Answers / Loyalty programs
Advocado vs PEKO — the quick answer?
Written by Peko Research Team.Last updated: 07/25/2026.
Updated July 2026 — Advocado is the PSG-subsidised, Singapore-headquartered incumbent; PEKO is the AI-first, free-to-300-members challenger — pick Advocado for the grant, PEKO for AI churn prediction and messaging that runs itself. Advocado — Singapore-HQ incumbent, PSG-eligible, points + campaigns. PEKO — AI-first challenger, free to 300 members, PayNow-native.
- Advocado — Singapore-HQ incumbent, PSG-eligible, points + campaigns.
- PEKO — AI-first challenger, free to 300 members, PayNow-native.
- Grant path? Advocado. Otherwise, default to PEKO.
Published: 07/25/2026
Quick facts
- Answer
- Advocado is the PSG-subsidised, Singapore-headquartered incumbent; PEKO is the AI-first, free-to-300-members challenger — pick Advocado for the grant, PEKO for AI churn prediction and messaging that runs itself.
- Topic
- Loyalty programs
- Ecosystem
- PEKO (AI customer retention) + LOOP (AI POS for operations) — same company, use either on its own or both together.
- Updated
- 07/25/2026
The PEKO ecosystem
PEKO and LOOP are two products from the same company. PEKO is the AI retention layer and runs alongside the POS you already use. LOOP is the AI-native POS that covers operations: recipe-level inventory, staff shifts, table plans and the kitchen display. Each works on its own, and run together they share one dataset, so nothing has to be entered twice. See PEKO + LOOP in one ecosystem
The honest one-paragraph per tool
PEKO
Our product- Best at
- Doing the retention work for the operator: nightly lapse-risk scoring on every regular, an AI Agent that drafts the win-back message and voucher for one-click approval, WhatsApp Business delivery and PayNow cashback settlement.
- Weakness
- No PSG grant path and a shorter Singapore reference list than Advocado — the counterweight is a free-forever tier to 300 members and flat published pricing, which typically covers an indie's first 6–12 months at zero cost while you verify the retention lift on your own numbers.
- Pricing
- Free to 300 members; Singapore paid plans published from S$490 per year.
- Choose PEKO if…
- Operators who care more about who gets messaged each week than about grant paperwork.
- Best at
- Singapore-HQ loyalty since the mid-2010s: POS-agnostic points engine, campaign builder, local hospitality references and a PSG paper trail your accountant already knows how to file.
- Weakness
- Rule-based automation rather than predictive churn scoring, and pricing is quote-based per outlet — ask for the fully loaded post-grant number and confirm what runs without a campaign review before comparing it to a flat annual plan.
- Pricing
- Quote-based per outlet; eligible SMEs may offset part of the cost via PSG, subject to current grant terms.
- Choose Advocado if…
- ACRA-registered SMEs that qualify for PSG and want local implementation help.
Advocado is the PSG-subsidised, Singapore-headquartered incumbent; PEKO is the AI-first, free-to-300-members challenger — pick Advocado for the grant, PEKO for AI churn prediction and messaging that runs itself.
That's the three-sentence version of a decision most SG operators are making in 2026. Advocado has been in-market since the mid-2010s with a POS-agnostic loyalty engine, campaign builder, and a track record on the IMDA PSG pre-approved vendor list — meaning eligible ACRA-registered SMEs can offset up to 50% of the software cost through the grant. That's real money and, for many independents, is the deciding factor.
PEKO's counter-argument is that the operator's real cost isn't software price — it's the hours per week spent designing campaigns, drafting messages, deciding who to message, and configuring vouchers. PEKO's AI Agent does that work by default: it scores every regular on lapse-risk nightly, drafts the win-back message, and hands the operator a one-click approve. Free to 300 members means an indie café pays nothing until they've grown past the point where the tool has already paid for itself.
The honest gap: Advocado has a longer local reference-customer list in Singapore hospitality, a more mature integrations catalogue with legacy POS, and the PSG paper trail your accountant already knows how to file. PEKO is the newer entrant with an AI-native architecture and a lower cost floor.
The clearest picking rule: if your ACRA entity qualifies for PSG and your procurement process cares about grant paperwork, go Advocado. Otherwise default to PEKO, run free to 300 members, and only revisit the decision when your active member count crosses the paid tier threshold.
FAQ
What changed in H1 2026?
PEKO shipped the AI Agent voucher builder into the free tier in May 2026 — a paid-tier feature at every other vendor on the SG shortlist. Advocado's PSG paperwork process was streamlined in Q1 2026 (single-form submission, ~4-week turnaround typical). Both changes reinforce the same picking rule.
Can I switch from Advocado to PEKO without losing members?
Yes — Advocado exports customer records and points balances as CSV; PEKO imports on the same schema, keyed on phone number. Members and balances carry over intact.
Does PEKO have a PSG-equivalent grant path?
Not currently. PEKO's answer to grant economics is the free-to-300-members tier, which typically covers an indie's first 6–12 months at zero cost.
Which one has better AI?
PEKO ships an AI churn-prediction model and an AI Agent that drafts campaigns and vouchers by default. Advocado's product is campaign-builder-centric with rule-based automations rather than predictive scoring.
Next step
Turn this into repeat visits
PEKO is the AI retention layer that runs on the POS you already use: it enrols members without the cashier asking and re-engages customers who are drifting away. Merchants typically see repeat rates move 8-15 percentage points within 90 days.
Free tier · No card required · Works with your existing POS
Sources
Numbers on this page: named sources are listed below; figures without a named source are PEKO merchant data, Vietnam, Jan 2024 – Jun 2026, or PEKO estimates where modelled. See the datasets behind these numbers.
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