Online business is growing every day, with marketers adding advanced technologies to their websites to create brand awareness and sell their ideas. E-commerce websites are optimizing their landing pages with these new technologies to invite more website visitors. And conversational AI is one of those advanced technologies increasingly attracting the attention of online business owners.
Optimizing the Landing Page of E-commerce Websites
To sell services and products, an e-commerce site must approach the challenge from the customer’s perspective. Before optimizing your e-commerce landing page, consider asking questions like, “What does a customer expect while purchasing products online?” And “What are all the obstacles that an online shopper faces while deciding to buy a product?”
When shopping, a customer surfs different websites to find the best value. An effective e-commerce website will resolve customers’ questions instead of losing the sell when the customer seeks answers and products elsewhere.
E-commerce businesses need to understand their customers’ questions when purchasing products online. Chatbots can address many online business owners’ stumbling blocks by performing a variety of tasks.
Most online visitors are actively looking for a product to buy, so a website that resolves customers’ problems quickly will generate more revenues. Online business owners are adding rule-based chatbots and conversational AI to their customer interface, providing customer service capabilities that would not be possible through live agents alone.
And the good news is that choosing between these two is not as challenging as it might sound.
Let us take a tour of rule-based and conversational AI to help you choose the best tool for your business.
Chatbots for E-commerce
Online business owners can become overwhelmed by the variety of chatbots on the market and their specifications. Conversational AI is the latest technology in chatbots and e-commerce sites must choose from different functionalities to decide what will work best for their specific business requirements.
Many e-commerce websites use rule-based chatbots to answer customers’ questions. Rule-based chatbots have branching questions that help visitors choose the correct option. The tree-like flow of conversation allows customers to select an option that will resolve their question or issue.
The structured questions invite customers to select their preferences, guiding them and increasing the odds of converting these website visitors into customers.
Rule-based chatbots have different specifications to make the customers realize the need for the product. The branching questions in rule-based chatbots allow customers to choose the right option!
Conversing with the rule-based chatbots might be frustrating for customers since rule-based bots don’t have Artificial intelligence behind them to understand every question. Rule-based chatbots don’t jump from one question to another, they don’t link new questions to the previous conversation.
Rule-based chatbots are most often used with live chat to ask a few questions then push the visitor to a live person.
Advantages of Using Rule-Based Chatbots
Follow up Questions
Some people visit e-commerce websites to shop for a specific product, but there are always a few shoppers that just happen by a site and realize they need the product or service! Chatbots help this second group by providing a set of questions (with answers and new information), and thus, visitors learn more about the product. Rule-based chatbots provide sets of questions to website visitors who can choose those that are relevant.
As the name suggests, rule-based chatbots follow a set of rules. It is relatively easy to integrate rule-based chatbots, as they have no role in collecting or analyzing customer data. They execute according to answers provided by conditional statements. And conditional statements are easier to add to a site than AI bots that require analytical algorithms and a body of customer data.
Rule-based chatbots reduce customer service expenses. The branching questions in rule-based chatbots resolve most customers’ questions and website visitors find it easy to choose relevant questions without wasting much time. An e-commerce website spends a lot of money managing customer data for tracking potential clients. Rule-based chatbots add new customers with a simple strategy
Disadvantages Of Rule-Based Chatbots
As mentioned, rule-based chatbots do not have artificial intelligence behind them.
Rule-based chatbots give mechanical responses when customers ask questions that differ from the programmed set of rules.
Cannot Handle Complicated Conversations
The rule-based chatbot doesn’t allow the website visitor to converse with it. There are a set of questions, and a website visitor must choose from those options. This programmed set of rules eliminates any sense of a real-life shopping experience.
The conversation process becomes more complicated (and time-consuming) when a rule-based chatbot transfers the connection to a live agent without resolving the issue.
Poor Decision Making
Rule-based chatbots are poor decision-makers, and there is a higher chance of misinterpreting brand ideas. Chatbots without artificial intelligence technology cannot collect and analyze customer data to resolve customers’ questions.
Rule-based chatbots cannot handle multiple questions of many users. Rule-based chatbots are not scalable and offer limited responses to the users.
Poor ROI for eCommerce Applications
Rule-based chatbots do not have the features conversational AI chatbots have to increase revenues such as recommending products live from the eCommerce systems database, upsell and cross-selling products, abandoned cart, overcoming sales obstacles, order status and order tracking, and more.
According to the recent PSFK research, 74 percent of customers prefer conversational AI for online interaction. As customers’ trust in a brand grows, so does the brand. Conversational AI acts quickly by linking customers’ previous questions to new ones. An AI chatbot not only gives options for customers to choose from, but they also interact much in the same way as a human agent by resolving issues quickly.
Machine learning technology and artificial intelligence program chatbots to work like human beings 24/7. Conversational AI personalizes the conversations and makes for smoother interactions.
Advantages of Conversational AI
Best ROI for eCommerce
Conversational AI chatbots for eCommerce have several features that create a 20% to 40% lift in revenue when the shopper engages with the chatbot. This is achieved with features such as; recommending products live from the eCommerce systems database, upselling and cross-selling products, abandoned cart, overcoming sales obstacles, order status and order tracking, and more.
Conversational AI can handle more tasks for the digital marketer. It manages and analyzes customer data to identify potential clients. Many online websites spend a huge amount of money on customer relationship management systems to identify and nurture leads for the business. Conversational AI lessens this load by executing efficient marketing strategies.
Creates Brand Awareness
Conversational AI can guide visitors through the sales funnel, improving the customer base. The relevant questions generated by artificial intelligence actively connect potential customers with a live agent when necessary. A good customer base increases brand awareness, improving brand credibility.
AI chatbots provide a real-life shopping experience to online shoppers. When online shoppers find it easy to converse with AI bots and resolve their issues, there is no need for them to visit another site to learn more about its specifications!
Overcoming Sales Obstacles
AI-based chatbots can answer complex questions with machine learning technology. Chatbots with artificial intelligence understand the user intent without delay. Artificial intelligence and machine learning technologies in chatbots overcome the sales obstacles in the conversation. AI chatbots ease the difficult process of scheduling meetings to reduce the obstacles by recommending products with upselling and cross-selling strategies.
Rule-based chatbots cannot jump from one conversation to another, whereas AI chatbots can link one question to another question and answer almost every question. Conversational AI can also connect the customers with a live agent to resolve a problem.
AI chatbots can easily handle increased users and other important tasks like integrating customer conversations with CRM systems. Automation grade in AI chatbots makes them easily scalable, AI chatbots get smarter every day!
Conversational AI can tackle almost every question a customer asks!
Disadvantages of Conversational AI
Many online websites use conversational AI to develop a customer-centric business. However, there are some disadvantages to consider in conversational AI.
Requires a Lot of Time to Train
Training a conversational AI is time-consuming, AI chatbots require a lot of time to train and test the algorithms. Machine learning algorithms without proper training can misinterpret conversations to get around this Human in the Loop is used to avoid ML pitfalls and speed up the training time.
AI chatbots are expensive to build compared to the other bots, to mimic a human conversation it takes a lot of time to build a bot. High cost is one of the disadvantages of AI chatbots. However, companies now have packages starting at $495 a month that include building and training conversation AI chatbots for e-commerce, support, and lead generation.
Both rule-based chatbots and conversational AI help the brand connect with its customers. While there is also an increased chance of miscommunication with chatbots, AI chatbots with machine learning technology can tackle complex questions.
Rule-based chatbots can have difficulty handling intricate suggestions—a tricky drawback to resolve. But with conversational AI, there are very few unmanageable drawbacks. And compared to rule-based chatbots, conversation AI can better implement a customer-focused approach.
Rule-based chatbots are a simple solution for pushing a visitor to live chat by asking a couple of questions
Conversation AI chatbots are best for e-commerce bots, complex business lead generation, and support bots. Conversation AI chatbots also provide deep business insights.
Frequently Asked Questions
- What is multimodal conversational AI?
Multimodal conversational AI is engaging with the customers via conversational texts as well as voice messages. Multimodal conversational AI uses visual elements in a conversation to interact with the customer.
2. What is Natural Language Understanding?
Artificial intelligence in chatbots uses natural language understanding(NLU) to process human language and make the chatbots converse naturally. NLU makes the machines understand human language better.
3. Are all chatbots conversational interfaces?
A conversational interface uses natural language processing to talk with a human. AI chatbots are conversational interfaces and they can handle human conversations like a real human agent.