The Delivery Booster Method
Availability
GrabFood and GoFood algorithms first check whether you can be relied on. Offline hours, cancellations and slow preparation hurt ranking more than anything else, and recovery is slow — the platform needs a new history.
- —Real-time open/closed monitoring on both platforms
- —Stop-list control: items switched off by accident and unnoticed
- —Cancellation and preparation-time work
From the dashboards: USSR Phuket: 3,977 offline minutes a month → 0, search impressions 0 → 7,481/month. Enjoy Healthy Food: offline rate 73% → 0%, impressions 7,038 → 25,543/month, driver waiting time 437 → 135 seconds.
Listing and menu SEO
There is a search engine inside the app, and it searches the words you wrote. Dish names, categories, descriptions and photos decide how many viewers open the menu and how many order. That is through-conversion — the number the whole funnel turns on.
- —Keyword map by city and category
- —Keywords in item names and descriptions, category structure rebuild
- —Photos and item order tuned for the first screen
From the dashboards: Etna Phuket: through-conversion 0.5% → 1.9% (x3.8) against a 0.9% fleet average; menu opens rose sharply. Zaytun Ubud: reach x1.84, reach → menu conversion 8.5% → 10.0%.
Pricing, promos and average check
A promo lifts your position and cuts your margin at once, so what counts is not orders but what is left after the discount and the platform commission. Average check is the second revenue multiplier and the forgotten one: it grows from menu structure, combos and add-ons — not from raising prices.
- —Per-promo economics: what is left after discount, commission and ad spend
- —Combos and add-ons that lift the check without price rises
- —A/B tests of items and prices
From the dashboards: Love U Pizza: average check +49.5% (Rp 217,397 → 324,999) alongside 14.1x order growth. Meat Point Phuket: average check +22.4% (785 → 961 THB) — in the low season, when Phuket restaurants typically lose 20–40% of revenue.
Rating and reviews
From 4.8 the algorithm serves impressions more generously, and a customer choosing between two listings looks at the number next to the name. One unfair review on a young account costs more than it seems — and can often be removed if you answer correctly and quickly.
- —Daily review triage and fast replies
- —Escalating unfair reviews up to removal
- —Root causes: what in the dish, packaging or speed is producing the minus
From the dashboards: USSR Phuket 4.5 → 4.8, Etna 4.6 → 4.8, Zaytun Ubud 4.67 → 4.8, Meat Point 4.6 → 4.8 with zero incidents. Love U Pizza held 4.8 through 14x order growth — harder than lifting it.
Ads
Ads come last by design: they buy impressions, and everything from stages 1–4 is what turns those into orders. Auto-bidding collects cheap irrelevant impressions, so we run campaigns manually and adjust weekly instead of launching once.
- —Manual CPO instead of auto-bidding, daily management
- —ROAS control per campaign, not on average
- —Budget grows only after conversion does
From the dashboards: Etna Phuket: ROAS 14.75x → 34.57x, CTR 2.8% → 5.59%, cost per order 42 → 29 THB; budget +50%, ads revenue x3.4. Zaytun Ubud: GoFood from a loss-making 0.25x to 15.52x (x62 payback), GrabAds 14.02x → 21.19x. Enjoy Healthy Food: ROAS 27.5x, 566 new customers acquired.
What the method does not promise
It will not make a restaurant profitable if the unit economics do not work before delivery, and it will not save a kitchen that cannot handle volume: 14x order growth breaks a bad process faster than it earns. The method works on what lives inside GrabMerchant and GoBiz — and stops honestly where the kitchen itself begins.
Full case studies
Love U Pizza — x21 · Enjoy Healthy Food — x9.4 · USSR Phuket — x3.9 · Zaytun Ubud — x2.6 · Etna Phuket — +87% · Meat Point — +46%
Frequently asked
Why are ads last rather than first?
Because ads multiply listing conversion rather than replace it. On a listing converting at 0.5%, every dollar buys a view without an order. First raise what gets multiplied, then multiply it.
Does this work for a new restaurant and an established one?
Both, differently. At launch the big levers are availability and listing: Love U Pizza grew x21 in 9 months from a near-zero base. On an established restaurant the easy gains are already spent, and every next percent comes out of conversion and menu: Zaytun Ubud was already making Rp 166.6M a month before us and grew x2.6 in 5 months.
Can I run the method myself?
Yes — that is why it is published in full. The constraint is not knowledge but that this is daily work across two dashboards: bids, stop-list, reviews, promos, weekly number reviews. Owners usually do it with whatever time is left, and the method breaks on consistency, not on understanding.
How long is a full cycle?
First movement in 2–4 weeks, full ramp-up in 3–6 months. Availability and bidding respond fastest; ranking and rating are slowest, because the algorithm needs history.
Related answers: can I hand the account over · agency or Klikit/Deliverect · why ads bring no orders
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