Our NLP database manager explains how the hundreds of conversations he’s had with customers informs how he trains machines to respond to customer inquiries.
“Some of these companies need to focus at least as much on testing their products as they do drafting press releases.”
Thomas Gouritin calls the lack of focus on user experience the “AI bulls***” — specifically getting one error message after another for tasks that logically should work.
His theory for this widespread problem?
Not enough focus on testing the product before launch, and way too much on the selling. Specifically, those press releases that tout their Artificial Intelligence-powered chatbots(capitalized, mind you) that in reality are programmed questions and answers.
His commentary is caustic, but accurate.
Reserving enough time to test is beyond valuable. It is essential to avoid becoming a screenshot of a failed bot on Twitter.
The goal is to account for both predictable and unpredictable errors. For the latter, the bot does not need to have a solution, but needs to route the user to a place or person with the solution.
1. Predictable Errors
Test ideal user paths and account for unforeseen edge cases to determine impact vs. effort of changes.
Happy paths are ones in which the user is able to complete a task smoothly by providing expected answers. These paths must absolutely work, because the bot is otherwise useless.
In edge cases, a user types or says something the bot was not designed to answer. For edge cases that are discovered during usability testing, we need to determine the value it provides vs. time and effort it takes that may compromise timely delivery.
Ex) When the bot asks the user what type of cuisine they’re looking for, the user may ask for restaurants with the least wait time. Here, the bot should tell the user that it can only give recommendations based on cuisine preference.
The user may misunderstand your bot as broken if you don’t provide an explanation that the feature is not supported at this time, as well as a call-to-action. However, in order tell them why something isn’t working, the bot must be trained to pick up why the error is happening. This is why training the bot to understand common user inputs is important for the overall user experience.
Otherwise, they’ll keep trying the same thing over and over again.
The novelty surrounding chatbots makes people’s expectation of chatbots much greater than what most bots can handle at the moment — and I’ve seen this first-hand in testing.
The point of usability testing is to gather insights, prioritize, then iterate; it is not to make changes to account for every finding.
2. Unpredictable Errors
Reserve time for these to arise, then prioritize again.
Then there are errors that we simply can’t predict, such as platform issues. The restaurant recommendation bot may experience issues pulling up database from Yelp and return an error message. Testing should ideally be done in a specified time window, after which you prioritize solving for usability issues over nice-to-have features.
How do you train the bot to respond to these errors?
Organize a spreadsheet that categorizes each intent* expressed by the user that the bot should understand, then gather a list of common phrases that they would type or say for each intent. One intent could be “unsupported feature,” under which you’d put common features requested, but unavailable in the bot. You can then train the bot to respond with a copy explaining that the feature is not supported at this time.
Example of a spreadsheet categorizing user intents and corresponding phrases
*Intents: what we determine the user is requesting when they say something to the bot
How to get the right help for testing
Allow each team member to use their domain expertise and get involved in the right steps, so that you can create a prototype, deploy to a testing environment, test specific user flows, then iterate. Though you should leave time for design changes, accounting for different scenarios as much as possible from the start will cut the time required to iterate.
Let’s take this scenario: when a user types “help” while shopping for shoes, what options should the bot offer? Are they asking for “help” with navigating the bot or with the item they’re looking at, thus asking for a customer service rep?
The NLP Trainer (link to Aldo interview) would work with the Bot Designer (link to Diana interview) to come up with possible solutions:
Direct user to menu options (one of which is talking to a human agent)
Connect user to a human agent directly
Ask what exactly user needs help with, then redirect
As you may have guessed, I usually go with the third option to avoid assuming the user’s intention.
Getting the answer to “what exactly are they likely asking for?” correct as often as possible — through usability testing and analytics — makes the bot “sticky,” encouraging users to use the bot again and again.
Like any good design process, the decisions must be collaborative and iterative.
In conclusion, you need to consider:
1. Realistic Users
Testing with the intended users informs designers of tweaks, and sometimes entire redesigns, that need to be made.
This includes users in the worst case scenario.
For chatbots, users in the worst case scenario would actually be not people who have never used the chatbot, but those who have used it andhated it.
We want to observe how those who are biased from previous experiences and those who are brand-new would use the bot.
The tone should be in line with how the user speaks, and avoid information fatigue.
For text-based chatbots, the designer’s job is to ensure that text fatigue doesn’t hinder task completion.
As UX Designer Eunji Seo says, “Don’t make users go TL;DR.” Generally, anything more than three lines of text is too long.
3. Handling Errors
The goal is to have as few fallback messages (“Oops, I didn’t get that!”)as possible.
As mentioned above, this requires the designer to adjust wording or change the order of messages so the conversation feels natural and helps users achieve the task quickly.
*Fallback messages: messages noting the request can’t be understood, then often followed by menu options
4. Task Completion Rate
One way to test fatigue is through the 60-second test.
“Can users perform a certain number of tasks with just one hand in under 60 seconds?”
Customer satisfaction can be achieved when a bot strategy is carefully developed. At Wizeline, we define chatbot objectives, identify the software integrations that work best, build types of experience, and design intents and flows. After validating the experience of using the chatbot with clients, we get them involved in testing to check if we need to add NLP, edit copy of the messages, shift actions when certain messages are displayed, etc. We also make sure to determine a marketing strategy to launch the bot so that it can be discoverable. Talk to us here.
Santa’s little helpers are no longer just cheery elves building wooden trains. The true stars helping consumers buy gifts this holiday season are chatbots.
Whether it’s on Alexa, Facebook Messenger, a website or any other platform, chatbots are now a strategic must-have for engaging target audiences.
According to a PWC study, chatbots have matured to the point that 27 percent of consumers weren’t sure if their last service interaction was with a human or a bot.Gartner predicts that chatbots will power 85 percent of all customer interactions by 2020. Business Insider Intelligence agrees the timing is right for businesses to leverage this inexpensive and wide-reaching technology to engage with more consumers.
Here are 10 reasons why consumer brands should leverage chatbots this holiday season.
1 | Chatbots open up a new sales channel
Nearly half of consumers are willing to buy items through chatbots, and on average, users are willing to spend more than $55 on purchases facilitated through chatbots. The good news? Chatbots are relatively inexpensive and quick to deploy for brands to leverage this new channel this holiday season.
2 | Messaging apps are the most engaging platforms on the planet
Text messages have a 98 percent open rate. Today, 66 percent of consumers prefer to interact with brands through messaging apps like Facebook Messenger and WhatsApp, which boast 20 percent more active users than social networks. Chatbots provide a way to interact with consumers in a way that is familiar and flexible. They can help brands grow their following and engage with users on a deeper level than with any other social platform.
3 | Users like chatbots more than consumer apps
According to Quantcast, only 1,000 of 1 million apps have over 50,000 users. Apps simply do not have the draw they used to. Apps are still valuable, but chatbots are keenly optimized for mobile engagement. Chatbots used for events increase user adoption and engagement by 24 percent, versus ordinary event mobile apps.
4 | Generate more sales with instant response times
Delayed responses to consumer inquiries can dramatically affect sales, especially during the holidays when consumers have an urgency to purchase gifts. Sales conversion rates start to drop dramatically when a consumer has to wait more than five minutes for a response. The chance that consumer will make a purchase decreases by 400 percent after 10 minutes. Chatbots give brands the opportunity to engage with customers instantly, capitalize on their interest, and convert them to purchase.
5 | Provide a top sales associate that works around the clock
Good sales representatives know their audience and can answer questions based on expertise to help the potential buyer understand the product. Chatbots allow brands to essentially clone that sales rep hundreds or thousands of times, providing an advantage over the competition.
6 | Increase sales with real-time, actionable analytics
Unlike traditional website analytics, chatbots allow you to measure performance and adjust in real-time to maximize impact. If the chatbot isn’t answering specific questions accurately or directing users to the right pages, bot trainers can update scripts and user workflows to course correct. These modifications are especially valuable during the holiday season because they allow brands to track trends in behavior and adjust to maximize conversions.
7 | Higher click-through rate than email and social ads
The average click-through rate (CTR) for email is five to 15 percent. However, the CTR on external links sent by a chatbot on Messenger is 15 to 60 percent. Chatbots also have a much higher conversion rate than social ads, driving up to 266 percent more clicks than the average social ad in some cases.
8 | Bots can reduce bounce rates and cart abandonment
Chatbots can increase the average time spent on a webpage by up to 40 percent while still helping users find what they need, fast. Chatbots can also significantly reduce cart abandonment. Most companies remind users that they have items in cart via email. Chatbots are tying customers back in more effectively, with a 619 percent higher engagement rate than email.
9 | Good bots can significantly lower operation costs
Chatbots cut costs by over $20 million in 2017 and will account for cost savings of over $8 billion annually by 2022. A report by BI Intelligence states that annual salary cost savings when using chatbots is between 29-46 percent. E-commerce companies can invest those resources into other functions of the business and better support holiday retail initiatives.
10 | Chatbots are essential to staying on the cutting edge
16 percent of Americans own a smart speaker like Amazon Alexa today. These conversational interfaces are at the forefront of modern consumer engagement. Consumer brands need to leverage interfaces or risk missing out on powerful opportunities to connect with users.
If you’re ready to reap the powerful benefits that chatbots can offer, Wizeline can help.
From website bots and Alexa Skills to Messenger bots and everything in between, our collaborative chatbot experts can help you come up with the right strategy.
Our team will help you choose the best solution for your objectives, whether it’s an out-of-box implementation for a particular use case or a highly-customized bot that meets your specific business needs.
When you’re ready to start brainstorming ideas for your ground-breaking new chatbot, click here.
To learn more about how Wizeline is helping businesses succeed with chatbots, check out a few of our case studies or our blog below.
Case Study: Digital Arts Network partners with Wizeline to build Australian Open chatbot
Case Study: USA Rugby partners with Wizeline to launch the Rugby World Cup Sevens 2018 chatbot
Case Study: pmNERDS increased conversion rates and decreased workload for community managers
Case Study: TWG and Wizeline improve the customer experience with artificial intelligence