The Rise of Chatbots in Customer Acquisition, Thanks to Generative AI
I’ve used chatbots before, but never thought I’d be a part of a whopping 88% of customers that have used a chatbot in the last year. According to a study by Tidio, around 23% of customer service companies currently use AI chatbots for marketing purposes. It's crazy how widely accepted chatbots have become in customer interactions.
But why are chatbots so popular, you ask? Well, to start with, it’s become real easy to to create and deploy a chatbot. At a previous job, we had to spend over 3 months writing, editing, and diagramming the user journey for a customer on the chatbot. It was a cumbersome process! But now, thanks to Generative AI, those days are long gone. You can have a chatbot up and running in just a matter of weeks, or even days!
So, where can one implement a chatbot in their business? Here are the most common use cases that have emerged in the past year for chatbots:
Lead Generation and Qualification: Chatbots are increasingly being used by customer service companies to qualify leads and gauge intent to purchase. Imagine leads entering your CRM database pre-scored.
Personalized Product Recommendations: 64% of businesses believe chatbots enable them to deliver a more personalized customer support experience, indicating their utility in providing tailored recommendations.
24/7 Customer Engagement: For 66% of millennials, the most significant advantage of chatbots is their ability to provide services around the clock, underscoring their importance in ensuring constant customer engagement.
Interactive Content Delivery: Imagine a chatbot that recommends blog posts, video content and services listed on your website.
Automated Follow-Ups: A substantial 75-90% of customer queries were handled by chatbots in 2023, indicating their efficiency in maintaining continuous communication with customers.
We’ve found various other use-cases of chatbots, which showcases the versatility and wide-spread adoption of this tech.
Slush's Innovative Approach: Slush, a global organizer of entrepreneurial events, adopted the LeadDesk chatbot to manage a significant portion of their customer interactions. The chatbot was tasked with handling 64% of customer support requests, resulting in a 55% increase in customer conversations from the previous year. The success of this strategy lay in the chatbot's ability to provide instant responses and be available 24/7, factors crucial for customer satisfaction and engagement in event management.
PVR Cinemas' Digital Transformation: PVR Cinemas, a leader in the Indian movie theater industry, implemented a chatbot on their website to streamline the ticket booking process and gather customer feedback. This approach was particularly effective in enhancing the customer experience as it provided a quick and user-friendly method for moviegoers to engage with their services. The chatbot's success was attributed to its ability to simplify the ticket purchasing process and offer real-time assistance, thereby improving overall customer satisfaction.
How to develop a chatbot?
Follow these simple steps to build your own chatbot, through content development and refinement:
Define the Chatbot's Purpose: When developing a chatbot, you should start by clearly defining its purpose and objectives. Begin with a limited scope, like customer FAQ on the website, and gradually expand based on customer queries.
Design Conversation Flows: Map out the conversation flows of the chatbot and the desired action from each customer query: do you want to recommend a product/service, suggest content already on your website or gather lead information? Have a clear desired action for each query.
Implement Natural Language Processing (NLP): Integrate Natural Language Processing techniques into the chatbot to enable it to understand and interpret user queries accurately. Train the chatbot with a dataset of relevant phrases and patterns, and use machine learning algorithms to improve its language understanding capabilities. NOTE: Don’t forget! Give the chatbot limitations/boundaries so that it doesn’t hallucinate, or answer questions that it is not qualified to answer.
Test and Refine: Thoroughly test the chatbot's content and responses across different scenarios and user inputs. Identify any potential issues or gaps in its responses and make necessary refinements. Conduct user testing to gather feedback and refine the chatbot's content and conversational flow to ensure a seamless experience.
Iterate and Improve: Launching the chatbot is not the end of the development process. Continuously monitor user interactions and feedback to identify areas for improvement. Analyze user data and conversational analytics to gain insights into user preferences and behavior. Use this information to iterate and enhance the chatbot's content and conversational flow over time.
By following these sequential steps, you can ensure that the content of your chatbot is well-developed, refined, and continuously improved to provide a valuable and engaging user experience.
Do you need help mapping, creating and implementing a chatbot? Contact me at [email protected].