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As a customer, it can be frustrating to have to provide a lot of context to a customer service agent before they can assist you, especially if the interaction feels scripted. This is one reason why people may hesitate to engage with customer service teams initially. The experience can be unpleasant. Implementing analytics-driven chat can help alleviate these frustrations by providing agents with relevant customer information upfront, enabling them to offer personalized assistance without the need for extensive explanations from the customer.
But as a customer service agent, it’s tough to provide solutions if you don’t have the context of what’s going on for the customer. This makes it pretty discouraging to be a customer service agent in a poorly set up customer service operation.
The good news is if you set up a live chat correctly, your agents can get context about the customer situation automatically. It not only makes it easier for the agents, but it makes for a really seamless feeling experience with customers that ultimately makes them happy (which means more sales).
At HelpFlow.com, we provide 24/7 live chat teams for over 100 e-commerce stores. Our chat system set up specifically to maximize the context our agents get about visitors automatically.
Agents use this to help visitors, but we also use it to create really simple and impactful customer service experiences for our clients.
While you can check us out to see how we can help you level up your live chat channel as a sales driver, we’ll break down the key elements we use here in this post.
A customer's previous online activity before visiting your website ultimately influences their mindset and what they are seeking on your site. However, it would feel awkward to directly ask them where they came from, so it's not something your agents can readily leverage unless it's gathered automatically. Implementing analytics-driven chat can help gather this information seamlessly, allowing agents to tailor their assistance based on the customer's previous interactions without the need for direct inquiry.
By tracking the below sources, you get key context for your agents:
Make sure your live chat system is set up to track the source that visitors came from.
When a customer has to repeat solutions they've already tried to bring the agent up to speed, it initiates the customer service experience in a frustrating manner. It's possible to access the navigation history of a visitor to provide your agent with context on what they've already attempted. Integrating analytics-driven chat can enable this functionality, empowering agents to understand the customer's journey and provide tailored assistance more efficiently, thus improving the overall customer experience.
Here are a few things to consider:
Hand-holding and guiding a customer through the solution can be beneficial, but it can be challenging through traditional customer service channels such as phone or email. With live chat, you can create an experience to seamlessly guide the visitor through the steps they need to take on the website to resolve the problem. Implementing analytics-driven chat can enhance this process by providing agents with real-time insights into the customer's browsing behavior and interactions, enabling them to offer proactive guidance tailored to the customer's specific needs.
Here are a few ways this can work:
Having context about where the visitor came from and what they are doing on your website can make a live chat experience a great support experience for customers. But you have to configure it in order to do that.
Do you want to increase the effectiveness of your live chat efforts and drive more sales? Here are a few resources.
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