Artificial intelligence in e-commerce is astounding to every online business owner. Chatbots and their ability to give a human touch to a conversation are one of the best examples of AI.
Talking about the exceptional specifications of chatbots moreover it is also significant to build a bot carefully. Bad bots are untrained bots that hamper the brand image and put the online business at risk.
Identifying the mistakes in bad bots and rectifying them is not a very big deal! Chatbots just need regular updates and evaluation. If you are planning to build an AI bot to optimize your website, make sure you test your chatbot regularly. For Online business owners, it is necessary to make sure that it is not becoming a bad bot!
Bad Bots are Dark Bots!
AI-powered chatbots and their internal functions are intricate. Building an AI chatbot by considering its complex mechanisms and testing it regularly can reduce errors in future conversations.
E-commerce websites are using chatbots to replace multiple tasks done by human agents. Artificial intelligence and machine learning tune an AI chatbot with NLP (Natural Language Processing. The conversation of chatbots can go wrong without proper testing and training.
Bad bots have two risky characteristics in a conversation that can jeopardize your healthy relationship with customers. Bad bots can be overconfident about their racist, misogynistic comments, and bots without proper training can converse with rude comments to customers’ texts. This is why you must absolutely focus, especially with a new bot, on training it to suit your customer needs, by testing it and updating it regularly. It’s kind of like teaching a child not to say bad words.
The inappropriate conversation is one of the risks but there are also many mistakes to rectify in a chatbot before setting it up!
9 Common Mistakes to Rectify in AI Chatbots
1. Responding with Wrong Information
Accuracy is essential when passing information to your customers. Most customers converse with a chatbot to avoid browsing about product specifications and information because they want a more “human” experience. Chatbots learn from the data and respond to the customers about the products quickly. If chatbots respond with wrong information, your brand can lose its credibility swiftly! The bad bot does not provide more resources about a question (i.e. no links to blog posts or guides that cover the topic of the question)
To avoid bad chatbots messing up the conversation, it is important to check your chatbot’s conversation and interactions regularly.
2. Poor CRM Integration
Chatbots integrated with customer relationship management systems can ease up the tasks efficiently. Popular CRM (Customer Relationship Management) systems like Zoho, Freshdesk, and Salesforce integrated with AI Chatbots complete the tasks fast by collecting relevant information about the customers from the conversation patterns. AI chatbots with CRM integration simplify the data entry without complex navigation to collect customer purchase insights. Chatbots with poor integration cannot access the data and hamper conversations with irrelevant questions. Not integrating the chatbots properly with CRM systems can result in:
- Irrelevant information about the customer conversation
- Inefficiency in transferring the information to the customer relationship management
- Poor CRM integration can lead to the loss of sales opportunities.
3. Not Connecting to Human Agents
AI chatbots with machine learning technology understand and analyze human language with NLP to replicate human speech. Customers can easily converse and get the proper information in a chatbot conversation but at the same time, they would like to get connected with a human agent.
Some chatbots can allow the customers to chat with a human agent to resolve problems outside of the chatbot’s ability. If an AI chatbot continues the conversation even after the customers prefer to talk with a human agent, customers might get frustrated!
4. Inability to Understand Customers’ Questions
Chatbots with artificial intelligence can answer the questions that are already learned and programmed, and their learning increases with use. Rule-based chatbots, on the other hand, are enabled with a set of rules to answer the common questions of the customers. When a customer comes up with an uncommon question about a product or service, chatbots should be able to answer it, and typically AI chatbots are better at this than rule-based chatbots. The bad bot doesn’t ask a question that’s appropriate for the page (i.e. bot asks the greeting question on the checkout page when it should ask a question that covers questions about checkout on the checkout page).
AI chatbots with machine learning technology can understand the uncommon questions of the customers compared to rule-based chatbots. Training a chatbot from the customers’ perspective is significant to avoid errors of misunderstanding. Customers will leave the site to browse a service if a chatbot takes too long to respond to their questions, or answers them incorrectly.
5. Unsupervised Chatbots
Artificial intelligence and machine learning cannot act alone! Many believe that AI can outpace human agents with deep and active learning, but that’s a ways off. The blatant truth is that artificial intelligence cannot tackle every problem without human intervention. AI-chatbots for e-commerce websites is a good idea but human intervention makes the chatbots perform better.
Unsupervised chatbots can jeopardize customer relationships with your brand; human supervision is necessary to check the customers’ needs and train the bot for future conversations.
6. Unclear Business/Sales Strategy
Bad bots with poor sales strategies do not recommend products with upselling and cross-selling strategies in e-commerce websites. Online business owners should set the business objective before training the chatbot: chatbots without a clear business objective cannot ask the right questions to the customers.
Lead generation bots in B2B business should ask clear lead qualifying questions to invite prospects. If a bad bot asks irrelevant questions to a potential client without any business objective, the client might lose interest in purchasing products.
7. Poor Customer Experience
One of the main reasons for using chatbots on websites is to enhance customer experience. A good customer service experience will pave the way for new customers to visit your website. An example of a good customer service experience in chatbots is Ochatbot, which allows the customers to ask specific questions and helps them add the product right to their cart from the chatbot window.
Poor customer service in bad bots pushes the customers away from purchasing your products and can lead the customer away from your site. Sentiment analysis is one of the advanced technologies in chatbots that make the machine better understand emotive questions.
8. Not Updating Frequently
Artificial intelligence is not perfect, AI needs updates constantly to improve its conversation. Conversational Commerce with AI chatbots can fail if online business owners are not ready to understand their customer’s questions through failure to update chatbots frequently.
AI chatbots without regular updates can find it difficult to interpret user intent and messages. Personalizing product recommendations to customers is a unique specification in AI bots- irregular updates can make chatbot conversations boring or frustrating!
9. Not Analyzing Frequently Asked Questions
A definite set of rules in AI chatbots can help them in resolving users’ requests. Effective chatbots should analyze the previous conversations and frequently asked questions to understand customer behavior.
Bad bots’ involuntary response comes from not analyzing frequently asked questions and following the improper set of commands, and this typically happens when a chatbot is not updated regularly.
Final Word :
Artificial intelligence is ultimately expected to outpace humans in answering questions fast and processing the data quickly but it can never work alone or improve without rectifications. Many successful companies have built chatbots and failed in their experiments by letting them work alone!
Frequently Asked Questions
1. What are lead-qualifying questions a good chatbot can ask?
Lead-generating, also known as lead-qualifying, chatbots can ask more questions about how the customer got to know about the product/service. Chatbots can understand what a customer is looking for by asking this and related questions. Lead-nurturing chatbots should try to help the customers reach out to people by scheduling meetings through questions.
2. Why did Tay chatbot fail in 2016?
In 2016 Microsoft introduced an experimental chatbot known as Tay chatbot became a bad bot when it was trained on Twitter, where it absorbed everything, including racist and misogynist tweets. Without proper programming, Tay started imitating the Twitter followers. Through Tay chatbot’s bad deeds, we quickly learned the importance of human supervision in artificial intelligence.
3. How AI Chatbots are effective?
In a nutshell, chatbots, especially AI chatbots, can improve your sales, business efficiency, and costs of operation with regular training. Artificial intelligence in an effective chatbot is only as good as it is training. It is important for any business to regularly test and update chatbots. In this way, you will know how your chatbot is interacting with customers. E-commerce site owners will be able to spot problems early that a bad chatbot experience is quelled early. AI chatbot doesn’t harm your brand’s reputation with regular updates.