Consumer & market intelligence · Food Delivery

Your platform sees every order. We see the whole market around it.

Rank every un-signed merchant customers in your market (Laos included) are already ordering from — by real consumer demand, consumer rating and fit — with the contact data to sign them. Then run the same off-platform view across price, promo, the delivery experience and cold-start recommendations. Across 252 countries, refreshed weekly.

Start with a pilot See the data behind it

Best Retail Insights Solution · VIP Awards – 2026

The blind spot

Your order data sees inside your app. It can't see the market around it.

Which merchant to sign, where to spend promo, why a zone is soft — every one of those decisions turns on what's happening off your platform. Your first-party data stops at your own orders.

Your order data

What happened inside the app.

Orders placed, GMV, conversion — on the merchants you already carry. Blind to the supply you don't have, the demand you're missing, and what customers actually think of the experience.

Realytics

What's happening across the market.

Every merchant in the market — signed or not — priced, rated and ranked by real consumer demand, with what customers say about each one and about the delivery itself, by zone.

Supply you don't have

The highest-demand, highest-rated merchants in a zone that aren't on your platform yet — and the catchment (the area's orders) leaking to whoever fulfils them.

Demand you're not meeting

The cuisines, categories and baskets a neighbourhood is ordering that your selection doesn't cover — by area, week over week.

The verdict you can't see

What customers say about every merchant — and about wait time, order accuracy and the delivery — read from consumer opinions.

Why Realytics

Your app makes the orders you already get more efficient. Realytics grows the ones you don't.

More of the right supply, demand you're not yet meeting, promo that closes a real gap, and a delivery experience customers come back to — read from consumer signal across the whole market, not just your own funnel.

What you can do

One market view. Every play that grows the marketplace.

Pick the job. The same off-platform view powers all of them — from signing the next merchant to the right recommendation on a first-time customer's screen.

Sign the merchants your market wants

Which to sign next — and the assortment gaps to recruit to.

Merchant acquisition

Find and sign the merchants your market wants

Every un-signed restaurant, ranked by real consumer demand, consumer rating and fit — with the contact details to reach them.

Selection & assortment

Close the gap between what's ordered and what you carry

See the cuisines, categories and items a zone is ordering that you don't offer yet. Recruit to the gap — not at random.

Grow into the next zone

Where to expand next, and where a rival platform is winning.

Zone & market expansion

Know which zones to launch or deepen next

Rank cities and delivery zones by unmet demand and where the competition is weakest.

Competitive intelligence

See where a rival platform is winning

Where the same item is cheaper elsewhere, which merchants are exclusive or multi-homing (listed on more than one app), and which zones a competitor is moving on — from menu and consumer signal.

A message you could send

Sample merchant-acquisition outreach

Subject: the poke orders your block is placing — and you're not on the list

Hi Daniel,

Customers within walking distance of Pacific Poke are ordering a lot of poke and healthy bowls on delivery — and you're one of the highest-rated kitchens for it in the area.

Consumer signal: that demand is strong and growing, but most of it is being fulfilled further out, because Pacific Poke isn't on [Platform] yet. The catchment is yours to win.

Getting you live takes a few days. Worth 15 minutes before the summer rush?

— Sam, [Your platform]

Names anonymized; every line is drawn from real consumer signal: the demand, consumer signals, the gap. That is what gets a merchant to reply.

Grow every order

Where promo closes a real gap, and where price is costing orders.

Promo efficiency

Spend subsidy where it closes a real gap

Concentrate budget on merchants priced above their real local set, where customers rate the value and will reorder — not on the ones already competitive. Where value perception is already saturated in a zone, a subsidy adds least.

Conversion & GMV

Recover the orders lost to price, not demand

Find where price is costing orders, rank merchants by repricing upside, and read average-check economics by area.

Price it right, protect the reorder

Give account managers a diagnosis, and keep the delivery experience that brings customers back.

Repricing & menu

Give account managers a diagnosis a merchant can act on

"You're priced above the rivals in your delivery zone" — concrete, by dish category, normalized to the category so every gap is apples to apples.

Delivery experience

Protect the experience that drives reorders

What customers say about the delivery itself — wait time, order accuracy, the handover — by zone, so ops fixes the right thing in the right place.

Personalize every recommendation

You know who your customer is. We know which merchants customers like them gravitate to, in aggregate — so you can recommend the right place from the first tap, even before a single order. You hold the customer; we provide the affinity, and the match runs in your stack. It's how you fix the cold-start that order data alone can't: a new customer, a newly-signed merchant, or a market you just launched.

New customer, no history

A relevant first recommendation

Match a customer's demographic and taste profile to the merchants that over-index with people like them, in aggregate — before they've ordered once.

New merchant, no orders

Surface it to the right people on day one

A merchant you just signed has no order history — but we already know, in aggregate, who its customers are. Put it in front of the people most likely to love it.

New market, no signal

Seed recommendations at launch

Launching a zone or city with no order data yet? Start from the demographic-to-merchant affinity already in the market, and improve as orders arrive.

A new revenue line

Turn the same data into a product your merchants pay for.

A Price Score, promo and price alerts, and assortment gaps — a paid tool that helps your restaurants price themselves, powered by the market view you already license. Your supply gets sharper; you add a line of revenue.

Let's build it

Talk to our team

Customer story

From one cross-shop read to 300+ cities.

A multi-country platform came in to find unsigned merchants. What the off-platform data showed — that a salad customer's real next order is a burger, not another salad — rewrote how they run cold-start recommendations across every city they operate in.

A multi-country food-delivery platform

The salad customer's real rival is a burger. Your order data will never tell you.

Cross-shop signal Cold-start recommendations Off-platform only

Seed a cold-start recommender from your own order history and it makes the obvious bet: the salad customer wants another salad. Off-platform consumer signal says otherwise. In one home metro, the customers of a national salad chain cross-shop a fast-food burger chain more than they cross-shop the nearest direct salad rival — 5.8% vs 5.2%, the ordering literally flips. In another city, a burrito chain's customers cross-shop the burger chain at 16% while the nearest same-cuisine rival sits below 1% — a 17x gap, with no direct competitor anywhere in the top 14. The same pattern holds in a third cuisine, same city: a national coffee chain's customers cross-shop a burger chain more than any direct coffee rival (15.7% vs 10.3%). Three categories. Two cities. The indirect rival beats the direct one every time. First-party data cannot surface this. It only records the orders that already happened on your app, never the burger the salad customer chose somewhere else. That blind spot is exactly where cold-start goes wrong — and it is exactly what off-platform consumer cross-visitation fixes.

The blind spot, quantified

What your order data assumes

Similar cuisine → similar customer

A cold-start recommender built on first-party history buckets customers by cuisine: salad customers get salad suggestions, burrito customers get burrito options. The assumption is natural. It is also wrong. Your app only records what already happened on it — never the off-platform choice that reveals the real consideration set.

What the market actually shows

The real rival is cross-cuisine — and ranked first

For a national salad chain in its home metro, the #1 consumer cross-shop rival is an indirect fast-food brand — sitting above the nearest direct salad rival (5.8% vs 5.2%). For a burrito chain in another city, every one of the top 14 cross-shop rivals is indirect; the nearest same-cuisine rival ranks 15th, at 0.96% against a 16% indirect leader. A national coffee chain in that same city: the burger chain again ranks first, ahead of the nearest coffee rival (15.7% vs 10.3%). The correct first-tap recommendation requires knowing the whole market, not just your funnel.

The proof, in numbers

17×

indirect vs. direct cross-shop gap — burrito chain, one city

16%

burrito chain cross-shop to top indirect rival

15.7%

coffee chain cross-shop to a burger rival — above every direct coffee competitor

cuisine categories, two cities — indirect rival ranked first every time

What cross-shop signal unlocks

Cold-start recommendations — built on the real consideration set, not cuisine buckets
Merchant acquisition — sign the merchants your customers already choose off-platform
New zone launch — map demand before a single order is placed
Newly-signed merchant targeting — find the right first customers before order history exists

Coverage & data

The data behind every answer.

One view of the market your platform competes in — every merchant signed or not, the demand around it, what customers say, and what they pay. Matched, refreshed weekly, and independently benchmarked.

288M

outlets mapped — every merchant in the markets you operate, signed or not.

1.5B+

consumer profiles, behind demand & recommendations

11.5B+

consumer signals — what customers say, by merchant & zone

350M+

menu items, priced and refreshed weekly

630K+

brand chains, matched

252

countries & territories

Weeklyrefreshed, since 2020

0.94correlation with Technomic foodservice data

100+languages of consumer opinion read

Delivered weekly as data feeds and via API, with QA and an SLA — aggregated consumer signal, never personal data, GDPR and CCPA compliant. Start with a pilot on a few markets, then scale to production. See the data coverage →

Start with a pilot

See your market — supply, demand, price and quality, in one view.

A fixed-scope pilot on a few of your markets: your merchants and the ones you haven't signed, matched to their real competitors, benchmarked by category, and read against what customers say. Then scale to production.

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