Calculating Chatbot ROI—and Understanding the True Cost of Automated Conversations

IChatbots are transforming customer service. Their promise of streamlined, always-on support entices organizations seeking to cut costs and boost satisfaction. But amid the excitement, vital questions remain for chatbot teams: Just how profitable are chatbots? What is chatbot ROI?

The key to unlocking chatbot ROI lies in a metric often overlooked within the industry: the true cost of automated conversations. This critical figure exposes the hidden expenses that can undermine chatbot profitability and make accurate ROI calculations elusive. Let’s delve into why this metric matters and how understanding it drives strategic decisions for maximizing the value of your conversational AI investments.

In the contact center industry, the cost per call is a routine KPI. Contact center leaders rely on it as an indicator of the performance and overall efficiency of the call center. Most call center managers can quickly tell you the cost per call. It’s pretty easy to calculate too: It’s determined by dividing the total loaded cost by the total number of calls, taking into account resources and average handle time. In a similar vein, the cost per live chat is commonly understood, and easy to calculate.

For high-touch contact centers in sectors such as telecommunications and retail, it is typical to anticipate a cost range of $10 to $14 per live agent call and $6 to $8 for a live chat interaction.

But what about the cost per automated conversation?

With so much emphasis being placed by the platform developers on the cost savings and ROI of automating customer service, there is, for some reason, still only little emphasis placed on calculating the cost per automated conversation.

And without an accurate picture of how much your automated conversations cost, how can you expect to get a clear picture of your chatbot ROI?

At a basic level, it might seem that the cost per automated conversation is as simple as dividing the bot platform and license fees by the number of conversations. However, the reality is more nuanced. This simplistic calculation overlooks key factors, such as whether the engagement genuinely fulfilled the customer’s requirements or if it prompted them to switch to a more costly channel—live chat or live agent—thereby inflating the overall cost.

To gain a better understanding of the actual cost, we need a different perspective.

Calculating the cost per automated conversation takes into account three main factors:

• Platform fees—including licensing and implementation;
• Conversation volume;
• Automation. Beyond mere containment, automation takes into account whether the bot was able to genuinely satisfy the customer’s query without repetition, excessive transitions, or escalations—and without added frustration.

When you first invest in a conversational bot, it’s normal for costs to be on the higher side, largely due to implementation and startup expenses. However, over time, a reasonable cost target for each automated conversation typically falls within the range of $1 to $2.

Along the way, though there’s typically limited opportunity to reduce platform and license fees, simple adjustments in bot management and automation can go a long way. Whether that’s upgrading NLU training, bot responses, introducing or adjusting intents, making sure the customer gets the answers they came for, quickly, and without escalation is the surefire way to increase chatbot performance and reduce overall cost.

Cost per automated conversation is one of the primary chatbot metrics and KPIs that bot management teams should monitor. Keeping track of it allows teams to measure the quality and performance of their conversational bots.

As this metric provides insight into the amount of money spent on each call, it serves as an indicator of how much you will want to invest in a conversational bot program in order to achieve your business goals.

Of course, it’s not uncommon for many bot program managers to be taken aback when they discover the actual cost of each conversation. And the need to adopt a regular, and systematic approach to evaluate and adjust bot responsiveness in the right ways, with the highest impact, is key. Equipping yourself with the right tools, including purpose-built chatbot analytics software, and the right processes is pivotal in effectively assessing your current expenses, setting attainable targets, and monitoring your progress toward your cost-reduction objectives that boost chatbot ROI.

Chatbot ROI, or return on investment, is a measure of the financial benefits gained from deploying a chatbot compared to the costs of its development, implementation, and maintenance. A positive ROI indicates that your chatbot is generating value and saving your organization money. In today’s digital world, where customer expectations for immediate, 24/7 service are high, understanding your chatbot ROI is critical for making informed decisions on improving and scaling your conversational AI efforts.

Importantly, a truly accurate chatbot ROI calculation directly factors in the actual cost of your automated conversations. This goes beyond simple licensing fees to include expenses like technology infrastructure, personnel needed for bot maintenance, and the potential cost of negative customer experiences due to chatbot errors or limitations. Accurately understanding these costs gives you a realistic picture of your chatbot’s profitability.

Ultimately, the formula for chatbot ROI is a simple one:

Chatbot ROI = (Gains from Chatbot Investment – Cost of Chatbot Investment) / Cost of Chatbot Investment

What’s typically difficult in determining ROI is accurately tallying the costs of your chatbot investment. Yet, equipped with a calculation of your automated conversations’ average cost, you can quickly understand the value delivered by your chatbot. You can get there in two different ways:

• Analyze the cost savings delivered by your chatbot: By comparing the costs of your automated conversations with the costlier live conversations your chatbot has replaced, you can effectively understand how profitable your chatbot deployment has been.
• Analyze the value added by your automated conversations: A more advanced calculation of ROI would take into account the gains delivered against KPIs by your chatbot. For instance, if your chatbot is being used to improve response times.

Understanding the cost of automated conversations is crucial to enhancing your bot’s efficiency and ensuring it delivers maximum ROI. It involves more than just platform fees and chat volume; it’s about meeting customer needs cost-effectively. Regular evaluations and adjustments can significantly lower costs—and sophisticated chatbot analytics tools can help you monitor and improve the quality of customer service chatbots.

Take control of your chatbot optimization and book a demo of Calabrio Bot Analytics software today.