Implementing Chatbots and AI in Customer Engagement: A Data-driven Approach

One of the biggest things that is revolutionizing customer support in the digital age is the use of chatbots. These days, bots possess remarkable sophistication, particularly if they are powered by AI-driven mechanisms. This has truly evolved customer interactions in business. And thanks to the use of large-scale data analytics, companies are able to use their bots not only to replace customer service representatives, but also to redefine their customer relations altogether.

Why use chatbots?

A significant percentage of businesses have already started using AI-driven bots, and those that haven’t are in the planning stages of adding one. These digital instruments are truly revolutionizing the way companies plan their long-term strategies.

Bots are divided into different categories, depending on their overall purpose. The three main types of bots are the following:

  • Informational – Informational bots are programmed using Natural Language Processing (NLP) technology, and they are capable of providing general answers to customer questions. Things such as FAQs can be addressed by informational bots.
  • Personalized – Personalized bots are bots that integrate customer data that has already been collected by a company into its conversations. These bots can provide personalized suggestions and help with troubleshooting problems.
  • Transactional – Transactional bots go beyond providing recommendations and actually carry out transactions on behalf of customers. This saves time for both the company and the customer.

Devising a bot strategy

Based upon information that you gather from your data analytics systems, you can create and hone the bots that you use to engage in customer relations. The steps that you use should include the following:

  1. Deciding the purpose of your bot. You might actually have more than one, depending on what you want to accomplish. You can design your website/social media in such a way that, depending on what they click on initially, different bots might pop up.
  2. Figure out what channels you want to distribute through. Based upon your research, you can determine the channels that your customer base uses most frequently. Bots can be used in any number of places.
  3. Give your bot(s) characters. Again, bots are not what they used to be. These days, they have names, personalities, you can even program them to speak in different tones of voice. The characteristics that you choose should be in keeping with the results of your research, as well. If you have a young demographic as your customer base, for example, you’ll want to create a bot that is hip and addresses people in an appropriate manner.
  4. Be sure you get your opening question correct. Starting with the right question is critical to ensuring that people continue the conversation with your bot.

You can integrate your bot with customer engagement software to create, refine, and multiply your bots as you need.

Benefits of AI in the use of chatbots

Using AI in your development and the analysis of your chats is essential. AI uses a process known as deep learning to simulate the neural networks of the brain and uncover hidden meanings in people’s language. In using NLP, companies can look at the history of their customers’ chats to determine attitudes and feelings through their choice of words.

Through the use of predictive analysis, AI-powered tools are able to decode the information that is gathered from chatbots and generate insights that are more sophisticated than what humans might be capable of. These tools are actually able to make predictions about future customer behavior based upon the data gathered that the customers themselves might not even be aware of. This might sound ominous for some, but if put to constructive, ethical usage it can bring about radical developments in the way companies approach their customers.

Practical uses for AI-powered analytics

In analyzing the results of AI-driven data analytics, companies are able to refine their bot marketing strategies and speak to customer needs with much greater accuracy. Bots can be programmed to remember individual customer histories, how they felt about particular items, the number of times they asked different types of questions, etc. This helps not only in streamlining the individual customer experience, but also in improving customer satisfaction levels.

Data analysis also helps marketing departments design bots to suit different purposes. Depending on the results of their analysis, marketing teams can refine the programming of their bots to suit different demographics, geographies, target group preferences, etc. Data analytics service companies can help you to develop a custom software product to analyze data in accordance with your individual business needs.

Today’s bots are not yesterday’s, and tomorrow’s will be different still

We all remember the days of primitive chatbots, where they were something that immediately needed to be wiped off the screen. Now, far from being a mere annoyance, bots are being welcomed as things that know us, understand our needs, and are able to help us on the spot. This will only continue to evolve. Technology of the future will allow for people to take a more active involvement in the creation of their own tools, and the interactivity between user and technology will become much more nuanced.

There are some risks involved, of course. The companies that develop these technologies – as well as the ones who use them – will need to take measures to ensure data privacy, as well as protection from hackers. And they will need to ensure that bots utilize the right kind of data as the massive amounts available also include information that can be off the mark for a particular task.

Implementing Chatbots and AI in Customer Engagement: A Data-driven Approach was last updated February 28th, 2024 by Evelina Brown