Feature
Customer retention analyticsCustomer retention analytics: see who comes back, and act on it before they don’t.
Customer retention analytics built into your loyalty programme. Cohort retention, RFM segments, Top Spender and Top Visitor leaderboards, points and outlet reports, all from the same data your members create every day.
Cohort retention & churn
RFM customer segments
Top Spender & Top Visitor
Top Spender · November
Aina L. · RM2,480 across 14 visits
Month-1 retention, Sep cohort
44%
Illustrative dashboard
Quick answer
What is customer retention analytics?
Customer retention analytics measures which customers come back, how often and for how long, so you can act before they drift away. Pixalink’s loyalty analytics turns member activity into cohort retention tables, RFM segments, leaderboards and points, reward and outlet reports, with filters by outlet and date.
Pixalink Sdn Bhd, Malaysia · Updated 8 November 2026
Loyalty Analytics at a glance
Retention
Cohort table, monthly active members, reactivation
Segments
Champions, Loyal, New, Needs attention, At risk, Inactive
Leaderboards
Top Spender and Top Visitor by outlet
Programme reports
Points, rewards, tiers, credits, paid membership
AI
Ask AI assistants about your data via a read-only MCP connector
Loyalty analytics dashboards
What does a loyalty analytics dashboard show?
One place to see members, sales from members, sign-ups and rewards, then drill into the report behind each number. Filter by outlet and date range.
Main
Customer Analytics
Member Insights
Retention & Churn
Outlet Performance
New Customer Trends
Membership Sign-Up
Membership Tier
Points
Rewards
Reward Performance
Credit Analytics
Paid Membership
Member sales, last 12 weeks
Sales from members
62%of total sales came from identified membersIllustrative data
Cohort retention analysis
How do you read a retention cohort table?
Each row is a group of members who made their first purchase in the same month. Each column shows what share of them bought again N months later. Select a cell to see what it means.
| First purchase | Members | Month 0 | Month 1 | Month 2 | Month 3 | Month 4 | Month 5 |
|---|---|---|---|---|---|---|---|
| Jun 2026 | 368 | ||||||
| Jul 2026 | 412 | ||||||
| Aug 2026 | 395 | ||||||
| Sep 2026 | 451 | ||||||
| Oct 2026 | 430 | ||||||
| Nov 2026 | 389 |
Select any cell. Example: of the 451 members whose first purchase was in September, 44% bought again one month later, the best month-1 result in this table. Worth asking what changed that month.
Illustrative data
1
Read across a row
How one group behaves over time. A steep drop after month 1 means the second visit is the problem.2
Read down a column
Compare groups at the same age. Is month-1 retention improving as you change your welcome offer?3
Spot the outlier
A month that beats the rest usually has a reason: a campaign, a new outlet, a reward that clicked. Repeat it.Customer Analytics · RFM
Which customers need a different message?
RFM scores each member on recency, frequency and monetary value, then groups them into six segments. Each segment calls for a different action, and most actions can be automated.
8% of members (illustrative)
Champions
Bought recently, buy often and spend the most.
Thank them first: early access, a members-only product or a temporary VIP tier.
Automate it17% of members (illustrative)
Loyal
Buy regularly and respond to your programme.
Ask for referrals and offer a points multiplier to move them up a tier.
Automate it14% of members (illustrative)
New
Joined or made a first purchase recently.
Run a welcome series and a second-visit voucher before the habit fades.
Automate it21% of members (illustrative)
Needs attention
Above-average customers who have started to slow down.
Send a personalised offer on what they usually buy.
Automate it18% of members (illustrative)
At risk
Used to buy often but have not returned for a while.
Trigger a win-back message with a voucher that expires soon.
Automate it22% of members (illustrative)
Inactive
No recent activity for a long time.
One last win-back attempt, then exclude them from paid campaigns.
Automate itOutlet Performance · Top Spender & Top Visitor
Who are your best customers this month?
The Top Spender and Top Visitor tables rank members by spend and by visits, per outlet and period. Staff can greet them by name, and marketers can turn the ranking into a game.
- 1Aina L.RM2,48014 visits
- 2Jason T.RM2,1159 visits
- 3Priya K.RM1,96011 visits
- 4Hafiz R.RM1,7207 visits
- 5Mei Xin W.RM1,58512 visits
- 1Wei Ming C.22 visitsRM860
- 2Farah Z.19 visitsRM1,240
- 3Aina L.14 visitsRM2,480
- 4Siti N.13 visitsRM690
- 5Priya K.11 visitsRM1,960
Illustrative data. Names are fictional.
A use case we have seen with merchants
The monthly leaderboard and the 30-second trolley dash
A retailer shows the monthly Top Spender and Top Visitor leaderboard on a screen in store.
Members compete for the top three places all month.
The top spender wins a trolley dash: 30 seconds to fill a trolley with whatever they can grab, paid for by the brand.
00:30
Tip: show first names and initials only, and tell members about the leaderboard when they join.
The leaderboard on screen keeps members talking about the race.
The prize: a 30-second trolley dash for the month’s top spender.
Points report · Outlet Performance
Are points being used, and which outlet is pulling its weight?
Points earned against points redeemed shows whether members see value in your rewards. Outlet performance compares branches on the metric you choose.
Points earned vs. redeemed (thousands)
Earned Redeemed
Redemption is rising from 43% to 56% of points earned: members see value. If it falls, refresh the rewards catalogue or send a point expiry reminder.
Outlet performance
Switch to New members: Johor Bahru has the fewest visits but the second-most sign-ups, so its counter QR routine is worth copying.
Illustrative data
Reports for daily decisions
How do merchants use loyalty reports every morning?
Reports earn their keep when they change what happens today. A ten-minute check before opening is enough.
9:00
Yesterday at a glance
Main dashboard
Member sales and sign-ups vs. last week. Brief the team on today’s sign-up target.
9:02
New members
New Customer Trends
Are welcome vouchers being used? If not, change the offer or the timing.
9:04
Who is slipping away
Customer Analytics (RFM)
Check the At risk count. Make sure the win-back automation is on and the voucher is attractive.
9:06
What rewards work
Reward Performance
Restock rewards that are popular, retire the ones nobody redeems.
9:08
Who to greet today
Outlet Performance
Top Spenders and Top Visitors per outlet, so staff can thank regulars by name.
A quick look at the numbers before the doors open.
Weekly: the cohort table and New Customer Trends, to judge welcome offers.
Monthly: tiers, reward performance, credit and paid membership reports, plus the leaderboard winners.
AI analytics
Can I ask AI questions about my loyalty data?
Yes. Pixalink offers a read-only MCP connector, so AI assistants that support MCP can look up your programme data and answer questions in plain language. The connector reads data; it cannot change anything.
You ask in plain language
Read-only MCP connector
Your Pixalink data
“Which rewards were redeemed most at Penang this quarter?”
“How many members have points expiring next week?”
“Compare new sign-ups by outlet for the last three months.”
Which outlet had the most at-risk members last month, and what did they usually buy?
Bangsar had the most at-risk members: 214, up from 168 the month before.
| Outlet | At risk | Top item bought |
|---|---|---|
| Bangsar | 214 | Iced latte |
| Mid Valley | 187 | Croissant set |
| Penang | 121 | Iced latte |
Most of them bought iced lattes on weekday mornings. A weekday-morning win-back voucher for that drink is a sensible test.
Illustrative conversation. Answers depend on your data and the AI assistant you use.
More expensive to win a new customer than keep one
5–25×
Harvard Business Review, 2014
Profit increase from a 5% rise in retention
25–95%
Bain & Company research, cited by HBR
Sources (1)
What is customer retention analytics?
It is the analysis of whether, when and how often customers come back. In Pixalink it covers cohort retention, monthly active members, reactivation, RFM segments and leaderboards, built from your members’ purchases and visits.
What is cohort retention analysis?
Cohort retention analysis groups customers by the month they made their first purchase and tracks what share buy again in each following month. It shows whether changes to your welcome offer or programme improve repeat buying.
What are RFM segments in loyalty analytics?
RFM ranks customers by recency, frequency and monetary value. Pixalink groups members into Champions, Loyal, New, Needs attention, At risk and Inactive, so each group can get the right message.
Can I see my top customers by outlet?
Yes. Outlet Performance includes Top Spender and Top Visitor rankings that you can filter by outlet and date range.
Can I analyse my data with AI?
Yes. Merchants can connect AI assistants that support MCP to Pixalink’s read-only MCP connector and ask questions about their data in natural language. The connector cannot change your data.
Which loyalty reports should I check daily?
Most merchants check the main dashboard, new customers, the At risk segment, reward performance and the outlet leaderboard. Cohorts and tier reports are better reviewed weekly or monthly.
Do the analytics include points, rewards and wallet credit?
Yes. There are reports for points, rewards and reward performance, membership tiers, credit analytics and paid membership.
Works well with
Features that pair with Loyalty Analytics.
Customer CRM
One profile per member, in real time
Omni-channel Marketing
Automated messages across the journey
Loyalty Points
Every ringgit earns a reason to return
Membership Tiers
Multipliers, tier-only rewards, invite-only tiers
Rewards & Vouchers
Vouchers staff can validate in one tap
Referrals
Three proven referral models
Ready when you are
Turn your loyalty data into daily decisions.
In a 30-minute demo we walk through the reports with sample data from your industry.
