Shopping is a highly personal activity for most. Some require the touch and feel of the products they are buying while others are on a hunt for saving a few bucks on discount. Some may have questions about the product. What are the color options available? Are there any discounts on selected products? Any other product recommendations? In case of brick and mortar stores, a sales rep can quickly respond and provide satisfactory responses. In case of online shopping, chatbots fill in the gap. In fact, 52% of consumers are more likely to make repeat purchases if the company offers support via live chat (Kayako).
Chatbots are no longer automated responses to most common questions asked by a visitor on your website. They have evolved to become a full-fledged conversational marketing tool that can help a visitor achieve their goals purely through intelligent responses. Let us understand chatbots better and learn how it can become every shopper’s handy assistant.
Concept of Chatbots
In simple terms, chatbots are a digital simulation of human interaction where one of the parties is an AI that continues the conversation based on a flow chart. In case of e-commerce chatbots, it helps the buyer in
- Completing their purchase
- Recommending similar products
- Provide customer support
For a business owner, a chatbot adds another layer of customer interaction that only allows relevant queries to be forwarded to customer service agents, while answering most of the commonly asked questions by self. According to Gartner, the implementation of chatbots in institutions reduces about 70% of calls and emails from Customer Service. This saves time and money in the longer run.
How do Chatbots work?
While the concept is same, a chatbot can implement any of the following logic methods to work efficiently:
- Rule-based
- AI enabled
- Hybrid (AI determines the rules)
Rule Based
This chatbot operates in a completely straightforward manner. You need to feed pre-set rules into the system and the bot provides information provided against every condition. The system follows a flowchart of user interactions available beforehand and only responds to user inputs that match any of the conditions mentioned. One such rule set is as shown below:
However, you can include a ‘Transfer to agent” option for queries not available in the bot’s library to ensure the communication is not dropped. While not smart enough to convert leads on its own, rule base chatbots are faster to deploy and easy to train. You are in more control of the direction the conversation will take. For businesses on a budget, a rule-based chatbot is the way to go.
AI enabled
AI enabled chatbots are complex logic that constantly evolves based on the interactions it has. It uses machine learning to ‘understand’ and interpret the query intent. It is superior to the Rule based chatbots when it comes to crafting a conversational tone with the visitor. Paired with a recommendation engine, it can study the user behavior and provide upselling or cross-selling opportunities.
How it works is that when the user enters a query, it is sent to the Natural Language Processing Unit that compares the query against a pre-set knowledge base as well as past interaction history. On a successful hit, the unit sends the response back to the user and based on the future interactions, the unit registers new responses.
