Return on investment (ROI) is a term often tossed around whenever companies discuss the efficiency of chatbots. It is especially important with first-time systems, where there is a clear distinction between businesses when assessing performance with or without a chatbot platform.
But what do the numbers and percentages really mean? In this article, we will look further into the inner makings of these claimed improvements and the origins of these figures. This includes what to expect, and if chatbot ROI is really worth quantifying first before considering its design-based benefits.
Where Do the Huge Percentages Come From?
Without a doubt, the biggest factor that drives the ROI of a chatbot is its absurdly effective displacement of traditional business processes. It is, after all, a form of automation, albeit a comparatively advanced one in today’s IT-centric world.
In simpler terms, chatbots provide huge cost savings by taking over a portion of specific business operations. While testimonials and case studies readily explain this, the following individual driving elements are often only briefly mentioned. This is understandably to simplify the demonstration of a chatbot’s potential for those who might be interested.
- Standard automation, or low-skill and repetitive task reassignment, is the most straightforward and self-explanatory driver of most chatbot ROI discussions. Although generally attributed to workflow subroutines related to FAQs, it may also refer to direct company-related queries, as well as internal/support uses such as handling information (commands, data fetching, etc.) for standard business operations.
- Reliable availability can be achieved using any type of (digital) automation technology in general. But in terms of ROI, the fact that a chatbot can work continuously without rest means that there is already a clear gain compared to hiring human workers. No vacations (except maintenance), no interruptions (barring unexpected issues), and virtually zero waiting time (chatbots reply almost immediately). You still have development and maintenance costs, as well as turnover systems, but that’s just part of keeping any support-related platform, chatbot, or no chatbot.
- Speaking of inherent factors, consistent performance and fewer technical errors make for less money and time lost in fixing errors, thus also naturally leading to larger returns. With humans, making mistakes in repetitive tasks (no matter how minimal) is usually considered as just a matter of time, regardless of skill level. As such, a chatbot becomes the more productive choice for its limited set of work, since it is very less likely to be mentally fatigued dealing with countless customers over several consecutive days.
- The idea of direct monetization might not be immediately apparent as something that drives chatbot ROI, but the potential is easy to see once a few examples are provided. Getting redirected to landing pages, for example, or placing the chatbot itself directly onto the landing page. Pointing targeted ads at potential customers is another idea for this type of driving factor. In both cases, not only can costs be controlled or mitigated, but the platform can help to increase customer spending.
- And with automation comes the obsolescence of human skill within the categories that chatbots have directly supplanted. This doesn’t mean that you’re out of work, but most instead reassigned. The human element is refocused on tasks that we are better suited for, increasing the efficiency of human work. That, or simply reducing the number of active agents at a given time.
Lastly, though not exactly directly related to chatbot ROI, the potential for professional growth by reassigned staff personnel can open promotion opportunities. Employees reassigned to better positions would then be better assets for the company simply due to the stronger ties they feel within it.
The Tangibility of Chatbot Performance
Analytically speaking, chatbot ROI is also directly affected by its performance metrics. As you may already know, not all chatbots are created equal. One chatbot will certainly be designed very differently than another by the sheer nature of the business or organization it was implemented into.
Regardless of client category, however, these are the most important criteria that need to be observed in gauging a chatbot platform’s theoretical ROI:
- Chatbot activity – quantitatively measured as the total number of chatbot users. No matter how simple the interaction is, knowing the level of chatbot activity gives you an idea of how many users are even aware that it exists in the first place. This is especially easier to see when implemented on a homepage, since you can also quantify it against the site’s visitors.
- Retention rate – now that you know how many users access your chatbot, the next thing to determine is how many of those users access your chatbot multiple times. If they’ve used it more than once, it means that they like the chatbot, or at least find it convenient to use.
- Conversation duration – so if visitors are interacting with your chatbot, how long do they usually talk to it for? Not exactly a direct measure of performance (your chatbot could simply be an FAQ resource, for example), but this metric still gives you some idea on the level of importance that users give it.
- Conversation depth – this “Y-axis” metric determines how engaged your users are, or how deep the responses are provided within the chatbot’s workflow. A good measurement of this analytic often demonstrates convincing (natural language) interaction, even if the user is still fully aware that it is a chatbot.
- Objective accomplishment rate – simply put, the rate at which the interaction leads to any sort of gain or income. For example, if it generated a sales lead, then it’s a plus one. If a user question was duly answered satisfactorily (therefore improving the chatbot’s reputation), then it’s another plus one.
- Objective failure rate – the reverse of the previous metric. If there was interaction, but no results came out of it, it is counted as a minus one. The goal, of course, is to get it as low as possible, so consider a redesign once the percentages start swelling up to more than what’s expected due to natural errors.
- User Rating – a metric manually added and filled in by users and visitors themselves. At the end of a chatbot session, it is often important to occasionally let a rating system pop up, so that input from the users themselves could be added to the overall assessment generated by the rest of the other automated analytics.
How Much ROI is Expected for a Particular Business?
Alright, so we know there is a huge potential for gain in using chatbots regardless of the nature of the business. So, how much of a saving can you expect? If we assess the global statistics of chatbots from 2020, a typical business can expect to save an average of about 30 percent in total operational costs. This includes personnel management, as well as additional costs in keeping physical facilities themselves operational. Depending on the level of service availed, the ROI could then easily be worth many times over the cost of the chatbot platform itself.
If you want a more quantifiable answer to your ROI query, there are several available chatbot ROI calculators around the web. These are often offered for free by chatbot providers themselves, though a sort of registration is required before you are given access. To give you an idea of how a chatbot ROI calculator might work:
- Basic specs requested include team size, (average) cost per staff member, work hours, and inquiry number.
- Formulas may vary slightly, but the averages around the inquiry number would usually be the most important component to be calculated.
- Higher chatbot provider plans usually have the most variation when it comes to predicted results.
- Enterprise-level clients have special quotes, and thus may have different determining ratios for chatbot ROI altogether.
- The numbers will always reflect the performance of a more or less perfect, optimized build of chatbot.
Practicality Collides with Ideality
As mentioned previously, the caveat in determining chatbot ROI is that it will always be equated with an ideal version of the implemented chatbot. Even with a provider’s professional guidance, each field is still a portion of the engagement experiment the chatbot is integrated on.
As such, any unknown factor (unexpected customer base, lower retention rate outside website platform, etc.) will always give rise to adaptations that alter the monetary gain of your chatbot. If your chatbot is still under improvement via its analytics, it may be best to project ahead. Think of ROI only after your chatbot has fully rooted itself into your business.