This dashboard displays the high-level insight performance overview of loyalty program and feedback features.
Choose your Analytics timeframes
By default, insights display your lifetime results on Marsello. You can view your analytics during a specific timeframe by clicking on the date picker.
You can also choose the time period displayed on the analytics graphs; i.e. Daily, Weekly, or Monthly.
🤖 Data analytics: Your analytics are updated every 8 hours. Marsello analytics are calculated using data from after you've installed Marsello. The analytics page does not show historical data.
Loyalty program analytics explained
The Loyalty program dashboard displays everything you need to know about the success of your loyalty program. With these analytics, they will be able to make effective changes and iterations to your program to increase engagement.
Statistic Definitions:
📝 Note: All of these statistics are measured against the selected timeframe.
Loyalty program engagement rate: The percentage of customers who have engaged in your loyalty program. This compares the number of customers who have earned points or redeemed rewards against those who haven't.
Loyalty points earned: Total loyalty points earned by customers.
Point redemption rate: The percentage of customers who have used their loyalty points to claim a loyalty reward. This compares customers who have used their points vs those who haven't.
📝 Claimed reward vs redeemed reward definitions:
Claimed reward: The customer has used their points to access their unique reward discount code, but hasn't used it in conjunction with order yet.
Redeemed reward: The customer has used their unique reward discount code in conjunction with an order.
Reward redemptions: Total loyalty rewards redeemed by customers.
Reward redemption rate: The percentage of customers who have claimed a loyalty reward vs customers who have redeemed the loyalty reward during the selected timeframe. This compares customers who have used their loyalty reward discount codes vs those who haven't.
VIP customers: The total number of customers that are in the 2nd tier or higher of the retailer's VIP Program.
Successful referrals: Total customers who have made an order after being referred to the retailer's store by an existing customer.
Key takeaways from graphs
Graph 1: Loyalty points earned vs spent over time
This graph tracks the number of points earned vs the number of points used (spent) during the selected timeframe.
This is a useful indicator of how many of your customers are engaging with your loyalty program and redeeming rewards.
💡Tip: If your customers' points spend is low, you may want to re-evaluate and adjust your loyalty rewards, turn on loyalty emails (especially reward unlocked emails), or enable points expiry (this will encourage customers to claim rewards before their points expire).
Feedback analytics explained
The Feedback survey is automatically embedded in the Earned Points loyalty automation email or Standalone feedback custom automation. One of these email automation must be enabled for the customer to receive your survey.
Graph 1: Customer Satisfaction Rating
This graph tracks your customers' response to the Feedback survey which they receive after completing an order. The percentage is calculated by dividing 'Positive' responses by total feedback responses from your customers. This is measured against the selected timeframe.
This is a useful indicator of your customers' overall satisfaction after shopping with your store.
💡Tip: If customer satisfaction is below 80%, you can find a breakdown of each customer response in the Feedback dashboard. To find unsatisfied responses faster, filter Feedback by 'Negative' under the Satisfaction condition. You can identify areas that need attention and action on customers' responses privately.
Graph 2: Feedback responses
This graph tracks the total number of 'Satisfied' vs 'Not Satisfied' responses to the Feedback survey which they receive after completing an order. This is measured against the selected timeframe.
This is useful to compare the amount of 'Satisfied' vs 'Not Satisfied' responses at a glance.
Graph 3: Feedback responses over time
This graph tracks the amount of 'Positive' vs 'Negative' responses to the Feedback survey over time. This is measured against the selected timeframe.
This is a useful indicator of customer satisfaction over an extended period of time.
💡Tip: If you identify an area to improve and make a change, you can visually track the impact of that change on your customers' satisfaction going forward. Also, under the Feedback dashboard, you can see if customers' responses reflect that change. For example, if you make a change to improve 'wait time', you could expect to see a change in customers' responses.
Graph 4: Overall Positive Feedback Reasons
This graph tracks the reason that your customers' left a positive response to the feedback survey. This is measured against the selected timeframe.
This is a useful indicator of why your customers were satisfied with their shopping experience.
💡Tip: If you identify an area where your store’s doing well, this can be a great thing to relay to your staff to help boost morale. For example, the feedback responses show that customers like your store's ‘customer service', telling your staff that they're doing a great job can boost team morale and also help positively reinforce this behavior 😊
Graph 5: Overall Negative Feedback Reasons
This graph tracks the reason that your customers left a negative response to the feedback survey. This is measured against the selected timeframe.
This is a useful indicator of why your customers were not satisfied with their shopping experience.
💡Tip: If you identify an area that your store can improve, then you can take action to improve that particular area of the store. For example, the feedback responses show that customers dislike your store's ‘wait time’, you would be able to track the success of the actions that you take to reduce 'wait time'. You would expect to see fewer customers listing wait time if they left negative responses, or alternatively, more customers listing ‘wait time’ as a reason for their positive response.