Melissa Lee

Conversational UX Best Practices

Melissa Lee

At Atura we’ve been developing bots for a few years now. Here are some of the conversational UX best practices we’ve gathered along the way.

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Melissa Lee

The Atura Process

Understanding the context

Melissa Lee

At Atura we follow a simple yet thorough process when designing our bots. We like to keep the process as streamline as possible, avoiding verbose and drawn-out spec docs. Instead, we prefer reader-friendly and lightweight documentation, visualising concepts and language flows through diagrams wherever possible.

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Melissa Lee

The Atura Process

Determining core intents

Melissa Lee

Once we have an idea of the context of our bot – who will be using it, and how, and why – we move on to examining the actual journey any user might take in order to achieve their aim.

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Melissa Lee

The Atura Process

Utterance generation and intent mapping

Melissa Lee

Once we’ve compiled a list of core user intents, it’s time to generate as many possible utterances to match to them as we can. We generate these utterances based on key customer personas identified in previous design stages. By now we should have a good idea of who the users are – but how do they speak?

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Melissa Lee

The Atura Process

Creating the bot persona

Melissa Lee

Before we can dive in to specifying what our bot is going to respond once it has successfully understood user intents, we need to create a personality for the bot. Who is this AI assistant? What is its name?

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Melissa Lee

The Atura Process

Designing the conversation flows and dialogue

Melissa Lee

So far, we know what the core functionality of the bot is, what users are expected to say to the bot, and which bot persona will most suit our client. This means we are ready to start formulating the responses our bot will provide.

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Melissa Lee

The Atura Process

Building, testing, improving

Melissa Lee

So far we've made sure we understand the context of our bot, created a list of intents, trained our bot to understand those intents, decided on a persona, and designed our conversation flow. The bot is now ready to be built.

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Dylan Brown

Case study

Nedgroup Investments 'Robo advisor'

Dylan Brown

A digital “Robo” advisor that facilitates needs analysis via a chat platform in order to provide investment recommendations to potential investors.

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