6 Chatbot Optimisation Strategies That Put Data to Good Use

When defining customer satisfaction, we tend to arrive at one of the most important factors in running a successful business: a positive customer experience. When a user of your products or services gets satisfaction out of it, they will continue to return.

Recent technological advancements in Artificial Intelligence (AI) and machine learning capabilities have led to an increase in the use of chatbots. Many experts see chatbots as one of the newest and most exciting prospects in the customer experience sector.

Statistics show that:

– 1.4 billion people use chatbots regularly.

– 85% of businesses will carry out customer interactions using chatbots by 2021.

– Chatbots can reduce the cost of operations by 30%.

– In 2018, Facebook was home to over 300,000 chatbots.

6 Chatbot Optimisation Strategies That Put Data to Good Use

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What are chatbots?

Chatbots are programmes that can automate an action based on certain triggers. More specifically, they can mimic human interaction and conversation.

Let’s pretend you’re a business that focuses on cloud communication. A user visits your website and asks your chatbot about TCPA compliance solutions. Similar to a customer to staff conversation, the chatbot will interpret the words given to them and produce pre-set answers to the customer.

When chatbots are successful they can provide a business with many advantages.

Why are chatbots useful?

Chatbots are available 24/7 and data shows that, according to 64% of customers, this is their top benefit. Whether it’s day or night, chatbots can swiftly respond and find solutions to any customer query. This increases their satisfaction and prevents them from finding another company that can resolve their issue.

Chatbots can increase revenue and improve gross profit margin. This is because chatbots can quickly find an answer to a customer’s question, increase their satisfaction, and in turn, increase the chance of a potential sale. Chatbots can also be used to market your product to a potential customer.

As mentioned above, chatbots can cut 30% of operational costs. This is because chatbots can reduce the number of staff required in your customer support team. Chatbots can answer the simpler questions and the more complex queries can be handled by the customer support staff. Even though chatbots require an initial investment, in the long run, this type of automation can streamline operations.

But, there is another side to chatbots to watch out for.

When can chatbots go wrong and how do you prevent this?

Even though there are many pros to companies using chatbots, when implemented incorrectly, chatbots can be a pain point in customer service. Chatbots can often lack sophistication, empathy, and intelligence, which can be frustrating for customers.

That being said, there are ways you can overcome the drawbacks and reap the chatbot benefits.

This article will show you six ways you can use data to optimise your company’s chatbot.

1. Train your chatbots

Just like staff, chatbots require training to become a useful member of your team. The dilemma here is that you need people to interact with the chatbot so that it can learn and improve. But, to get customers to interact in the first place, your chatbot needs to be functional.

A survey showed that 81% of respondents said the chatbot training process was far more troublesome than they had initially anticipated.

Open source data can provide a solid foundation for initial chatbot development and optimisation. Open source training data such as Twitter Support and Ubuntu Dialogue Corpus allow you to increase your chatbot’s knowledge base.

But, a chatbot using open source data can be generic and unrepresentative of your brand. It can also find it difficult to jump between conversational threads and translate dialogue to other languages.

This is why it is vital to also collect your own conversational data. Comparing open source generic data to your own personalised, conversational chatbot data is like comparing fax to email.

A unique dataset can give your chatbot an advantage and differentiate you from your competitors. This dataset can be developed by categorising your main customer requests and creating specific answers for each query. The data doesn’t have to just be conversations, you can use: emails, secure online chat, telephone conversation transcripts, transactions and FAQ pages.

After you have developed your own personalised chatbot dataset, you need to allow real users to participate in a functional test. This means checking for:

– Conversational flow

– User experience

– Accuracy

– Speed

2. Location of your chatbot

Where your chatbot is located plays a big part in whether or not you see a good ROI and whether or not your customers benefit from this technology. Figuring out the right chatbot platform is crucial to its success.

Carrying out your own internal research or sending out surveys can provide you with the data to identify where your customers spend their time. Depending on your business, you can build chatbots across various platforms such as your website, SMS, messenger apps and web conference apps.

6 Chatbot Optimisation Strategies That Put Data to Good Use

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But most importantly, it must be a location where your customers congregate. Some chatbot website locations include:

  1. High-traffic pages – these are your website’s most popular locations. A chatbot located here is more likely to stimulate customer interaction and conversation. A home-page chatbot can allow new customers to understand what your business is and what product or service you can provide them.
  1. High-intent pages – when customers visit these pages there is an indication that they intend to work with or purchase a product from your business. Examples include pricing pages and services pages. A chatbot here is vital as customers tend to have very specific questions.
  1. High-intent negative pages – visitors find themselves on these pages when there is a negative intention such as an email unsubscribe page. A chatbot here allows you to change the visitor’s mind and let them know they are valued as a customer.

3. Personalise your chatbot to your customer

Providing a personalised chatbot customer experience can be as simple as including a customer’s name. A more personalised experience may include accessing a customer’s account details to answer a specific booking query. Not only will your responses be more accurate but the customer will appreciate your service and inform other potential customers of the advantages of an online booking system chatbot. Doing this is one of many effective digital marketing strategies for small businesses and enterprises alike.

Even though you may have trained your chatbot with a personalised dataset, your customers’ needs and interactions are always evolving. To ensure you are continuously providing a positive customer experience it is important to collect information.

  1. Actively collecting information – this involves directly asking customers about their interactions with your company like their location, goals, experience and age. This includes collecting customer complaints. For example, you might be providing a VoIP service and customers keep informing you that they’ve been assigned an incorrect VoIP number.
  2. Passively collecting information – this involves observing and recording customer behaviours and actions. For example, taking into consideration a customer’s recent purchases and recommending items they may also be interested in.

4. Give your chatbot a personality

Personality can greatly affect whether or not users interact with your chatbot. Your chatbot’s personality offers you a way to extend your brand identity from just design and logos to real actions. Having a well-defined chatbot personality with an array of responses prevents you from falling back on error loops.

6 Chatbot Optimisation Strategies That Put Data to Good Use

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But, how do you define your chatbot’s personality? You need to consider three things:

Your users

To create a unique chatbot personality you should separate your customers into groups based on their needs and actions. This is known as customer segmentation. Figuring out your core audience’s hobbies and passions will prevent you from creating a chatbot with a teenager’s personality when you’re trying to sell candles to mums.

Your brand

If all your chatbot answers are just an amalgamation of copy from a variety of databases, then it’s difficult to create a personality that aligns with your brand.

Your chatbot’s voice should be the same as your brand’s voice. You don’t want your yoga business chatbot to have the persona of the rapper Ice Cube.

Openness, conscientiousness, extraversion, agreeableness, and neuroticism are the five factors in the Five Factor Model (FFM) of psychological dimensions that drive responses. So, if you’re a company that sells confidence self-help books then having a neurotic chatbot isn’t a good idea.

Your chatbot’s purpose

Imagine your chatbot was human. What would its role in the company be? This is important to define since creating a personality for a chatbot that gives podiatry advice should be very different from a chatbot that sells luxury wallets.

5. Write engaging dialogue for your chatbot

Whether you’re interacting with customers via an email, a toll free number, or a chatbot, clear communication is vital. There is a big difference between a chatbot answering queries and actually keeping customers engaged with informative conversation. Good dialogue can vastly improve your chatbot experience.

Many companies fall into the trap of being too creative too early. It’s important to first establish what your average customer is attempting to achieve from this conversation. Use web traffic analytics and previous interaction information to identify customer journeys and scenarios. After that, you can then develop answers for each of these potential scenarios.

You can of course write unengaging answers and still resolve the customer’s query. But, you want to be memorable. Develop your tone-of-voice and analyse how your customers interact with certain dialogue. To find out which dialogue resonates the most with your users, run A/B tests.

A/B tests allow you to carry out your own research to find out which sentence of dialogue is more suitable. Two different lines of text are run separately over a specific time period and the one with the higher conversion rate is chosen.

6 Chatbot Optimisation Strategies That Put Data to Good Use

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After creating your initial dialogue, it is important to constantly measure and track its progress as brand voice is constantly changing. This doesn’t mean just tracking conversions but tracking every little detail. Sentence length, words, emojis, pictures, videos, memes, and chatbot typing time are all elements that should be constantly monitored and changed if necessary.

6. Evaluate and test your chatbot

In the same way that you carry out eCommerce website maintenance or product maintenance, chatbot maintenance is also vital. In other words, the journey doesn’t end when the chatbot launches, the optimisation process is continual.

6 Chatbot Optimisation Strategies That Put Data to Good Use

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Here are some tests you should be carrying out:

  1. Conversational Flow testing – this is a form of UI/UX testing. Begin with more general questions and testing scenarios and then focus on the fringe questions.
  2. Error handling testing – this is a test that focuses on the way your chatbot deals with unexpected customer entries. If the chatbot fails the test, it is then advisable to work with your developers and copywriters to come up with emergency answers for these exceptional circumstances.
  3. Intelligence testing – this can be as simple as ensuring that the chatbot understands the user’s questions, idioms, emojis, and curse words. But, it also means ensuring that your chatbot can recall specific information the user has provided during their conversation.
  4. Automated testing – you can use another chatbot to interact with your own chatbot. This means that conversations are constantly running and transcripts are produced automatically. With that being said, it is still necessary to evaluate your chatbot’s replies and find ways to improve them.

The questions you should constantly be asking are:

– Does the chatbot understand the user?

– Are the responses prompt and accurate?

– Is the chatbot engaging?

– Is it obvious to the user what the purpose of the chatbot is?

Wading through countless FAQ questions and complicated customer email forms is something of the past. With spending on cognitive and AI systems expected to reach $ 77.6 billion by 2022, it is clear that chatbots are the future.

A chatbot provides 24/7 support to your customer and reduces your operational costs. This gives you more time to focus on other business aspects such as marketing, inventory accounting, or seeking investment.

A fast and seamless customer experience is one of a chatbot’s most important benefits. But what is equally as important is continually optimising your chatbot using the data and insights you have collected.

Let’s quickly recap our top strategies:

– Train your chatbot using personalised data

– Find a prime chatbot location using analytics

– Personalise your chatbot to your customer

– Give your chatbot a personality that aligns with your brand

– Create engaging dialogue that your customers will actually want to read

– Constantly measure, track, test and evaluate your chatbot progress

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Author: Richard Conn

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