Overview
The Perkstar dashboard is your central hub for monitoring business performance, customer behaviour, and loyalty programme effectiveness. This comprehensive analytics interface provides real-time insights into visits, revenue, customer retention, feedback, referrals, and customer demographics—all in one place.
What the dashboard shows:
Visit patterns and customer frequency
Revenue metrics and average order values
Customer retention rates over time
Feedback ratings and satisfaction levels
Referral programme performance
Customer demographics and profiles
Top customers by visits or spending
Tip: The dashboard transforms raw loyalty programme data into actionable insights, helping you make informed decisions about marketing, operations, and customer engagement strategies.
Before You Begin
Requirements:
Active Perkstar account
Loyalty card(s) created and in use
Customer transactions recorded in the system
Some historical data for meaningful trends
Note: The more data your system has collected, the more valuable your dashboard insights become. New accounts with limited data will show basic metrics that become more meaningful over time.
Accessing the Dashboard
To view your dashboard:
Log in to your Perkstar account
The main dashboard typically appears immediately after login
Or click Dashboard or Home in the left-hand menu
What you'll see:
Multiple sections with different metric categories
Graphs and charts visualising your data
Time period selectors for customising views
Interactive elements (hover for details, click for deeper analysis)
Dashboard Sections
Info: The dashboard is organised into six main sections: Visits, Activity, Retention, Feedback Rating, Referral Programme, and Customer Profiles. Each section provides specific insights into different aspects of your business performance.
Visits Section
Overview
The Visits section tracks customer visit patterns, showing total visits, repeat customer behaviour, and referral activity.
Key metrics displayed:
Top summary cards:
Total Visits - Total number of customer visits in selected period
Repeat Customers - Number of customers who visited multiple times
Last Period - Comparison to previous equivalent time period
What these numbers mean
Total Visits:
Counts every visit recorded in your system
Includes first-time and repeat customers
Higher numbers indicate more foot traffic
Shows overall business activity level
Repeat Customers:
Counts unique customers who visited 2+ times in the period
Measured by number of customers, not number of visits
Key loyalty indicator (repeat customers are engaged)
Shows programme stickiness and customer retention
Last Period:
Compares current period to previous equivalent period
Shows growth or decline trends
Green/up arrows indicate improvement
Red/down arrows indicate decline
Visit Patterns Graph
Main visualisation:
Bar graph showing visits by day/week/month (depending on time period selected)
X-axis: Time (dates)
Y-axis: Number of visits
Bars color-coded for different customer types
Hover functionality:
Hover over any bar to see detailed tooltip with:
Total visits on that date (or period)
New customers (first-time visitors)
Repeat customers (returning visitors)
Referrals (customers from referral links)
Color-coded values for easy identification
Reading the graph:
Tall bars = high-traffic days/periods
Short bars = slow days/periods
Patterns reveal busy times (weekends, paydays, etc.)
Anomalies show special events or issues
Right-Side Indicators
Three circular progress indicators:
1. Repeat Customers
Graphical representation (pie chart or ring)
Shows percentage of repeat vs. new customers
Higher percentage = better loyalty and retention
Goal: Increase repeat customer percentage over time
2. New Members
Shows new customer acquisition
Percentage or count of first-time visitors
Indicates programme growth
Balance needed: New + Repeat = healthy growth
3. Referrals
Customers who installed card via referral link
Word-of-mouth effectiveness indicator
Shows viral growth potential
Higher numbers = satisfied customers sharing
Time Period Selection
Customise your view:
Located at top-right corner of Visits section:
Day - View hourly or daily breakdown for today
Month - Current month's data (default)
Year - Full year overview
All Time - Complete historical data since account creation
Period (Custom Range) - Select specific date range
Why time periods matter:
Day view:
Understand daily patterns
Identify peak hours
Staff scheduling insights
Month view:
Track monthly performance
Compare to previous months
Identify weekly patterns (weekends vs. weekdays)
Year view:
Spot seasonal trends
Annual growth trajectory
Long-term planning
All Time:
Complete programme history
Major milestone tracking
Overall growth story
Custom Period:
Compare specific campaigns
Seasonal analysis (Christmas 2023 vs. 2024)
Event-based performance
Definitions and Calculations
Total Visits:
Every recorded transaction where customer earned stamps/points
Includes all customer types (new, repeat, referral)
Does not include card installs without transactions
New Customers:
Customers who made their first visit during selected period
Only counted once (on their first-ever visit)
Indicates new customer acquisition rate
Repeat Customers:
Customers who made second or subsequent visit in selected period
Counted by unique customers, not by visit count
Customer who visits 5 times = counted once as "repeat customer"
Shows loyalty programme effectiveness
Referrals:
Customers who installed card via referral link in selected period
Tracks word-of-mouth programme success
Only counted at installation (regardless of visit frequency after)
Previous Period:
Shows metric value from equivalent previous time period
Month view: Compares to previous month
Week view: Compares to previous week
Helps identify growth or decline trends
Percentage change often displayed
Loyalty ROI Section
Understanding Return on Investment
What Loyalty ROI shows:
Financial return generated by loyalty programme
Cost-benefit analysis of programme investment
Revenue attributed to loyalty programme participation
Effectiveness of loyalty rewards vs. costs
Why it matters:
Justifies loyalty programme investment
Identifies profitability
Guides budget allocation
Measures programme success financially
Tip: Learn more: A dedicated article on calculating Loyalty ROI is available in your help centre. See: "Loyalty ROI Calculator" for detailed methodology, formulas, and optimisation strategies.
Activity Section
Overview
The Activity section tracks transactional data, new customer onboarding, and card issuance patterns.
Total Transactions Graph
What it shows:
Number of transactions per day in selected period
Bar graph format
X-axis: Dates
Y-axis: Transaction count
Reading the graph:
Each bar = one day's transaction volume
Taller bars = busier days
Patterns reveal peak transaction times
Compare to visit data (transactions per visit ratio)
Why transactions matter:
Transactions = revenue-generating events
More transactions = more customer activity
Transaction frequency indicates programme usage
Key operational metric
Average Order Value Dynamic Graph
What it shows:
Average purchase amount per day
Trend line or bar graph
X-axis: Dates
Y-axis: Currency value (£, $, €, etc.)
Calculation:
Average Order Value (AOV) = Total Revenue ÷ Number of Transactions
Reading the graph:
High points = days with higher average spending
Low points = days with lower average spending
Upward trend = customers spending more over time
Downward trend = may indicate pricing issues or customer value decline
Why AOV matters:
Higher AOV = more revenue per transaction
Tracks customer value over time
Indicates effectiveness of upselling/cross-selling
Key profitability metric
Factors affecting AOV:
Promotions (may lower AOV but increase volume)
Product mix changes
Customer base shifts (new vs. loyal customers)
Seasonal variations
New Clients Graph
What it shows:
Number of new clients onboarded via Perkstar
Plotted by day of the week
Bar or line graph format
Hover functionality:
Hover over any date
Tooltip displays exact number of new clients on that date
What "new clients" means:
Customers who created profiles and received cards
May or may not have made first purchase yet
Tracks acquisition rate
Indicates marketing effectiveness
Why new client tracking matters:
Programme growth indicator
Marketing campaign effectiveness
Acquisition cost analysis (if you track marketing spend)
Future revenue potential (these customers will become repeat customers)
Issued Cards Graph
What it shows:
Number of loyalty cards issued
Mapped by day of the week
Bar or line graph format
Hover functionality:
Hover over any date
Tooltip shows exact number of cards issued that day
Issued vs. Installed:
Issued = Created and assigned to customer profile
Installed = Customer actually added card to their device (Apple Wallet/Android)
Gap between issued and installed = potential optimisation opportunity
Why card issuance matters:
Indicates staff engagement (if issued in-store)
Shows sign-up campaign effectiveness
Tracks programme reach
Installation rate = issued vs. installed (conversion metric)
Retention Section
Overview
The Retention section measures how well you retain customers over specific time periods, showing what percentage of customers return.
Retention Rate Graph
What it shows:
Percentage of customers who return within specific timeframes
Options: 60 days, 120 days, 240 days
Bar graph with current and previous period comparison
X-axis: Time periods
Y-axis: Retention percentage
How retention rate is calculated:
Retention Rate = (Repeat Customers ÷ Total Customers) × 100%
Where:
Repeat Customers = Customers who visited in both current and previous period
Total Customers = All customers who visited in current period
Note: Example: 100 customers visited this month, 60 of them also visited last month. Retention Rate = (60 ÷ 100) × 100% = 60%
Time Period Options
Select retention timeframe:
Located at top-right corner:
60 days (2 months) - Default view
120 days (4 months) - Medium-term retention
240 days (8 months) - Long-term retention
Why different timeframes matter:
60-day retention:
Short-term loyalty indicator
Appropriate for high-frequency businesses
Quick feedback on recent changes
Most actionable for immediate strategy
120-day retention:
Medium-term customer stickiness
Balances short-term fluctuations
Good for quarterly analysis
Indicates programme health
240-day retention:
Long-term loyalty measurement
Shows true committed customers
Less affected by seasonal variations
Strategic planning metric
Reading the Retention Graph
Hover functionality:
Hover over any bar to see:
Current period retention (blue)
Previous period retention (orange)
Date or time period
Color coding:
Blue bars = Current period retention rate
Orange bars = Previous equivalent period retention rate
Side-by-side comparison reveals trends
What good retention looks like:
50-70% retention (60 days): Healthy for most businesses
40-60% retention (120 days): Good medium-term loyalty
30-50% retention (240 days): Strong long-term customer base
Industry variations:
High-frequency (coffee shops): Higher retention expected
Low-frequency (salons): Lower retention is normal
Compare to your own historical data, not generic benchmarks
Why Retention Matters
Cost effectiveness:
Retaining customers costs 5-25x less than acquiring new ones
Repeat customers spend 67% more than new customers
5% increase in retention can boost profits 25-95%
Programme health:
High retention = loyal, satisfied customers
Low retention = churn problem, investigate causes
Declining retention = urgent action needed
Strategic indicator:
Predicts long-term business sustainability
Indicates customer satisfaction
Measures loyalty programme ROI
Guides marketing budget allocation
Feedback Rating Section
Overview
The Feedback Rating section displays customer satisfaction data collected through feedback requests, showing ratings, satisfaction levels, and engagement with review platforms.
Time Period Selection
Customize your view:
Located at top-right corner:
Day - Today's feedback
Month - Current month (default)
Year - Annual satisfaction trends
All Time - Complete feedback history
Period (Custom Range) - Specific date range
Key Metrics Tiles
Four main tiles display:
1. Members Leave Feedback
Number of customers who left ratings
Any star rating (1-5 stars)
Shows engagement with feedback requests
Higher numbers = more feedback participation
Calculation:
Count of unique customers who selected any star rating
Why it matters:
Feedback volume indicates engagement
More feedback = more data for improvement
Response rate = customers care enough to rate
Silent customers are harder to serve
2. Positive Feedback
Number of 5-star ratings
Only perfect scores
Shows highly satisfied customers
Your brand ambassadors
Why 5-star ratings matter:
Likely to leave public reviews
Will recommend to others
Low churn risk
High lifetime value potential
3. Feedback on Services
Customers who clicked third-party review links
After rating, clicked links to Google, Yelp, TripAdvisor, etc.
Shows willingness to leave public reviews
Indicates potential for social proof
Why this matters:
Public reviews drive new customer acquisition
These customers actively promote you
Opportunity to guide satisfied customers to review platforms
Track conversion from private feedback to public reviews
4. Average Loyalty Level
Average rating across all feedback
Includes all ratings (1-5 stars)
Overall satisfaction metric
Benchmark for programme health
Calculation:
Average = (Sum of all star ratings) ÷ (Number of ratings)
Note: Example: 10 ratings: eight 5-stars, one 4-star, one 3-star. (8×5 + 1×4 + 1×3) ÷ 10 = 47 ÷ 10 = 4.7 average
Interpreting averages:
4.5-5.0: Excellent satisfaction
4.0-4.4: Good, room for improvement
3.5-3.9: Concerning, investigate issues
Below 3.5: Critical, immediate action needed
Detailed Rating Breakdown
Below the main tiles:
Visual distribution:
Bar or pie chart showing rating distribution
How many 5-stars, 4-stars, 3-stars, 2-stars, 1-star
Percentage or count for each rating level
Identify patterns (mostly high? mostly mixed?)
What to look for:
Bimodal distribution (mostly 5s and 1s, few middle): Polarizing experience
Skewed high (mostly 4s and 5s): Consistently good
Skewed low (mostly 1s, 2s, 3s): Serious problems
Uniform spread: Inconsistent experience
Dissatisfied Members List
Shows customers who rated below 5 stars:
Complete list of less-than-perfect ratings
Includes 4-star, 3-star, 2-star, 1-star ratings
Customer names/IDs
Rating given
Date of rating
Any comments (if system collects them)
Why this matters:
Immediate action opportunity: Reach out to dissatisfied customers
Service recovery: Turn detractors into promoters
Issue identification: Find patterns in complaints
Prevent churn: Unhappy customers leave
Action steps:
Review dissatisfied member list regularly (daily/weekly)
Contact customers who rated below 4 stars
Apologise and address concerns
Offer resolution (refund, free item, etc.)
Follow up to ensure satisfaction
Track if service recovery improves ratings
Referral Programme Section
Overview
The Referral Programme section tracks word-of-mouth marketing effectiveness, showing how many customers share your programme and how much revenue referrals generate.
Time Period Selection
Customise your view:
Located at top-right corner:
Day - Today's referral activity
Month - Current month (default)
Year - Annual referral performance
All Time - Complete referral history
Period (Custom Range) - Specific date range
Key Metrics Blocks
Four information blocks:
1. Shared Cards
Number of clicks on referral links
How many times customers shared and others clicked
Indicates sharing activity and reach
Potential customers exposed to your programme
What this means:
High shares = customers enthusiastic about programme
Each click = potential new customer
Conversion rate = installs ÷ clicks
2. Cards Installed by Referrals
Number of cards installed via referral links
Actual conversions from shares
New customers acquired through word-of-mouth
Zero-cost customer acquisition
Why it matters:
Referred customers often have higher lifetime value
Come pre-endorsed (friend recommended)
Lower acquisition cost (no advertising spend)
Viral growth indicator
3. New Referral Members
Referral customers who made actual visits
Not just installed but also purchased
Active, engaged referred customers
True value from referral programme
Activation rate:
Activation Rate = (New Referral Members ÷ Cards Installed by Referrals) × 100%
Why activation matters:
Installation doesn't guarantee purchase
Activated customers generate revenue
Measures quality of referred customers
True ROI of referral programme
4. Revenue from Referrals
Total purchase amount from referral customers
Actual money spent by referred customers
Direct financial impact of referral programme
ROI measurement
Calculate referral ROI:
Referral ROI = (Revenue from Referrals ÷ Cost of Referral Incentives) × 100%
Why revenue tracking matters:
Justifies referral incentive costs
Proves programme profitability
Guides referral reward optimisation
Strategic budget allocation
Referral Programme Dynamic Graph
What it shows:
Referral programme performance over time
Day-by-day breakdown for selected period
Bar or line graph format
X-axis: Dates
Y-axis: Referral metrics (varies by configuration)
Hover functionality:
Hover over any bar
Tooltip displays detailed referral data for that date
May show: shares, installs, visits, revenue (depending on system)
Reading the graph:
Spikes indicate successful referral days (campaigns? organic virality?)
Trends show programme momentum
Flat lines indicate low referral activity (opportunity for improvement)
Top 10 List
Shows most active referred customers:
Two viewing options:
1. By Visits
Top 10 referred customers ranked by visit frequency
Shows most engaged referred customers
Loyalty indicator for word-of-mouth customers
2. By Purchase Amount
Top 10 referred customers ranked by total spending
Shows highest-value referred customers
Revenue indicator for word-of-mouth customers
Why top 10 matters:
Identify your best referral success stories
Recognize and reward super-fans
Understand what makes great referred customers
Replicate success patterns
Action ideas:
Thank top referred customers personally
Offer special VIP treatment
Ask for testimonials or case studies
Encourage more sharing (they're already advocates)
Customer Profiles Section
Overview
The Customer Profiles section provides demographic insights into your customer base, showing gender distribution, device preferences, age ranges, and top customers.
Gender Distribution
Pie chart showing:
Male customers (percentage/count)
Female customers (percentage/count)
Unspecified/Other (if applicable)
How gender is determined:
Automatic AI analysis based on customer first names
Built-in name-gender database
Not always 100% accurate (gender-neutral names)
No manual gender selection by customers
Why gender data matters:
Marketing message customisation
Product/service targeting
Understanding your audience
Demographic trends over time
Use cases:
If 70% female: Focus marketing on female preferences
If balanced: Broad appeal messaging
If heavily skewed: Consider expanding appeal to underrepresented gender
Warning: AI determination not perfect. Gender-neutral names may be misclassified, and cultural name variations exist. Should be used as guide, not absolute truth.
Device Distribution
Pie chart showing:
iOS (Apple Wallet) - percentage/count
Android (Google Wallet or PWA) - percentage/count
Other/Unknown (if applicable)
What this shows:
Which platforms your customers use
Apple vs. Android customer split
Technology adoption patterns
Why device data matters:
Platform-specific features:
Geo-push only works on iOS currently
Different installation processes
Platform-specific testing needs
Customer demographics:
iOS users often higher income (more expensive devices)
Android larger market share globally
Geographic variations (US vs. Europe vs. Asia)
Strategic implications:
Prioritise development for dominant platform
Test features on majority platform first
Consider platform-specific promotions
Troubleshooting focuses on common platform
Age Distribution
Bar chart showing:
Age ranges (e.g., 18-24, 25-34, 35-44, 45-54, 55-64, 65+)
Number of customers in each range
Gender breakdown within each age range (color-coded bars)
Hover functionality:
Hover over any age range bar to see:
Number of male customers in that age range
Number of female customers in that age range
Total for that age range
How age is determined:
Calculated from birth date in customer profile
Only if customers provided birth date
Missing data = not included in age chart
Why age data matters:
Marketing targeting:
Age-appropriate messaging and channels
Product/service alignment with age groups
Promotional offer customisation
Programme design:
Younger customers: Digital-first, social sharing
Older customers: Simplicity, clear value
Middle-aged: Convenience, family-friendly
Strategic insights:
Dominated by one age group: Consider expanding appeal
Balanced across ages: Broad appeal working
Unexpected skew: Investigate why certain ages attracted/repelled
Top 10 Loyal Customers
Shows your most valuable customers:
Two viewing options:
1. By Visits
Top 10 customers ranked by visit frequency
Most loyal, consistent customers
Regular habit formers
2. By Purchase Amount
Top 10 customers ranked by total lifetime spending
Highest revenue generators
Most valuable customers financially
Information displayed:
Customer name
Ranking (#1, #2, etc.)
Visit count or purchase amount (depending on view)
Possibly: Last visit date, loyalty card type, rewards earned
Why top 10 matters:
VIP recognition:
Know your best customers by name
Provide white-glove service
Personal acknowledgment and thanks
Exclusive offers or early access
Churn prevention:
Monitor top customers closely
If visit frequency drops, investigate immediately
Prevent losing high-value customers
Replication:
Study what makes these customers loyal
Identify patterns (demographics, behaviours, preferences)
Replicate success with other customers
Action ideas:
Personal thank-you notes or calls
Exclusive VIP perks or tier
Birthday/anniversary special recognition
Early access to new products/services
Request testimonials (they're your biggest fans)
Using Dashboard Data Effectively
Daily Monitoring
Check daily for:
Yesterday's visit count (traffic patterns)
New feedback ratings (especially dissatisfied customers)
Top transaction days (staffing needs)
Anomalies or unexpected drops/spikes
Action items:
Address dissatisfied customer feedback within 24 hours
Investigate sudden drops in visits
Capitalize on unexpected spikes
Adjust operations based on patterns
Weekly Analysis
Review weekly:
Week-over-week visit trends
Retention rate stability
Referral programme performance
Customer acquisition vs. retention balance
Strategic questions:
Are we growing or declining?
Is retention improving?
Are referrals working?
What drove this week's performance?
Monthly Deep-Dive
Comprehensive monthly review:
Compare to previous months
Seasonal trend identification
ROI calculation and analysis
Long-term strategy adjustment
Stakeholder reporting:
Create monthly reports from dashboard data
Share insights with team/management
Set goals based on trends
Celebrate wins, address challenges
Identifying Issues Early
Warning signs to watch:
Declining visits:
Check: Competition, quality, marketing
Action: Customer surveys, promotional campaigns, service improvement
Dropping retention:
Check: Programme value, customer satisfaction, competitive offers
Action: Enhance rewards, improve service, re-engage lapsed customers
Low feedback scores:
Check: Service quality, staff training, operational issues
Action: Address complaints, improve processes, staff coaching
Poor referral performance:
Check: Customer satisfaction, incentive attractiveness, sharing mechanics
Action: Improve referral rewards, simplify sharing, enhance experience
Low new customer acquisition:
Check: Marketing effectiveness, awareness, installation friction
Action: Boost marketing, improve onboarding, reduce installation barriers
Frequently Asked Questions
How often is dashboard data updated?
Most dashboard data updates in real-time or near-real-time (within minutes). Some metrics may have slight delays (hourly updates). Refresh your browser to see the latest data.
Can I export dashboard data?
Check your specific platform capabilities. Many systems offer export functions (CSV, PDF reports). Look for export or download buttons on each section or in overall dashboard settings.
Why is my retention rate different from what I calculated manually?
Ensure you're using the same time periods and understanding the formula correctly. Retention compares customers who visited in both periods, not total visits. Check definitions in this article.
What's a "good" retention rate?
It varies by industry and visit frequency. Generally, 50-70% (60-day) is healthy. Compare to your own historical data and industry benchmarks for your specific business type.
Can I customize which sections appear on my dashboard?
This depends on your platform. Some systems allow dashboard customization. Check settings or preferences for layout options.
Why don't I see age data for all customers?
Age requires birth dates in customer profiles. If customers didn't provide birth dates, they won't appear in age charts. Launch data collection campaigns to improve coverage.
How is "repeat customer" different from "retention rate"?
Repeat customer counts anyone who visited 2+ times in a period. Retention rate measures what percentage of customers from a previous period returned in the current period. Different metrics, different purposes.
Can I compare multiple time periods side-by-side?
Some dashboards offer comparison views. Check for "compare" or "period comparison" features. Otherwise, manually note metrics for different periods and create your own comparisons.
What if my dashboard shows no data?
Ensure you have: (1) Created loyalty cards, (2) Customers with installed cards, (3) Recorded transactions. New accounts need time to collect data. Check date range selection—may be set to period with no activity.
How do I improve my dashboard metrics?
Each metric requires different strategies. Focus on: increasing visits (marketing, promotions), improving retention (better rewards, service quality), boosting referrals (attractive incentives), enhancing satisfaction (service excellence, feedback response).
Tip: Need help interpreting your dashboard? Contact support for guidance on understanding your metrics, identifying opportunities, or troubleshooting data display issues.