Introduction
Conversational AI has significantly impacted different professional domains: education, business, banking, construction, travel, etc. It goes beyond saying that the outreach of Conversational AI is immense, and the scope of the novel technology is greatly promising. Conversational marketing is the mantra for leading organizations if they want to stay ahead of others today.
Factors Leading to the Rise Of Conversational AI
Automation, speed, immersion, lead conversion, and convenience are the factors that determine the success of any organization today. This is where conversational AI comes to our aid. This state-of-the-art technology is revolutionizing businesses as they can deliver successfully on these parameters.
Changing Buying Trends
Consumer buying patterns are changing, where buyers prioritize interacting with the businesses in real-time. And, of late, real-time conversations between AI chatbots and consumers are a reality, thanks to conversational AI. Conversational marketing forums can influence the buying decisions of consumers by involving them in a one-to-one interaction. It plays a vital role in molding the buyer’s opinion about the product, its worth and helps in developing the reputation of the brand.
It is essential to understand the reason behind the surging demand for chatbots for businesses in developing a brand. They are programmed to take on the challenges posed by several browsing options at the buyer’s disposal. Thus, virtual assistants like chatbots for small businesses can accelerate the chances of conversion during a critical selection procedure.
Besides coming up with speedy responses to customer queries, chatbots come in handy as an in-house sales representative, enhancing the visibility of products and assisting a customer until the stage of final purchase. Consequently, it brings down the support costs of a business as multiple functions are performed simultaneously.
Conversational AI – One Stop Solution to Speed
Conversational AI comprises technologies like understanding and continuing a conversation. Hence, Conversational marketing can transform the process of consumer engagement completely. In an era of speedy and seamless communication, conversational AI is highly valued as it is quick at answering complicated questions efficiently and quickly. With 24*7 availability, virtual assistants like chatbots aided by conversational marketing don’t miss a single customer request that infinitely expands your business’s scalability.
Besides Natural Language Understanding (NLU), the other technological components of Conversational AI, such as Automatic Speech Recognition, Machine Learning (ML), and Advanced Dialog Management (ADM), makes a business scenario highly automated that eliminates errors.
The Demand For Ready Availability of Information
The demand for conversational marketing and its associated tools like chatbots for business is on a surge as they make information accessible. This is what the customers exactly want. You serve them best if you make data available to them at the tap of a button or in a single click. Hence, a tool like an AI chatbot can respond to customers’ inquiries or fetch data on your brand at the customers’ disposal instantly and lead them to the fastest solutions through self-service.
Rise of Deep Neural Networks
The steady demand for voice assistants has led it to be coupled with conversational AI. A watershed moment in conversational AI was when in 2019, Google introduced and open-sourced a neural network-based method for natural language processing (NLP), popularly known as the BERT model. This has led to Google’s speech recognition technology achieving an outstanding accuracy rate when comprehending inquiries spoken in English.
Conversational marketing as a domain is gradually making its giant strides in business. And coupled with neural networks, Conversational AI will become a potent tool for solving highly complex problems, which can be leveraged to a large extent in different sectors.
Machine Learning: The Driving Force
Machine Learning enables AI chatbots to self-learn and becomes ‘smarter’ all by themselves. The increasing demand for voice-enabled tools implies that the algorithms of voice technologies have access to large amounts of data, thus becoming more intuitive at an exponential rate.
ML as a viable technology can gain insights from raw data to solve data-intensive business problems swiftly. As a vital AI component for businesses, ML can help develop foresight on customer behaviors and buying patterns and help determine how to increase customer base and customer retention.
The Necessity of Decoding Human Emotions
The day is not far when voice assistants aided by conversational AI will be able to decipher customers’ emotions with foolproof accuracy. If conversational AI is thoughtfully implemented through chatbots for small businesses, it can bring on miraculous results for the brands- equipping them to target buyers with relevant offers based on their mood.
The Need For a Frictionless Consumer Interaction
A key implementation of conversational AI in commerce is its capacity to virtually reproduce the feel of visiting a shop and being assisted by a sales assistant, that too from the comfort of their homes.
By interacting with chatbots that runs on conversational marketing technology, customers can explain requirements without any hassle, place their inquiries, or get customized recommendations based on their purchase history and past behavior. Moreover, communicating with AI chatbots can seem like chatting with a friend, personalizing the experience, and making it more engaging.
Rising Need For Contactless Buying
COVID -19 has hit the retail sector hard. Hence, the abilities of voice assistants have been exploited to the fullest during this phase. Reports reveal that there’s been a sharp decline in offline shopping during the pandemic. So, if the powers of conversational AI are exploited to the fullest, there can be no limits to what the brands can achieve with an alternative of online shopping.
Reasons to Adopt Conversational AI Today
The rising technical complexities of mechanical systems are no longer challenging to handle these days. Conversational AI makes it possible to decode any intricacy owing to its different components that have made communication innovative yet straightforward. The article further talks about the reasons for implementing conversational marketing techniques.
Popular messaging platforms such as Facebook, WhatsApp, Telegram, etc., are actively taking the growth of conversational AI a step further.
Natural Language Processing (NLP)
Conversational AI is featured with Natural Language Processing (NLP), which helps understand the various human language layers. Conversational AI is equipped to manage instant pauses, rollbacks, or repetitive conversations.
NL technology analyzes visitor utterances for specific words, modifiers, and phrases like connotation and word positioning, typically referring to various emotional states. The tool generates average tone scores in real-time to examine user input, set off custom flows, put human agents on board, and drive conversations. The accuracy and efficiency of such automated self-services ensure a premium quality customer experience for brands.
Conversational marketing uses the components of NLP to the fullest by offering accumulated insights, overviews and recommending possible customized responses by tracing information and offering speedy resolutions.
With the rapid use of newly adopted technologies of conversational platforms, NLP is emerging to determine that conversations engineered by AI chatbots are spot-on and as personalized as possible.
Ability to Contextualize
Multiple contexts surface in a conversation when we talk to each other. However, human beings can comprehend, identify, and switch between contexts. The same is applicable for bots, thanks to the blessings of Conversational marketing technology.
Conversational AI identifies the intent and relevance of the message beyond the written text by analyzing the inquiry semantically and provides an accurate answer. Thus, chatbots can manage to switch between complex contexts effectively. This will help set up problem-solving chatbots for small businesses more efficiently and simply.
Conversational AI knows that every communication involves a specific context. It is also aware of the fact that in the context lies the essence of information. Conversational AI records the context from previous conversations. As a result, it can resume the dialogue from the exact endpoint—for instance, user preferences, information, queries, etc.
Sentiment Analysis
Conversational AI makes chatbots capable of comprehending the tone and emotion of the conversation by breaking down the phrases and sentences into single words. Each utterance or word is further examined, considering its critical connotations and positioning in the sentence. Every word can be regarded as an individual metric that defines the nature of the emotion articulated through the conversation.
Although many businesses aim to replace or improve their traditional live agent experience with advanced technologies such as bots, they don’t want to miss out on the human touch present in a conversation. Sentiment analysis allows chatbots to comprehend the user’s mood by decoding syntactic and sentence structure cues. Thus, bots can handle the amiable customers themselves and identify the unhappier customers whose calls are transferred to human agents.
Understands Multiple Languages
Conversational AI is equipped to understand almost every language. Named Entity Recognition (NER) is a vital component of Natural Language Processing (NLP), enabling bots to respond to specifications. By virtue of NER, AI chatbots accurately understand relevant information in the inputted text, such as location, time, and date that web visitors enter using different languages.
For a chatbot to comprehend the specifics of multiple languages, it is necessary to identify entities in these languages. NER equips a bot with such multilingual abilities. A chatbot for small businesses facilitated with conversational AI imparts multilingual support without the aid of a translator. Preparing bots to interact in more than one language has manifold consequences for an organization.
- It would ensure a first-rate consumer experience by eliminating chances of bot breaks prompted by web visitors inputting queries in vernacular languages.
- Equipping AI chatbots with the ability to converse in regional or other non-English mediums would make an organization accessible to the vast number of customers hailing from diverse linguistic backgrounds who are increasingly approaching digital forums and interfaces for an enormous range of requirements and wants.
- Multilingually programmed chatbots will be able to cater to large volumes of queries and thus, can increase an organization’s outreach among a more significant number of people. This can help a business foray into regional markets and create brand awareness among people of different cultures. Hence, conversational marketing influences the growth of your business by enabling you to gain clients across the globe.
Provides Behavioral Analytics For Chatbots
Chatbots are deployed for assembling metadata on the users. And, the analytics of conversational marketing scrutinizes the information provided by the data and delivers vital insights into what is needed. Conversational AI provides a visual representation of the user journey by plotting the flow of dialogue in the conversation between the user and the bot. This dialogic flow defines the behavior and the intent of the user.
The benefits of Conversational AI’s behavioral analytics are manifold. It gears an organization up for taking preemptive measures to upgrade its future performance in the following ways:
- Resolving Problems on the First Call: Every consumer service aims to fix issues on the first call with the customer. The behavioral analytics of Conversational AI helps agents identify escalation better, learn from previous hits and misses, and resolve issues quicker.
- Identify Scopes For Up-sell: Behavioral analytics helps identify red flags before a customer decides to abandon your services. It also identifies the best chances for upsells based on consumer emotion and behavior encrypted in call data.
- Analyzing Buyer Journey: Conversational analytics helps channelize the opportunities for sales and marketing professionals to identify the deciding points in a buyer’s journey towards a call to action.
- Predict Future Behavior – As conversational analytics predict behavior for the future, AI chatbots can gain real-time insights on the best time to take action and the ways of doing so.
Conclusion
The inclusion of conversational AI in organizations will bring a sea change in our lives. Integrated voice assistants built by no code bot-building forums like WotNot will significantly influence our behavior and consumption patterns as such systems gradually attain a greater level of sophistication.
No matter how complicated Conversational AI may seem, WotNot makes the technology simple with its no-code bot builder. It makes designing and implementing powerful and innovative AI chatbot interfaces within a nick of time a reality. Thus, businesses can’t help but adopt this versatile technology as its multiplex benefits will take organizational abilities to new heights.
