As we dive deeper into different use cases for Activechat in enterprise environments, we notice that many of our customers combine the live chat feature with various automations to achieve their goals quicker – both for customers and for support reps.
So, we decided to compile this short guide that will take you through some not-so-obvious ways to improve your customer care efficiency.
1. How to handle non-working hours in the live chat
In Activechat, new chat requests are assigned to available support agents instantly. If there are no agents on your team logged into your bot (for example, during the afterhours or on weekends), the Live chat block will trigger an error, and this can be disappointing for your customers. So, before engaging the Live chat block it makes sense to check the current time and day of the week and trigger a specific sequence during non-working hours. Here’s how this can be done:
The _default_fallback skill is assigned to the “Fallback” intent in the Intents manager, and it will be triggered if the bot does not understand the customer’s message (i.e., no other intents are triggered). Once it happens, we’ll do the following:
- Display this hated “Oops, I don’t understand” message with a button to activate the live chat.
- Once the button is clicked, we’ll check the $_day system attribute. If it’s equal to 0 (Sunday) or 6 (Saturday), we’ll display the “We’re off for a weekend” message and launch another skill (support_afterhours) that will get customer’s details and forward it to a support rep to be answered on Monday.
- If the $_day attribute is neither 0 nor 6, we’ll move on to the next SWITCH block to check the current $_hour (also a system attribute). If it’s in the 9 to 16 range (our working hours in the GMT timezone), we’ll add the “livechat” tag to the customer and trigger the LIVECHAT block. Otherwise, we’ll display the afterhours “we’re offline” message and, again, launch the support_afterhours skill.
- If the LIVECHAT block triggers an error (it means that the assigned agent failed to respond to customer’s request within 180 seconds), we’ll display two more messages apologizing for this, and proceed to the same support_afterhours skill. Note that this chat will appear in the “Abandoned” chats section of the “Conversations” menu for the agent that was assigned to handle it.
This afterhours sequence helps us handle dozens of support requests every week.
2. How to assign chats to specific groups of agents with tags
You can use tags to route conversations to specific groups of agents (think of sales and tech support teams, for example) or even specific agents personally. Just use the “Assignee” field in the live chat block settings to choose between “any”, “tag” or “agent”.
Tags can be assigned to agents in the “Team – Agents” menu:
Next, in the live chat block settings choose “Tag” in the “Assignee” field and type the tag that you need – live chats started with this block will be assigned only to agents who have the specified tag.
This feature can be combined with the Intents manager to start live chats when customers ask about specific topics, and assign these chats automatically. Just create two different skills, each with a single live chat block, but with different tags, and choose the required skill in the “Action” part of the intent settings.
Read more about intent detection
3. How to automate repetitive tasks inside live chats
Customer support routines often include repetitive tasks, like filling in various forms, collecting emails and other data, and so on. It often makes sense to automate some of these tasks as bot skills, and allow support agents to trigger these skills in the conversation, returning control to the same live chat agent again once the automation flow is done.
In Activechat, agents can launch skills when they close the live chat session. You can use this feature to trigger specific skills inside the live chat – just don’t forget to finish the skill with another live chat block, assigning the chat to the same agent (each of your agents will need a personal set of such skills to achieve this).
Here’s a simple example of a skill that automates the email and phone collection from the customer, saves this data to bot attributes, and then returns the conversation back to the live chat session:
To launch this skill in the middle of a live chat session, agent should use the “Close and launch skill…” button in the live chat interface:
4. How to collect feedback from customers after a live chat session
When the live chat session is done, almost all customer service and contact center leaders would love to know how the customer rates the experience with an agent. With Activechat, it’s easy to customize this process by building a skill that will ask your customer for the feedback and store it in the database.
We intentionally did not include this as a pre-built feature, since we believe that every company will need a custom feedback collection system, both in terms of the words used and ratings / comments collection process.
Here’s a simple example of a skill that will collect the feedback and comments from the customer after the live chat session is done by the agent:
The values of attributes ($_live_chat_rating and $_live_chat_comment) can be sent to your favourite back-end that your company is using to track the performance of support agents, or just displayed in the stats dashboard in Activechat.
What’s your hint?
The goal behind Activechat is to build the most flexible customer service platform. That’s why we put the power to customize everything in the hands of customer service leaders and support agents. We’d be happy to learn more about your experience building customer support automation with our platform, so don’t hesitate to contact us if you have a story to tell or a question to ask. We’re always around to help!