👾 This feature is currently in Open Beta 👾
Please let our support team know if you have any feedback.
This guide provides an overview of key business, loyalty, and customer metrics, along with suggestions to help you learn from your data, interpret it effectively, and refine your strategies to take meaningful actions aligned with your business goals.
📝 Note: This article is designed for easy navigation using the contents bar →
Omnichannel loyalty dashboard overview
Confidently track performance, optimize customer loyalty efforts, and drive measurable business growth – all from a single, easy-to-use dashboard.
This omnichannel loyalty dashboard does just that! It consolidates data from your Point-of-Sale and eCommerce platforms populating this unified dashboard, providing you with a complete view of your business. You can then dive deeper into the business & loyalty report details, filter by specific sites, and update the timeframe for more targeted insights.
The Omnichannel loyalty dashboard is made up of three key sections:
Business and loyalty metrics
Member snapshot
Timeline
Here’s what makes the omnichannel loyalty dashboard so powerful
View your performance across your entire business in one, unified dashboard 👀
Understand and track the key business and loyalty metrics that drive customer engagement and impact revenue 📊
Use these insights to build and refine data-driven marketing strategies that achieve your business goals 🔎
Free up more time to focus on growing your business by eliminating the need to compare data across platforms ⏱️
Key things to note
Term update: 'Customer' to 'Member'. You’ll now start to see the term ‘member’ used within your Marsello admin. A member refers to anyone listed in your Marsello database with a mobile number or email address. Members are known individuals for whom you’ve begun collecting contact details, demographic and purchase data.
Order timestamps: Orders' date timestamps are currently being calculated based on UTC timezone.
Currency: Currency is displayed in your local currency with '$' displaying as a monetary symbol.
Business and loyalty report
Monitoring your business and loyalty metrics allows you to understand customer behavior, identify growth opportunities, and refine your strategies, helping you make informed decisions that drive profitability and long-term success.
Revenue
Total revenue: Represents the total business revenue for the selected timeframe and site(s), calculated using all orders synced from your Point-of-Sale and eCommerce integrations.
🆕 Change: Based on your feedback, this metric has been updated from attributable revenue to total business revenue. This change is designed to provide a clearer and more comprehensive view of how your business is performing over time. Thank you for helping us improve!
For a detailed breakdown of attributable revenue, you can visit the Analytics section to see which of your marketing efforts are driving revenue for your business.
Total revenue breakdown: Represents how your total revenue is distributed among returning members, one-time members, and unknown customers.
Why it’s important: Understanding where your revenue comes from is key to driving sustainable growth. Revenue from members is repeatable because you can re-engage them with targeted marketing and loyalty initiatives. In comparison, revenue from unknown customers isn’t repeatable, as you are unable to contact and build relationships with them. By converting unknown customers into members, you can create more predictable and consistent revenue streams.
Definitions:
Returning members revenue: Revenue from orders placed by members who have made two or more purchases in their lifetime for the specified timeframe and site(s).
One-time members revenue: Revenue from orders placed by members who have made one purchase in their lifetime for the specified timeframe and site(s).
Unknown customer revenue: Revenue from orders where no customer was attached for the specified timeframe and site(s).
🎓 Key insights you can gain from these revenue breakdown metrics:
| High % | Middle % | Low % |
Returning members revenue | 🟢 If your repeat member revenue is 70% of total revenue or more, that would be considered "high." It shows strong loyalty and repeat business.
You should focus on nurturing these relationships by offering exclusive rewards, personalized marketing, and referral incentives to deepen engagement and encourage continued purchases. | 🟠 If your repeat member revenue is between 40% and 69% of total revenue, that would be considered "middle." This shows a decent level of repeat business but indicates potential for further growth. | 🔴 If your repeat member revenue is 39% or less of total revenue, that would be considered "low." This suggests that customer retention needs improvement.
You should focus on refining your loyalty programs, increasing post-purchase engagement, and enhancing the overall member experience to drive more repeat purchases. |
One-time members revenue: | 🟠 If your one-time member revenue is 50% or more of your total revenue, it would be considered "high." This suggests strong customer acquisition and that many first-time buyers are contributing significantly to your revenue. You should focus on converting these first-time buyers into repeat members by offering personalized incentives, follow-up communication, and loyalty program enrollment to drive future sales. | 🟢 If your one-time member revenue is between 25% and 49% of your total revenue, this would be considered "middle." It shows a healthy balance between attracting new customers and converting them into repeat buyers, but there is room for growth.
| 🔴 If your one-time member revenue is 24% or less of your total revenue, this would be considered "low." This indicates that fewer new customers are making purchases, and it suggests an opportunity to improve customer acquisition strategies. |
Unknown customer revenue: | 🔴 If your unknown customer revenue is 40% or more of your total revenue, it would be considered "high." This suggests that a significant portion of transactions are not linked to members, indicating room for improvement in customer data collection.
You should focus on encouraging more customers to sign up, enroll in loyalty programs, or provide their contact information to improve tracking and future engagement. Staff training plays a crucial role in ensuring they effectively promote these initiatives and guide customers through the sign-up process. | 🟠 If your unknown customer revenue is between 20% and 39% of your total revenue, this would be considered "middle." It shows a balanced level of unidentified transactions, meaning you have a solid base of identifiable members, but there is still some room to capture more customer data.
You should focus on increasing customer registrations, incentivizing sign-ups, and improving your checkout process to capture more customer data for better engagement. Staff training is essential—double down on what’s working, and experiment with new strategies to effectively promote these initiatives and guide customers through the sign-up process. | 🟢 If your unknown customer revenue is 19% or less of your total revenue, this would be considered "low." This indicates that most of your transactions are linked to identifiable members, which is a positive trend, suggesting your customer data capture methods are working well.
You should focus on maintaining this trend by continuing to encourage account sign-ups, loyalty program participation, and customer data collection during the checkout process. |
Graphed Revenue: View the total revenue for the specified timeframe and site(s), broken down by returning members, one-time members, and unknown customers.
🎓 Key insights you can gain from these revenue breakdown metrics:
Compare how much revenue comes from returning members, one-time members, and unknown customers.
Filter: | Graph displays: | Insight: |
This Month | Daily breakdown.
| 'This Month' filter examples:
|
This Quarter | Weekly breakdown. The graphed orders are displayed as a weekly breakdown, allowing you to analyze revenue trends on a weekly basis within the given quarter.
Quarters are defined as:
Note: All time is from the creation date with Marsello. | 'This Quarter' filter example:
|
This Year | The graphed orders are displayed as a monthly breakdown, helping you track revenue patterns on a monthly scale for the current year.
Year is based on a calendar year January 1 - December 31 Note: All time is from the creation date with Marsello. | 'This Year' filter example:
|
Repeat Purchase Rate
This represents the percentage of orders made by members who have made one or more purchases in their lifetime, within the specified timeframe and site(s).
Calculation: (The number of members who made 1 or more purchases ÷ total number of members) x 100
Why it's important: It helps you measure customer retention by tracking how often existing members return to make additional purchases.
🎓 Key insights you can gain from repeat purchase rate
A high repeat purchase rate suggests that customers are coming back to make additional purchases, which is a positive sign for a business's long-term growth.
A low repeat purchase rate suggests that only a smaller percentage of customers are returning to make additional purchases, which indicates low customer loyalty. The retailer needs to improve customer engagement, satisfaction, and retention strategies.
🤖 Key industry statistic: A 5% increase in customer retention results in a profit increase of 25% to 95%.
Key loyalty metrics
Average member order value:
Definition: The average amount spent per order by a member within the specified timeframe and site(s).
Calculation: Number of orders by members ÷ Total Amount spent by members
Why it's important: Average order value provides valuable insights into how much members typically spend per transaction, enabling you to understand purchasing behavior. Use this metric to identify opportunities to increase spend per order, such as upselling, cross-selling, or enhancing loyalty program incentives.
📝 Note: The average member order value may also be referred to as average purchase value.
Average orders per member:
Definition: The average number of orders placed by a member within the specified timeframe and site(s).
Calculation: Total number of unique members ÷ Total number of orders by members
Why it's important: Average orders per member provides insights into the purchasing frequency of your members, helping you evaluate engagement and loyalty. Use this data to identify trends in repeat purchases and consider strategies such as loyalty rewards, personalized marketing, or subscription offerings to encourage more frequent orders.
📝 Note: Average orders per member may also be referred to as average purchase frequency.
Average spend per member:
Definition: The average total amount spent by a member within the specified timeframe and site(s).
Calculation: Total revenue from members ÷ Total number of members
Comparison: The % change shown in the top-right corner represents a comparison with the previous period based on the selected timeframe.
Why it's important: Average spend per member provides insight into the overall spending habits of your members, helping you gauge customer value and identify high-value segments. Use this information to tailor promotions, loyalty rewards, and personalized experiences to maximize member engagement and increase overall spend.
New members from orders:
Definition: The number of members who have signed up when making an order within the specified timeframe and site(s).
Calculation: Total number of orders with a customer attached who didn't previously exist in your Marsello account.
Why it's important: This metric tracks how effectively your business converts new customers into members at the time of purchase. A high number indicates successful engagement and sign-up processes. Use this data to refine your onboarding strategies, optimize opt-in touchpoints, and encourage membership sign-ups during the checkout process.
Members attached to orders:
Definition: The percentage of orders that are linked to a registered member within the specified timeframe and site(s).
Calculation: (Number of orders with a registered member ÷ Total number of orders) × 100
Why it's important: This metric shows the proportion of orders coming from members, helping you assess the strength of customer loyalty and engagement with your brand. A higher percentage indicates a strong member base, while a lower percentage may suggest opportunities to enhance membership sign-ups or increase member-driven purchases. Use this data to optimize loyalty programs and target strategies to convert more customers into members.
Happy members (Customer satisfaction rate):
Definition: The percentage of members who have expressed positive sentiment following their purchase experience, through Feedback, within the specified timeframe and site(s).
Connected to: Feedback
Calculation: (Number of Positive Feedback Responses ÷ Total Number of Feedback Responses) × 100
Why it's important: This metric reflects the satisfaction level of your members, providing insight into the overall customer experience. A higher percentage indicates strong member satisfaction, that is crucial for retention and repeat business. Use this data to identify areas of success in your customer experience and find opportunities for improvement where sentiment may be lower.
🎓 Key insights you can gain from these loyalty metrics individually & combined
| Insight examples: | Action in Marsello: |
Average member order value | If Average Order Value (AOV) is low, then offer upsell or cross-sell opportunities. | Review loyalty rewards: For those simple $ off or % off rewards, consider adding a minimum spend requirement.
Send personalized marketing: Send email campaign(s) and automations that include a product recommendation block to display products customers are likely to purchase next. |
Average orders per member | If Average Orders Per Member is low, then implement a loyalty program to encourage repeat purchases. | Send personalized follow-up emails: After each purchase, send a personalized email thanking the customer and suggesting complementary products or how to take care of the items they purchased. You could include product recommendations, or a time-limited incentive (e.g., a discount or double points) to encourage their next purchase sooner.
Create obtainable rewards: Encourage repeat purchases by ensuring loyalty rewards require multiple purchases to claim, making the rewards meaningful while motivating consistent engagement.
Shorten reward expiry periods: A 30-90 day expiry on rewards creates urgency, prompting members to return and use their points before they expire.
|
Average spend per member | If Average Spend Per Member is low, then introduce personalized discounts or special offers
| Use segmentation: Create custom segments to identify the group of customers who have made at least 1 purchase but have a lower total spend than the average.
Use special offers: Offer limited-time promotions or VIP events for members with lower spending to make them feel valued. For example, provide early access to sales or double points for purchases over a certain amount to incentivize higher spending. |
Average member order value & average spend per member | If both Average Order Value (AOV) and Average Spend Per Member are high, consider enhancing your loyalty program by introducing tiered rewards or VIP levels to encourage even more spending. | Create a VIP Program Based on Average Spend Per Member:
This structure ensures each segment feels valued while incentivizing members to increase their spend and advance to the next tier. |
New members from orders | If New Members from Orders and Member attachment to orders is low, then optimize the sign-up process during checkout Review the registration process, work with staff on how they ask customers to join or offer an immediate incentive, like a discount or bonus loyalty points, to encourage customers to sign up while purchasing. | Customer Display at POS: Enable self-sign-up via a customer-facing display (coming soon to Marsello).
|
Happy members | If Happy Members (Customer Satisfaction Rate) is low, then gather and act on customer feedback. Use post-purchase feedback surveys to identify pain points and make improvements in areas like product quality, delivery, or customer service to boost satisfaction. | Satisfaction ratings: 3. Promote Feedback Opportunities: Let customers know how they can provide feedback, or run a competition to encourage responses. |
Happy members | If Happy Members (Customer Satisfaction Rate) is high, gather and act on customer feedback. Use post-purchase feedback surveys to identify what members love about your brand and leverage this insight for customer acquisition opportunities. | Testimonials: 2. Showcase Testimonials: Feature positive feedback prominently in emails, ads, and on your site to attract and reassure new customers. 3. Reward Happy Members: Thank loyal customers with exclusive perks, discounts, or loyalty bonuses to maintain their satisfaction. 4. Implement a Referral Program: Let happy customers refer their friends and reward them for bringing in new members. |
Member Snapshot:
Your Member Snapshot provides a high-level overview of your members and their relationship with your store. You can identify and target specific member groups based on their shopping behaviors, including; how recently they’ve shopped, how frequently they make purchases, and how much they spend.
This analysis is powered by RFM (Recency, Frequency, Monetary) analysis.
📖 What is RFM Analysis?
RFM is a marketing technique used to analyze and segment members based on three key factors:
Recency (R): How recently a member has made a purchase. Members who have purchased recently are more likely to engage again than those who haven't purchased in a while.
Frequency (F): How often a member makes a purchase. Frequent buyers are typically more loyal and valuable to your business.
Monetary (M): How much money a member spends. Members who spend more are typically more valuable to your business.
RFM analysis is a widely used and highly effective technique, especially in fields like retail, e-commerce, and direct marketing. Businesses leverage RFM analysis to enhance member segmentation and personalize their marketing efforts. It’s popular because it provides clear, actionable insights into member behavior, enabling companies to optimize their marketing strategies, improve member retention, and boost sales.
Segments
Using RFM, members can be organized into segments. These segments range from 'Best' members (very loyal and huge fans of your store) to 'Cold' members (may need reminders to shop with you again).
How segments are created and calculated:
Initially: When you connect Marsello to your eCommerce or POS site(s), your customer database and order history (last purchase date, total spend, number of orders) syncs into Marsello and distribute members across the seven RFM segments appearing on your dashboard.
Historical customer and order sync is available for the following integrations:
Shopify; Shopify POS, eCommerce and Plus
Lightspeed: X-Series, R-Series, O-Series, C-Series
Cin7
Heartland
WooCommerce
Historical customer and order sync is not available for the following integrations:
Lightspeed K-Series, E-Series
Bopple (Lightspeed Ordering)
BigCommerce
📝 Note: Historical sync can take 1-2 days depending on the quantity of data syncing.
Going forward: All segments are recalculated daily, and each individual is re-categorized after every purchase to ensure the segments accurately reflect their most recent shopping behavior.
RFM Member Segment definitions:
Best: Members who have ordered very recently, order most frequently, and spend the most.
Loyal: Members who have ordered recently, order often, and spend a substantial amount.
Promising: Members who have ordered recently, ordered more than once, and spend an average amount.
New: Members who have made their first purchase recently.
At Risk: Members who haven’t ordered in 2 or more average purchase cycles.
Cold (Previously Lost): Members who haven’t ordered in 4 or more average purchase cycles.
Potential (Previously Window Shoppers): Members who have provided an email or mobile number but have never made a purchase.
📝 Note: These segments are mutually exclusive, meaning that each member can only be in one segment at one time.
Chosen marketing channel(s):
This displays the distribution of members who have opted-in to receive marketing from your business, highlighting their preferred communication channels.
Email only: These members only accept email marketing from your store.
SMS only: These members only accept SMS marketing from your store.
Email & SMS: These members accept both email and SMS marketing from your store.
🎓 Key insights you can gain from chosen marketing channel(s):
Knowing your members' preferred communication channels is essential for optimizing engagement, personalizing interactions, and ensuring your marketing efforts are both effective and customer-focused. For example:
SMS only, Email & SMS: Have you considered using SMS as a marketing channel?
Reviewing the number of members who have opted-in to SMS marketing can give you the confidence to experiment with this channel.
Or if SMS isn't part of your strategy yet, it's worth revisiting your marketing opt-in process to grow your SMS opt-in member base. This will ensure that, when you're ready to implement SMS marketing, you have a solid foundation for success.
RFM member segments & chosen marketing channels:
Click into each Segment to see more information about each RFM segment.
For each segment you'll see the follow details:
RFM segment name
Order size: The average amount spent per order by a member for the specified RFM segment
Order rate: The average number of orders made by a member for the specified RFM segment.
Spend: The average total amount spent by a member for the specified RFM segment.
Chosen marketing channel: Displays the distribution of members who have opted-in to receive marketing from your business, highlighting their preferred communication channels for the specified RFM segment.
🎓 Key insights:
Personalize the marketing communication channel and message depending on the RFM segment you're looking to focus your efforts. For example:
| Insight | Action |
New segment | The 'New' segment has a higher number of members who have opted in to SMS, indicating that this channel may be an effective way to connect with these new customers and foster stronger relationships. | To engage these new customers, consider implementing a "thank you" automation for first-time buyers, sent via SMS. This could include a personalized thank-you message, an exclusive offer, or a notification on how many loyalty points they earned. This approach can help solidify their loyalty early and encourage repeat purchases, while leveraging SMS as an effective communication channel for building customer rapport. |
Best & Loyal segment Comparison | The 'Loyal' segment has an average order value (AOV) of $150, which is significantly lower than the 'Best' segment’s AOV of $500. This suggests that while these customers are frequent and recent buyers, there is an opportunity to increase their spending per order. | To encourage higher spend from your 'Loyal' customers, consider offering personalized incentives such as exclusive rewards with a minimum spend, or limited-time promotions that encourage upselling or cross-selling to drive higher average order values within this segment. |
Member timeline
The daily activity feed provides a feed of any loyalty actions completed by your members. You can track new member sign-ups, as well as see who is earning and spending their loyalty points. This feature helps you stay updated on member engagement and provides valuable insights into how your loyalty program is performing.
🆕 Change: Back by popular demand, previously your loyalty activity feed was available on your home page – this was greatly missed, and is now back!
Simply click Open timeline for your daily feed to display.
Timeline loyalty activities include:
All earn options,
e.g. [Member name] created an account [time]
Points manually adjusted
Referred a friend
Product review
Birthday celebration
All orders, e.g. [Member name] made a purchase, earning [##] points [time]
All reward actions, e.g. [Member name] claimed reward: [reward title] [time]
🔮 Want to see more? If you'd like additional activities added to this timeline, please reach out to our support team to let us know!
FAQs
Feedback
We’d love to hear your feedback on this Omnichannel loyalty dashboard! Let us know what’s helpful, what improvements or additional metrics you'd like to see, and if anything is unclear or needs further explanation. Our goal is to create the ultimate dashboard that provides you with clear insights and actionable data to support your omnichannel business.
Simply send us a message through the chat icon or send an email to [email protected].
Common questions
Q: Can I filter the RFM segments by site(s) and timeframe?
A: RFM Segmentation is an analysis that is across all members, all time. The ability to see movements overtime is currently a feature request, if this interests you, please reach out to our support team to let us know!
Q: What is the start date for the 'All time' timeframe?
A: If you select, 'All time' for the reporting period, this begins from the date your Marsello account was created.
Q: Can I see my historical data in the Business and Loyalty report?
A: Currently the Business and Loyalty report data displays from the date the date your Marsello account was created forward. Historical data is currently a feature request, if this interests you, please reach out to our support team to let us know!
Q: Can I download/export my Omnichannel loyalty dashboard?
A: If you want to capture a snapshot of the data, we suggest downloading GoFullPage - Full Page Screen Capture from the Google Chrome add-on store or equivalent. The ability to export this page is currently a feature request, if this interests you, please reach out to our support team to let us know!