Reporting Dashboard

Statistics & Reporting

It is vital to monitor the performance of your chatbot to keep up with the changing demands of your user’s world. This could include adjusting the language used or to user journey’s that you require due to a change in operations.

Bot performance can be reviewed within ‘Reports’ tab found at the top of your MLC page. Here you will be able to monitor the use of your chatbot in real-time by viewing unique users and message numbers sent in a prescribed time period.

With account access, you will automatically be granted permissions to design and build your own reporting dashboards. Your dashboard is fully customisable and can be siloed for different projects, people, or bots.

Perhaps your conversation design team require one dashboard to review drop-off points and fallbacks, however your project manager requires a high-level dashboard report on chat volumes and Goal Completion Rates. This is all achievable within your personalized dashboard settings.

What can be reported on?

New Users

User interacting with the bot for the first time.

Returning Users

User who re-engages with the chatbot after an elected time period.

Active Users

New and/ or returning users who engaged with the bot within a stated time frame. Active Users count does not count unique users: a new user coming back after 8 hours will be displayed as 2 active users during the selected period.

Messages (Chat Volumes)

Number of messages generated during a time period.

Unhandled Messages

Count of fallback messages or wrong replies.

Average Conversation Length

Average count of minutes passed between first message and last before the conversation becomes idle. (idle recorded after 15 minutes of inactivity).

Retention Rate

Expressed as a percentage of returning users over total number of users during a selected period.

Human Takeover Rate

Percentage of conversations that result in operator hand-over.

Average Bot-to-Human Handover Time

Average time in minutes taken for a human operator to send their first message once the conversation has been assigned to them.

Average Human Conversation Length

Average time in minutes of a conversation between a human operator and a user.

Goal Completion Rate & ROI Values

Goals are created inside the bot builder as a specified interaction called ‘goal completion’. Goals can be defined in the reporting zone by providing a name, description, unit value, measure unit, goal value and time frame (low as hourly, high as yearly).

Example goal. Daily Users Conversion Goal: Have at least 30 users transformed into leads daily.

o Name: Daily Users Conversion

o Default Value: 1

o Goal: 30

o Reference Period: Day

Data Consolidation

All Connect data points will be collected by the application by real-time conversation events that will be consolidated into statistical data by the analytics microservice.


MyLINKConnect’s analytics centre provides chatbot builders and stakeholders the ability to identify conversation lengths, drop-out stages, unique versus total conversation counts and more. Our roadmap sees analytics as a key area for development. More on roadmap?

Analytics are very powerful for brands when launching and maintaining a bot. They allow the builder to recognise pain points for users and act to overcome these. It will also be valuable for brands to be able to recount the ROI and associated resources saved by using the bot. For example, a bot with 5,000 conversations, is a bot that has reduced on average 416 hours of customer service’s time (with a 5-minute average call time). Not only this but when NLP cannot determine the user’s intentions, designers can identify areas of knowledge that the bot is absent in and address this through training.

The broad range of channels is a great pull for customers and means that should trends shift within their needs or customer base, they are easily able to shift to a different distribution channel for their bot, without the need to uproot all previous designs and work.

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