conversational insights. Experience FLASH here
Let’s understand how a conversational AI can help connect the problems to the solutions effectively in real-time. Take an instance where there is a conversation between a customer care executive of a fashion store and a customer that is effectively solved with the help of a conversational AI.
The conversational AI uses sentiment analysis to understand the customers’ state of mind, makes recommendations to the executive for better solutions, and quick recommendations related to the offers of the brands the customer liked or has in their wishlist increases the overall satisfaction of the customer.
This is how conversational AI helps in solving customers’ issues in real-time. Many contact centers are already infusing AI into their operations and help desk tasks. Although AI is not going to eliminate the staff, it is going to aid a huge scale-up of the help desk services.
Are you a contact center organization looking for real-time & customized analytics solutions for your business?
You would have learned how Advanced Analytics aids the contact centers to enhance the customer experience thereby converting contact centers to revenue centers. Our Conversational AI product FLASH comes in handy providing meaningful insights in just a matter of seconds.
Conversational AI-led analytics is indeed the game-changer for contact centers was a 3 part blog. The part 1 concentrated on the problems faced by the contact centers which was followed by the solutions conversational AI could offer in part 2 and how the conversational AI solved the problems in real-time in part 3 of the blog.
BPO – Analytics: A prerequisite for operational efficiency:
The contact center has extensive information about customers, their behavioral and non-behavioral data, product experience, and the interactions with the frontline staff. With appropriate analytics, the information could be modeled to predict very useful characteristics to promote the product, up-sell/cross-sell, predict the intent of the customer call, etc.
BPO sector sets forth the following expectations which can be achieved through Advanced Analytics:
The historical and current data needs to be analyzed to uncover the masked opportunities for the strengthening of the organization.
The potential customers have to be identified, segmented, and targeted for the marketing campaign.
The unstructured data from the customer complaints have to be extracted and analyzed further to enhance customer service strategies.
The data from social media requires to be mined to determine emotions and opinions about brands, products, and services.
The customers who are likely to cease the service from the business need to be predicted.
The intent of the customer has to be predicted to give what exactly the customer wants before they ask for it.
There is a need for prediction of the future using extensive evaluation of the past performance
Recurrent issues of a product should be categorized for future enhancements.
The best products to be recommended to customers are to be predicted so that they can easily find their desired product.
The total value a customer can bring to a company throughout their lifetime is to be measured.
Analytical Solutions for Contact Centers:
geniSIGHTS understands the pressing needs of Business Process Outsourcing companies and has come up with a handful of analytical solutions. These intelligence solutions yield valuable insights to organizations ensuring the highest level of customer satisfaction.
Some of the analytical solutions offered are:
The Uplift Modelling ensures that the customers who have higher propensity scores are rightly identified and targeted for the marketing campaigns. The customers are segmented into four categories based on their behavior after being encountered with a marketing action.
Sure Things – Customers who would have responded whether they were targeted or not.
Lost Causes – Customers who will not respond irrespective of whether or not they are Targeted.
Sleeping dogs – Customers who are less likely to respond because they were targeted.
Persuadables – Customers who only respond to the marketing action because they were Targeted.
The cross-sell recommendation suggests the customers for the complementary product when they purchase a new product. The upsell recommendation shows up the customers with a better version of the product that they plan to buy. This system uses affinity analysis/association rules mining to analyze the co-occurrence of relationships among activities performed by customers and discover the cross-sell/up-sell opportunities accordingly.
The recommendation system exceptionally helps the business to predict the most likely product that the customer will buy. This system can therefore provide more personalized offers for the items of the customer’s interest.
Predicting customer churn rate
Customer Churn analysis predicts the customers who are likely to cancel their subscription from the company. The analysis also helps to understand why the customers are leaving and the possible ways to reduce the churn.
Sentiment mining extracts the necessary information from social media to understand what people think about a product or how they look up to a brand. The emotional tone behind each mention in social media can be derived from this analysis.
Customer Effort Analysis
The customer effort analysis brings out the amount of effort a customer puts in getting his issues resolved through various touchpoints.
These are some of the advanced analytical solutions that the conversational AI could offer for the problems faced by contact centers. Wait for edition 3 to find out how Conversational AI resolves all the problems of contact centers in real-time.
Are you a contact center organization looking for real-time & customized analytics solutions for your business?
Learn how Advanced Analytics aids the contact centers to enhance the customer experience thereby converting contact centers to revenue centers. Our Conversational AI product FLASH comes handy providing meaningful insights in just a matter of seconds.
Conversational AI-led analytics is indeed the game-changer for contact centers is a 3 part blog. Part 1 concentrated on the problems faced by the contact centers which is now followed by the solutions conversational AI could offer in part 2 and how the conversational AI solves the problems in real-time will be in part 3 of the blog.
Advanced Analytics assists Contact centers to hasten the decision making with real-time insights. It extends tremendous support for the Business Process Outsourcing Companies in improving their Key Performance Indicators thereby enhancing customer satisfaction.
In the competitive industry, building trust over a brand is inevitable. The companies are increasingly investing in service centers to improve the key determinants like customer acquisition, customer retention, and customer margin. The contact centers are continuously evolving at a fast pace to meet the customer’s demand anytime. They serve as a bridge between the brand and the customers. Establishing a strong customer base is vital for every business and the contact center does this job effectively.
Frontline staff at the war front:
The frontline staff is the first point of contact for the customers with the company. They are also responsible for retaining a business reputation. The expectations of the customers are tremendously increasing over time and the frontline staff needs to be well equipped to satisfy the customer’s needs. Also in the fast-paced environment, everyone expects things to get done fast.
The Frontline staff are upskilled on the product completely to deal with the most difficult customers. But due to high attrition in the service center sectors, the new staff are not well educated on the product leading to the frustration of the customers.
There is a pressing need in the industry to implement a software solution that behaves like more of a data assistant to these frontline employees. The conversational AI ensures that the customer receives a more personalized and quick response. When the frontline staff is faced with similar kinds of requests from the customers, the conversational AI connects to the data in the past and provides the relevant suggestions to the staff. The resolution time of the queries will greatly be improved which in turn provides positive customer feedback.
Major Concerns of a Contact Center:
High Attrition Rate:
High Attrition Rate is an alarming concern of the contact center industry that has to be addressed. Every customer expects instant resolution for their real-time queries. The front-line staff should be well equipped and trained with accurate solutions to avoid potential customer’s turn-off. Oftentimes, the new service staff is unaware of the past queries and how the organization resolved them previously. The attrition rate necessitates the contact center company to hire and train the new staff which imbibes huge costs.
First-call resolution (FCR):
First-call resolution (FCR) is widely regarded as an important facet for achieving customer satisfaction in the Contact Centre. However, as today’s customers tend to ring with increasingly complex queries, it isn’t always possible to provide an immediate answer. If callers end up having to speak to several agents regarding a single inquiry, the customer experience becomes inefficient and satisfaction levels plummet.
A recent survey reveals that 20 to 30 percent of a Contact Centre’s call volume is callbacks from previous, unresolved issues. In another survey, it was found that 70% of UK customers speak to an average of two to five customer service representatives before resolving a single issue which has reflected the preference of consumers across the UK from Contact Centres to various other channels like email, chat, or use social media or mobile apps and a host of other sources to drop a line.
Lack of Information:
The customers contact the service centers for information. When the service agent is unequipped with the solution, they put the customers on hold. The customer gets aggravated and frustrated when they have to wait for long. The waiting time is the biggest turn-off for a customer seeking help on an issue.
Many of the contact centers have been using Interactive Voice Recording Systems to reduce the number of calls reaching an actual agent. This helps reduce the cost of the customer care service of a company but also has its downsides. Some say the voice prompts are difficult to understand and give too much data in too short a time (Misrouted analysis). Also, most of the time, customers dislike talking to a machine and request to be transferred to an agent thereby increasing the customer drop out rate.
These problems faced by contact centers can be effectively resolved by Conversational AI-led analytics. Stay tuned to find out how Conversational AI could resolve the contact center’s problems in our 2nd edition of ‘Conversational AI-led analytics is indeed the game-changer for contact centers.’ If you are looking for a tool that will resolve all of these issues efficiently, we have an amazing tool “FLASH” available to you. Contact Team FLASH at email@example.com or visit the website https://flash.genisights.com/ to know more about its capabilities and benefits. You can also schedule a demo now with the Team FLASH to discuss the details of your requirements.
Learn how Advanced Analytics aids the contact centers to enhance the customer experience thereby converting contact centers to revenue centers. Our Conversational AI product FLASH comes handy providing meaningful insights in just a matter of seconds.
Conversational AI-led analytics is indeed the game-changer for contact centers will be a 3 part blog. The first part concentrating on the problems faced by the contact centers followed by the solutions conversational AI could offer in part 2 and how the conversational AI solves the problems in real-time in part 3 of the blog.
We feature Mr. Dorai Thodla in our monthly Feature corner, He’s Founder of Technology Strategies LLC and iMorph Innovation Center Pvt. Ltd. this month. He has co-founded 4 software companies – two in India and two in the USA. Mr. J. S. Sridharan, our Co-Founder, and Senior Vice President ask a few questions to Mr. Dorai Thodla. You may follow Dorai on Twitter (@dorait) and LinkedIn.
He helps organizations leverage emerging technologies for building skills and creating innovative products. His companies build Information Assistants, a collection of tools for gathering and analyzing information.
He considers the ability to do informal research and tracking technology trends as important skills for the future of work.
Sridharan – With reference to the informal research process, could you tell us more about which areas this would apply to?
Dorai – There are a few areas where quick informal research can help.
1. A product team trying to validate a set of ideas. They may need to know what already exists and whether they should build a product.
2. A startup with reasons similar to product groups, but may need additional information about the market size, how the market is growing, current players, and whether there is a viable business model.
3. Finding gaps and opportunities in emerging technology trends. Inferring latent needs from discussions and analyzing competitive market spaces.
Sridharan – Why do you think organizations would undertake informal research and at what level?
Dorai – It depends on the size of the organization. Small to medium organizations may use it at a tactical level. For example, a small product group may use it to do competitive analysis, opportunity analysis for product extensions, etc.
Sridharan – We know that we can leverage Twitter as a tool for any informal research. Can you share insights on how twitter hashtags will help organizations in this research?How can we leverage LinkedIn for this? What are some other tools we could use for doing this informal research?
Dorai – Hashtag’s usage is not uniform. Some of the most influential tweeters (like Paul Graham) do not use hashtags at all. An analysis of hashtags shows that they are used when you want to join conversations or when you are in a conference or other similar events.
Twitter is a broad platform serving a wide variety of people. You can see authors, journalists, news organizations, technology people from the small, medium, and large organizations. LinkedIn is different. It started serving the needs of HR and recruiters. For a while, now LinkedIn is broadening the base but the type and quality of conversations are very different. It is easier to find influencers and people from large organizations. The profiles on LinkedIn are much richer.
The major problem with LinkedIn is a highly restricted API. So gathering information using automated tools is a bigger challenge.
With respect to other tools, If you cannot afford to subscribe to expensive research resources from experts in the field (students and startups have this problem), there are many tools you can cobble together to do your own research. You can call this DIY Research or Informal research. These tools include:
– Search engines
– Blogs and syndicated feeds
– News sources (both raw and aggregated)
– Websites and Portals
– Social media tools like Twitter but also LinkedIn and to some extent Facebook
– Wikis including Wikipedia and its properties
– Trade and Research publications
– Data and Scholarly search engines
Sridharan – How can startups leverage social media for tracking technology trends?
Dorai – If you want to speak the language of your customers, you need to use the vocabulary of your market place. These include idioms, phrases, and memes in those places. For example, tl;dr (too long did not read) is a common term among software developers. Other terms include “code smells”, “tech debt” etc. You can gather tweets of developers, do a frequency analysis of the terms to understand the terms of the group.
The importance of understanding the vocabulary of users may be much fold. If you want to use content marketing, you may want to use that language in your content.
There are a few ways. The more open the social media, the better. That is why Search and Twitter are our primary tools of choice.
1. Google, Facebook, LinkedIn, Twitter will provide you data about the size of a specific niche audience.
2. The search parts of Google, Twitter, and others will provide discovery tools. I prefer tools that provide good APIs. These tools make data-driven decisions easier. For example, on Twitter, I can type a search, find popular hashtags, lists, and mentions, and can mine them for more information. This is not so easy to do for example in LinkedIn (despite their having an API) and Quora. So people resort to using scrapers and RPA (robotic process automation) tools.
3. Blog searches or Feed Searches
4. Job searches – for certain types of research jobs are a leading indicator
5. Conferences, meetups, and discussion forums are useful tools for identifying watch signals.
6. Funding patterns, especially Angel-funding are leading indicators. You can also track other rounds of funding and private equity to understand the market space.
7. Books and articles are mostly lagging indicators but they are good sources to track the popularity of certain technologies.
Sridharan – How can start-ups and organizations leverage this informal research for new product markets and finding new opportunities?
Dorai – There are several stages for a product startup. Let us look at the needs at each stage.
1. You come up with an idea for a product. You need to find out whether products similar to yours are there already and what are the pros and cons of each product (an analysis of alternative solutions). Having some competition validates that there are a problem and the need for a solution. But a lot depends on how established the competition is. At the end of this research, you identify a niche and some potential early adopters.
2. You build a prototype or a minimum viable product. You do this in stages. Once you have a proof-of-concept prototype or a functional, usable prototype, you need to validate that it solves the problem. You need research to identify these users, ways to reach them, and interact with them.
3. Once you have a few users using your product, you need to expand the number and also identify paying customers. You need research to go from 100s of users to thousands or tens of thousands of users.
4. Once you have sufficient users to feel comfortable with your validation, you need to price the product. If similar products exist, you need to research their pricing models. If there are no similar products but the market is being served by services, you need to research those pricing models.
As the number of users and types of users grows, you need more research to get to the next stage. Most of this research is not available in the market. Even if available, it may not be current.
Sridharan – Could you elaborate on some new research methodologies that can help startups?
Dorai – Startups have several free and paid resources for product discovery, content discovery, keyword discovery, and competitive analysis. Informal research strings together available tools to create your own Research Assistants. I see this as a multi-stage process.
– Info tools – tools to gather data from a variety of sources – Web, RSS feeds, Tweets, Posts, Discussion boards, Forums, and Blogs.
– Analyzers – Analyze information gathered via info tools – segment/cluster, discover topics, mine entities, derive the vocabulary of conversations, etc. The analyzers use Machine Learning, Deep Learning, Natural Language Processing, semantic tagging, and other emerging techniques.
Sridharan – With reference to businesses tracking technology trends, how do you think digital analytics help track the trends?
Dorai – Data gatherers will bring in a lot of data in various digital forms – text, images, speech (podcasts), videos. You need analytics for different levels of filtering. The first level simple analytics are early filters to separate signal from noise. Next level analytics provide good inputs for inference and prediction.
Sridharan – To understand customers and market size, which tools or platforms to look for?
Dorai – We can start with some of the available free tools. These include search engines, Twitter, LinkedIn, Facebook. They help you understand the market sizes since they need to know it to guide you in advertising. For example, using Facebook or Google ad products you can understand the size of a reachable market.
Using product hunt, beta list, and other similar services you can identify similar products. But nothing beats search. You can come up with a list of key terms that describe your product and try searches and analyze the results. Google provides a search API that you can use to automate this process.
You can use services like angel list to locate startups. You can use search to locate directories, professional associations in your product or technology space.
Twitter is becoming a great resource for discovery. Twitter APIs allow you to automate searches. Using Twitter you can find companies, products, trends, research reports, influencers, and discussions. You can create lists to manage the vast amount of information, retrieve tweets and links, and analyze the results.
Sridharan – How does text analytics help organizations in the changing business landscape?
Dorai – The outcome of searches (web search, Twitter search, Blog Search, Product Search, etc.) is short documents.
You need to text analysis to mine useful information from documents. Let us take an example of a blog comparing several products. You can use topic and keyword extraction techniques to derive useful information. You can use entity extraction to identify companies, products, and events mentioned in the article.
With huge quantities of data generated every day, and sophisticated algorithms fuelling data modeling, we look at the scope of the expanding AI market in North America. In our monthly Feature corner, our Co-Founder and Senior Vice President, Mr. J. S. Sridharan asks a few questions to Mr. Pat Krishnan, a seasoned C Level executive, from Bay Area, California, who has worked with leading organizations with disruptive technologies and has also provided strategic direction and leadership to various organizations in India and the US.
Sridharan – Having worked in AI, cybersecurity, analytics, and various other innovative ideas, please tell us how the pre-COVID and future priorities are changing for organizations in terms of adopting technologies like AI.
Pat Krishnan – AI as one knows is the “mantra” for every organization and every domain such as healthcare, cybersecurity, retail, financial to name a few. I think the market has been growing regardless of the COVID situation as far as AI goes. With COVID-19 and scientific community still trying to understand the nature of this RNA genome, AI and mathematical models come in very handy to provide more insights into this Coronavirus. The models can get very advanced once they decipher the pattern and I personally think that we will be able to predict the future mutations of this SARS COV 2. This is a prediction with some level of certainty that is only possible with AI models.
Sridharan – What are the problem areas you think AI can solve in the coming 3 to 5 years for these organizations?
Pat Krishnan – With COVID 19, new normal is happening and it will only be time before we get adapted to this. That said, Pharma (drug development), healthcare, retail, financial, insurance, real estate, entertainment, and food industries will go through a massive transformation and their reliance on AI and machine learning models will increase monumentally to an extent where vital decisions will be taken using data and technology. Problem areas AI can solve are InSilico drug modeling and profiling, Telemedicine, Disease mgmt such as Diabetes (CGM) and terminal illness, Money movement and payments, Insurance Risk and underwriting, Food deliveries, and Online Retail merchandise (from groceries to apparel and the likes).
Sridharan – With more conversational agents like Alexa and Echo, and while reports state that 70% of the total US smart speaker owners will continue to use an Amazon Echo device, tell us more about the adoption of conversation AI and how conversational AI is seen as the next paradigm shift in the AI technology in the North American market?
Pat Krishnan – I consider the consumer-driven lifestyle type applications such as Alexa, Ok Google is the guinea pig for the Conversational AI technology which is about to invade into enterprises. Increasing working patterns like WFH have pushed the envelope to adopt Conversational AI in call centers and contact centers. According to reports, Conversational AI can save the industry $150 billion by eliminating the drudgery of communication and enhancing the customer experience in leaps which will benefit the business. The next 5 years will see a lot of growth in conversational AI and related technologies in enterprises.
Sridharan – What according to you, are the areas organizations -small and big can supercharge customer engagement with the help of virtual agents and intelligent automation tools?
Pat Krishnan – Telehealth and continuous monitoring use cases, disease management are plum for engaging virtual agents and tools. Where there is a need for continuous engagement with the customer, automation tools will come in handy. The beauty of virtual agents stems from the fact that the back end Ai engine does the heavy lifting converting the customer queries and intent to tangible actions. The day will not be far off when most of the invasive questions are answered by virtual agents themselves.
Sridharan – How do you think organizations can leverage AI for higher levels of stakeholder engagement?
Pat Krishnan – Stakeholders live and die by making decisions that are important for the company be it operational or strategic level. AI is so democratic and objective that it does not differentiate any area of specialization. Where there is data, there possibly could be a need. Stakeholders should engage with AI service providers and work closely to close the gap that exists between science and technology. It will become increasingly necessary for stakeholders to come up to speed on the science aspect of AI which can help implement effective AI systems and platforms in the organization. Operationally the IT organization in the company should get aligned with the stakeholder and service provider.
Sridharan – What do stakeholders need to do to jumpstart their conversational AI journey?
Pat Krishnan – Stakeholders should start engaging with AI vendors and get the problem statement clearly laid out. This cannot happen in a silo and AI vendors should handhold the execs and help refine the problem. This is key to the successful implementation of an AI solution. This calls for stakeholders like the C suite giving enough time to go thru the implementation process which alone will pay rich dividends in the future.
With the recent technology advancements in Artificial intelligence (AI), neuro-linguistic programming, machine learning, the internet of things (IoT), and web speech APIs, it is now possible to streamline interactions between computer and human languages more effectively. Every day practically we see Google Home or Alexa ads on social media and on television.
We dig deeper into the world of chatbots in this interesting series on
Conversation AI: Chatbot Series- understanding chatbot -part 1 of 2
What is a chatbot?
A chatbot is a service that people interact with via a chat interface. You can ask questions using your voice or by typing in the same way you would ask a person. The chatbot will usually respond in a conversational style, and it may carry out actions in response to your conversation. It answers your question, rather than directing you to a website.
Chatbots are great conversational assistants for businesses. From simple conversation to complex transactions, a chatbot can perform everything. AI technologies like Machine learning, RPA, and NLP can take chatbots to the next level with intuitive capabilities.
Chatbot adoption is happening across all industries and functions because of its scalability and assistance capabilities. Chatbots live inside instant messaging apps such as website chatbots, dashboard chatbots, and integrated into third-party applications, with which users interact daily. This enables businesses to leverage the digital spaces that are already growing.
These messaging platforms which support AI chatbots are a more socially acceptable form of personal interactions than social networks. While social networks still connect users with brands, messaging platforms via personalized offers, photos, videos, GIFs, memes, links, and documents create one-on-one interaction between brands and users.
AI chatbot solutions have the transformative power to provide end-to-end services ensuring the business objectives of different industry sectors. Whether it is retail, customer service, or hospitality, AI-powered chatbots are building a vast channel ecosystem. Today’s chatbots are powerful personal assistants. They can call a Cab, place a lunch order, make a hotel reservation, order office supplies when you get low, and even help manage your calendar.
Broadly Chatbots powered with AI can be used for two purposes:
For Enterprise – In the last few years, the e-commerce market has grown a lot, so does the chatbot market. Businesses are inclining towards bots for jobs like order tracking, delivery confirmation, customer support, feedback & reviews, and surveys.
Undoubtedly, the applications of chatbots are also benefiting the education sector. Enterprises can automate their admission registration system, provide virtual assistants to their staff for decreasing their workload, and enable parents to connect with teachers in real-time with chatbots
For Consumers – Chatbots provide better service to users. Mainly in these following ways:
Quick Response time – Compared to a human being, a smart computer program will answer queries much quicker. This, coupled with an AI chatbot’s machine learning and multitasking abilities makes it a highly efficient virtual assistant that can revolutionize customer interaction metrics.
Improved Conversions – Chatbots can study past search data and offer more personalized shopping options via retargeting. The AI is constantly learning, and it can pull up multiple options that will be more appealing to the user based on their search history and captured data points. This can lead to increased conversions for you in the long term.
The demand for chatbots is increasing at a tremendous pace across verticals. In a recent survey, Gartner predicted that 85% of their engagement with businesses will be done without interacting with another human by 2020. Instead, we’ll be using self-service options and chatbots.
Chatbots are being adopted to automate processes like voice-driven assistants, sales, marketing, lead generation, and customer service. During this survey, 42% of participants responded that automation technologies in these areas will improve the customer experience. 48% said that they already use automation technology for various business functions, and the other 40% said they are planning to implement some form of automated technology by 2020.
The shift towards intelligent assistants
The massive adoption of AI in the user’s everyday lives and businesses is fuelling the shift towards voice applications and conversational agents.
Powered by Conversational AI platforms, chatbots are becoming smarter and more human-like in engaging customers with smooth, conversational messages. Conversational interfaces are not limited to chatbots. With the rapid developments in voice technology that converts speech to text capabilities, businesses can build applications that can engage in voice-based conversations. Voice-enabled assistants will be the drivers for improving customer engagement for organizations and value to customers. Voice-enabled applications can not only accurately understand the requirements, but can also understand the intent or the context in which they are said.
There are a lot of opportunities for much deeper conversational experiences with customers with the evolving technology space.
We uncover advanced AI-powered chatbot applications in part 2 of this series. So watch this space for our next article on chatbots.
If you are willing to score in on the opportunities in the world of conversational businesses, connect with us for a chatbot or voice-enabled assistant experience at firstname.lastname@example.org.