The data we have today shows that customers are more likely to take their business elsewhere if an experience with a brand doesn't meet their ever-increasing expectations. According to The Rockefeller Corporation's study on why customers leave a company, 68% leave because they think the brands don't care about them.
Building a good relationship with customers in an offline shop is easy with the help of friendly shopping assistants. However, making the visitors of a webshop feel welcome and valued is challenging when that direct, personal interaction is missing.
Visitors to e-commerce websites can waste a lot of time searching for what they’re looking for. Browsing can be tedious when a user needs to go through infinite menus and filters that involve endless clicking. At the same time, users are left to fend for themselves through most of the shopping process.
Why e-commerce sites need a user-friendly interface
E-commerce websites often lack a simple, user-friendly interface that drives a consumer towards the right purchase decision through conversation and, consequently, creates a frictionless shopping experience.
A conversation can provide more personalized support, similar to the support offered by the salesperson in the physical store. Technology which is currently available doesn’t supply enough first-party, in-the-moment user data to provide more personalized and contextualized communication.
User data gathered from the time of browsing and purchasing is of unquestionable value, as it can enable the brand to help lead the user to complete a purchase - or at least know what the consumer's concern was at that moment. Without talking to the user in that exact moment – and assuming companies aren’t able to read minds yet – this data would be impossible to gather.
What can first-party user data be used for? Virtually anything: improving user flows, optimizing website content, restocking items, new product ranges product development, etc.
What e-commerce is missing is innovative Artificial Intelligence (AI) technology that would help customers through every step of their journey: when they search for products, create an account, sign up for a newsletter, find discounts and deals, and check out.
As every user has different needs and habits, they’re likely to travel different paths on e-commerce websites. For that reason, businesses need solutions that would adjust to different user's flows. It’s all about understanding the consumers' desires and concerns in the specific moments of the buying process, to provide them with the right solution.
So how can brands build that understanding and put together a customer engagement strategy that delivers excellent experiences and genuine connections with consumers?
The growing importance of AI in e-commerce
AI holds the answer. Specifically, AI and machine learning can be used to create conversational chatbots and digital shopping assistants. This goes a step beyond the traditional bottom-right-corner chatbot with scripted responses - Conversational Commerce uses the full spectrum of customer data to build a holistic picture and deliver bespoke, context-appropriate recommendations and advice.
Some online retailers are already reaching for AI conversational chatbots to inspire online shoppers on certain types of purchases. For example, product inspiration for gift purchases is a common problem for online retailers and customers alike.
To give you an idea of how AI-driven chatbots can overcome the challenge of gift recommendations, let’s look at a real-life use case of an e-commerce website which implemented an AI chatbot to cover customer service and product recommendations.
DoucheBags, a Norwegian company that designs bags for convenient travel, introduced a chatbot named Astrid, supporting customer service by answering questions regarding delivery, warranty, and shipping costs.
However, answering common questions is not the only optimization that Astrid offers. The chatbot works as a shopping assistant too. Astrid asks a few questions to personalize the recommendation, e.g. “What type of bag are you looking for?” Then it gives some options.
To know the purpose of the purchase, it asks another question: “What do you plan on using it for?” Based on the customer's input, the chatbot offers a few alternatives and explains why it selected specific bags. Now, instead of a customer being presented with any bags of a certain category, they have a more tailored selection of the type of bag they would actually want.
Another example: as an experiment and a proof-of-concept during the holidays, Saxo, Denmark's largest bookstore, introduced Alfred Chatbot to help customers with their Christmas gift purchases. This project's motivation was to solve a lack of data when a user buys for someone else. The bot would ask customers a couple of questions, and based on their answers, fetch relevant products live from the product database.
Saxo experienced a massive 400% higher conversion rate when supported by the bot. It meant that more people could be helped to make more product purchases, which is one of any online retailer's primary goals.
A digital connection with a human touch
If your brand is struggling to connect with customers on a positive level, the evidence points towards Conversational AI as a vital tool to improve engagement and let them know you care about them.
A Conversational Website allows the chatbot to improve site usability by reducing clicks. It can show product pages directly in the main browser, without requiring the user to make endless clicks or open a new browser tab. This way, the overall flow gets less confusing, and your customers keep the focus on what they were doing. All that is required is for the AI chatbot to ask the browser to show the relevant information.
As more and more e-commerce websites (and all other types of websites!) focus on accessibility, the Conversational Web epitomises the newest way to re-think UX and turn the tables to serve users first.