Journey Analytics:
Journey analytics provides insights into the effectiveness and efficiency of customer journeys. This involves analysing the interactions customers have with various touch points and understanding how these interactions lead to conversions, engagements, and triggered actions.
To navigate to the journey analytics please click here.
The journey analytics is divided into three main sections:
1. Conversions: Measures the end goals like orders placed, revenue, and other key performance indicators.
2. Engagement: Analyses how users interact with various elements within the journeys.
3. Triggers: Tracks the specific actions that prompt user interactions within the journeys.
Date Range Filter: Users can filter the data by selecting a specific date range.
Journey Channel Filter: Users can filter the data based on specific journey channels to get more granular insights.
Conversions:
The conversion screen provides a detailed view of how well the customer journeys are performing in terms of achieving desired outcomes.
1. Conversion Overview:
This section provides a summary of key metrics indicating the effectiveness of the journeys that have been set up. The metrics include:
Orders Placed: The total number of orders completed by customers for the selected date range.
Revenue Generated: The total revenue generated from these orders
Average Order Value: The average amount spent per order.
Products Viewed: The number of product views by customers for the selected date range via journeys.
Add to Carts: The number of products added to carts by customers for the selected date range via journeys.
Reviews Collected: The number of reviews that were submitted using the JudgeMe block in journeys.
2. Return on Investment (ROI):
This metric indicates the profit made from the journeys. Note that these figures are estimations and can be slightly off due to the nature of predictive calculations.
ROI = (total revenue - total cost ) / total cost * 100
ROI (WhatsApp)= number of delivered count * 0.8
3. Channel-Wise Split of Revenue & Orders:
This section breaks down the revenue and orders by different channels (e.g., email, social media, direct traffic) to understand which channels are most effective.
4. Top 5 Journeys in Terms of Revenue:
Provides detailed insights into the top-performing journeys based on revenue.
Details include:
Journey: The name or identifier of the journey.
Channel(s): The channels through which the journey is executed.
Orders: The number of orders attributed to the journey.
Revenue: The revenue generated from the journey.
Add to Carts: Number of times products were added to carts in the journey.
Product Viewed: Number of product views in the journey.
Total Triggers: Number of triggers activated within the journey.
Messages Sent: Total messages sent to customers in the journey.
Unique Customers: The number of unique customers who interacted with the journey.
5. User Growth:
This summary includes metrics related to new leads and user interactions:
New Leads Collected: Total number of new phone numbers or emails collected via journeys.
6. Retention:
Monitors the impact of journeys on customer retention:
Number of Repeat Orders: The total number of repeat purchases attributed to the journey.
Repeat order is based on the number of repeated orders placed per customer for that particular selected date.
7. Channel-Wise Split of Leads Collected & Repeat Orders:
Breaks down the leads collected and repeat orders by different channels.
8. Top 5 Performing Price Please Automation:
This section includes details on the top-performing price please automations in terms of engagement and revenue: It includes
Revenue: Revenue generated from these automations.
Total Comments: The number of comments on social media posts related to the automation.
Triggered: Number of times specific actions within journeys are triggered.
Messages Sent: Total number of messages sent to customers as part of journeys.
Links Clicked: Number of times links within journey messages were clicked.
Ordered: Number of orders placed as a result of the journey.
9. Lifecycle of Journeys Triggered Day-on-Day/Week-on-Week:
This section provides a daily and weekly analysis of journey triggers and their performance:
Average Orders Placed Daily: Average number of orders placed each day, including percentage change compared to the last x days.
Average Revenue Generated Daily: Average revenue generated each day.
Average Flow Triggered: Average number of times a journey is triggered each day.
Average Repeat Orders: Average number of repeat orders each day.
The lifecycle includes Product Views, Add to Carts, Orders Placed details on day-on-day or month-on-month basis.
Note:
The data is only for journeys triggered within the selected dates.
"All channels" filter includes data for SMS messages sent.
Top 5 journeys are sorted based on the Revenue.
For each metric you can compare the difference & % difference in parameters with respect to the previous x days.
For today filter, there will be no Lifecycle graphs.
For Instagram - there will be no ROI & channel wise revenue/order split.
For channels with one channel id connected there will be no ROI, channel wise revenue/order split, user growth, retention, channel wise split of leads collected and repeat orders. To get details for these please choose "All channel" from dropdown.
To get details for ProductViewed & Add to Cart events please turn on frontend event tracking in settings.
Product viewed and add to cart data only counts events happened with the help of redirection to client website and not direct cart addition from cart.
If email is disconnected ROI for email channel will not be visible.
Review Collected data in conversion overview will only be visible if Judge me is integrated.
Engagement :
Engagement analytics focuses on measuring and analysing how users interact with the content and messages sent through various customer journeys. It includes metrics related to message delivery, user interactions, and engagement rates. This helps in understanding the effectiveness of the engagement strategies and identifying areas for improvement.
The engagement screen is divided into several key sections, each providing insights into different aspects of user engagement. Below is a breakdown of the subcategories within the engagement screen:
1. Engagement Overview:
This section provides a summary of key engagement metrics over the last x days, with percentage changes compared to the previous days:
Journeys Triggered: The total number of journeys that were initiated.
Messages Sent: The total number of messages sent to users.
Links Clicked: The total number of times users clicked on links in the messages.
Read Rate: The proportion of messages that were read.
Click Through Rate: The proportion of messages that resulted in a click.
Unique Customers: Total unique customers who interacted with journeys
Read Rate = messages read/ total messages sent
Click Through Rate = Links Clicked / total messages sent with or without links
2. Top 5 Journeys in Terms of Engagement:
This section provides details on the top 5 journeys with the highest engagement.
Details include:
Journey: The name or identifier of the journey.
Channel(s): The channels through which the journey is executed.
Total Triggers: Number of times the journey was triggered.
Messages Sent: Total messages sent within the journey.
Links Clicked: Total link clicks within the journey.
Read Rate: The rate at which messages were read within the journey.
Click Rate: The rate at which messages resulted in clicks within the journey.
3. User-Initiated Conversations:
This section tracks the conversations that were started by users and their interaction patterns:
Conversations Started by User: Total number of conversations initiated by users.
New Users Interacted: Number of new users who interacted with the system.
Agent Handovers: Number of conversations handed over to human agents from chatbot.
4. Chatbot Performance:
This section provides insights into the performance of the chatbot in handling user interactions:
Average Messages per Conversation: Average number of messages exchanged per conversation.
Bot Closures: Number of conversations successfully closed by the chatbot without needing human intervention.
Bot closure = [(UIC sessions - agent handover) / (UIC sessions)] * 100
5. Channel-Wise Split of Links Clicked:
This section breaks down the number of links clicked by the channel used to send the messages.
6. Lifecycle of Journeys Triggered Day-on-Day/Week-on-Week:
Provides metrics related to message engagement:
Average Messages Sent per Day: The average number of messages sent each day.
Average Messages Delivered per Day: The average number of messages successfully delivered each day.
Average Messages Read per Day: The average number of messages read each day.
This section also includes a graph based on the following events:
Messages Sent
Messages Delivered
Messages Read
Link Clicked
7. Lifecycle Over Last X Days:
This section provides a graph for message engagement over the last X days:
Average Links Clicked per Day: The average number of links clicked each day.
Funnel of Sent, Delivered, Read, Clicked: Visual funnel showing the progression from messages sent to messages clicked in case of WhatsApp & email.
Funnel of Sent, Read, Clicked: Visual funnel showing the progression from messages sent to messages clicked in case of Instagram.
Graphical representation of Sent, Delivered, Read, Clicked in case of "All channel" filter.
Note:
The data is only for journeys triggered within the selected dates.
For Instagram - there will be no delivered event.
All channels includes data for SMS messages sent.
For each metric you can compare the difference & % difference in parameters with respect to the previous x days.
For today filter, there will be no Lifecycle graphs.
Top 5 journeys are sorted based on the Click Rate.
Link clicked count are not unique.
Conversation started by user includes the count of instagram triggers like comments, pp, dm on post/ad, story replies.
Triggers:
Triggers analytics focuses on measuring and analysing the actions that initiate customer interactions within various journeys. This includes tracking the total number of triggers, identifying capped and cancelled triggers, and monitoring the number of active customers within journeys.
1. Triggers Overview:
This section provides a summary of key trigger metrics over the last x days, with percentage changes compared to the previous days:
Total Triggers: The total number of triggers activated.
Triggers Capped: The number of triggers that reached their limit and were not activated further.
Cancelled Triggers: The number of triggers that were cancelled.
Customers Active in Journeys: Total number of customers whom at least one message was sent.
Active Customers %: This metric indicates the percentage coverage of journeys across all your customer active customer base.
Active customer % = (Customers Active in Journeys / Total Active customer) * 100
2. Top 5 Journeys in Terms of Triggers:
This section provides details on the top 5 journeys with the highest number of triggers. Details include:
Journey: The name or identifier of the journey.
Channel(s): The channels through which the journey is executed.
Total Triggers: Total number of times journeys have started.
Triggers Capped: Number of times journeys were stopped because of frequency capping.
Cancelled Triggers: Number of times journeys were cancelled because of another intersecting journey.
Customers Active in Journey: Number of customers with brand whom at least one message was sent.
Note:
The data is only for journeys triggered within the selected dates.
For each metric you can compare the difference & % difference in parameters with respect to the previous x days.
Top 5 journeys are sorted based on the number of total triggers.
For further assistance or to raise feature requests related to journey analytics, please contact [email protected].