Conversation Analytics

Measure your team’s responsiveness to your customers’ messages on Interakt

‍As a business, after you have taken the wise decision of including WhatsApp as a crucial channel for customer communication, you need to start measuring and improving that communication as well. Customers expect super quick responses and resolution via WhatsApp and if your business provides that, they will find comfort in transacting with you.

To figure out whether your team is super quick in responding to and resolving customer conversations, we provide some metrics:

Definitions of Metrics

Why should you close chats?

Examples of calculations

Conversation Analytics1

You can filter the above metrics for specific time periods like

Last 7/30/90 days‍
• Yesterday

Or, you can also set custom dates.

Definitions of Metrics:

Total Conversations: Number of conversations initiated by customers in the selected time period.‍

Conversation Analytics3

What is a conversation?

A chat on Interakt is made up of different conversations.‍
Every time you close a chat
(by clicking the tick mark at the top right of the chat panel), a conversation ends.
‍The 1st message sent by you or your customer in a closed chat starts a new conversation again.

Note:
We don’t consider notifications sent via campaigns or any automated messages (like Out of Office messages) as part of a conversation.

It is very important that your team actively closes chats when the chat does not require their attention any more. Unless this is done, the analytics won’t be meaningful for you.

Why do we say so?

In the above example, the customer’s issue on 13 July was solved on 13 July itself within 15 minutes (2 pm to 2:15 pm). Similarly, the resolution time for 15 July and 17 July was 10 minutes each. However, if the chat hadn’t been closed on those 3 days, the entire exchange would have still been 1 unresolved conversation, which in turn, wouldn’t be an accurate representation of reality.

Responded: Out of customer initiated conversations, those conversations which were responded to, by your team, in the selected period.

Resolved: Number of customer initiated conversations which were responded to and closed in the selected period.

Closed without Response: Number of customer initiated conversations which were closed without a response in the selected period. Check out Example 2 below to see an instance of how this metric is calculated.

Wait time for first agent response: Time taken to respond to the customer’s first message in a customer-initiated conversation. On the dashboard, we show a median of 1st response times across different conversations.

Average Wait time for agent responses: Average time taken to respond to all customer messages in a customer-initiated conversation. Then, a median of the averages obtained from different conversations is taken.
Note: Only closed conversations are considered for this metric.

Resolution time: Time taken to resolve customer initiated conversations (duration between the 1st and last messages in the conversation). On the dashboard, we show a median of resolution times across different conversations.

Confused? We have explained this below using 2 simple examples:

Example 1:

Conversation Analytics4

Total Conversations: 3
Responded: 3
Resolved: 3
Closed without Response: 0

1st Response Time:
=> Median of (2:10 – 2), (4:10 – 4), (3:20 – 3)
=> Median of (10, 10, 20)
=> 10 mins

Average Response Time:
=> Median of:
Average (2:10 – 2), (4:15 – 3)
Average (4:10 – 4)
Average (3:20 – 3)
=> Median of (42.5, 10, 20)
=> 20 mins

Resolution Time:
=> Median of (4:15 – 2), (4:10 – 4), (3:20 – 3)
=> Median of (135, 10, 20)
=> 20 mins

Example 2:‍

Conversation Analytics5

Total Conversations: 2
Responded: 1
Resolved: 1
Closed without Response: 1

1st Response Time:
=> Median of (2:15 – 2)
=> 15 mins

Average Response Time:
=> Median of:
Average (2:15 – 2), (4:10 – 4)
=> Median of 12.5 mins
=> 12.5 mins

Resolution Time:
=> Median of (4:10 – 2)
=> 140 mins

If you want to see data for each conversation, you can click on ‘Export Data’ to obtain a CSV of all conversations in the selected time period. Here, you can conduct your own analysis to get a deeper understanding of how your customers are being responded to.

We strongly suggest setting targets for each of these metrics and aligning your team on those targets. We will soon be sending you weekly emails with a summary of the week’s performance. Having a weekly review with the team should be helpful in gradually achieving your set targets and enhancing your customer’s experience on your WhatsApp channel!

If you have some requirements for analytics which aren’t getting solved by the above, you may let us know here and we will try to help you out 🙂