What Is Conversational UX and Why Is It Taking Over?

What Is Conversational UX and Why Is It Taking Over? cover

With the latest advances in AI technology and the widespread adoption of chatbots in the SaaS industry, conversational UX design has become a necessity to avoid low-effort conversational interfaces over customer satisfaction.

In this guide, we’ll go over what conversational UX is, why it’s beneficial for SaaS businesses, and which best practices to abide by with your UX design philosophy!


  • Conversational UX combines chat, voice, and other forms of user communication to create a human-like conversation flow between customers and AI-powered chatbots/assistants.
  • Among many other benefits, conversational UX can improve the customer experience, increase engagement, drive conversions, and reduce support costs.
  • AI chatbots, voice assistants, and interactive apps are the main examples of conversational UX use cases.
  • Before implementing a conversational UX strategy, you should first analyze existing engagement data and support tickets to see what common queries your chatbots/virtual assistants will need to address.
  • Instead of building conversation flows manually with a predefined script, you can use tools based on natural language processing (NLP) to automate this process and have more contextual dialogues.
  • The golden rule of conversational UX is to always keep the dialogue natural. There’s nothing wrong with prioritizing customer education as long as the conversation doesn’t come off sounding robotic.
  • Conversational UX can be continuously improved by split-testing various elements over time. This strategy of iterative testing will help you fine-tune every aspect of your conversational UX system and maximize customer satisfaction in the process.

What is conversational UX?

Conversational user experience (UX) combines chat, voice, and other communication mediums to enable artificial intelligence to have a natural conversation with leads, users, and customers.

Technological breakthroughs with chatbots, voice assistants, virtual assistants, and virtual agents let humans interact with AI in direct conversations that can provide customer support and solve their technical issues.

Familiarizing yourself with conversational UX will help you capitalize on one of the biggest UX trends to grace the SaaS world. Below, we’ll go over the ways that conversational UX design can improve the user experience while benefiting your business in the process.

Why is conversational UX beneficial for SaaS?

There are plenty of benefits to conversational UX design, but the most notable three are better customer experiences, higher engagement/conversion rates, and reduced operating costs. Let’s take a closer look at each of them.

Better customer experience

AI used to be a suboptimal approach to any activity that involved direct conversations. You’d often find users complaining about chatbots with poor conversational systems that were incapable of addressing even the simplest queries.

Nowadays, with better natural language processing algorithms, technological interactions feel increasingly human. In fact, digital interactions with chat or voice assistants can be simpler, more accessible, and faster than the average support call with a human representative.

Leveraging UX design to create an environment of automated engagement also helps users get more value and faster support with less effort — which makes these technological interactions more enjoyable for customers and improves the customer experience as a whole.

This explains why automated conversational interfaces have become a key element in customer experience management (CXM).

Customer experience management CXM SaaS

More engagement and conversions

Conversational UX design is one of the most effective ways to reduce the time to value and provide 24/7 accessibility to every customer. These speedy and always-ready conversational systems lead to higher engagement which itself leads to better retention rates.

Conversational UX design can also help you collect more customer data through chat history and therefore identify previously hidden conversion opportunities. This data will also help you optimize the user flow to eliminate any funnel leaks that might be robbing you of revenue.

Reduced costs

Seeing as conversational UX design is mostly automated (once you’ve got it set up), you’ll be providing a 24/7 self-service support option to users at scale. This reduces the amount of time your human agents need to spend on tickets, allowing them to address more complex cases that require human intervention.

With fewer support agents needed to tend to repetitive customer queries, you can significantly cut down on costs without sacrificing efficiency in the process.

What are examples of conversational UX?

There are plenty of UX examples that you could look at for inspiration on your own UX design. Chatbots, voice assistants, and interactive apps are the most common use cases, so we’ll focus on these examples in the sections below.

AI chatbots

Chatbots are very versatile as they can be trained to respond to common queries, direct users to a specific page or representative, and answer FAQs so your human agents don’t spend their entire day answering the same questions over and over again.

AI chatbots can either be integrated into websites or inside the product itself, depending on which approach would best suit the target audience. Chatbots are also able to collect historical data and provide various user insights.

Last but not least, you could integrate your entire resource center into your AI chatbot so that it has a larger knowledge base to draw its responses from. HubSpot is the prime example of how existing resource centers can help digital interactions feel more contextual:

HubSpot chatbot conversational UX
Source: HubSpot.

Voice assistants

Google Assistant, Siri, and Alexa have all become such an integral part of our lives that we often forget about the technology behind these voice assistants. In fact, they’re leaps and bounds more advanced than your run-of-the-mill chatbot.

This is because voice assistants heavily rely on machine learning to become more knowledgeable and engaging over time. As a result, their scope of capabilities has quickly expanded beyond day-to-day chores and into other business and customer communication use cases.

The most obvious example is Amazon’s Alexa for Business and how it has created new opportunities (not to mention revenue streams) for the already-gargantuan tech/e-commerce giant.

Amazon Alexa conversational UX
Source: Amazon.

Interactive apps

Interactive apps include conversational (voice, gesture, face, etc.) elements in the UX to make the product more engaging for users. Voice-enabled apps (and their features) can be triggered with a single callsign, such as “Hey Spotify” when you want to search for a new song.

Conversational UI capabilities are especially common amongst learning apps, healthcare products, and media players. Duolingo’s speech feature is a prime example of using conversational UX — in this case, voice — to interact with users.

Duolingo conversational UX example
Source: Duolingo.

4 conversational UX best practices

While conversational UX design is undoubtedly going to be a big part of the SaaS landscape moving forward, there are four best practices that you should adhere to if you want to get the most out of your conversational UX improvements.

1. Identify opportunities

Good conversational UX needs to factor in the ways that users are already interacting with your website, product, or social media channels to identify the improvement areas that would get you the highest ROI.

You could also draw from your existing support contact database to find the most common customer questions that you could incorporate into your conversational UX and conversational UI systems. This creates a solid foundation for which queries to prioritize early on.

Once both user interaction patterns and common support tickets have been analyzed, it’s time to start building your conversational UX strategy. This includes the channels you’ll deploy on, which formats you’ll use and the functionalities that your customers could require.

In-app analytics software like Userpilot can also help you collect vital user behavior data to point your optimization efforts in the right direction.

In-app analytics Userpilot dashboard
Detailed in-app analytics with Userpilot.

2. Define the flows

The next step is to select the product areas that you’d like to cover with your conversational UX efforts. You can select the topics based on the data you gathered in the first step to ensure you’re building conversational flows that center around the most common queries.

There are two approaches to building conversational flows. The old (and time-consuming) approach would be to do it manually. However, leveraging natural language processing (NLP) tools is a more efficient path forward that has only been made possible by modern software.

3. Keep it natural

The golden rule of conversational UX is to keep the language as simple as possible. You want to optimize for educational value but still sound human in the product. After all, users don’t mind talking to robots as long as the actual conversations don’t sound robotic.

NLP-equipped assistants are inherently better at engaging with customers since they’re able to factor in the context of the conversation rather than having to rely solely on predefined scripts.

Whenever possible, try to throw your brand personality into the conversations. This will make the interaction more memorable and drive brand loyalty in the long run.

ClickUp merges customer communication with sales funnels by redirecting customers to the comparison page. And notice how they do so while also preserving their brand voice and humanness in the conversation:

ClickUp chatbot conversational UX

4. Continue testing

The more interactions that your chatbots or virtual assistants have, the more data you’ll be able to analyze. Leverage these insights to improve your flows moving forward and work out any kinks.

You should also take an iterative testing approach to conversational UI elements like placement, colors, and button sizes to see which combination provides the highest customer satisfaction rates.

In fact, A/B testing conversational UX flows is just like split-testing your product since you’re experimenting with different tweaks until you find the perfect arrangement — i.e., one that your users respond most positively to.

Creating A/B tests and product experiments is super easy with Userpilot. All you have to do is set your goals, select which elements to split-test, and you’ll be able to start experimenting without needing to write a single line of code.

Userpilot A/B testing
Running an A/B test with Userpilot.

Summing up

As you can see, conversational UX is a rapidly-developing field of study for SaaS businesses that want to make the most out of the recent strides in AI technology. Think about a future where every platform has its own voice-enabled Google Assistant equivalent ready to assist customers with their every need.

If you’re ready to create a more engaging and educational in-app experience for your users, then it’s time to get your free Userpilot demo today!

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