What is a Chatbot and Why Should You Care?
Throughout 2020, usage of chatbots for brands and consumers to communicate increased by 92% over 2019. Much of that growth must be attributed to the realities of living with the COVID-19 pandemic, which confined millions of people to their homes and forced thousands of purchases and shopping experiences to remain strictly online.
But that’s not all. Gartner predicts that by the end of 2021, 15% of all global interactions will be handled by AI-powered solutions, which includes chatbots. To give an example, experts predict that 75% to 90% of all queries in the healthcare and banking industries will be managed by chatbots in 2022. The same report also suggests that chatbots will reduce business costs by more than $8 billion per year.
Clearly, there’s plenty of pent-up demand for chatbots and clear results that can transform how business is conducted by using this technology. By incorporating a chatbot into your own online business, you can help guide shoppers through the buying journey and convert more of your existing traffic into loyal, paying customers with lifetime value. You’ll increase customer satisfaction, convert more passive shoppers into active buyers, and create communities of your most engaged customers who can then go on to become advocates for your brand. Advocacy is like free advertising, which attracts more new shoppers to your site!
What is a chatbot and how does it work?
Most shoppers have seen a chatbot and nearly 40% of shoppers have used one at some point as well. But few shoppers fully understand how a chatbot works and what value it truly provides to enhance their shopping experiences. As brands, it’s important to convey the importance of the chatbot in order to encourage shoppers to use it and gain value in return from it. That’s how the chatbot continues to learn, grow, and evolve.
A chatbot is a computer programmed virtual assistant that supports digital buyers as they shop online for products and services. It’s programmed using rule-based coding to interact with shoppers using written or verbal dialogue. Rule-based chatbots are designed to handle specific tasks by responding to customer inquiries and routing people to the pages that are most likely to answer their questions.
What is an AI chatbot?
While rule-based chatbots are still used by many companies, much of today’s chatbots are powered by artificial intelligence (AI), natural language processing (NLP), and machine learning (ML) technologies. They’re programmed to have real conversations with people, learn and respond to new queries as they’re exposed to customer questions, and function as a website digital support rep to guide shoppers through a website buying experience.
Here at Kindly, our chatbots are easy-to-use solutions that improve your customer experience and empower your brand with 24/7 global customer support. We’ve seen examples of live chat sessions being reduced by up to 75% and calls to customer support lines down by 50%.
Going back to NLP, we use it to understand the user’s intent. Rather than looking for exact matches, our chatbots look for the intent behind the query and use machine learning to identify the intended behavior of the searcher. With NLP, our chatbots learn and evolve every day in order to further optimize the customer experience for each one of our customers.
5 common criticisms about chatbots that simply aren’t true
People who have little to no experience with chatbots often create misconceptions about how they work and what impact they have on shopping experiences. This is a common habit when dealing with a relatively new product or concept. If you don’t know much about a subject, it’s human nature to create your own perceptions and fill in the blanks.
According to product managers experienced in building, maintaining, and supporting chatbot experiences, these are some of the most common misconceptions created about chatbot products and how they function.
1: Chatbots are just rule-based and can’t understand me
There’s quite the distinction between rule-based chatbots and AI-powered chatbots. Rule-based chatbots are closer to that perceived myth. They’re designed to field basic queries from customers and direct people to the web pages that have been built to answer those questions. But that’s only the story from 10 years ago - chatbots have come so much further than this.
AI-powered chatbots are far more flexible and knowledgeable of human behaviour. AI chatbots are programmed to engage in conversational dialogue, similar to an in-store sales rep engaging in conversation with a buyer as they browse through available products. AI chatbots are built to replicate that in-store experience online.
2: I don’t use chatbots, so no one else does either
Another common misconception is that some people are naturally skeptical of new ideas, particularly those that involve technology and the tracking of shopping behaviours. The very idea triggers a defense mechanism in some shoppers, warding them off from wanting anything to do with a chatbot, refusing to engage with it, and having no interest in learning more about it.
The fact is that more and more companies are going to rely on chatbots to support customers as the years go on precisely because so many people are using them. Globalization and e-commerce business means companies must be able to provide 24/7 support, regardless of timezone, language, cultural identity, and any other variable. The more they do this, the happier their customers are and the most they purchase.
The COVID-19 pandemic also reinforced why digital chatbot support is so important to keeping business running and allowing people to purchase the items they need to maintain their day to day lives. The trend is here to stay, and people have to get comfortable with the modern ways of shopping online.
3: I had a bad experience with a chatbot, so I’m done with them
You know the old saying ‘don’t judge a book by its cover?’ Unfortunately, when it comes to services and solutions, it’s natural to be turned off by an experience altogether if the first time is a disappointment. In the league of earning our trust and devotion, it’s one strike and you’re out.
But many of these disappointing experiences with platforms like chatbots date back several years to when they were first emerging as a solution for online shopping. Nowadays, chatbots are far more sophisticated, such as Kindly’s chatbots that are powered by AI, NLP, and machine learning technology. They’re programmed to service people in different ways: some people use bots like a Google search field, while others write long messages akin to emails. Some shoppers use it like a chat messenger with a support agent.
However you use them, today’s AI chatbots are intelligent enough to function in all of those roles, and they do help shoppers find the solutions they need in faster and more convenient ways.
4: A chatbot only answers direct questions, so what’s the point?
Many people feel they should only use the chatbot if they’re stumped and can’t get the answers they need on their own. It’s your job as a site manager to encourage people to use the chatbot as soon as they arrive on your site, and treat it as more of a virtual shopping assistant that guides them through their time with your brand. That’s how you’ll drive up more interaction with the chatbot. Chatbots aren’t just FAQbots!
5: I don’t like chatbots, because I don’t like robots
If anyone has ever seen any of The Terminator movies, we can understand why there’s skepticism and perhaps fear towards anything robotic. The grim future portrayed in those movies was wrought by machines that took over the world.
There will always be people who are against AI and advanced technology. You can’t please everyone and setting that as a business objective is an unattainable goal. Instead, focus your efforts on optimizing chatbot and shopping experiences for the people who have the highest likelihood of converting on your site and returning to your site for more interactive experiences with your brand.
Types of chatbots
So what are the most common types of chatbots that can be put to good use for your brand? We’ve highlighted three of the most common examples in order to help you determine which platform is best suited for your business needs. Keep in mind that not every company has the same challenges, and that there is no one-size fits all solution.
However, more sophisticated chatbots are flexible and programmed to evolve as they learn more from interacting with shoppers. The flexibility and machine learning capabilities means you can continuously customize and optimize your chatbot and further enhance the experience for your shoppers.
1. FAQ Chatbots
FAQ bots are less chatbot and more chatbot-like. They function in a manner very similar to an FAQ page on a website. They list and present information that answers some of the most frequently asked questions submitted to a business in order to provide direction to people with common challenges or concerns.
2. AI Chatbots
These chatbots are arguably the most effective at providing customer support and improving customer satisfaction. People value the personalized touch of in-person experiences, and AI chatbots enable one-to-one digital dialogue that replicates the back and forth dynamic between an in-store buyer and salesperson. The technology is programmed to learn and evolve with each new interaction, allowing you to automate and personalize online customer support for each individual visitor.
3. Rule-based Chatbots
Rule-based chatbots are also referred to as decision-tree bots. As the name suggests, they use a series of defined rules to answer common customer questions. These rules are the basis for the types of problems the chatbot is familiar with and can deliver solutions for.
Benefits of chatbots
In addition to streamlining and satisfying the customer shopping experience with your brand, chatbots also provide other underlying benefits for your business. From greater insight into audience behavioural patterns to sparking creative inspiration for new marketing and promotional campaigns, you can gain a lot of indirect value as much as direct value from the chatbots you program across your website.
1. Analysis of end user satisfaction to improve website experiences
This is one of the biggest benefits of chatbots. The conversations between the chatbots and the shoppers are archived within the program, allowing your team to analyze the interactions that drove shoppers to a (hopefully) satisfying decision to purchase one of your products.
These insights help you understand what triggered the decision for the buyer and what ultimately got them across the finish line. As the chatbots interact with more people, you can identify patterns that lead to the highest amount of conversions. This helps you profile your shoppers and you can use those insights to optimize the experience on your website by tailoring messaging, offers, promotions, and even paths to conversion to the interests of each individual shopper.
2. Higher percentage of inquiries solved without human involvement
Many companies incorporate chatbots into their customer service simply because of the limited number of people available to handle such high volumes of customer inquiries. It’s especially common if your e-commerce business welcomes shoppers from all corners of the world. Are you really going to have people available to handle inquiries through all hours of the day to support each and every timezone?
A chatbot is a support agent that never sleeps, and an AI-powered chatbot can learn to speak in most common languages throughout the world. You can provide the same level of support that customers expect without overstretching your human resources to the breaking point. This allows you to make better use of your customer support team and delegate the more repetitive inquiries to the chatbot, making more efficient use of business resources.
3. Inspiration for new marketing and promotional campaigns
As the chatbot handles more inquiries and you acquire enough data to profile your most common shoppers, you’ll start to identify the most common messages, offers, and product categories that most contribute to conversions with high average order values (AOVs). This is your golden ticket to create more of those opportunities.
When you know what converts people who are already on your site, and you have a profile of your most valuable shoppers, you can start creating new marketing and promotional strategies to attract more of those same shoppers with the highest potential to convert at the same rates. All of those insights you glean from the chatbot serve as the foundation for your new campaigns and help you scale your business to new levels of growth.
What are chatbots used for?
AI-powered chatbots can be programmed to support any number of customer use cases across a wide spectrum of industries. Using NLP and machine learning, chatbots have the ability to answer common inquiries, offload excessive customer support calls, and improve website experiences with improved metrics in data points like time on site, pages per session, average order value, and total conversion rates.
Here is a list of some of the common use cases from Kindly customers who have built and implemented chatbots for their own shopping experiences.
1. How Helthjem used an AI-powered chatbot to reduce customer enquiries by 30%
Helthjem is a Norwegian shipping and logistics company that delivers packages, magazines, and newspapers to customers. As they expanded their business to also include food delivery, they found that many of the support requests provided by customers were recurring questions that needed the same answers. So they decided to implement a chatbot to handle the bulk of those inquiries and reassign their human resources to more strategic business needs.
The decision was a great one for the company: Helthjem was able to offload 30% of their tracking follow-up inquiries to the chatbot, and they reduced the number of support requests routed to agents by 10%. All of these accomplishments were achieved after only 4 weeks of development and deployment.
2. How Kindly’s hotel chatbot improved Thon Hotel’s customer experience
Thon Hotels is the third largest hotel chain in Norway, and operates over 50 hotels across Norway, Belgium, and the Netherlands. As they began conducting business in multiple countries and accepted guests from all over the world, their goal was to provide 24/7 digital service to help answer customer concerns and improve the brand reputation.
They used Kindly’s hotel chatbot to further enhance their customer service in order to provide satisfying experiences for their guests. The chatbot had a huge impact on customer service, successfully reducing the number of call centre referrals and customer emails sent to reps by 30% each. It also helped analyze over 90,000 emails in order to gain greater insight into the behaviour and intent of guests interested in staying at a Thon Hotel.
3. How Kindly’s e-commerce chatbot helped millions of Elkjøp’s customers
Elkjøp (known as Elgiganten in Sweden and Denmark, and Gigantti in Finland) is the largest consumer electronics retailer in the Nordic countries, and their customer center processes 4.8 million queries each year. While they wanted to increase their ability to provide exceptional customer service, they had a limited in-house support team that could handle the bulk of those inquiries.
So, Elkjøp used Kindly’s AI chatbot to provide 24/7 customer support and improve user satisfaction. The decision was a great one for the company; they saw a 50% increase in automated conversions and, most impressively, generated an 80% user satisfaction rate. Since launch, the chatbot now handles over 2.3 million interactions every year.
4. How Kindly’s airline industry chatbot improved response times for Norwegian Airlines
Norwegian is the fifth largest low-cost airline and one of the fastest growing airlines in the world, with approximately 11,000 employees and 37 million passengers in a given year. Naturally, travellers will contact the airline before their flight to verify their booking information, ensure flights are on time, and potentially negotiate upgrades in their plans. It’s a lot of inquiries for a low cost airline with a limited in-house support staff.
Norwegian turned to Kindly’s airline chatbot to reduce the number of live inquiries handled by agents, free up their time to handle more logistical issues, and still maintain exceptional service for customers. Thanks to the chatbot, Norwegian saw a 30% reduction in live chats, a 5% decrease in incoming phone calls, and an 80% reduction in live inquiries handled by agents.
5. How Kindly’s recruitment chatbot reduced Adecco’s live chat inquiries by 75%
Adecco is Norway’s leading recruitment and staffing firm. They match great candidates with various exciting projects to support many different clients in their own paths to growth. But both clients and candidates have questions about the process, and handling multiple case loads at once means there are always questions that need answers.
Adecco used Kindly’s recruitment chatbot to reduce the number of inquiries submitted to their live chat feature, which was the tool handling the bulk of customer inquiries for a long period of time. Thanks to the chatbot, Adecco saw a 75% reduction in live chat inquiries that also decreased the number of employees required to use live chat full time. Additionally, Adecco reported 50% fewer phone calls after one month of the chatbot being live.
Use chatbots to give your customers a memorable shopping experience
Memorable shopping experiences are what motivate customers to come back to your website and do more business with your brand. It’s your job as the site manager to provide that experience from the first meet and greet opportunity all the way through the point of conversion and post-sale engagement.
A chatbot facilitates those experiences in order to build a loyal following of brand advocates. From reactive to proactive bots, from supporting bots to selling bots - helping Nudge shoppers in the right direction - chatbots anticipate user needs based on their behaviour, and you can use those determinations to provide a more memorable site experience that drives up conversion rates.
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