#Food Pie Fight ! '#Foodonomics' decoded
"Chase the vision, not the money; the money will end up following you."
-Tony Hsieh, CEO of Zappos
Indian food-tech or rather food-internet sector in very short span has seen quite a steep sinusoidal pattern in its quest to grab funds. Currently there is so called correction phase or 'funds winter' which has hit Indian startup landscape. What was apple of eye of all VCs in 2015, food tech space is undergoing refinement - focus is more on positive unit economics, sustainable models. Majority of food tech startups which had mushroomed in 'me-too' mode have either disappeared due to lack of follow-on capital or got acquired or pivoted to pure logistics play but after a high cash burn-out.
There are multiple articles spanning this canvas, intention of this write-up is not to dissect on what went wrong or figure out rectification course for the existent startups. I am not expert on these :) (Slowly learning though!). This post's goal is just to bring out a perspective on what is 'As-Is' scenario currently in Indian Food-Tech aggregators, decode key business levers of significant players & build some surmise on which firm is better positioned to win this battle. Play arena considered comprises of 3 key players - Swiggy, Zomato & Foodpanda.
Pls note this post may seem very rudimentary to few, but objective behind analysing & sharing stuff is to align these findings with beginner folks who are in learning phase like me!
Food-Delivery-Tech Model Basics
► Revenue Drivers
☛ Avg Order Value (AOV) : This is avg bill value a firm generates spanning across all orders.
☛ Take Rate (TR%) : This is commission rate charged by firm to restaurant per transaction or bill
☛ Delivery Revenue (DR) : This is a delivery fee charged to customer per order (if any). Any delivery revenue from restaurant is built in Take Rate only
☛ Avg Revenue Per Order (ARPO) = (AOV x TR%) + (DR)
► Variable Cost Drivers
☛ Delivery Charge Per Order (DCPO) : This is a loaded cost inclusive of fuel, vehicle, salary of delivery person, his incentive etc.
☛ Packing Charges (PAC) : If there is any branded packaging done (if any)
☛ Processing Cost (POC) : Ops cost per order which includes handling communication b/w restaurant,
customer & delivery person (if direct)
☛ Avg Variable Cost Per Order (AVCPO) = DCPO + PAC + POC
► Contribution Margin
Contribution Margin per Order (CMPO) = Avg Revenue - Variable Cost
CMPO = ARPO - AVCPO
Now with these basics in mind, we can focus on where all these individual firms stand on CMPO & what it means for them. Pls refer to detailed model computation for all 3 firms here in google spreadsheet. All 3 firms' business models have been analysed in this framework. All relevant data sources used for derivation for Swiggy, Zomato & Foodpanda are listed in last tab of sheet. Pls note for each factor some suitable assumptions are taken wherever data points are not publicly available
Excel Model Link provide here again.
Following is a short summary table which crisply tells the story.
CMPO : Foodpanda (4X) > Swiggy (1.2X) > Zomato (X)
Though Swiggy has lower AOV & CMPO than FP, it has much better control on last leg of customer experience i.e. delivery by owning it completely. Going by these figures, CMPO for Zomato appears the lowest as its take rate is not as aggressive as in case of Swiggy & Foodpanda.
► Zomato Can Make It !
Zomato is an established food discovery & review-based player moving into food delivery vs. Swiggy which currently is purely into food delivery. Though it is a very different logistics play for Zomato to win, it can be aggressive in leveraging its harvested network model effect. Its product (site/app) can be a big footfall driver by revamping into much crisper, more intuitive & super engaging for a customer to search the nearby restaurant list + look at their reviews in parallel & then place an order in few clicks.
Also note Zomato's AOV > Swiggy's AOV. There is still room for Zomato to slightly jack up its take rate % thereby increasing its ARPO. If it charges same Take Rate% as Swiggy or FP, its CMPO will easily shoot up to 65 from current 15! More than 4X jump! What lies in its bag - a big advantage lever is its customer review platform - a powerful medium through which it can implicitly drive restaurants partners to ensure a decent delivery customer experience without owning a delivery fleet!
► Swiggy has Controlled but Pricey Customer Experience
If we factor in just delivery fleet employed by Swiggy, there are 4200 delivery boys fuelling its hyper-growth (Source). If we take avg monthly salary of delivery person (which are scarce resources) ~ 15K INR then it computes to total of 63 Million (INR) as fixed salary cost of delivery staff alone. So with CMPO of 18, it will take 3.5 Million orders monthly for Swiggy to break-even just on this delivery fixed cost. (Other Fixed Cost Heads not considered here for simplicity of computation)
Break-Even Orders = Fixed-Cost / CMPO
Break-Even Orders = (Salary per Delivery Person x Delivery Persons) / CMPO
That derives to 116K daily orders. It's currently clocking 35K orders daily, 30% of target or break-even figure. There is a long way for Swiggy to go as it carries additional baggage of its delivery fleet. So though it clicks on customer experience, it has to build up a scale quickly to justify the cost.
► Foodpanda - Confusing Picture
Well if I believe the data collated across for this post, Foodpanda seems to be riding the wave ahead of Swiggy & Zomato. By huge leap ! Both in terms of avg daily orders, AOV, ARPO, CMPO - all metrics ! If it is in so good business health, then why there is speculation of its sale? (News here) Honestly I couldn't get data to deep-dive to validate which picture is truer version. So from perspective of this post, FP looks like a leader for now!
PS : Pls note you may feel Foodpanda figures are quite off-track, I wish to state that not much public data about its India only ops was available (even though FP is publicly listed) & I had to connect dots from various media excerpts/interviews by Foodpanda India leadership to arrive at a partial picture.
Your feedback/thoughts as always are most welcome!