Chatbots, or formally known as conversational agents, are software applications that are integrated into various platforms to automatically engage with incoming messages or actually start conversations in a naturally human way.
Now, the idea is not new. However, the implementation of chatbots by various businesses will continue to grow in 2021 and beyond.
Business Insider reported that the global chatbot market was expected to grow from $2.6 billion in 2019 to $9.4 billion in 2024, forecasting a compound annual growth rate of 29.7%. The same report also suggested that the highest growth in chatbot implementation would be in the retail and ecommerce industries, due to the increasing demand of providing customers with seamless omnichannel experiences.
That alone should be enough to convince you that chatbots are the way to handle customer relationships moving forward, but they will also continue to grow as internal tools for enterprise tools and nearly every industry will adopt the technology if it hasn’t already.
2020 was a year like none other; everyone experienced drastic changes in their lives within a span of weeks. In a time where human contact had to be limited, chatbots came in to fill the gap. Businesses that weren’t already there had to adopt digital transformation to conduct their operations.
Throughout this process, chatbots have been at the center of the fight against COVID-19. From supporting healthcare workers by enabling better communication between health authorities and the community to reshaping retail, chatbots have been supporting various industries to revive themselves. And contrary to some fears, chatbots are here to help, not replace the regular workforce.
Now that you understand the importance of chatbots, let’s discuss how they work.
How does a machine talk in a natural way? This is a question people often ask themselves when they think about implementing chatbots. The actual process of how chatbots are programmed and work is complex and requires deep technical knowledge, but the process of them being able to converse in a humanized way is very interesting and in fact easy to understand.
To process and optimally answer incoming queries, chatbots rely on knowledge bases. The incoming text is broken down and a combination of algorithms and patterns are used first to find the intent of the message.
To find the intent of the message, chatbots use natural language processing (NLP). This process helps the chatbot to extract the relevant information from the text. NLP is the framework that enables conversational assistants to understand the context of the conversation and decode the intent (positive or negative), hence organizing queries into categories that allow the bot to select the appropriate auto response or escalate the issue to a customer care agent.
The first generation of chatbots were purely configured for text-based conversations, but thanks to technological innovations and advanced NLP, there are bots that can conduct speech-to-text and speech-to-speech conversations (e.g. Siri, Alexa, etc.).
The task of computers understanding human inputs and creating structured data from plain text is solved by NLP. However, the work of the chatbot does not end there.
After understanding the intent of the query, bots need to search for relevant structure data in the knowledge base framework and present it as unstructured text responses. The process of converting insightful structured data to plain text is taken care of by natural language generation (NLG).
The main function of chatbots is to assist customer care teams in handling FAQs, allowing them to focus on more important issues while giving customers the most valuable asset of all: time. In a survey, 66% of customers said that valuing their time was the most important thing a company could do to provide them with good service. Chatbots are a win-win in that regard, giving valuable time back to both the company and its customers.
To answer FAQs, most chatbots will use a set of predetermined responses created by the customer care team – this allows for a much more efficient management of incoming queries. With NLG in place, more advanced chatbots can even decode complex structural data and create plain text summaries for them, allowing live agents to work on other areas.
Overall, this process improves response times, as a large volume of queries can be answered directly by the chatbot, while the more complex cases will be transferred to a live customer care agent.
Chatbots are gaining significant popularity around the world. Due to the various convenience factors of chatbots, both organizations and customers are getting used to the idea of bots to drive conversations.
A 2019 survey found that 62% of US customers liked using chatbots to interact with businesses. The same study also found that for the surveyed European countries, the most demanded functionality (65%) was messaging. Companies such as Starbucks, eBay, and British Airways are among those that recently started using the technology.
Chatbots are not just used by B2C organizations; in fact the implementation in the B2B sector is higher. In an analysis conducted by Relay, 58% of companies with a chatbot feature were categorized as B2B.
The traditional use case for chatbots was in the customer service area; brands implemented chatbots in their operations to cater to customer complaints and generic requests. Now, the use of chatbots has expanded into more business areas, such as sales, marketing, and customer care. All of these departments have had to start thinking about how chatbots can help their business.
One way to stay ahead of the competition is to provide a seamless customer experience, and this is where the self-service benefits of chatbot come into play. Chatbots improve the customer journey at various steps by responding quickly and efficiently to frequently asked questions, or by seamlessly escalating the request, with the full context of the query, to a human agent.
Chatbots can be programmed to your specific needs: they can be programmed to answer the same way each time, to identify keywords in messages that trigger different messages, or even use machine learning to tweak the response according to the situation.
Chatbots can deliver enormous opportunities for business growth in various departments. The most common use of AI-driven conversational chatbots is for post-purchase customer service, but they can actually be deployed at any stage of the customer journey, from pre-purchase product queries to post-purchase reviews and complaint handling.
Imagine having a chatbot deployed on a job portal website, which asks you the optimum questions and guides to the perfect job offers without you needing to spend hours searching. Better yet, a virtual assistant of sorts that not only guides you to job offers but also lets you apply for a job of your liking via the chat, eliminating the need for you to open different tabs and getting lost in the process.
Chatbots also present key benefits by automating conversations and eliminating the need of having people waste time answering simple queries, and instead allowing them to focus on other matters.
Here are some of the key advantages of implementing a chatbot in your organization:
Personnel needing to cater to every customer query can waste a lot of their time that would be better spent helping customers in other areas. According to Harvard Business Review, the cost of a live-representative interaction (via phone, web-chat or email) for a B2C company is more than $7 and more than $12 for a B2B company.
Now pair this with the long waiting times that users might have to experience because agents can’t handle queries from various users at the same time as well as the time taken by the representative to search for the right information from various sources, and it can add up to a lot of overall costs.
Additionally, longer wait times also have a negative impact on customer experience. A study released by Juniper Research claims that chatbots will help businesses to save $8 billion annually by 2022. IBM predicts that chatbots can help reduce 30% of customer service costs by answering 80% of routine questions and speeding up response times, thus freeing up agents to handle more difficult questions.
Due to a chatbot’s ability to manage multiple tasks and offer faster, improved, and more efficient collaboration in the workplace, conversation agents are highly sought after. Gartner predicted that by 2022, 70% of white-collar workers would interact with conversational platforms on a daily basis.
Another reason for the high popularity is that chatbots can significantly simplify tasks. A task that originally used to take various steps can simply be achieved by a single verbal request (assuming the chatbot supports the language).
Data! It’s one of the most talked about topics in almost every industry. It’s extremely important to understand the type of conversions that users drive with your business and then adapt the process to deliver an optimum customer experience.
People can’t grasp every little detail from tons of conversations, and there is always a chance of missing out on important information due to human error. Chatbots are able to communicate and gather all information, which can later be used for various purposes. All incoming user queries can be classified as big data, as brands might have thousands of user conversations, if not more. Big data is defined by three characteristics, volume, velocity, and variety (the 3Vs).
Chatbots encounter all of these characteristics; the volume of incoming messages is immense, the velocity is high due to the ability of providing fast-paced information, and there is definitely variety as each customer is unique. Chatbots store all the information from each instance, creating a repository of real data that can be used to create better versions of the conversational agent or even product development when considering customer feedback.
Through chatbots and their data repositories, businesses can also optimize their knowledge bases according to the information the users want and not just have information the brand wants to convey. That’s how you successfully bridge the customer expectation gap.
As mentioned earlier, the popularity of chatbots has grown in the last few years, and it is only predicted to keep growing. Considering how millenials and the modern consumer prefer to interact with brands via messengers or chatbots, businesses can leverage this opportunity to generate leads and also, to some extent, qualify those leads.
Chatbots can help to get a better understanding of the audience such as likes and dislikes, product interests, etc., by proactively asking questions and storing information in the data repository. Bots can use this information for audience segmentation, enabling lead nurturing, and allowing brands to communicate ideal products/solutions.
Chatbots can also be used as a replacement for lead forms. This would be a new interactive experience for users and if the chatbot is completely integrated with the sales workflow, then new leads could be automatically created in the CRM system.
The final aspect of lead qualification can also be covered by chatbots. Chatbots can be programmed to ask specific prequalification questions and direct leads to the right team based on the responses for further nurturing. This would help in automating the sales funnel and allow sales reps to focus on more time-consuming tasks, such as closing deals!
This is one of the basic advantages of implementing a chatbot: 24/7 support without needing agents always standing by. Chatbots allow brands to constantly engage with their audiences and provide instant responses all throughout the year, without long-waiting times or having to inconvenience a representative at 2 a.m.
In a survey, 64% of respondents cited 24/7 availability as the top benefit of a chatbot, followed by getting an instant response and being able to answer simple questions.
This also helps in reducing operational costs as not so many live agents are required to sit on the back-end.
Technology and machines are good, but your human support team is still the backbone of your operation. There could be instances where chatbots are not able to respond to certain queries or requests as the necessary information could be missing in the backend knowledge base. Or, chatbots might not be able to understand the context of the message due to language or some complex key terminology.
In such cases it is important to have a live agent transfer system, where a human takes over the conversation. Since bots record all the information, there is no need for the user to explain themselves once more as the human agent receives the summary during the handover itself. The live agent simply picks up the conversation from the point the transfer was initiated, making the entire process seamless.
Whenever a live agent is required to take over, the chatbot informs the user about the transfer to make sure they know there might be a slight delay in response and in the meanwhile notifies a human agent to join the conversation.
A knowledge base can be defined as the brains behind the chatbot. This is a repository of data and information about a business, its offerings, etc., which is maintained and updated regularly and deployed by the chatbot at the right time (based on the context of the request). A well-structured knowledge base can enhance the effectiveness of a chatbot by helping it in delivering unified messages.
This is specifically helpful for businesses that have a multi-chatbot implementation (e.g. web, social, instant messaging, etc.). Once all these chatbots are linked to the same knowledge base, they will be able to provide unified communication to the same user even if they reach out via different touchpoints, defining a unified omnichannel experience.
In combination with NLP, chatbots need an expanding knowledge base that helps them recognize patterns and converse with appropriate responses. A knowledge base is what makes a chatbot truly intelligent and classifies it as an AI chatbot.
Chatbots that are connected to robust knowledge bases are able to drive AI-led and customer-centric conversations, and at the same time feed information to other resources such as CRM systems, marketing automation tools, FAQs, etc.
Personalization has been a focal point for marketing teams for many years. There have been many studies revealing that personalization leads to an enhanced customer experience, and rightly so as the customer receives customized information/products just for themselves.
Chatbots can also offer the same level of personalization that fulfills the psychological needs of the user. Gone are the days of one-size-fits-all thinking; modern chatbot solutions are highly customizable and are not shrink-wrapped generic solutions.
For example, the Astute Bot allows organizations of all sizes to create perfect personalized chatbots to cater to their audiences. Chatbots should serve as a user’s personal assistant who knows important information about them and can tailor the experience accordingly.
Personalized bots are able to remember and utilize information from prior conversations as this information is stored in a knowledge base. Truy personalized bots enable businesses to have a 1-to-1 conversation with each user, and they go beyond just focusing on demographics and product interests. By creating chatbots with personality and characteristics, organizations can enhance the customer journey and even increase conversion rates.
Strong customer experiences are a necessity. According to Chatbots and CX study, 31% of consumers expected a personalized experience in 2020. Chatbot personalization is also a major advantage for diverse businesses that function in multiple verticals, as one chatbot can then have various personas for different audience segments.
Chatbots can also be extremely helpful to drive net promoter score (NPS) and enhance overall customer satisfaction. NPS is a customer satisfaction benchmark that measures customer loyalty and how likely customers are to recommend a brand further.
NPS is measured through customer surveys on a 0-10 rating and presents three categories of customers: promoters (loyal), passives (indifferent), and detractors (unhappy). In general, customer surveys are not interactive and intuitive, and it can be challenging to convince users to participate.
With chatbots, businesses can implement conversational customer surveys that go beyond asking repetitive questions and collecting metrics. AI-driven conversational surveys talk to the customers to understand how they feel and why they marked a particular score.
Chatbot surveys allow users to express themselves in their own words and guide them throughout the process. Chatbots can also adapt the questions in real time based on previous behavior patterns – thanks to a knowledge base – and presenting only relevant topics to the specific customer. This enables organizations to actually learn and improve from customer feedback, leading to a possible higher NPS and improved overall customer satisfaction.
As an example, Astute’s voice of the customer solution enables businesses to drive targeted customer feedback to help elevate experiences using customer-centric insights.
At the end of the day, implementing chatbots is an investment of multiple resources: time, money, and manpower (developers as well as agents and representatives). Additionally, there would need to be a dedicated team to make sure the chatbot is functioning seamlessly at all times.
Every business needs some sort of an ROI to justify the business decision. There is no direct way of calculating ROI on chatbots as various factors have to be considered, but here are some simple calculations to help you get an initial idea.
The first thing would be to measure the time saved per query/ticket. This can be found by measuring the average time taken by a live agent to solve a query and then doing the same for the chatbot. Multiply this with the total average number of queries per month, and this would give you a good estimate of time saving.
The second factor to consider is the ROI from a workforce perspective. Agents can only attend to a single user at a time. On the other hand, chatbots can handle multiple queries from various users at the same time and are available 24/7.
With chatbot implementation, businesses do not have to hire live agents for basic inquiries and can instead let their workforce focus on the higher-level issues that will be transferred to them. That leads to a better allocation of funds and easier workforce management. The simple way to calculate this ROI would be to measure how much rudimentary work of one live agent could be handled by a chatbot.
Not all ROI is linked to monetary or time savings; some of it can also be measured in both workforce and user satisfaction.
Chatbots ease the workload of live agents, provide better information to various teams like marketing or sales, and help create a better lead-generation process. Also, due to the quick response times and ability to save all user information, chatbots provide fast and relevant information to each user and drive personalized conversations.
These factors result in higher satisfaction both for the customer and employees. Satisfied employees are willing to give a higher output and satisfied users can turn into loyal customers.
It is important to remember that ROI for every business will differ, as it depends on many factors, including:
The main question to consider is, “Are chatbots worthwhile for my business?” This is not a simple yes or no answer as it requires a deep analysis of your business, its operations, and most importantly measuring the average number of incoming digital queries.
If you only get two incoming requests per month, then of course the investment is not worthwhile. However, businesses with a digital presence inevitably get more user queries and either do not have a trained workforce to respond to such requests in an efficient manner or simply do not have enough live agents. This is where chatbots present their value.
The role of a chatbot is not to replace human agents; rather it is to support them by giving back time to focus on tasks and interactions that AI cannot effectively resolve.
By implementing chatbots in digital channels, businesses will enable the wider workforce to deal with more complex tasks and live agents to resolve queries that need human attention. This can be called a cohesive effort for the entire organization to enhance customer experience.
Whatever the key metrics to measure ROI might be, companies of all sizes and all industries can benefit from chatbots if implemented correctly. Chatbot technology empowers organizations to serve their customers with frictionless, omnichannel experiences and enables them to address the unique challenges of customer engagement. Socialbakers’ AI chatbot software provides a single platform for customer self-service across channels.