The Revenue created by Loyalty customers graph shows your revenue with a daily breakdown including data on:

• Total revenue - The total revenue is the sum of all purchases during the selected time period, based on your sales data uploaded to Emarsys. This also includes returned items (refunds), the value of which decreases the total revenue.
• Revenue generated by Loyalty customers - The revenue from Loyalty customers.
• Loyalty revenue impact: The percentage of total revenue generated by Loyalty customers out of the total revenue
• Tier impact: The percentage of revenue generated by a specific Loyalty tier out of the total revenue

The Average Order Value graph shows your daily Average Order Value (AOV) broken down by:

• Loyalty customer - Loyalty customer who purchased at least once in the last 365 days
• Non-Loyalty customer - Non-Loyalty customer who purchased at least once in the selected period
• Loyalty tier breakdown

You can also see a trend of your Loyalty uplift which is the increase value (calculated in percentage) you earned from Loyalty in the selected period.

The uplift calculation is done as the following:

The difference between Loyalty and Non-Loyalty AOV is divided by the Non-Loyalty AOV: This gives you the percentage change of Loyalty AOV compared to Non-Loyalty AOV.

The KPI of Loyalty and Non-loyalty AOV is the average of the daily data seen on the graph.

The Number of purchases in a time period graph shows the average number of purchases made by customers who bought during the selected timeframe, during a period based on your Smart Insight recency settings. This period is equal to your Defecting Recency limit set in Smart Insight.

This period is unique to your account.

The calculation for the daily values in the graph is the following: 

• For each day in the selected period, we find the customers who purchased on the same day. 
• For these customers, we look at the last X days ending on the day in the selected period, where X = Defecting recency limit.
• For each customer, we find all their purchases done in the last X days 
• We divide the customers into groups:
  • Loyalty customers
  • Non-loyalty customers
  • Further breakdown by tier level
• Finally, we average the number of purchases per group. This gives us the average number of purchases for that group for that day in the selected period,  which you can see on the graph.

The assignment of a customer to a group is done according to the day you choose on the graph. We check to which group the customers belong to on that day: Are they Loyalty customers or not? If they are Loyalty customers, to which tier do they belong.

You have the option to switch the graph to the uplift mode, to see the percentage value of uplift of Loyalty customers compared to Non-Loyalty customers.

This is a cumulative graph which shows your total amount of Loyalty members per day. The graph also breaks down the members into tiers and shows the percentage of each tier from all members.

This graph shows the amount of new customers who joined day by day. It will differentiate between:

• Customers - contacts who already purchased in the past, before becoming Loyalty customers
• Leads - contacts who joined Loyalty and have not purchased before 

This graph helps you to know your new enrollments, and it is very useful to check if a specific promotion you ran contributed to a higher rate of contacts joining your Loyalty program.

This graph shows the percentage of members who have accumulated points from purchases and actions, or have redeemed points for rewards, in the selected time period.

It also provides a breakdown by tier: It shows the percentage of customers from that tier that were active on that day.

This graph shows you percentage for points redeemed for rewards, out of the earned points, during the selected time period, based on your Smart Insight Recency settings. It will show you if customers who earn points are also redeeming them or there are points not being used. The higher the percentage, the more your customers are redeeming their points.

The rate is shown with a daily breakdown per tier and also in general for all Loyalty customers.

The calculation is as follows: 

• For each day in the selected period, Loyalty finds the customers who earned or spent points for that day.
• For those customers, Loyalty looks at the last X days ending on the day of the selected period, where X = Defecting recency limit. 
• Per customer, we find all earned and spent points in the last X days 
• Loyalty divides the number of redeemed points by the number of earned points for that customer and this gives you the individual redemption rate.
  The rate can never be higher than 100%, we always cap it at 100%. (Theoretically, the redemption rate can be higher than 100%, if the customers are also redeeming points collected in earlier periods.)
• Loyalty divides the customers into tiers according to the day you choose on the graph. 
• Loyalty averages the redemption rate per tier. This gives you the average redemption for that group for that day.

This graph shows data about the balance points of your customers with a daily breakdown divided into:

• Accumulated points: The total number of confirmed points accumulated by Loyalty members in the selected time period
• Redeemed: The total number of redeemed points in the selected time period
• Pending: The number of points that are in pending state
• Expired: The number of points expired (Points to spend)

This graph shows the data about vouchers with a daily breakdown:

• Issued vouchers: The total number of confirmed vouchers accumulated through actions, and the total number of vouchers issued for fixed benefits, in the selected time period, before redemption.
• Redeemed vouchers: The total number of vouchers accumulated by actions and fixed benefits, whose code is exposed in the Wallet in the selected time period.
• Voucher for points: The total number of vouchers purchased in points in the selected time period.