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26 4月, 2022Customize your widget text
26 4月, 2022How does BON Analytics feature work?
Welcome to Analytics, your powerful tool to gain valuable insights into how BON is benefiting your store and how customers are engaging with your loyalty program. Use these insights to optimize your program and drive even greater results.
Overview about Analytics feature
The Analytics feature is divided into four main sections: Loyalty Performance, Program Engagement, Points Overview, and Referral Program. Depending on the goals of your loyalty program, each section in the Analytics feature will provide you with the most up-to-date and practical information about the effectiveness of your program, specifically:
- Loyalty performance: This section highlights the impact of the current Loyalty program on the store’s revenue through metrics such as Revenue Generated, Orders Influenced, and Average Order Value.
- Program engagement: This section indicates the reach of the loyalty program among the store’s current customer base.
- Points overview: This section provides an overview of the points being used by the merchant’s customers, showing how the points program is operating within the store.
- Referral program: This section illustrates the impact of the referral program on acquiring new customers through referral activity and the revenue generated from it.
Metrics explanation
1. Loyalty performance
- Revenue influenced (Order involved BON): Total revenue generated from orders where customers used BON rewards (points, discounts, etc.).
- Order influenced: Total number of orders where customers used BON discounts.
- Average order value (AOV): Average amount spent by BON members per transaction.
2. Program engagement
- Action earn points over time: This chart shows how often customers have earned points within a selected period.
For example, imagine a store’s chart shows a peak in point-earning actions during a promotional week. This might indicate a strong interest in the loyalty program, with customers actively engaging to earn points.
Let’s say the store also has an expiration date for discount codes earned through points. Customers who are earning points more frequently are likely planning to use those rewards, which may encourage them to make repeat purchases before their rewards expire. This kind of behavior reflects an increase in the store’s repeat purchase rate—demonstrating how the loyalty program can boost customer retention through frequent engagement with points.
- Action redeem points over time: This chart displays the total number of times customers have redeemed points during a selected period.
For instance, if the chart shows a high number of point redemptions, it indicates that customers find the rewards enticing. This level of engagement often correlates with increased spending, as customers who redeem rewards tend to make more frequent purchases to accumulate points and reach the minimum spending requirements for further discounts.
On the other hand, if redemptions are low, it may suggest the rewards aren’t as appealing. For example, if customers need to collect a high number of points to redeem a reward, they might find it challenging to engage fully.
- Top ways customers earn points: This chart shows the top five actions that customers most frequently perform to earn points.
Store owners can use this information to identify which point-earning activities are most effective and potentially promote these actions further to drive higher engagement.
- Top ways customers redeem points: Similarly, this chart displays the top five rewards that customers redeem most often.
For instance, if discounts on future purchases and free shipping are the top rewards, it indicates that customers are particularly drawn to these options. This insight helps store owners understand which rewards resonate most with their customers, allowing them to focus on these popular offerings or explore similar rewards to enhance program appeal.
3. Points overview
- Total points earned: Points earned by customers during time period A-B, excluding points from refunded orders
- Total points redeemed: Points redeemed by customers for discounts during time period A-B
- Redemption rate: This metric shows the percentage of points that customers have redeemed at the store, calculated by dividing the total points redeemed by the total points earned.
Helpful tips: This data allows you to monitor the overall effectiveness of your loyalty program. By displaying both the total points earned and redeemed by your customers, you can gauge how engaged they are with the rewards you offer.
For instance, if your report shows that 3.400 points were distributed in the first week of the month and 850 points were redeemed, you can quickly see that 25% of the points have been used. This redemption rate provides insight into how appealing your rewards are to customers.
If this percentage is low, it could indicate that the points required to redeem rewards might be set too high, or that customers may be choosing to save points for higher-value rewards instead. Additionally, a low redemption rate could suggest that the current reward offerings aren’t enticing enough, leading customers to accumulate points without redeeming them. Observing this rate helps you decide if any adjustments in point requirements or reward options could encourage greater customer engagement with your loyalty program.
- Points volume over time: the total amount of points awarded or redeemed within your loyalty program over a specific timeframe.
This time-based chart gives you an overview of how points are being redeemed each day. By analyzing this data, you can identify patterns in customer behavior, such as which days have the highest redemption rates.
For example, if the chart reveals a spike in redemptions on certain days, you can use this information to predict future trends and tailor your marketing efforts accordingly. Understanding these trends will enable you to optimize your reward offerings and better align them with your customers’ habits, ultimately enhancing the effectiveness of your loyalty program.
4. Referral program
- Revenue from referred customers: Number of orders purchased successfully by referred customers via referral program.
- Successful referral: Number of successful referrals (Order of person B is fulfilled and person A receives rewards)