DEV Community: Oodles AI

Integrating Chatbots Into Supply Chain For Improved Operational Efficiency

Oodles AI — Wed, 11 Sep 2019 10:42:44 +0000

The fourth industrial revolution has brought several drastic changes to supply chain management processes. With the advent of cross-industry IoT applications, supply chain and logistics operations are becoming increasingly complex. However, the widespread adoption of several innovative technologies has brought significant improvements in supply chain processes due to automation. Artificial intelligence (AI) is improving the management of inventory movements with advanced analytics and real-time tracking. Chatbots and virtual assistants are the most recent AI applications that are improving supply chain processes.

In this blog post, we will discuss how chatbots improve day-to-day communications in the supply chain.

The Impact of Chatbots on Supply Chain
The traditional information-gathering process in supply chain management requires person-to-person interactions. For instance, if a routing problem arises, a forklift operator approaches a warehouse manager through a wireless headset. With the forklift being idle, the manager then assesses the problem, looks at other scheduled work and suggests an alternate route. These person-to-person interactions are time-consuming and prone to errors.

With chatbot software in place, the forklift operator can simply speak a question into a headset. The chatbot then analyzes data from across the warehouse in real-time to notify the operator of the best action. It accelerates decision-making ability for improving processes across the entire supply chain.

Advanced Inventory Management

Traditional inventory management systems have several shortcomings like inappropriate tracking methodologies, superfluous inventory, and human errors leading to several discrepancies. AI-powered chatbots provide accurate information to warehouse managers about their existing stock and inventory movements.

Order and Tracking Related Issues

Situations may arise when a customer wants to cancel an order or modify it to add or remove some products. A chatbot can process such requests by using the information like tracking IDs and integrating it with the unique customer ID. Chatbots can also assist in tracking multiple shipments. Customers simply need to enter their tracking ID to access the shipment details on the go.

Predictive Analytics

Chatbots can gather, analyze, and process a large amount of customer data. It includes customer habits, their product preferences, frequency of queries, the percentage of fulfilled orders, supplier’s location, and so on. The data collected by chatbots is evenly segregated using customer ID and tracking ID for easy retrieval and accessibility. Analyzing customer data enables various organizations to understand their customers’ preferences and predict their future requirements. It further enables them to strengthen their customer relations.

Using predictive analytics and ML, chatbots can effectively forecast the demand for a particular product. It can also predict potential changes in trends and keep suppliers and manufacturers in sync with their strategies.

Feedback and Surveys

Feedback and surveys are essential to align business operations in-line with customers’ requirements and expectations. To improve their products and services, businesses must seek feedback from their customers. Using chatbots is the most convenient way to obtain customer feedback without wasting effort.

Businesses often conduct surveys to categorize their customer base and gain insights into their personal habits and shopping preferences. However, a majority of customers don’t have time to participate in these surveys that typically take 5-10 minutes. Chatbots can be extremely useful in conducting surveys as they eliminate the need to fill extensive online forms. They can simply obtain the required information by indulging in human-like interactions with the customer.

Employee Management

Companies rely heavily on drivers for delivering and procuring goods. Supply chain managers can use chatbots to retrieve real-time information about drivers and vehicles in transit. The real-time information enables them to manage deliveries as per the availability of vehicles and manpower.

Conclusion
Chatbots can significantly improve supply chain processes with effective strategies for tracking, monitoring, and performance optimization. The use of chatbots in the supply chain industry is increasing manifold with innovative functions designed to handle the growing complexities. It significantly improves the day-to-day communications and reduces human efforts so that businesses can focus on their core operations and services.

Why choose Oodles for Chatbot Development Services
We develop intelligent virtual assistants to conduct meaningful conversations and reduce customer service costs. We integrate third-party AI applications provided by leading platforms to accelerate chatbot development. Talk to our AI team to avail chatbots with advanced features.

Gain a competitive edge with our chatbot app development services.

Improving Industrial Processes with Machine Learning

Oodles AI — Tue, 10 Sep 2019 07:36:40 +0000

Industrial processes can be expensive and time-consuming for companies that don’t have the right tools in place for product development. As of today, machine learning has become more prevalent in the manufacturing industry as it accelerates the development cycle and reduces time-to-market. Besides, the use of machine learning technology significantly reduces labor costs, eliminates product defects, and prevents unplanned downtimes. Using ML in assembly processes is termed as smart manufacturing, wherein robots perform assembly functions with surgical precision.

This blog post focuses on the applications of machine learning in manufacturing processes and how it is revolutionizing the manufacturing industry.

Predictive Maintenance
Most often, maintenance is performed only when a problem arises. Taking equipment offline for troubleshooting leads to manufacturing overheads. In such circumstances, business managers face challenges in making decisions. Either they have to take the equipment offline for maintenance which causes temporary disruptions or face even greater risks down the line.

Companies can proactively monitor maintenance processes if they use ML to predict the potential breakdowns of manufacturing equipment. Predictive maintenance ensures that an equipment is serviced before a problem arises. Besides, it eliminates errors that cause equipment failure, reduces downtime, and human-capital costs with minimal manpower requirements.

Minimizing Equipment Failures
Determining the right time to conduct maintenance of equipment might be a difficult task. Each time a machine is taken out for maintenance, it affects business productivity and causes downtime. According to Uptake, worldwide business losses incurred due to equipment downtime adds up to $647 billion annually. That being said, the average worldwide business losses due to equipment downtime is $5,600 per minute. The use of ML algorithms can significantly reduce these losses by eliminating unplanned equipment outages. ML algorithms can predict and determine optimal repair time by identifying potential errors that may cause equipment failure. Besides, ML algorithms use historical data to identify patterns of previous equipment failure instances and determine the right time for maintenance.

Supply Chain Optimization
Robust and reliable supply chain equipment is an essential requirement for a seamless manufacturing process. A shift in weather or hike in fuel prices produces cascading effects throughout the supply chain with a significant impact on business operations. ML takes these factors into account and optimizes each element of your supply chain in response. It includes calculating shipment time or determining shipping location, based on weather patterns and other potential challenges. ML algorithm analyzes and processes multiple factors to take important business decisions for the supply chain.

Inventory Optimization
Apart from supply chain optimization, machine learning algorithms are equally beneficial for inventory optimization. According to Waspbarcode.com, the cost of storing inventory can add up to 20-30% of the entire product cost. Nevertheless, a small reduction in inventory holding costs (say 10%) can reduce per-unit costs by 2-3%. Holding unsold or undelivered products unnecessarily increases storage costs and have a negative impact on cash flows. Here, ML algorithms can be used to determine the right time to hold and sell inventory for enhanced business productivity. This is done by monitoring the supply chain elements including market prices, holding costs, and production capacity.

Quality Control
Quality control is an essential part of the manufacturing process, where products are filtered based on several quality metrics. It enables machines to identify defective items and remove them from inventory. The process of identifying the root causes is time-consuming and often requires multiple disciplines to collaborate. Using machine learning techniques, machinery and product data can be monitored throughout the manufacturing life-cycle to predict potential failures before they arise. Integrating ML into quality management processes can reduce quality issues, reduce manufacturing costs, and minimize product recalls.

Read More: Transforming CRM Operations With Artificial Intelligence

Concluding Thoughts
Maintaining efficiency in industrial processes is essential as it directly affects the top and bottom lines. The use of ML and AI enables performance optimization at all levels to eliminate potential challenges including hardware management. Integrating ML algorithms into quality control processes can minimize product defects to reduce unnecessary production costs. From predictive maintenance to supply chain optimization and quality control, machine learning can improve multiple industrial processes.

Why choose Oodles for artificial intelligence services
Avail the benefits of artificial intelligence to deliver engaging user experiences. Our AI team analyses your business requirements to identify the areas of improvement through AI. Based on your requirements, we build advanced AI and ML applications to streamline your business processes.

Click here to know more.

5 ways AI is transforming Document Management Systems (DMS)

Oodles AI — Fri, 06 Sep 2019 10:54:21 +0000

As an organization grows, the amount of newly generated data also keeps growing. According to Forbes, 15 Exabytes of data was generated worldwide in 2005 and almost 1200 Exabytes in 2010. As of today, this figure has reached 2.5 quintillion bytes. At this pace, the global data volume is expected to grow up to 44 zettabytes by the year 2020. Traditional data management systems cannot cope with the rising volume of data. Several leading enterprises that generate large chunks of data cannot rely on traditional document management systems (DMS). Over recent years, artificial intelligence (AI) has transformed conventional document management systems. The advent of AI has streamlined the way they store and archive important documents and extract useful information.

This blog post highlights five ways in which AI is transforming DMS.

The Power of AI in Document Management
If you search a document on a computer, you either need to know its exact location or perform a keyword search. AI enables human-like interactions with machines to accelerate the task of locating documents in a more engaging way. It not only reduces time and effort but also increases productivity. With AI, document management becomes smarter, simpler, and easier. Moreover, it delivers real-time contextual information that significantly improves workflow efficiency. artificial intelligence services can significantly improve document management systems, making them smarter and less time-consuming.

Five AI Applications That Are Transforming the DMS Industry
Data Analytics: One of the most interesting prospects of AI in DMS is the support for analytics and the value it provides for decision making. An AI-based DMS uses machine learning, predictive analysis, and data visualization to derive insights from data contained in documents. For example, several cognitive platforms like OpenText Magellan and IBM Watson provide data analytics to transform document management.

Data Extraction: An AI-powered DMS takes data extraction to a new level by analyzing information to identify the context. The given data is analyzed and crawled to retrieve relevant information from a DMS in a specific pattern. All small-to-medium businesses produce massive chunks of data on a daily basis. Therefore, it becomes critical to extract relevant information to accomplish a particular task. Integrating DMS with machine learning algorithms enables users to easily extract essential information.

Document Clustering: In document clustering, all the documents are grouped based on their topics without any prior classification. With artificial intelligence, this process becomes quick, simple, and more organized. An AI-powered DMS can effectively assign documents to different topics when the topics or hierarchies are not known in advance. It enables users to understand how documents are related to one another within a wider context.

Automatic Classification and Processing: The advent of AI has enabled the use of OCR (optical character recognition) technology to automatically classify documents based on their content. Machine learning is being used to improve the identification and processing capabilities of DMS systems. It can automatically identify and process the information from repeated exposure to documents based on the actions taken upon them. For example, an AI-powered DMS can identify invoices by recognizing elements such as invoice numbers or line items.

Advanced Security: AI-based DMS uses data-driven techniques to accurately detect Personally Identifiable Information (PII) and sensitive data, and protect it when needed. Any attempt to gain unauthorized access to data will be immediately detected by the DMS. Besides, AI prevents unauthorized viewing or alteration of documents using secure biometric techniques.

Read More: Food and beverage industries are becoming AI hotspots

Concluding Thoughts
With the advent of artificial intelligence, AI-based DMS systems are transforming the way a business operates. AI is one of the emerging technologies for creating a smart workplace by automating routine tasks and optimizing everyday workflows. With significant adoption of AI, document management systems are improving at a rapid pace. The advent of AI and ML has streamlined the data management processes and they continue to improve with machine learning algorithms.

Transform your business with our Artificial Intelligence Service
We introduce AI in your business operations with smart applications developed by our Artificial Intelligence Services team. As an artificial intelligence development company, we use the latest AI toolkit to develop data-driven DMS systems that deliver tangible results. Our services range from NLP, computer vision to predictive analytics and recommendation engines.

Get in touch with us to explore how AI can transform your business. Click here to start.

Assembling an Ideal Team to Build AI Chatbots

Oodles AI — Tue, 03 Sep 2019 07:05:52 +0000

The first generation of AI bots goes back to the year 1966 in the form of text bots like Eliza. It was not until the 1980s that AI bots evolved into voice-based bots. In recent years they have become popular as digital assistants that can resolve customer queries and engage with customers. They have found acceptance across multiple industries due to their effectiveness in saving customer service efforts and costs. This blog post explores key considerations for developing chatbots.

Read More: Chatbot applications are augmenting customer satisfaction efforts

Ensuring Scalability
Chatbot development requires strategic oversight to accommodate future requirements. AI chatbots that can provide answers to basic customer queries can fulfill present requirements, but meeting future requirements can be challenging. The same is true for their ability to handle several customer interactions simultaneously. The architecture of your chatbot application should be flexible to support your growing customer service requirements. It not only includes the number of interactions your bot can handle but also an increasing level of complexity. For instance, if you are a bank, you may want your chatbot to provide customers their best investment options rather than just balance inquiries.

Involvement of Various Personnel With The Right Skills
The development of an AI bot that delivers desired results is subject to a well-composed team. Here’s what an ideal team is made up of –

Business Analyst: A business analyst is a person who understands all organizational processes and who can apply knowledge to the chatbot. Business analysts don’t necessarily require technical expertise, but their deep understanding of information workflows is beneficial for chatbot development.

Product Owner: Product owners routinely monitor chatbot applications to improve their performance on an ongoing basis. They represent customer interests to incorporate features that go along with them. Their primary involvement is to monitor the development process and make necessary adjustments.

Conversational Copywriter: Conversational copywriters write texts for chatbots. They are responsible for crafting responses that can seamlessly accommodate computational output. Their goal is to develop content that is as conversational in tone as possible to keep customers engaged.

Frontend Developer: Depending on the channel you want to integrate your chatbot with, you may need the services of a Frontend Developer. In many cases, the platforms in which you can develop chatbots provide their frontend. However, if you still need tailor-made frontends, it is good to have an in-house specialist. A Frontend Developer, for instance, can create the front view of the chatbot if you want to implement it on your website.

Developer: It is advisable to hire developers who have seasoned experience in creating chatbots. That being said, there are several platforms where it is easy to avail chatbots with minimal programming skills. In such a case, you do not need a technical developer. The choice for this is therefore largely dependent on two factors. First, the platform you choose to develop the bot and second, the desire to be able to develop advanced features yourself.

Concluding Thoughts
Artificial Intelligence chatbots are the future of customer service across industries. Ensuring that a chatbot evolves with a skilled team is very important. A team comprising of a Business Analyst, Product Owner, Conversational Copywriter, Frontend Developer, and the Developer must work together to build impactful AI chatbots.

Why Choose Oodles for Chatbot App Development Services

We, at Oodles, develop intelligent virtual assistants to conduct meaningful conversations and reduce customer service costs. We integrate third-party AI applications provided by leading platforms to accelerate chatbot development. Talk to our Artificial Intelligence team to avail chatbots with advanced features.

Gain a competitive edge with our chatbot app development services. Talk to us now for a demo.

Building Engaging Conversational Interfaces with DialogFlow

Oodles AI — Tue, 27 Aug 2019 07:26:46 +0000

Back in the mid-60s, with text-based user interfaces, chatbots and conversational interfaces became areas of research for better customer service. Now with the advent of conversational interfaces, chatbots and virtual assistants have become an essential part of CRM operations. That being said, chatbots have become increasingly popular because of their ability to handle users’ queries effectively. Their main benefit is that they enable businesses to improve their customer support services without affecting the user experience.

STUDENT, an example of the early conversational interfaces was developed in 1964, eight years after John McCarthy coined the term Artificial Intelligence. Another example is ELIZA, which simulated conversation by using a pattern matching and substitution methodology. It had no actual framework for contextualizing events, nor a database or real-world knowledge. Work on natural language processing and artificial intelligence continued over the decades. One of the most significant milestones for today’s conversational interfaces is IBM’s Watson, which can respond to queries posed in natural language.

Using Artificial Intelligence Services company, you can develop a custom chatbot application to effectively handle customer queries. DialogFlow is one such tool that can be used to build conversational interfaces with natural language interactions. Combined with Google’s text-to-speech technology, it enables developers to build chatbots and voice assistants capable of performing human-like interactions with customers. Moreover, DialogFlow is powered with machine learning to recognize the intent and context behind user queries. It enables a conversational interface to provide highly accurate and efficient responses.

In this blog post, we will discuss the advantages and needs for building engaging conversational interfaces with DialogFlow.

Read More: Artificial Intelligence is Redefining Business Operations

Why is it required
A chatbot can significantly reduce human effort by handling hundreds of conversations simultaneously. Also, it is capable of providing round the clock support to customers. Chatbot applications make your business more approachable and streamline its CRM operations for increased responsiveness.

A majority of customers might be busy intellectuals who don’t have time to wait for sluggish replies from the CRM team. Chatbot integration can consolidate your relations with these customers by providing prompt replies to their queries.

Although chatbots cannot replace a human-to-human interaction, they can definitely speed up the conversations. The complex problems can be passed on to the human customer support executives whenever needed.

DialogFlow and its benefits
DialogFlow provides a complete solution to implement voice and text-based conversational interfaces. It employs machine learning (ML) to conduct a conversation more effectively. The entire process is performed using the simple user interface in DialogFlow’s web console.

There are several advantages that make DialogFlow a compelling choice for business. It can be integrated with various social media platforms and implemented easily across web and mobile platforms. DialogFlow’s Small Talk feature can customize answers for questions like “Who Are You” or “How Old Are You. It can motivate users to engage in a natural conversation.

Delivers natural and rich conversational experiences: Built-in natural language processing (NLP) feature enables chatbots to process the natural language (chat or voice) carry the conversation forward. This cognitive capability distinguishes AI chatbot from the normal chatbot that operates on simple pre-defined rules coded into it.

Offers cross-device support: DialogFlow enables developers to create a device-antagonistic chatbot to meaningfully engage users on phones, cars, wearables, speakers, and other smart devices. Therefore, businesses can connect with their customers or prospects anytime, anywhere.

Services Integration: DialogFlow can be easily integrated with many external services. For instance, you can create a Facebook Messenger chatbot for your brand’s Facebook page.

Enables chatbots to speak more than 15 languages: DialogFlow supports 15+ languages, including Chinese, Brazilian Portuguese, English (Australian/Canadian/Great Britain/Indian/US locale), Dutch, French (Canadian locale/France locale), German, Italian, Korean, Japanese, Portuguese, Russian, Spanish, and Ukranian. Thus, businesses can transcend geographical barriers to establish healthy customer relations.

Track chatbot’s performance with built-in analytics tool: Similar to mobile app analytics, business owners can track the performance of their chatbot functions. The integrated analytics tool can read the session including usage patterns, latency issues, as well as the high and low-performing intents. The intelligence further serves as a guiding principle for businesses to improve their chatbot.

Conclusion

DialogFlow is a great tool to build effective conversational interfaces. Apart from providing accurate and efficient responses, it delivers natural and rich conversational experiences to the customers. A well-trained bot aligns with the company’s workflow to render an engaging user experience. With Artificial Intelligence Services, technology owners can develop a solution for various businesses with chatbot requirements.

Why choose Oodles for building Conversational Interfaces
We have an experienced team that develops intuitive and user-friendly conversational interfaces for business applications. Our vast experience in business intelligence, ML, and AI strengthen your business processes with increased growth. We use the latest AI-toolkit to provide tangible results for your AI project.

Avail our Artificial Intelligence services, ranging from natural language processing to predictive analytics and chatbot development.

Click here to get started.

Strengthening Customer Relations with Facebook Messenger Bot

Oodles AI — Thu, 22 Aug 2019 09:37:41 +0000

Facebook’s reputation as one of the top social media platforms makes it an ideal marketing channel for consumer businesses. Apart from Facebook business pages and ads, brands can now use Facebook Messenger bots to keep customers engaged. They can avail chatbot messenger app integration services to maximize the benefits Facebook provides with its bot feature.

Integrating chatbots (or bots) with Facebook Messenger is enabling brands to scale their customer interactions. A chatbot (or bot) is a piece of automated software that provides automatic responses to customer chats. They are programmed to understand basic questions, provide answers, and execute various tasks.

According to Gartner, by 2020, 85% of our engagement with businesses will be done without interacting with another human. Instead, we’ll be using self-service options and chatbots. It is already happening with over 300,000 active chatbots on Facebook Messenger today.

Messenger chatbots share the same simplicity and convenience as human customer service executives. Consumers don’t have to open several apps or links to find the information they are looking for. All they have to do is have a normal conversation with the bot.

In this blog post, we will discuss the importance of integrating a chatbot with Facebook Messenger and how to do it.

The Benefits

Leads generation and engagement: While website chatbots yield information about those interested in your services, Facebook Messenger bots provide more engagement opportunities. Messenger bots can not only obtain precise information but also engage potential customers when they appear online.

Seamless conversations: A traditional chat always starts from scratch, even if the same user visits your site twice. But, with a Facebook chatbot, the conversation always has context. Previous messages you have exchanged with a user will appear, and the chat can continue even after they leave the site.

Improved user experience: Since Facebook Messenger bot provides a familiar user interface, users are more likely to respond to your messages.

Targeting potential customers: Facebook messengers have sponsored ads, which can be sent to anyone who has previously interacted with a particular business page. You can use these ads with your chatbot to target potential customers.

Engaging push notifications: With your bot in Messenger, you have the option to handle users manually or automatically. You can send them follow-ups or reminder drip campaigns and keep them engaged after the initial conversation.

Re-engaging customers: As opposed to advertising, a Facebook Messenger bot can reach out personally with relevant content at the right time. For instance, you can remind a customer that they sent a birthday gift to their sister this time last year.

Improving customer service: Facebook Messenger bots provide prompt autonomous responses to potential customers.

How smart businesses are using Facebook Messenger bots

Personal care and beauty chain Sephora’s bot eliminates five steps from booking a makeover in one of their stores. It has increased their booking rate by 11%.

Woebot, a downloadable chatbot acts as a robotic therapist. It is very useful for people who need to monitor their moods and follow-up with themselves on a regular basis. It provides a non-intrusive way for people to keep track of their self-care without visiting a real therapist.

Kayak is an air ticket and hotel booking platform that uses Facebook Messenger bot to serve customers. It provides attractive recommendations, sends updates about planned trips, and evaluates the best travel times.

Concluding Thoughts

Gradual development in chatbot integration will enable companies to provide better and faster customer service. Facebook Messenger bot has set new standards in efficiency and customer satisfaction. It is enabling businesses to offer a wide range of services.

From reaching your target audience to re-engaging customers, chatbots can play a very vital role in enhancing business processes. With Chatbot App Development Services
, companies are developing AI chatbots to augment their customer service efforts.

Choose Oodles for Chatbot Messenger App Integration Services

Our experienced team develops AI chatbots and integrates them with business applications. Our chatbot integration services on existing chat platforms enable your business to reach a broader audience.

Get a step ahead with our chatbot app integration services. Click here to get started.

Conversational Banking: Future of Banks with Chatbots

Oodles AI — Tue, 20 Aug 2019 06:26:24 +0000

Less than three decades ago, the banking industry experienced disruption with the digitization of multiple processes. It was sparked by the proliferation of desktop PCs, fast processors, and the advent of the internet. With further advancements in banking technology, customers were able to review their financial transactions, check account balances, and pay bills according to their convenience. The next wave of transformation in banking is led by AI technologies.

Chatbot Application Development Services enable banks to consolidate their internet and mobile banking services with a single platform. It provides a unified user experience across various channels like online banking, mobile banking, and ATM services with a more personalized experience.

Chatbots developed using AI and ML techniques enable banks and financial institutions to reduce costs with significant improvement in customer satisfaction. It establishes two-way communication, and in many cases, replaces channels like phone, email or text. Moreover, customers can ask questions or request services in a conversational manner. The goal is to provide effective customer service and transactional support using a chatbot, freeing customer care agents’ time to resolve complex issues.

In this blog post, we will discuss how conversational AI technology enables banks to establish long-term relationships with their customers.

The Benefits
Frequently Asked Questions (FAQs): Leading banks and financial institutions are strengthening customer relations with AI. One of the most basic tasks of a banking chatbot is to provide an automated service. It may include requests such as resetting a password, blocking lost cards, finding the closest ATM, and much more.

Some banks have developed bots that assist customers to block their cards instantly in case of misuse or theft. They ask certain questions related to the card and an OTP is sent to the registered mobile number. Once fed, the card is blocked instantly.

Increasing customer satisfaction: Chatbots have the potential to enhance customer satisfaction by answering a host of queries within seconds. A majority of customers want prompt responses to their queries and an IVR system often puts their calls in queues. It leads to bad customer experience.

Chatbots are effective in improving the customer experience. They provide real-time responses to simple queries raised by customers. With predictive analysis, the bots can gauge customers’ intent and answer accordingly.

Bank of America introduced an AI-based virtual assistant called Erica. It effectively caters to the bank’s customer service requirements in a number of ways. It notifies the customers, provides balance information, money-saving tips, and credit report updates. Erica also assists customers to perform simple transactions and take important financial decisions. As of early 2019, Erica surpassed 6 million users and has serviced over 35 million customer requests.

Suggesting products and services: Apart from answering common FAQs related to banking operations, bots are also being used in customized product recommendations. For example, if a customer inquiries about a personal loan, the bot lists all available products offered by the bank. Additionally, it can calculate a customer’s loan eligibility and the loan amount based on the inputs provided.

Financial goal setting and spend tracking: Chatbots have the potential to answer customers’ queries related to budget and other financial activities. Clari, a newly launched chatbot was integrated into TD bank’s top-ranked mobile app. It empowers customers with in-the-moment personal spending insights and enables them to make everyday transactions. Clari provides a personalized experience to customers by using conversational artificial intelligence.

Reduced costs: Deploying a fully-functional chatbot is much cheaper than developing a cross-platform application or hiring staff for each task. Businesses now have multiple options to choose from such as ready-made software developed by Microsoft, Facebook and other tech giants. They can handle multiple customers simultaneously. As a result, costs and errors resulting from human errors can be minimized to a great extent.

Closing Thoughts
The adoption of conversational AI services is rising in the banking industry. AI-powered chatbots have demonstrated their ability to handle queries and keep customers engaged at every stage of the customer life cycle.

Why Choose Oodles for Chatbot Development Services
We develop intelligent virtual assistants to conduct meaningful conversations and reduce customer service costs. We integrate third-party AI applications provided by leading platforms to accelerate chatbot development. Talk to our AI team to avail chatbots with advanced features.

Gain a competitive edge with our Chatbot App Development Services. Talk to us now for a demo

How AI Is Transforming The Healthcare Sector

Oodles AI — Fri, 16 Aug 2019 06:55:06 +0000

Artificial intelligence is a rapidly emerging technology that can transform the healthcare industry. AI solutions can diagnose illnesses with significant accuracy. With the latest advancements in science and technology, researchers are exploring new ways to improve medical facilities using AI applications.

The effectiveness of computer-aided diagnosis (CAD), virtual assistants, and clinical decision support systems is due to AI algorithms. From hospital care to clinical research, drug development and insurance, AI applications are making a big impact throughout the industry.

AI solutions enable doctors and surgeons to make well-informed decisions by efficiently analyzing historical health reports of patients. They enable medical institutions to gain detailed insights into diagnostics, care procedures, action unpredictability, and patient outcomes. Accenture predicts that AI applications can provide annual savings of $150 billion by 2026.

In this blog post, we will explore how AI is going to play a crucial role in transforming the healthcare industry with new technological innovations.

Advantages of Artificial Intelligence in Healthcare

Virtual Health Assistants (VHA)

As healthcare technologies continue to evolve, VHAs can proactively assist patients in a number of ways. For instance, VHAs enable dementia patients to stay on course with their medicines by providing expert suggestions. They enable doctors to interact with their patients periodically and suggest medicine refills. VHAs also enable patients to keep tabs on the progress they make towards recovery.

Well-informed Decisions

AI solutions can improve the accuracy of clinical documentation to detect anomalies. It is enabling clinicians to focus better on delivering effective patient care. The applications of AI technologies improve clinical decision-making and diagnosis. During medical emergencies, AI neural networks can provide inputs to treat patients instantly by analyzing their medical history.

Reduce Human Mistakes

Errors in healthcare have grave implications on patient care with fatal consequences. The complications involved in treating critically ill patients create challenges for doctors and surgeons to treat patients. AI healthcare solutions can significantly reduce human errors and doctor fatigue. In addition, studies have revealed that AI and ML algorithms can enable doctors to outperform their counterparts to diagnose certain illnesses.

AI-based Visual Tools

AI technologies can detect and rectify anomalies that might be missed by humans. An AI-powered visual recognition software can use the same technique used by specialists to diagnose diseases 5% more accurately. The tool can scan numerous clinical images and compare them to provide an accurate and quick diagnosis. Researchers believe that the accuracy gap between human and digital eye is expected to increase with further advances in AI technology.

Advancement in treatments

AI is helpful in improving treatment methods and monitoring patient health. It can immediately recognize the symptoms of various diseases, allowing a quick diagnosis to provide timely care. A startup in San Francisco is using AI to explore how machines learn by observing doctors. Instead of analyzing the data generated by doctors, the machine can follow its procedures step-by-step. Their AI records enable doctors to formulate effective treatments for their speedy recovery.

Concluding Thoughts

AI has the potential to eliminate diagnostic challenges to avoid fatalities. Medical care is expected to improve with AI advancements. Diagnosis of rare diseases or the detection of chronic diseases at an early stage is already possible. Since AI solutions can aggregate and examine a large variety of data, they can facilitate quick and accurate diagnosis.

Transform your business with Artificial Intelligence Services

We introduce AI in your business operations with smart applications developed by our Artificial Intelligence services team. Our AI app development services enable you to accelerate processes and serve customers better.

Talk to us for a demo of our work. Click here to get started.

AI Chatbot Integration Services on Various Social Media platforms

Oodles AI — Wed, 14 Aug 2019 10:52:44 +0000

Chatbots can provide round the clock customer support by effectively handling thousands of conversations at the same time. It enables customer care executives to focus on complex cases without requiring customers to queue up for a long time. With the proliferation of social media, it has become the preferred choice of customers to voice their concerns with businesses. According to a report published by Smartinsights, an average adult spends 5 hours per day on mobile. Out of this, 50% is spent on social media.

Leading businesses now use chatbots as an essential part of their CRM operations. The operational efficiency of chatbots is responsible for their widespread adoption. In this blog post, we have discussed the benefits of chatbot integration across popular social media platforms.

Benefits of Chatbot Integration
Integrating chatbots with social networks results in customer service automation. A chatbot replaces human customer care executives with smart responses. It can extract useful information about customers’ likes and buying habits to serve them better.

People are more concerned about spending less time in shopping. They prefer to use their smartphones to evaluate their favorite products and buy them. For instance, Amazon Echo users can shop for products using voice commands.

We often face difficulties while trying to find an important piece of information on the internet. It happens because sometimes we don’t find the right term to search for. Since a chatbot can interact with us as humans do, it can easily provide the right information in no time.

Customers expect round the clock access to information and answers to queries. Implementing a chatbot augments your customer service efforts across social channels preferred by your customers.

Chatbot integration across leading social media platforms
Every social media network attracts users from a unique demographic group that has its own purpose and motivation. Nevertheless, chatbots are a universal option to serve customers on different social platforms. Let’s explore their use on popular social media platforms.

WhatsApp
WhatsApp is an ideal platform to market brands, products, and services. The messaging app ran several beta tests on their WhatsApp for a business platform which now has more than 3 million users. Chatbots that connect artificial intelligence with customer experience is an ideal choice for WhatsApp.

Being the preferred messaging app for over 1.5 billion people, WhatsApp provides an ideal customer service platform with its chatbot features. WhatsApp has launched a standalone business tool to improve customer interactions and communications. With the advent of WhatsApp Business App, several established businesses and new enterprises are experiencing better interactions with customers.

Slack
Slack’s chatbot known as Slackbot can automate repeated tasks like sending DMs, post messages or upload files. It acts as an email management tool, sends reminders to team members, and analyzes data.

Slackbots can be integrated with other platforms to improve sales operations. They can sell goods, enabling users to order food, hire taxis, and avail other services without leaving their Slack channels.

Companies like 1-800-Flowers, Uber and Lyft enable their users to place orders directly from their Slack channels.

Facebook Messenger
Integrating a chatbot with Facebook fanpage can increase the volume of daily chats with your followers and potential customers. Messenger integration allows you to quickly include bots on Facebook fan pages.

Headliner Labs found that people are 3.5 times more likely to read a Facebook message than a marketing email. Since customers can respond by clicking a CTA button, they’re more likely to engage with businesses.

Moreover, Facebook messengers have sponsored ads, which can be sent to anyone who has previously interacted with a particular business page. You can use these ads with your chatbot to target potential customers.

Concluding Thoughts
Gradual AI improvements will enable companies to provide faster and better customer service. Chatbot integration with social media platforms has set new standards in efficiency and customer satisfaction. Businesses are in a better position to strengthen their customer relations using chatbots.

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Benefits of Using AI Chatbots in Insurance

Oodles AI — Mon, 12 Aug 2019 11:04:44 +0000

Today, chatbots are enabling new efficiencies by resolving thousands of queries simultaneously. As new technologies make bots more intelligent, their applications in the insurance industry are bound to increase in the coming years. With the help of chatbots, insurance companies can explain complex products to their customers, improve sales, and drive brand engagement.

Although AI initiatives in the insurance industry are in their infancy, Accenture

estimates that big investments in AI can increase the annual profitability of insurers by 20%. Chatbots will find their way into the insurance world with more AI advancements. They improve customer experience and speed up the claims process. This blog post explores the new ways in which chatbots are transforming the insurance industry.

The global rise of chatbot popularity

There are several factors that fuel the proliferation of chatbots. A few of them are the advancements in AI and related cognitive technologies, the rise of messaging apps, a fascination with conversational user interfaces, and a wider reach of automation. The global chatbot market is expected to reach USD1.25 billion by 2025, growing at a CAGR of 24.3%.

Leading enterprises see chatbots not only as a means of reducing operational costs but also enhancing the customer experience. A

2017 report says, 41% of businesses have implemented chatbots or have prepared cognitive AI technologies to be implemented soon. It includes 34% of businesses who have already launched a pilot prototype. In another study, one-third of AI start-up founders said that chatbots would be the top consumer application over the next five years.

How Chatbots add value to Insurance Companies
Chatbots are used for a different sort of tasks, however, finding the perfect fit for your industry is very important. Here are a few basic tasks where chatbots can help in the insurance industry:

Policy Queries
Insurance policyholders don’t remember every little information an insurance company’s policy offers them. Often, they find it difficult to navigate through the policy documents to find the required answers. A policyholder might want to know whether or not their spouse is covered under the current insurance policy. Someone might want to know the list of hospitals that are covered under the cashless scheme. In such scenarios, they often reach out to customer service for answers. People, these days prefer to just send their queries to a bot rather than go through the effort of calling someone. A bot can easily assist customers to find answers to their questions, instantly.

Filling a Claim
Chatbots can help insurance policyholders to quickly check their existing coverages. They can teach how to file insurance claims and track claims status. With no paperwork, insurance companies can improve customer satisfaction by accelerating the claims procedure. However, the overall process duration varies with the type of claims, but, chatbots can certainly lessen insurance wait times.

Customer Service
Customers can communicate with a chatbot in a way similar to an online conversation with a live customer support executive. Since many chatbots use NLP methods, they can analyze customer’s queries and deliver an accurate response. Customers have a common concern about the delay in response due to the use of IVR systems. These systems ask the customer questions and route the calls based on the customer’s responses. However, a chatbot can be used in a similar way, but in a more efficient manner.

New Policy Suggestions
Insurance companies are gradually using AI to sell policies and assist customers with insurance advice. Since chatbots communicate through textual or auditory methods, they have started replacing humans at insurance firms. ICICI Lombard is using a program called MyRA. It is used to underwrite two-wheeler insurance as well as fire and burglary insurance for SMEs and offer them quotations in real-time.

Future of Chatbots in the Insurance Industry
Gradual AI improvements will keep insurance companies at the forefront. As chatbots become smarter, they have ushered in new standards in efficiency and customer satisfaction for the insurance industry.

Although some insurers have reduced the tedious tasks in traditional processes, customers frequently experience long wait times even for a single request. Chatbots not only strengthen policyholders’ relationships with their insurers but also drive sales through touchpoints that span a range of digital channels.

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Conversational AI: The Advanced Form of Chatbots

Oodles AI — Wed, 07 Aug 2019 07:01:57 +0000

Healthy customer relations are an outcome of efficiently managed customer support channels. Leading enterprises now use chatbots on their websites and mobile apps to augment their customer service efforts. Chatbots are effective at handling routine customer interactions in real-time to improve customer relations, making them an ideal choice for CRM.

Early chatbot applications were limited in their scope. However, recent machine learning and natural language processing (NLP) advancements have increased their capabilities with new innovative features. A growing number of businesses now handle a significant volume of customer interactions by integrating chatbots into their CRM systems. This blog post explores the different ways in which the conversational features of chatbots can be enhanced.

Adding human-like capabilities to chatbots

Adding human-like features to chatbots or giving them a human name may not be enough to effectively engage customers. They must maintain a conversation back-and-forth with the person on the other end. A popular journal, Computers in Human Behavior has suggested that chatbots with human features that lack interactivity disappoint users.

Although chatbots are enabling businesses to handle a variety of interactions, several mechanisms and techniques are available to enhance their capabilities. Leading consumer brands use NLP mechanisms to analyze customer interactions and provide inputs to decision-makers. NLP enabled chatbots can assess the intent of input from users and create human-like responses with contextual analysis.

Royal Bank of Scotland uses NLP in their chatbots to enhance customer experience through text analysis. They interpret customer feedback gathered from surveys, call center discussions, complaints, and emails. It enables them to improve their services by identifying the root cause of customer dissatisfaction.

The importance of NLP for a chatbot application is in addressing customer concerns in real-time. A chatbot uses NLP to communicate with customers like human customer service agents. An effective chatbot can respond to customer queries accurately. It identifies the relevant information in the conversation to automate and accelerate customer service processes.

Chatbots as Reliable Customer Assistants

Eugenia Kuyda, co-founder and CEO at Luka, created a chatbot named Replika. She wanted it to stand out among the voice assistants and home robots that had begun to take root in peoples’ lives. AI chatbots are now capable of scheduling an appointment or sharing updates about weather forecast simply by sending a voice note. It uses neural networks to hold an ongoing conversation and gradually learn how to speak like a human being. More than 2 million people have downloaded the Replika app. Many individuals discovered something like friendship, a digital companion with whom to lament failures, celebrate victories, and trade weird internet memes.

The information collected daily when combined with previous data improves the work process of conversational AI. The system becomes smarter with new chunks of information as they are programmed to work in specific ways. It analyzes relevant keywords based on communication and natural language processing to learn about users’ interests and preferences. It enables Chatbots to provide a personalized customer experience.

With the developments still on, conversational AI is adding new skills to redefine user experience by solving the challenges. Further, it improves customer satisfaction and the company's growth simultaneously.

Future of conversational AI chatbots
A survey was conducted by Usabilla to figure out peoples’ preferences about chatbots. 54 percent of the respondents preferred chatbots over human customer care representatives, even if it saves ten minutes of their time.

Businesses identify the need for a system that provides more human-like responses, if not completely human. Chatbots are not here to replace human agents but to improve their work quality. Using NLP and sentiment analysis chatbots can infer customer's tone from any text document.

Soon, it will be possible to understand higher-level interactions like emotions or sarcasm.

AI-powered chatbots have made a significant impact on businesses since their advent. Researchers are rigorously training them to effectively handle customer queries and improve customer satisfaction level.

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Artificial Intelligence to speed up trip planning

Oodles AI — Thu, 01 Aug 2019 07:37:20 +0000

Until two decades ago, planning a trip was a strenuous activity that involved scouting for a reliable travel agent to arrange trips and book accommodation. With the advent of the internet, things began to change. Travel websites like Expedia and Orbitz have enabled vacationers to book everything online with minimal hassle.

Now, artificial intelligence (AI) is all set to revamp the travel experience of millions of travelers several innovations. AI-powered systems can provide smart recommendations to personalize trips and create itineraries for enriching travel experiences.

AI-powered systems can identify and suggest new travel destinations to users based on their travel history. At the same time, machine learning algorithms can enable them to populate itineraries depending on factors like weather conditions and ongoing activities.

According to a survey by Booking.com, nearly one-third of travelers are comfortable letting a computer plan their trip by accessing their travel history. Using AI, travel agencies are now able to create tailored recommendations based on a host of unique preferences.

AI-based trip planning solutions aim to overcome travel challenges with advanced recommendation features. This blog post highlights the key benefits of artificial intelligence and how it streamlines operations in the travel industry.

How artificial intelligence applications populate itineraries with efficiency?
Researchers are exploring new possibilities with AI to transform different industries. From retail to finance and F&B, AI has influenced every industry in one way or another. Similarly, leading travel and tourism industry players have now adopted AI and machine learning to improve the travel experiences of millions of individuals.

According to Google, 85% of leisure travelers finalize their activities after arriving at their destination. Due to this, they lose valuable travel time by picking up the spots to travel. Travelers also miss out on a few places on their itinerary due to time constraints. Therefore, there has been a dire need for travel planners that save time so travelers can enjoy their trip.

Companies are formulating mechanisms to create real-time and personalized itineraries for travelers using AI. The idea is to cut short the planning time and present options based on specified preferences.

In 2018, TUI Group and AI-powered trip-planning service Utrip, teamed up to create a personalized trip planning service. This online tool asks travelers to rate their preferences across various categories, like “Food & Drink”, “Nature & Adventure”, “Shopping”, and “Relaxation”. Additional filters such as “Trip Style”, “Travelling With”, and “Trip Purpose” help to refine things further. Utrip’s AI algorithm then analyzes millions of potential combinations to create a personalized itinerary for the entire trip.

With AI’s immense potential, travel agencies are now adopting AI mechanisms to evaluate traveler needs more effectively. It is providing faster and cheaper ways to improve their offerings.

AI mechanisms improve the travel experience

Smart recommendations that enable travelers to save time go a long way in improving satisfaction levels. Travel companies are extensively using AI technologies like machine learning (ML) and natural language programming (NLP) to improve customer experiences. They are mining customer data and using analytics to predict customer behavior and intent. In addition, they keep travelers updated about their travel schedule.

For instance, a new start-up, Lola revolutionized the concept of travel agents by making trip planning more convenient. Lola uses AI algorithms to manage hundreds of clients at any given point of time.

How does it work? Lola users have to set up an account and punch in their debit or credit card details. They can simply send messages to a representative through the app mentioning their preferences for the trip. A traditional booking website requires users to type in dates, preferences, and other parameters, whereas Lola simplifies the process. Users can make requests in conversational language.

For example, users can type “need a flight to Sydney next weekend” instead of punching info into little boxes. These requests are analyzed by the company's AI and then forwarded to one of Lola's 15 human travel agents. With the help of computer-generated recommendations, an agent then sends potential itineraries and suggestions back to users.

Companies can learn from Lola’s trip planning capabilities and build more such platforms that connect travelers with their potential destinations.

Conclusion

Travelers love to explore new places and make memories but face challenged in planning trips beforehand. Travel agencies can use AI to render an extraordinary travel experience to their customers. Using AI-based applications, they can recommend travel options instantly. Providers of artificial intelligence services can develop travel solutions that make travel planning smarter and less time-consuming.

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