Best Practices for Integrating Chatbots Into Your Business

By Josias Hartmann, Indicium

When it comes to integrating chatbots into business operations, the question is no longer if businesses should adopt chatbots. Instead, it's how they can best go about leveraging chatbots to gain efficiencies and unlock new forms of value.

That's because modern AI technologies — especially generative AI models and multimodal capabilities — have made today's generation of chatbots significantly more powerful. At the same time, chatbots have become easier to deploy in some respects, thanks to options like the ability to outsource chatbot development to third-party AI development experts. In a world where chatbots have so much to offer and are relatively simple to deploy, there's little reason not to use them.

Exactly how businesses should best go about implementing and managing chatbots, however, remains an open question. And while there are no simple answers, there are important pointers and best practices to keep in mind to unlock the full potential of modern chatbots, as I explain in this article.

Why Businesses Need Chatbots

Chatbots are hardly new. Arguably, chatbot technology dates all the way back to the 1960s, when an MIT professor introduced the first computer program capable of engaging humans in conversation. In more recent decades, chatbots have become commonplace in some business environments as tools for answering customer questions or helping to automate basic operations.

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Over the past few years, however, we've seen the emergence of a fundamentally new breed of chatbots. Instead of using techniques like dialog trees (which are inventories of fixed responses that a chatbot can issue to predetermined queries), modern chatbots are in many cases powered by large language models (LLMs), the type of technology behind generative AI services like ChatGPT. In addition, many of today's chatbots are multimodal, meaning that they can engage humans in conversation and generate content via text, voice, image, and video.

These advancements have resulted in much more powerful and flexible chatbots — as well as surging adoption of chatbots by businesses. Fifty-eight percent of B2B companies currently deploy chatbots, and analysts predict a 23.3% CAGR for the chatbot for the remainder of the decade.

Trends like these mean that chatbots are no longer a nice-to-have resource for the typical business. They are evolving into a critical type of asset that organizations need if they want to remain efficient and competitive.

Best Practices for Leveraging Modern Chatbots

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That said, simply deploying a chatbot is no guarantee that your business will gain a competitive edge or enjoy critical efficiencies. If you want to leverage chatbots to their fullest effect, you need to think beyond conventional approaches to chatbot deployment.

The following best practices can help.

1. Don't restrict chatbots to simplistic use cases

Historically, most chatbot use cases have centered on relatively simplistic needs, like handling basic customer support needs. Businesses can and should use modern chatbots for these tasks, but they should also leverage chatbots for more sophisticated purposes — such as automating complex business processes and helping employees predict customer behavior.

In other words, don't think of chatbots merely as a way to direct customers to documentation databases or route questions. Instead, think of them as a core part of your business operations, including but not limited to those involving customer support.

2. Measure chatbot ROI

To ensure that chatbots actually create the value you intend, it's critical to track chatbot ROI in a systematic way. To do this well, look beyond basic metrics like cost savings or the query volumes of your chatbots. Instead, measure KPIs like customer satisfaction scores, support response times, engagement levels, and conversion rates. By monitoring how these KPIs change after you deploy chatbots, or after you tweak the way your chatbots work, you can measure how much value chatbots are truly bringing to your business.

3. Develop the right chatbot acquisition strategy

There are three basic ways to go about creating a chatbot. One is to build it yourself. This approach offers the greatest level of control and customizability, but it also requires deep and extensive AI development skills on the part of your business. You'll need programmers who understand key concepts in machine learning (ML) and natural language processing (NLP), and who possess expertise in working with tools like vector databases for efficient data storage and retrieval-augmented generation (RAG) for enhancing chatbot response quality.

Another approach to chatbot acquisition is to purchase an off-the-shelf solution. This tends to be much faster and simpler, but the downside is that you are restricted to the functionality that the chatbot vendor supports, and you typically can't customize the chatbot extensively.

A third option is to work with an outsourced chatbot development firm to build a chatbot tailored to your needs. This way, you don't have to hire your own AI experts, but you still get a custom chatbot.

The best approach to acquiring a chatbot varies based on business needs and priorities. But whichever strategy you choose, it's important to assess your various options and the pros and cons of each, rather than defaulting to a certain approach simply because you didn't consider alternatives.

4. Ensure that your chatbot strategy can scale

At first, it's common for businesses to deploy just one or two chatbots and to use them on a limited scale. But over time, organizations typically add more chatbots and increase the number and complexity of queries they need to handle.

To ensure that you can scale your chatbot strategy up and keep your chatbots in sync with changing business needs, think from the start about how your chatbots will change and scale over time. For instance, you might decide to leverage cloud infrastructure (as opposed to hosting chatbots on-prem) to help your chatbots handle increasing query volume. You should consider whether the LLMs and training data you use to power your chatbots are flexible enough to support a range of business use cases, even if you don't target all of them at the outset.

Conclusion: The Path to Chatbot Success

In short, chatbots are quickly transitioning from a peripheral technology that addresses a narrow range of use cases into a core component of business operations. To keep up, organizations must develop strategies that allow them to take full advantage of the powerful capabilities that modern chatbots offer, while also ensuring that they have access to the AI expertise and infrastructure necessary to create world-class chatbots using the latest technology.

About the author:

Josias Hartmann is a Data Engineer at Indicium, an AI and data consultancy.