Customers report

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What this does

The upgraded Customers report shows customer health metrics, AI-powered insights, and customer segmentation breakdown. Use this to identify your most valuable customers, find at-risk segments, and get actionable recommendations for retention and win-back campaigns.

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When to use this

Use this report to answer:

• What is my median customer lifetime value? (Median LTV metric)
• How many new customers did I gain this month? (New customers metric)
• Are my customers staying active? (Active customers metric and retention comparison)
• Which customer segments are most valuable? (Customer segmentation table)
• Which customers are at risk of churning? (Slipping regulars, Lost regulars, Gone segments)
• What actions should I take to improve retention? (AI insights)

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Filters

The report starts with two visible filters:

• Type: Filter by customer account type (e.g., email, phone, loyalty member)
• Customer segment: Filter by behavioral segment (VIP regulars, Solid regulars, Slipping regulars, Lost regulars, Gone, Others)

Click + 3 to reveal additional filters. See Using reports - Filters for detailed instructions on how to apply filters and use operators.

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Summary metrics

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Total customers

Total count of all customers in the system (excluding guest accounts).

• Value shown: Customer count (e.g., 289)
• Comparison: Month-over-month change (e.g., ↑ 4, 1.4%)
• Baseline: Comparison to last month (e.g., “from 285 last month”)
• Drillable: Click to see underlying customer data including names, emails, activity status, and loyalty status

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Median lifetime value

The typical amount a customer has spent across their entire relationship with your restaurant (50th percentile).

• Value shown: Median LTV in SGD (e.g., $21.60)
• Comparison: Percentage change over 30 days (e.g., ↑ $1.58, 8%)
• Baseline: Comparison to 30 days ago (e.g., “from $20.02 thirty days ago”)
• Interpretation: Represents typical customer worth; higher is better

What affects this metric:

• Number of inactive or one-time customers (lowers median)
• Strong repeat purchase behavior (raises median)
• Guest accounts included in calculation (may lower median)

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New customers (30D)

Count of customers who placed their first order in the last 30 days.

• Value shown: New customer count (e.g., 4)
• Percentage: New customers as % of total (e.g., 1% of 289 total customers)
• Visual: Progress bar showing percentage
• Interpretation: Low % indicates mature customer base with low new customer acquisition

Typical benchmarks:

• 1-3% monthly new customer rate: Mature, established restaurant with stable base
• 5-10% monthly: Growing restaurant with active marketing
• 10%+ monthly: New restaurant or aggressive acquisition campaign

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Active customers (30D)

Count of customers who placed at least one order in the last 30 days.

• Value shown: Active customer count (e.g., 11)
• Percentage: Active customers as % of total (e.g., 4% of 290 total customers)
• Visual: Progress bar showing percentage
• Interpretation: Low % indicates low repeat purchase frequency or customer churn

Typical benchmarks:

• 3-5% monthly activity rate: Low repeat frequency (common for casual dining)
• 10-15% monthly: Moderate repeat frequency (coffee shops, fast casual)
• 20%+ monthly: High repeat frequency (daily coffee, office lunch spots)

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AI insights

AI-generated analysis covering guest account conversion opportunities, dormant customer revenue potential, and outlet-specific performance. See Using reports - AI insights for how to interpret AI recommendations.

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Customer segmentation

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Segment definitions

Atlas groups customers into 6 behavioral segments based on order frequency, recency, and lifetime value:

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Segment table

The customer segmentation table shows:

1. Row number: 1-6 for each segment
2. Customer segment: Segment name with icon/emoji
3. Description: Plain text definition of segment’s behavior and characteristics

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Drill-downs and clickable elements

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Metric cards

Click on any metric card to drill down into underlying customer data:

• Total customers: Opens customer list with names, emails, activity status, loyalty status
• Median LTV: May open customer spend distribution (verify in production)
• New customers: Opens list of customers who placed first order in last 30 days
• Active customers: Opens list of customers who ordered in last 30 days

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Customer segment rows

Right-click or click on a segment row in the table:

• Copy value: Copies the segment name to clipboard
• Expand: Shows tooltip/preview of the segment name
• Expected (in production): Navigate to detailed customer list filtered by segment

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What should happen

After loading the report, you should see:

• Four metric summary cards with month-over-month comparisons
• AI insights section with 3-5 actionable recommendations
• Customer segmentation table with 6 segments defined
• Yellow banner showing “Data in this report refreshed hourly. Last updated at [time]”

When you click on a metric card:

• Drill-down modal opens with detailed customer data
• Table shows customer names, emails, activity status, loyalty status
• “Run without cache” option available to fetch live data

When you click on a segment row:

• Context menu appears with “Copy value” and “Expand” options
• (In production) Detailed customer list filtered by segment may open

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If it doesn’t work

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Problem: “New customers (30D)” is very low (1% of total) — is this normal?

Likely cause: Your restaurant has a mature, established customer base (good!) but may have low new customer acquisition. How to check:

1. Review your marketing spend and channels — are you running ads or promotions?
2. Check “Active customers (30D)” — if it’s also low (3-5%), you may have a retention issue, not just acquisition
3. Look at AI insights for segment-specific recommendations
4. Consider running a referral program or paid ads to boost new customer acquisition

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Problem: Median lifetime value seems low ($21.60) — what does this mean?

Likely cause: Your customer base includes many one-time or low-spend customers (common for delivery/QR code orders). The median can be pulled down by many small orders. How to check:

1. Check if “Type” filter includes guest accounts — filter to “Registered customers” only if guest accounts are skewing the number
2. Compare to your average order value from Sales report — if AUV is $15 and median LTV is$21.60, customers average ~1.4 orders
3. Set a goal to increase LTV through loyalty programs or cross-selling
4. Focus retention efforts on “Solid regulars” and “VIP regulars” segments

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Problem: I see “Dormant customers represent untapped revenue” in AI insights — who are they?

Likely cause: These are customers who haven’t ordered recently (3+ months, in the “Gone” or “Lost regulars” segments) but spent money in the past. How to re-engage:

1. Identify the outlet/location mentioned in the AI insight (e.g., McNair Road)
2. (In production) Click on “Lost regulars” segment to see customer names and last order dates
3. Run a win-back campaign: email them a discount, highlight new menu items, or ask for feedback on why they left
4. Track re-activation rate to measure campaign success

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Problem: AI insights mention “Guest accounts” — are these real customers?

Likely cause: Guest accounts are customers who ordered without signing up (QR code, one-time delivery order, walk-in scanning kiosk). They’re “customers” in that they purchased, but may not be loyal. How to handle:

1. In the standard Customers report, uncheck “Include guest users” to see only registered customers
2. In BETA report, filter by “Type” to exclude guest accounts if the filter is available
3. Focus loyalty/retention efforts on registered customers
4. For guest accounts, focus on converting them to registered customers (email capture, loyalty signup)

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Problem: The report hasn’t updated in several hours — is it broken?

Likely cause: Data refresh is hourly, but dashboard may cache results. Last update is shown as “12:06PM, 7 Jan 2026.” How to fix:

1. Refresh browser (Ctrl+R or Cmd+R)
2. Wait until next hourly refresh (top of the hour + a few minutes)
3. Check that you haven’t filtered data to zero results (check filters on “Type” and “Customer segment”)
4. Contact Atlas support if data is missing for more than 2 hours

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Problem: Metric cards show “0” or no data

Likely cause: Filters are too restrictive, or no data exists for the selected cohort. How to fix:

1. Click “Type” filter and set to “is any value” to remove type filtering
2. Click “Customer segment” filter and set to “is any value” to remove segment filtering
3. Click ”+ 3” to check if additional date range or outlet filters are active
4. Reset all filters and reload the page

If the issue persists, contact support at [email protected] with:

• The report URL
• The specific metric or chart that’s not working
• The filters you applied (screenshot if possible)

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Next steps

After reviewing your customer health metrics:

• View the standard Customers report to export customer lists for email campaigns
• Set up discounts for loyalty members to increase engagement
• Check the Loyalty report to see loyalty program performance
• Review the Discount report to see if promotions are driving retention

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Practical workflows

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Workflow 1: Understand customer base health at a glance

1. Open the Customers report (BETA version)
2. Look at the four metric cards:
   • Total customers: 289 (growth: +4 month-over-month) — stable base
   • Median LTV: $21.60 (up 8% in last 30 days) — sign of stronger customer base
   • New customers (30D): 4 — indicates low new customer acquisition; may want to increase marketing
   • Active customers (30D): 11 — indicates low repeat purchase rate; consider loyalty program or retention campaign
3. Scroll down to read AI insights for specific actionable recommendations

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Workflow 2: Identify customers at risk of churn

1. Open the Customers report (BETA version)
2. Look for the “Slipping regulars” and “Lost regulars” rows in the Customer segmentation table
3. Read the descriptions:
   • Slipping regulars: 30-90 days inactive; at risk of churn
   • Lost regulars: 90+ days inactive; severe churn risk
4. (In production) Click on segment row to see detailed customer list and export for email/SMS outreach
5. Plan win-back campaigns:
   • Slipping regulars: New menu items, discount offer, personalized messaging
   • Lost regulars: Heavy discount, apology/miss-you messaging, referral incentive

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Workflow 3: Find your best customers and reward them

1. Open the Customers report (BETA version)
2. Look at “VIP regulars” and “Solid regulars” rows
3. These are your most valuable customers (high LTV, high frequency)
4. Consider:
   • Inviting them to a loyalty program (if not already members)
   • Offering exclusive menu items or early access to promotions
   • Personalizing their experience (remember their usual order, birthday discounts)
5. (In production) Click on segment row to identify these customers by name and order history

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Workflow 4: Monitor customer health trends over time

1. Open the Customers report (BETA version) daily or weekly
2. Watch the four metric cards for trends:
   • Is “Total customers” growing? (Good sign of acquisition)
   • Is “Median LTV” growing? (Good sign of stronger spend per customer)
   • Is “New customers (30D)” growing? (Good sign of marketing effectiveness)
   • Is “Active customers (30D)” growing as % of total? (Good sign of retention/engagement)
3. Read AI insights each week for emerging patterns
4. Adjust marketing/loyalty strategies based on observed trends