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Nov 10, 2021 | 11 minute read
written by Kirsten Aebersold
There are any number of ways consumers today can connect with a brand and purchase products online – whether that’s on a website, in a mobile app, over email, on the phone, through social media, or in-store.
While the number of options can at first seem disorienting, the majority of modern customers are using more than one channel to engage with brands and could have anywhere up to 20 touch points before buying. They demand convenience and speed and are more than willing to find an alternative when they have negative experiences, or their expectations aren’t met.
When only 9% of consumers today say they’re brand loyal, it’s vital that companies make it as simple and frictionless as possible for customers to connect with their business. Whether they’re purchasing a product for the first time, a returning customer looking to connect with support or return products, businesses need to provide positive, seamless experiences.
This is why chatbots have become such a hot commodity for ecommerce companies. According to drift, they are the fastest growing brand communication channel. Gartner even predicted that chatbots would power 85% of customer service interactions by 2020 and Nielsen found that 56% of online shoppers said they preferred to resolve issues through messaging apps than call customer service. Chatbots can even act as another purchasing pathway. In fact, ecommerce chatbot transactions are projected to amount to $112 billion by 2023.
In this post we will dive a little deeper into chatbots and answer some of the top questions you might have, including:
So what is a chatbot? A chatbot is a computer program designed to simulate human conversation, either as voice or text communication. They allow consumers to quickly and digitally interact with companies, without having to talk to a real person.
In many cases, chatbots are artificial intelligence (AI)-based programs designed to provide answers or support for consumers based on pre-defined programs or specific keywords. They can also however, help facilitate live conversations between businesses and customers, speeding up response times to support inquires and improving the overarching consumer experience.
According to HubSpot, 90% of customers rate an “immediate” response as essential or very important when they have a customer service question. 60% of customers define “immediate” as 10 minutes or less. Having the ability to answer questions 24/7, either automatically or via live chat, is the number one benefit of chatbots according to consumers (source: Drift).
However, there are several other advantages, especially for ecommerce businesses:
Chatbots will ultimately help alleviate some of the most frustrating experiences online shoppers face, including hard to navigate sites, poor search experiences, the inability to find answers quickly, and poorly designed mobile experiences.
A key differentiator between chatbot tools is whether they’re rules-based scripting or leverage learning algorithms and natural language processing.
Chatbots are programmed with conversation trees, a mapping of “bot says / user says” dialogs. Responses can be closed (predetermined) or open (type a question/response), or a mix of both.
Image: Chatteron.io Demo
Scripted scenarios are great for common customer support inquiries that can easily be served by quick answers or links to shipping and return policies, or similar content. Of course, this limitation may leave customers unsatisfied. Some rules-based chatbot tools allow you to transfer a user to a live agent if their questions can’t be resolved by the bot.
More nuanced chat requires natural language processing to infer intent and to map open responses to bot replies. A chatbot using NLP (natural language processing) looks at a user’s utterance, parse out entities to infer intent. It then matches intent to predetermined intents you create, such as “showGifts.”
Utterance is what the user says. For example, “I’m looking for a gift for my 3-year old son.”
Intent is what it sounds! It’s what your user most likely wants to know or do.
Entities are data buckets that include keywords and phrases with similar characteristics that modify user intent. For example, “gift ideas,” “gift suggestions,” “gift recommendations,” “gifts,” “best gifts for,” “presents for,” “present recommendations.” And “3 year old son,” “three year old boy” “3 yr old,” “toddler boy,” “son,” et cetera.
Natural language programming can match intent to pre-built responses more flexibly than rules-based bots. But NLP without a machine learning component falls short of truly being “AI-driven.” AI chatbots will recognize patterns and optimize itself based on user interaction and feedback, but often require human training to fine-tune their algorithms.
*Chatbot solutions that use NLP but don’t include training capabilities are not considered AI chatbots in this guide.
Whether you choose a rules-based, NLP-enabled or full-on AI chatbot solution, be prepared to invest time in mapping out and scripting conversation trees, building sets of entities and defining intents. Many chatbots offer pre-built templates to guide your conversation, but still require contextual input from you.
Also, keep in mind good AI requires more training before release than people think. Natural language processing doesn’t just “know everything” out of the box.
Join the many brands leveraging conversational commerce today. Chat with an Elastic Path expert to see how our headless solutions will help.
There are a few types of chatbots to consider, and which route you choose will depend entirely on your business strategy. You may want to enable support, personalized shopping, or even transactions from within your bot. You may also decide at the end of the day that you want your bot to be purely informational, helping users find resources and answer questions themselves.
If your goal is simply to make live help available 24/7, relieve chat agents of the 70% of questions that can be handled by a chatbot, or configure light product recommendation dialogs, you’ll be covered by any business-user friendly, self-service tool. Most support Facebook Messenger and/or your own site widget, and many use natural language processing to match responses to intent.
If chat is one part of a larger Facebook marketing strategy, including cart recovery, automated sequencing (remarketing) and ads, look for platforms that include these tools.
If you see conversational commerce as a key initiative, you want more flexibility to train your AI, deploy to multiple messaging platforms, devices and touchpoints, and own your code. Look for a build framework that jives with your platform, cloud services and IT’s preferred programming languages.
You may opt to host your own chatbot, or leverage third-party messenger applications such as Facebook Messenger, WhatsApp, WeChat, Telegram, KiK or Skype. You may also want to jump into voice commerce, integrating with Alexa or Google Assistant.
First-movers like 1-800-Flowers, ASOS, Sephora and Nike have all embraced Facebook Messenger, thanks to its high user adoption rates and in-chat purchase capabilities (63% of shoppers are willing to buy through SMS). Messenger chatbots support natvie payment through Facebook Pay (US only) or Stripe.
Image: ChatbotGuide.org
An added benefit -- whether a visitor engages with your Facebook chatbot or not, they can be retargeted through Messenger with offer codes, cart recovery messages, back-in-stock alerts and other notifications (with up to 80% open rate). Some Facebook chatbot vendors described below allow you to build and manage segmented “automated sequencing” campaigns in addition to building chatbot scripts.
Why use your own chatbot To ensure all-inclusivity, consider using your own chatbot. You can use multiple bots, but keep in mind the impact on performance when running multiple scripts. You may choose to leverage Facebook Pixels for Messenger retargeting without using a Messenger bot as your on-site concierge.
While only 2% of Alexa owners made a voice purchase in 2018, voice-enabled commerce has since become a touchpoint within a broader shopping journey. Just over ten percent (10.8%) of digital shoppers used Alexa for shopping in 2020. 47% of smart speaker owners (around 25 million in the US) use voice assistants for product search and research, and 43% use them to make shopping lists. If you want to get in early on this action (like Walmart’s Voice Order), consider building Alexa Skills or Google Assistant applications.
Regardless of whether or choose to build or buy your bot, you should know your must-have features before you get started. Make note of any of the following that apply to your project:
With the general growing acceptance of chatbots from customers, they have quickly become a staple channel for brands across a wide array of industries. 34% of online retail store customers accept AI chatbots, more so than in any other industry. While retail businesses and their consumers might have been some of the earliest adopters, we are seeing companies in a wide array of industries including travel, leisure, banking, and finance, implement chatbots as a part of their overarching business strategy.
Lulus
Popular online clothing retailer Lulus leverages their website chatbot to help customers understand more about what size will fit them, answer questions about tracking & orders, give stylist advice, and even offer specific bridal support.
Bank of America
Bank of America, one of the leading banking brands today, offers a personal financial assistant, called Erica, that can be access via their online portal or through their mobile App.
With Erica, users can quicky look up their bank account information, recent activity, pay bills, schedule appointments, report fraudulent activity, or request budgeting support. Users can also set up bill reminders, monitor recurring payments, or even credit score changes with FICO Score Insights.
Erica reached 7 million users by 2019, one year after debut, and completed over 50 million secure client requests.
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Sephora
Beauty giant Sephora is at the top of our list for a number of different ecommerce experiences, including providing one of the world’s leading omnichannel ecommerce experiences, and their chatbot is no exception.
Sephora actually offers three different chat experiences, two on Facebook, and their Kik bot. Between the three, customers can book in-store beauty appointments, leverage the brand’s iconic AI Color Match (an experience allowing customers to find the best shade of makeup for their skin tone), find tips and how-to videos, and read reviews.
In implementing Kik, Sephora noted that once a user engages, they will send on average 10 messages a day.
Chatbots are HOT. They help brands build better customer engagement by enabling them to answer questions or support inquires quicker, provide personalized recommendations, and can improve the bottom line by facilitating in-chat commerce and reducing returns and abandoned shopping carts.
Any business looking to boost brand loyalty and revenue should consider adding a bot to their channel mix.