Effective Virtual Assistants Implementation Strategy for your Business

This article was published as a part of the Data Science Blogathon.

Introduction

Conversational AI tech has significantly evolved in the last decade, allowing many businesses to use virtual assistants, aka bots in the chat & voice mediums, to resolve customer queries.

Several bot provider companies take many approaches to deploy & optimize virtual assistants to automate most customer queries.

With ever-changing customer queries and needs, businesses always have to reach out to bot providers to optimize the virtual assistants. This dependency on the bot providers delays the assistant’s automation and thus costs revenue to the business.

Learning to build & improve these virtual assistants helps businesses meet their customers’ ever-changing needs faster and thus save costs & effort.

Here is the list of steps the business can follow to improve their bots.

                                                    Photo by Alex Knight on Unsplash

Number of Customers & Revenue Generated in Each Channel & Medium

Depending on the type of business, location, customer, etc., the channel & medium of customer interactions with the business change significantly.

For example, in the US, the young generation often uses a Facebook messenger or iMessage app to chat with businesses. Here the medium is chatted, and the channel is the Facebook messenger and the iMessage app.

In Conversational AI terminology, the medium is also called modality. The two common types of modalities are chat & voice.

It is vital to determine the proportions of the customers and the revenue generated in these channels & mediums. These attributes will help build the bot for customers, channels, and mediums that generates revenue and adoption. However, there are some nuances, as discussed below.

Determine Medium to Launch the Bot

When you understand where your customers are spending time from above, you will know what type of medium they are using. However, it is not straightforward that you would design & deploy the bot in this medium. Most times, the customer behaviors now and in the future are different. So the business should first focus on understanding the vision and the customer behaviors to decide where to deploy the bot for future proof.

Vision determines where the business is investing for the next 5–10 years and guides what type of customers you will acquire.

Customer behavior is tricky to determine; however, focusing on the changing technology trends or evolution of the new technologies often gives you the best idea of customer behavior.

A combination of the vision and customer behavior helps you identify the medium to deploy the bot.

Evaluate the Critical Queries Customers are Trying to Resolve

Once we determine the channel and medium, decide on the critical queries you would like the bot to handle. Queries/questions are called intents in conversational AI terminology.

Here are the ways you would determine the critical queries:

1. Identify the revenue-generating queries: Some intents have a higher revenue impact than others. For example, subscription cancellation or product purchase intents have a much higher impact than forgetting usernames or changing account information queries. So it’s essential to list down all of these high revenue-generating queries.

2. The top questions the customers are asking: Understand the volume of the questions the customers have been asking over the last 6-12 months. This analysis will help understand the impact of automating these specific questions.

3. Top confusing products or features: Identify the top products or features that customers are confused about using. Usually, the disjointed nature is because the product is in the MVP stage, the technology is hard to explain with a clever UI, or the customers are not tech-savvy, so there might be confusion.

Now a combination of all these ways determines the most critical queries.

Determine the Queries to Automate

Now that the most critical queries are identified, it is essential to pick top questions rather than investing energy in automating all of the queries.

Now that you have the list of critical queries, it’s crucial to pick a few top ones from this list rather than automating all of them. The rule of thumb is to partially automate the most revenue-generating queries with a fallback to a human agent and automate the questions that are repeated.

Design the Conversation and Launch the Bot to your Customers

After the list of queries to automated are identified, work with a conversation designer to design the flow the bot will follow to solve the customer problems.

A Conversation Designer is responsible for designing the user experience of a virtual assistant. They ensure the bot (virtual assistant) is conversationally engrossing, impactful for the user, and matches the brand’s identity. The designers translate the brand’s business needs into natural dialogue flows backed by UX study and suitable design methods.

Based on the guiding principles from the design, build the flows on the bot builder tool and launch the bot to your customers.

Now the customers can start engaging with your bot and resolve their queries.

Measure & Optimize the Bot

As the customers engage with the bot, the data flows into the analytics tool, where you can identify many metrics that tell you the bot’s performance.

Some of the key performance indicators that help measure the performance are

• Total queries handled over time.

• Total queries with a resolution or without resolution.

• Questions that are escalated to a human agent.

• Customer satisfaction.

You can have a north star metric as the customer satisfaction that helps you measure how customers feel about interacting with the bot.

Once you have a list of performance indicators, it is essential to identify how you can improve the bot to get better customer satisfaction. Most analytics tools guide companies on how to improve their bot.

Different technologies, such as real-time tagging or auto-improving the bot, can improve the bot without human involvement. But these technologies are in the research stage, and it would take a couple of years to see the light of the day.

Conclusion

In a dynamic world, customer needs are fast changing, and businesses must continuously evolve to meet these needs to increase revenue and save costs. Learning to build & improve virtual assistants is one-way businesses can meet their customers’ dynamic needs faster.

Building & Improving the virtual assistants is a streamlined process where the business needs to understand the customer’s behaviors in each of the channels that help them understand the revenue distribution of these channels. Revenue distribution & the company strategy inform the business on the channel & medium to focus on deploying the virtual assistants.

The history of the customer’s queries helps determine the top questions to automate. With the help of a conversation designer, a business can design the automation flows for the top questions and deploy them in the channel & medium that helps the business.

By Deploying & continuously monitoring virtual assistants, the business can save time, effort, and money & increase revenue.

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Raghuvardhan Reddy