What is page speed worth for food delivery? A worked example.
Food ordering is impulsive, mobile, and time-boxed to a hungry moment. A slow menu or a stalling cart is enough to send the order to whichever app loads first. On this profile, going from 3.2s to 1.6s models about $67.7K a month in extra revenue.
assumptions
A planning profile for this kind of site. Every figure is yours to change in the calculator.
- Current load time (p75): 3.2s
- Target load time: 1.6s
- Monthly visits in scope: 280K
- Current conversion rate: 4.5%
- Value of a placed order: $28.00
- Conversion lift per 100ms faster: 1.2%
revenue_uplift
+$67.7K/ month
$812.9K / year · +2,419 placed orders / month
- Time shaved off
- 1.6s
- Relative conversion lift
- +19%
- Conversion rate
- 4.5% → 5.36%
- Each 100ms is worth
- $4,234/mo
- Revenue now → at target
- $352.8K → $420.5K
Computed by the Page Speed → Revenue model · planning estimate, not a guarantee
why_speed_pays_here
Why speed maps to money for food delivery
Order values are small but conversion rates and visit volumes are high, and the audience is almost entirely on mobile networks where every byte costs more. That combination makes food ordering one of the most speed-elastic flows: the lift per 100ms is large because patience is short.
Where the load time goes. Menu pages carry many images and live availability, and on a phone over cellular that adds up quickly. Prioritize the first screen of the menu, lazy-load the rest, compress and right-size dish photos, and keep the cart interactive without a full round-trip on every tap.
faq
Questions & answers
- How much revenue can faster page speed add for food delivery?
- On this profile (3.2s to 1.6s at 280K visits a month), the model puts the gain at about $67.7K a month, or $812.9K a year, from a roughly 19% relative lift in conversion. Your real numbers will differ; tune them in the calculator.
- Is the 19% conversion lift realistic?
- It comes from one assumption you can change: a 1.2% relative conversion change per 100ms faster, applied to the 1.6s this profile shaves off. That sensitivity is in the range of widely cited retail studies; for lower-intent traffic use a smaller figure, for high-intent checkout flows a larger one. The model also caps the modeled lift so an extreme speedup can't imply a fantasy multiplier.
- What's the fastest way to speed up food delivery?
- Menu pages carry many images and live availability, and on a phone over cellular that adds up quickly. Prioritize the first screen of the menu, lazy-load the rest, compress and right-size dish photos, and keep the cart interactive without a full round-trip on every tap.
That uplift is the business case. Hitting the target is the work.
I'll find where your real load time goes and what it takes to actually reach the target. Book a call, or leave your email and I'll reach out.
Prefer proof first? See how this plays out in real case studies →