Artificial Intelligence

Best 4 ways to create a more conversational chatbot experience

The digital shopping experience has changed dramatically over the past few years thanks to the adoption of digital assistants known as chatbots. Though customers were once a little wary of these robotic chat options, they are now becoming quite common in e-commerce. Over one-third of customers have used a chatbot on an online retailer’s website as of last year, and as big data and AI become more sophisticated, customers are really starting to understand the kind of benefits they can offer.

However, this does not mean that all customers have a positive view of all chatbots. In fact, many consumers think that brands have a long way to go with this technology before it can be truly beneficial. According to a recent report from PWC, 71% of shoppers would still rather speak to a human representative than a chatbot. They also find that automated responses from these services are frustrating and impersonal; two emotions that can stop engagement and conversions dead in their tracks.

In order to create a better shopping experience when interacting with a chatbot, brands need to find a way to create that personal connection via technology. One of the best ways to do so is to ensure that the experience feels more humanlike by building a chatbot that can hold a real conversation. Let’s talk about how you can do this.

1. Define your brand voice first

A good chatbot is going to have a “personality” that your team creates in order to hold a conversation with customers. But, if it’s going to support a positive CX, it will need to match up with the rest of your branding efforts for a consistent message.

Before you can create a chatbot for your site, your brand voice must be clearly defined first. The easiest way to do this is to think of your brand as a person.

  • What kind of personality do they have?
  • Are they funny and casual or strictly business?
  • How do they act and what are their objectives?

Now, take these descriptions and imagine how that “person” would speak when they were talking to a customer to help you understand the tone for your chatbot. Here is a great example from Fandango:


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It is interesting to note that global audiences feel differently about using a chatbot with a personality. If your e-commerce site caters to an international audience, pay attention to how various customer segments will react to your chatbot and make adjustments accordingly to provide a better CX.


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2. Create a customer intent conversational path

According to Drift’s report, the most common reasons that a customer will utilize a chatbot on a website is to get a quick answer, resolve an issue, or get more details about a product or service. Therefore, your customers have a clear intent in mind when they reach out, so your chatbot must be able to guide them along from the beginning of their issue to the end.


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Big data analysis can support a better customer service experience if businesses know how to interpret and apply the information accordingly. Therefore, your customer data sets are going to be an important resource here to observe your audience’s typical behavioral patterns and identify common issues. Look and see which steps along the buyer’s journey are causing the most trouble. If users are finding it difficult to locate information about your brand, then an automated chatbot popup message could be beneficial.

Online tools like Lucidchart and Google’s Chatbase are designed to help you create a logical conversational path for your chatbot based on previous customer queries. Both of these programs are great starting points to help you put your customer behavioral data into a visual diagram, and both platforms do offer analytical tracking to help optimize this pathway as more customers interact with it.


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3. Use a comprehensive NLP program

A conversational chatbot is not going to sound like a computer program. But it is not just the words that make a chatbot conversational; the way it understands your customers and processes what they are saying is a big part of it, too.

This is often the trickiest part of designing an AI-assisted program. How many times have you asked Siri a question or given her a seemingly simple command and she doesn’t know what you mean, or worse, does something you didn’t want to happen.


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In order to avoid this frustrating situation, it is best to utilize an effective natural language processing program (NLP) that uses behavioral data to better understand what your customers are saying – no matter how they phrase it. While some of this processing capability can be built-in with AI Markup Language, your chatbots can actually be trained over time as it collects richer customer data sets to learn how your specific audiences speak, as well as what they most likely want to happen next.


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4. Pay attention to the results

You should have some set goals established so your chatbot efforts can be qualified as successful. This could be boosting the number of conversions, seeing an increased number of issues resolved, or even just an improvement in overall customer sentiment towards your brand.

According to Applied AI’s report, there are fifteen key metrics to look at when determining the effectiveness of your chatbots.

  • Total number of users
  • Number of active users (people who read the message)
  • Engaged users (people who communicate back with a chatbot)
  • Number of new users
  • Conversation starter messages (how many conversations were started by your chatbot and how many were started by a customer)
  • Bot messages (total number of messages sent out by the bot during a conversation)
  • In messages (total number of messages sent by the customer)
  • Missed messages (number of times a chatbot was unable to process a message)
  • Total conversations
  • New conversations
  • Retention rate (how many customers used a chatbot more than once)
  • Goal completion rates (how many messages were required to meet that goal, how long did it take, etc.)
  • Fall back rate (how many times did the interaction fail)
  • User satisfaction rate
  • Virality (has your brand’s recognition or customer base grown as a result)

Every good business understands that their work is never truly finished. There is always room for improvement, and complacency can lead to destruction. As you start to implement a more conversational chatbot system, you and your team will need to stay on top of the metrics to identify weaknesses or mistakes in the design.

Conclusion

Chatbots are a highly efficient tool that online businesses can use to provide instant assistance to customers. However, if they are not creating a better experience, they could actually be doing more harm than good.

Adding the human element to a technical feature is by no means easy. Making your chatbots more conversational can be a huge contributor for more conversions, so it is important that businesses find a way to add the human element.

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