Chatbots are diminishing ROI, human agents come at a price. Conversational AI is the best foot forward for customer engagement and lead generation. 

Chatbots have been widely hailed as a game-changer for businesses, offering cost-effective automation, 24/7 customer support, and improved efficiency. However, the reality is that not all chatbots deliver the expected return on investment (ROI). In some cases, chatbots may even diminish ROI, leaving businesses wondering what went wrong. 

In this article, we’ll explore the reasons behind chatbots that underperform and discuss actionable strategies that businesses can implement to maximize their ROI.

The ROI Challenge: Why Chatbots May Underperform

1. Inadequate User Experience: Chatbots that offer poor user experiences, including generic responses and difficulty in understanding user queries, can drive customers away, resulting in a decreased ROI.
2. Limited Functionality: Some chatbots are designed with a narrow scope, capable of handling only basic tasks. This limitation can lead to missed opportunities to engage users and deliver value.
3. Lack of Personalization: Failing to personalize interactions with users can lead to disengagement and decreased ROI. Users expect tailored responses and relevant recommendations.
4. Data Privacy Concerns: If chatbots mishandle sensitive information or fail to address data privacy concerns adequately, it can erode trust and harm the ROI.

Real Estate Case Study: How Chatbots are Diminishing your ROI

A recent experience from our competitor analysis revealed related evidence of chatbots unknowingly compromising lead data. 

Real estate builders spend huge money on online lead generation and regularly upgrade their CRM process to maintain the confidentiality of the prospects. 

However, they are caught unaware of the compromise of lead data in choosing a cheaper chatbot system to attend to website visitors provided by (name undisclosed) and convert them into prospects. 

Visitors are expected to browse through a builder’s website or connect directly via Facebook or WhatsApp. They are usually asked to provide contact information in the chat for receiving project details. 

As the visitor is still in the initial phase, they browse multiple builder’s websites as well. There is a high chance that they come across competitors in the same area or some project with the same budget and the competitor is using the same chatbot solution on their websites. 

During such interactions, the chatbot asks the visitor if it can e-mail all the details. The moment the visitor clicks “YES”, it identifies repeat visitors gathers the contact details from the existing database, and shares the email of the visitor without asking for permission. 

In effect, the lead details from the first website as the response are BEING shared with competitors using the same chatbot integration for nurturing the same prospect. 

The first builder must have spent a huge money and time in creating interest in the visitor, but the same lead is pulled by the competitor by spending less time and money in the campaign. This is the reason why customers using Chatbot are getting fewer conversions. 

Thus, when a chatbot is sold at a cheaper price remember you are getting sold!

Strategies to Improve Chatbot ROI – Switch to Conversational AI

1. Prioritize User Experience: Invest in Natural Language Processing (NLP) and machine learning to enhance your chatbot’s ability to understand and respond to user queries effectively. Create conversational flows that feel more like human interactions, reducing user frustration and abandonment.

2. Extend Functionality: Evaluate your chatbot’s capabilities and expand its functionality. Consider adding features such as e-commerce capabilities, appointment scheduling, or troubleshooting guides, depending on your business model.

3. Personalize Interactions: Implement user profiling and behavior tracking to deliver personalized recommendations and content. Segment users based on their preferences, browsing history, or purchase behavior to tailor chatbot interactions.

4. Prioritize Data Privacy: Invest in robust data encryption and secure communication protocols to protect user data. Clearly communicate your data privacy policies and ensure the chatbot complies with industry-specific regulations.

5. Seamless Integration: Ensure your chatbot seamlessly integrates with your CRM, content management systems, and databases to provide users with accurate and up-to-date information. Implement omnichannel capabilities to maintain a consistent user experience across various platforms.

Chatbot vs. Conversational AI: What’s the Difference?

While both chatbots and Conversational AI involve automated conversations, the key distinction lies in their capabilities and the level of sophistication. The choice between the two depends on the specific requirements of the application and the level of complexity needed for effective automation.

How is Conversational AI better:

1. Broad Capabilities: Conversational AI is designed to handle a wide range of conversational tasks and interactions. It’s more versatile and adaptable, making it suitable for various applications, from customer support to virtual assistants.
2. AI-Powered: Conversational AI leverages advanced artificial intelligence techniques, including natural language processing (NLP), machine learning, and deep learning. These technologies enable it to understand and respond to user input in a more human-like manner.
3. Context Awareness: Conversational AI systems are context-aware. They can remember past interactions and maintain context throughout a conversation. This enables more coherent and meaningful dialogues.
4. Intent Recognition: Instead of relying solely on keywords, Conversational AI employs intent recognition to understand what users are trying to accomplish. It can understand and respond to queries, even if they don’t contain explicit keywords.
5. Machine Learning-Based: Conversational AI continually learns from user interactions. It can adapt and improve its responses over time, providing a more personalized and effective user experience.

How are Chatbots inferior: 

1. Narrow Focus: Chatbots are typically designed for a specific, narrow set of tasks or interactions. They excel at performing pre-defined functions and responding to simple queries. For example, a chatbot on an e-commerce website might help users track orders or answer frequently asked questions.
2. Rule-Based or Scripted: Many chatbots operate based on predefined rules or scripts. They follow a decision tree or set of if-then-else rules to determine responses. This limits their ability to handle complex or unstructured conversations.
3. Limited Context Awareness: Chatbots often lack context awareness. They don’t remember past interactions, making it challenging to have natural, ongoing conversations. If you ask a chatbot a follow-up question, it might not remember the context of the previous question.
4. Relies on Keywords: Keyword recognition is a common method for chatbots to identify user intent. They look for specific keywords in user input to generate relevant responses. This approach can be limiting if the user input doesn’t contain the expected keywords.
5. Minimal Machine Learning: While some chatbots incorporate basic machine learning for improved performance, they generally lack the advanced natural language processing (NLP) and machine learning capabilities that Conversational AI possesses.

By focusing on user experience, extending functionality, personalizing interactions, ensuring data privacy, and seamless integration, businesses can turn their chatbots into effective tools for enhancing ROI. And this would be possible through conversational AI builders like Livserv.ai

After all, it’s not just about having a chatbot; it’s about having the right chatbot that aligns with your business goals and user expectations.