Having had more than 1,800 meals delivered at my doorstep over the last 5 years I realized something was missing in the uberised food delivery industry.
And it was more than just the lack of mayonnaise with my French fries.
In this post I will try to take you on a journey that is larger than this industry. It is a more exciting journey which is about us, humans — and also accidentally the targets of the abundant tech apps.
To get my point across I’ve made this post very specific to two cases that many of us know — UberEats and Postmates. For the Doordashes, Deliveroos and Caviars of this world: it could equally have been you.
Spoiler alert: if you are too lazy (like me) skip to the conclusion at the bottom.
We live in a world of instant gratification
Open the app, select, confirm, wait. Knock knock, food is here.
Behind this knock knock could have as easily been a Tinder date, your Rinse laundry or if you’re into a dodgy business, Heisenberg.
Outcome is the same: a happy user.
We are thriving for efficiency…
Sit back. With tech you now have more time. Use it to either work or relax more.
UberEats, Postmates, Deliveroo, Doordash, Caviar and the many others are built to provide an experience as functional as possible. Efficiency, minimization of efforts and speed.
… but there is more to it: we are hooked by variable rewards
People love being surprised. People love getting more than what they expect — remember Nir Eyal’s description of habit-forming products.
The winner is not the one with the best product, but with the first habit-building product associated with a certain emotion which has the monopoly in the user’s mind — Nir Eyal
The first food delivery business which understands how to successfully provide variable rewards to its users will be the winner.
You will tell me that no one wants to get pizza instead of the ordered salad. Or that no one wants to get variable food quality. True.
Then how can rewards in the food industry be variable while fulfilling the ambitious goal of being aligned with the company’s mission, of meeting the company and the users’ needs and of being economically interesting?
Instant deals. But not like Forkable. More like Groupon meets UberPool
My pitched feature for food delivery businesses is the following:
Imagine every time you open the app you are surprised by a different deal. A deal that disappears in a few minutes.
Variable discounts will be the reward component for food orders. Not like current static in-app promotions which last for days, but instead changing deals by the minute which are based on who is around you at that moment and on what they ordered.
Giving you, as a customer, control over the discounts you can have.
For those interested in the mechanism of such feature I am detailing below the key aspects through mockups and working principles.
Transportation logistics through matching algorithms between drivers, restaurants and customers is already done at UberEats and Postmates. This concept further optimizes operations and will lead to a stronger community.
For those who know Nir Eyal’s “Hook canvas”, steps (1) and (3) above would be the “investment”. Another investment could be customers moving closer to each other to trigger better deals.
Since a mockup is worth a thousand paragraphs…
I designed an interactive simulation (see below) of how it would feel from the point of view of a neighbor joining a group order.
Feel free to try it! [currently unavailable]
If it isn’t fully clear, the interface explanations below hopefully fill the gaps.
You might wonder why only UberEats’ mockup is provided — well spotted! Since the feature is the same and that only the interface changes between apps, I didn’t insert it here. But for the most curious of you I’ve uploaded the Postmates mockup here.
Bonus: did you open it? I was struck by UberEats’ 50% shorter path to the check out page vs. Postmates. This is ergonomy my friends.
It is the sum of 2 components:
The restaurant discount thresholds are pre-agreed with restaurants and are a function of the number of neighbors per group order for that restaurant and/or for a specific meal (e.g. “5% for 3 neighbors ordering any meal from restaurant X, 10% for 4 neighbors ordering the Hawaiian Poke Bowl from restaurant X”)
Rationale: ↗ revenues, ↗ staff utilization and ↗ economies of scale (many orders of same meal)
The delivery discount thresholds are a function of the number of neighbors per group order (i.e. reduction of delivery cost) and are depending on the financial metric to prioritize: e.g. profit (min. Deliv.Disct, only Rest.Disct), revenue (max. Deliv.Disct and of Rest.Dict to attract volume)
Rationale: ↗ revenues, ↘ costs (↘ avg. #drivers / order), solves issue of peak time (efficient deliveries)
→ Upon creation of a group order by the initiator, an estimate of the discount (Rest.Disct + Deliv.Disct) per potential additional neighbor is indicated. Joining neighbors can also see these estimates.
→The final applicable discount is calculated once the group order is placed (end of validity period). All neighbors of that group order benefit from the same final discount.
The intention is to have these group orders especially activated during peak times. A customer placing an order will probably be happy to wait an extra 10–30 minutes if this provides a 5–20% discount in peak times.
The extra 10–30 minutes is the time necessary (i) for the group order to reach the end of its validity period and (ii) to deliver the meals to the neighbors ahead in the queue (e.g. first come first served). An initiator could for instance be rewarded by being delivered first.
We, humans, love offers which expire, it makes us feel like we live in the moment. Having a validity period has 2 benefits: (i) Limited waiting time, and (ii) Create a sense of urgency.
Over 40–45% of UberEats and Postmates customers’ annual income is lower than 50 k$. In addition, 20–30% customers earn up to 100 k$ per year. It is fair to assume most customers are price sensitive hence group orders will appeal to them because it allows them to eat for a lower price.
Most users order from urban areas where density is high, making group orders between strangers feasible. Additional information on customers’ density (e.g. number of customers located within 200 meters radius) would need to be further obtained to confirm this fully.
Assumption: age is somewhat correlated to a customer’s finickiness (picky about food choice):
Even if most customers are not expected to be finicky, UberEats and Postmates will collect data to better understand their preferences. Once a group order matches a customer’s preferences, a notification will be sent as invitation to join the order.
The low average time spent ordering on the apps indicates that customers are focused on satisfying their appetite rather than eating out of pleasure. Group orders will make it even easier to quickly order.
Since I have no access to UberEats’ or Postmates’ data (nor to Storm, Spark or even simply enjoying SQL queries) I had to rely on SurveyMonkey Intelligence. The data above is specific to the USA. Hence the displayed charts might not fully reflect the reality.
Uber’s Marketplace and Postmates solution already funnel the real-world, real-time requests and locations into their tech infrastructure.
Their systems already handle pings from customers, restaurants and drivers in real-time to match them. Only an extra “matching” mechanism between customers (neighbors) is needed for group orders to become reality.
CB Insights’ competitive landscape of the food delivery industry
The above chart is based on my own assumptions. Breakfast orders and late night ones are not represented here.
By now I might have lost you in an excessive level of details, only managing to trigger a desire to grab that big fat snack from your office’s fridge.
So let me recap this in a more general manner.
In a very saturated market where little differentiation can be achieved on the core offering of a product, it is essential that companies understand how fungible and non-core this very offering actually is.
The focus instead should be back on the fundamentals. On fostering a sense of belonging to a community and on rewarding the community members for joining it.
The ephemeral character of the community does not matter — it can come and go opportunistically. As long as its members are continuously and variably rewarded.
I know there are a lot of smart minds out there and I believe in the power of crowdsourcing so shoot your comments and feedback!
Now let me leave you by sharing what is on my mind.
Imagine customers (colleagues, friends, strangers) who are located in each other’s vicinity become initiators and collaborate to maximize discounts, turning food ordering into a collective and fun effort…
… Imagine creating an entire community with initiators getting ratings, restaurants activating “hidden discounts” to create hype, customers getting notifications indicating their preferred meal is available right now at discount of 20%, neighbors sharing with their followers their discounted meals on social media, …
If you want more right now, check out why 8tracks should follow Spotify’s steps here!
Enjoyed that read? Click the ❤ below to recommend it to other interested readers!