Chatbot Value: 4 Steps to Measure Your Bot’s Effectiveness

There’s no denying the benefits of conversational AI technology – With the global industry thriving and expected to be worth $18.4 billion by 2026.

Simply look at Google trends for the keyword ‘chatbots’ over the past 10 years….

chatbot value

The hype around conversational bots is enormous. But often, companies fail to identify and prove the value of CAI in a tangible way, leading to top management suffocating funds and causing their chatbots to fall behind competitors.

This article will provide the 4-step process for defining and measuring the value of a conversational AI solution – to help you secure and generate internal budget and stakeholder advocacy for your bot. 

1 – Identify Where the Value Lies

Let’s start by defining value in this specific context:

“The importance, worth, or usefulness that a conversational AI project adds to a company.”

By using this definition, we also highlight that value comes in the form of short and long-term impact.

So, how exactly do you identify it? 

It’s simple. To add value, a chatbot should always be tied to a business driver, or in other words, your company’s rationale for developing an AI bot in the first place.

So ask yourself: ”Why am I implementing a chatbot solution in this company?

This is THE question to ask and it’s also fundamental for defining the business case and scope of your project.

For example, do you want to provide better customer service? Do you want to increase sales? 

Your intention defines your strategy.

With your business driver clearly defined, it’s easy to see how and when value will be delivered by your chatbot.

The most common value drivers for Conversational AI projects are:

  • Increase customer satisfaction through lowering waiting times and quick resolutions to customer issues
  • Drive cost efficiencies in the call center by freeing up valuable agent time
  • Boost sales conversions by helping the user more effectively and reducing abandonment rates

Let’s take a look at an example of a company for which the main business driver is increasing sales. To do this, they have developed a chatbot that collects user emails to generate leads.

Quite simply, the company can define that the chatbot provides value whenever it collects a user’s email.

2 – Map Your Business Drivers to Your Conversations

Now that you have a high-level idea of when value will be delivered, it´s time to turn to your solution.

In this step, you need to map the business driver to your dialouges and clearly identify the point in the conversation where value is delivered. This may be:

  • When a form has been filled
  • When the bot has given the same answer that an agent would
  • When a conversation has been completed with no handover to an agent
  • When the bot has helped to finalize a purchase process on the website

There are no wrong answers here but it’s essential that whatever point of your conversation you decide on, must be directly tied to a business driver. 

Failing to do this will leave you with results that don’t add any value. 

Identifying where value is added in your conversations is one thing, but tracking the data is another.

Teneo has the capability to accomplish this using Metadata. With this functionality, developers can tag any flow node that they have identified as “value adding”.

Returning to the lead generation example above, the flow will be tagged when the user responds with an email address.

This brings us one step closer to measuring the value of their chatbot. 

3 – Define and Measure KPIs

It’s now time to turn value-added moments into KPIs. If you’ve followed the steps so far, this part should be pretty easy.

Using our lead generation example, a good KPI for measuring value would be “Amount of emails collected”. 

But how do you get from the flow to the KPI? 

As mentioned earlier, metadata can be analyzed in Teneo. So, by querying the number of times that users provide their emails, the company now has a clear KPI to include in a dashboard to assess the impact the bot is having.

And Remember: when defining KPIs, be sure to keep them SMART. Avoid confusing them with performance-oriented KPIs such as bounce rate or session duration.

For example, a bot with a 0% bounce rate does not necessarily add value if it´s not reaching the points in the conversation that you’ve identified as the value-adding moments.

4 – Look at the Bigger Picture for Chatbot Value

Now it’s time to connect your KPIs to your main business drivers for a full view of your bot’s performance and value.

By now, you should have a list of clearly defined KPIs.

The next step is to consider the added impact that the KPIs could have on other areas of your business when they are achieved.

We´ll explain by continuing the example of our lead generation bot.

Knowing that the bot “collected X number of e-mails last week” is clearly valuable information, but how is that helping to increase sales? 

By digging deeper into this information, we can start to see the bigger picture come into play by asking questions such as:

  • How many of the emails generated turned into actual customers?
  • How much revenue has been generated from those customers?

By doing this, the business driver of “increasing sales” is tied directly to the conversational bot. The business can then clearly measure and quantify the value that the project is adding from an ROI perspective.

This exercise is relatively straightforward when assessing the monetary value a bot provides. It’s a little more difficult when assessing the non-monetary value added – but possible nonetheless. 

Let’s say your business driver is “improving customer experience” and the relevant factor for your company is time. 

You could measure the time a user takes to complete a request using the virtual assistant versus the time it would take to go to an office or make a phone call.

The quantifiable angle for the bot then becomes “Users have saved X amount of time, thus improving the user experience.”

Finding a precise ROI for your conversational AI solution so that its value can be continually proven to the wider business is critical for its long-term success.

Conclusion

Every conversational AI project is unique because every organization and its business goals are unique.

Clearly assessing the value of your conversational AI solution goes beyond KPIs and measurements. 

It relies on clearly aligning your chatbot to your business strategy. By identifying your key value drivers, mapping them to critical points in your conversations, and quantifying the tangible ROI your conversational project adds. 

Are your existing solutions not measuring up to your key value drivers? 

Talk with one of our experts today about how we can support your organization with a platform that helps you connect your conversational AI project to generating real value.