In our modern world, chatbots are an increasingly important way to reach customers and allow them to interact with your business. When customers are unable to reach a company after business hours, they are annoyed and could turn to the next competitor to get the services they are looking for. Three major factors trigger the most common need for a chatbot-
- Immediate response in times of emergency
- Consumers are looking for automated conversation, then human interaction to avoid long waiting hours.
- Get a detailed and elaborate explanation or answer.
And the hidden factor: When users need an answer to a simple question, it’s not worth waiting around for human support.
Their fast-paced workflow and ability to provide quick and efficient customer service have made them a favorite among the growing number of consumers who prefer to interact with businesses via messaging services.
These days users expect to get immediate responses to their queries, and chatbots, compared to other business communication channels, stand out, only losing out to live chat support.
Table of content
What exactly is a decision tree?
A decision tree is a knowledge management tool that sorts through vast data sets to learn the best course of action. It can be used by chatbots to allow users to reach desired outcomes or make decisions through conversation. It helps predict event outcomes, identify pain points, and track services to understand customer journeys.
A decision tree is a graphical representation of the best possible solutions to a problem, based on certain conditions. It starts with a single box or “node”, which then branches off into a number of solutions, just like a tree branch divides into smaller branches.
It is a tool for building a linear classification model, which will help customers take steps by choosing the cause that leads to the effect (or the solution). The chatbot can display decision trees for different use cases and become better at predicting what the user needs. It works by using its training data set to create a series of yes or no questions that will narrow down the possible user inputs to categories it needs to classify.
Based on historic data and question patterns, a thorough analysis of the historical customer service journey is mapped out. These scenarios help identify and narrow down each expected range of questionnaires that any conversation can potentially carry towards providing the visitor with the answer.
Overall, chatbots save businesses by providing a sustainable solution by helping customers decide what the best course of action is.
Why should an e-commerce organization invest in chatbot decision trees?
E-commerce platforms are filled with active users trying to buy a particular product or service. By deploying a chatbot decision tree, the algorithm decides on what questions should be asked to users that will guide them more precisely towards the app test answer.
It provides a safe 2-way communication gateway enabling premium and dedicated customer service, hearing their questions, and building a relationship with them by understanding their persona.
Chatbots can attend to customers over multiple communication channels to drive sales and deliver an impacting engagement strategy.
Instant response improves the chances of the product reaching the payment stage rather than staying in carts. Around 53 percent of online shoppers are recorded abandoning their products if they do not receive instant answers to their questions.
1. Personalization builds brand loyalty
Decision tree-backed chatbots track every response and factor in all the past interactions of the users and refer to them to customize the ongoing and future conversations. Moreover, bots can focus on the customer’s needs and provide them with product recommendations that best suit their needs. By adding this personalization factor, customers can connect better with the brand.
People reconnect with brands that offer products in line with their specific interests. As time chatbots become more intelligent, they will generate more human-like responses.
2. Steady repeat customers
Chatbots record and analyze each transaction and identify key products that grab the user’s attention. Automated trigger emails based on those interests can help retain customers over a long time. By being in constant touch with the customer, there is a high conversion rate.
Social media ads can be customized to reach the target audiences and convert them into potential leads. But unfortunately, statistics show that the conversion of chatbots is much more likely to fall through than traditional methods.
3. Provides usage metrics
Think of an AI-powered knowledge base intelligent conversational interface when it comes to a chatbot decision tree. With the right methods, they can act as a goldmine. In addition, harnessing the potential of user metrics can do wonders for businesses at large. The chatbots, as mentioned, record exclusive details of users that include preferences, products, conversational patterns, etc.
Based on this data, when utilized correctly, they can help e-commerce businesses understand the customer experience and improve them at the basic level. Also, they can directly track the new implementations and generate reports to monitor these metrics constantly.
- Total number of active users
- Percentage of conversion
- Messages that completed the conversation
- Rate of retention, rate of engaged users
4. Active feedback implementation
The chatbots can offer an instant response option to understand customers’ level of satisfaction after each transaction. Based on the genuine rating and suggestions provided by the customers in real-time, it helps identify the lacking factors without any additional effort.
Bad reviews hurt business, and thus there’s always scope to improve customer experience. E-commerce businesses can trigger feedback implementation. The bot will assure them that their issue will be resolved, and the support team will take the necessary action to resolve the customer’s issue.
The immediate action strategy improves brand image and sympathizes with them, reducing the impact of bad marketing.
A decision tree for a chatbot is a critical component for any e-commerce application, as they struggle to improvise customer experience. A conversational chatbot will improve customer engagement and help bring down the cost of operations.