EVOLVING JOURNEY OF CHATBOTS

A surge in the use of smartphones has changed the way people communicate with each other. Most people now prefer to text or message their friends or family members when they want to speak with them. According to Statista - a leading provider of market and consumer data, the mobile phone messaging app users went up by 15.5% in 2017 and is projected to rise by another 10.8% in 2018, with the number of messaging app users touching 2.01 billion globally.

The adoption of messaging apps clearly indicates that customers prefer messaging, and expect to interact with the brands in the same manner. According to a study published by Chatbots Magazine, and I quote, “67% of consumers now expect to talk to retailers and service providers via chats”. Businesses are taking a notice of this and pursue to expand their definition of customer communications. Hence, the marketers aim to enhance their two-way conversational capabilities through conversational commerce resulting in the introduction of “Conversational Chatbot”.

Increasing number of brands are shifting their focus from the traditional digital communication channels to developing Artificial Intelligence (AI) and Natural Language Processing (NLP) enabled Conversational Chatbots, that go beyond providing simple buying options but create more personalized interactions.

As per a recent research report published by Capgemini, “The secret to winning Customers’ heart with Artificial Intelligence: Add Human Intelligence”, 73% of the survey respondents are aware of AI powered interactions, and of these AI-aware consumers 69% are satisfied with their AI-enabled interactions. Customers who prefer AI chatbots seek quicker resolution to their complaints, 24X7 accessibility, convenience over using separate apps, instant response in case of an emergency, or to allow them to keep a record of their conversations.

CUSTOMER EXPERIENCE THROUGH CHATBOTS

Chatbots empower the brands to redefine their overall customer experience. From helping them to find right pair of denims, analyzing their preferences to give updates on latest arrival, providing make-up tips, assist in flight booking, making payments or check balances, etc., Chatbots help business to provide cost effective customer support, responsive advice and instant help with consumer queries.

As stated by Van Baker, Research Vice President at Gartner, “by 2020, over 50% of medium to large enterprises will have deployed product Chatbots”.

While businesses are increasingly looking forward to leverage these conversational Chatbots for customer services, users have also experienced frustrations when the simplest commands have not been understood by the Chatbots, when they are forced to input their requirements in a specific format or when the transition to human customer representative has not been seamless.

Hence, it is safe to say that the effectiveness of the Chatbots relies heavily on how the users experience a conversation with it, usually referred to as Conversational UX. A good Conversational UX allows seamless interaction without forcing the user to alter the way they converse to get their commands or instructions executed. An excellent conversational UX assists users to find out what they are looking for in the shortest possible time and ensures user engagement. This encourages me to highlight an essential component of Chatbot i.e. “Content”. 

CONTEXTUALIZING CONTENT

While a lot of time is put in gathering the right set of technical components to develop a Chatbot, less has been thought about the importance of a “Content Strategy”. Devising an appropriate content mapping strategy can help shape the user experience which is directly linked to how quickly users can reach their goal. Creating a content strategy depends on the purpose, objective & audience of the Chatbot or to put it differently whether it is an Informational, Transactional or Advisory Chatbot.

It is essential to understand that the users don’t want to “Chat” with a Chatbot instead they are looking to find relevant information quickly and conveniently. Therefore, the effort of making a Chatbot successful rests heavily on Contextualizing Content. This can be achieved by understanding the information users are looking for during their interaction with the Chatbots. Whether you intend to use this virtual assistance internally to answer sales related queries, assist employees with HR related questions, or create an unmatched customer experience, surfacing the relevant information is of at-most importance. 

Hence, the content strategy should aim at a combination of creating new content (focusing on Cognitive Knowledge) and repurposing & contextualizing the existing structured & unstructured information available. Right from a welcome message to helping users navigate to relevant topics, provoking responses through response buttons and swiftly connecting them to a human executive in case of a failure (through a failure message); content strategy plays a crucial role in designing conversations. It also aims to understand the ‘intent’ of a human phrase thereafter identifying ‘entities’ and form ‘utterances’. 

LEARNING CURVE OF CHATBOTS

Deploying an AI Chatbot with a clearly defined, articulated and contextualized content is a good head start but isn’t an end. Instead, there begins a continuous loop of “Training and Teaching the Chatbot”. These virtual assistances are eventually expected to mimic human-like conversations by capitalizing on NLP that recognizes the same intent from the infinite ways the users ask a similar question and enables seamless conversations. Gartner predicts, 25% of customer service and support operations will integrate virtual customer assistant (VCA) or Chatbot technology across engagement channels by 2020, up from less than two percent in 2017. Enhancing conversational experience by using AI and NLP will depend heavily on what these systems learn. In recent past we have come across scenarios where the self-learning Chatbots have made to the headlines for creating their own secret languages or making offensive racist and sexist comments.

This isn’t surprising, because entire concept of AI and Machine Learning is based on the data fed to them. Hence, it is important to understand that the training and learning is crucial to create a mature Chatbot. "A Chatbot is like a baby, it needs to be nurtured and taught, you can't just set up a Chatbot and let it go," Said Rob Harles, Managing Director at Accenture Interactive. Therefore, it is essential to perform regular analysis of the conversations to understand customer dynamics, their requirements, what goes well in the conversation and the failure points. This evaluation helps the business to make their virtual assistance smart and enable them to assist customers to find what they are looking for and enhance customer experience.

With the growth of AI and NLP, Chatbots have potential of emulating human conversations and provide solutions to the consumers at their fingertips, but they have a long way to go. Brands need to understand that at this point Chatbots are not proficient to eliminate human interface completely. To begin with, they should focus on simple use cases and let human executives handle more complex and subjective requirements, along with training the Chatbots to tackle complex requests. “The secret to winning Customer’ heart with Artificial Intelligence: Add Human Intelligence” research also pointed out that 55% of the respondents would prefer to have interactions with a mix of AI and humans.  

CONCLUSION

According to a report ‘Chatbots Market: Global Industry Analysis’ published by Research and Markets, a leading market research firm, the global Chatbot market is forecasted to grow at a CAGR of 27.5% over the period of 2018-2024. While the business are willing to embrace conversational commerce and be a part of the Chatbot growth story, they also need to evaluate the areas where this implementation will bring value to both the customers and the business.

I would like to conclude this article with quoting Microsoft CEO, Satya Nadella - “People-to-people conversations, people-to-digital assistants, people-to-bots - that’s the world you’re going to get to see in the years to come.” 

Note: All views expressed above are based on compilation of various articles, studies and reports along with my personal understanding and interpretations of these reports.

#Chatbots #ConversationalUX #Virtualassistants #NLP #Machinelearning #Digitaltransformation #Digitalfuture

Sources:

Worldwide mobile phone messaging app user growth from 2016 to 2021: https://www.statista.com

Chatbot Report 2018: Global Trends and Analysis: www.chatbotmagazines.com

The Secret to Winning Customers’ Hearts with Artificial Intelligence: Add Human Intelligence: https://www.capgemini.com

Gartner Predictions: https://www.gartner.com

Chatbots Market: Global Industry Analysis, Trends, Market Size and Forecasts up to 2024: https://www.researchandmarkets.com

Adopting the power of Conversational UX – Deloitte Digital

References:

TechRepublic: Various articles related to Chatbots

Forbes: Various articles related to Chatbots