In 2015, food tech was the most celebrated sector, with investors funnelling in as much as $300 million. Then came the downturn in 2016, which witnessed the closure of Dazo, Peeto, TinyOwl, SpoonJoy and several others. Now, the recent news of Swiggy getting $15 million in funding is being touted as a sign that the confidence in the sector may be reviving. I tend to agree with this positive outlook and believe the food sector will increasingly give rise to newer innovative models and entrants, while current ones will move towards stabilization.
Even if I take a conservative estimate of 5% fake orders, it translates to mind boggling figure of ₹35 crores annually.
Being an integral part of food tech, my numerous interactions with Foodpanda, Zomato and Faasos have unearthed a niggling issue that still plagues online food delivery players — fake orders. Even players like Dominos and Pizza Hut (which receive more than 60% of their orders over phone) are regularly blighted by such experiences. These are orders which are intentionally made to either hurt the player (by other competing players) or are done by testers who test various websites for bugs/errors. To make it more clear, fake orders do not refer to customers' cancellations or changes in decision.
Although fake orders are prevalent across the e-commerce business, they are scarier for food tech companies since food is perishable and can't usually be sold to some other customer at a later date.
In my interactions, I've gathered that fake orders comprise anywhere between 5–10% of total orders received by online food delivery players. The waste of time and resources is undeniable, since most such orders are detected after the kitchen has prepared the meal and when the delivery person discovers that there are no takers for the order at the given address. The chef's efforts, the ingredients used, the packaging, the delivery boy's travel, the fuel consumed... they all go to waste. Bigger chains such as Dominos, McDonalds etc have policies wherein they discard returned orders, but other kitchens who can't afford such luxuries sometimes attempt to resell the prepared food. This food is often not in the best condition and the customers who land up with them (unknowingly), are dissatisfied and write off the establishment in question. The business in such cases might have won the battle but lost the war.
Number of orders: the most important metric
Every food tech company or internet kitchen has few basic metrics to track:
(1) Number of orders
(2) Cost of acquisition
(3) Repeat frequency
(4) Average ticket size.
Of these, number of orders is the most important metric for food tech companies. This is what gets reported to investors to prove that their product is scalable. Some companies report their numbers net of cancelled orders, but some do this correction at the time of auditing of financials. This over-reporting is a cause of concern for VCs/Investors, which is what happened in the case of Foodpanda.
How do companies protect themselves?
Despite the frequency of the problem, most companies don't have very stringent processes to prevent or address the problem. I checked with some companies to find out the measures they deploy and most fell short.
1. Customer registration: Some players have a mandatory customer registration process that must be completed prior to placing an order. However, there are exceptions such as Freshmenu and all restaurant websites built by limetray.
3. Call centres: Larger companies such as Freshmenu, Faasos, Dominos etc. use call centres to confirm orders before processing then. Ironically, calling and confirming every order kind of defies the point of online ordering as a business model.
4. Banning errant customers: A few (very few!) internet kitchens have gone to the extent of banning such users from placing any order on their platform. However, ordering platforms such as Zomato, Foodpanda and Swiggy are not in a position to take such a stern action.
Magnitude of loss
On-demand food orders amount to about 1.1 lakh per day, with an average ticket size of ₹200. This makes the daily gross order value to be ₹2.2 crores a day (₹700 crore annually). Even if I take a conservative estimate of 5% fake orders, it translates to mind boggling figure of ₹35 crores annually. As the industry grows, so will this figure.
Breakthrough ideas to counter fake orders
1. Using predictive analytics : Rather than calling every customer, companies should use predictive analytics to identify orders (extremely high order value, too many orders within a short span of time, unprecedented as per the order history) that are beyond a threshold score to be passed on to call centres for confirmation.
2. Common keywords for bug testers: Bug testers are critical resources to developers as they help build a more secure online world, whether it is in terms of customer information or transaction security. These bug testers have no interest in food or harming the company by placing fake orders, but in their process of finding bugs, they place orders that are not real. In order to avoid getting misguided by them, companies can assist bug testers through their source code console area with a message that goes something like, "Use code 'BUGFOODIE' in case you are trying to gatecrash to help us save food."
3. Trackingreal-time bounce of e-mails: Most food ordering portals send a confirmation/receipt mail to the e-mail ID used for placing the order. Companies should have a real time monitoring of whether the mail has bounced, which is a good indicator of a fake transaction.
In case your company deploys any such novel techniques to counter fake orders, do let me know at firstname.lastname@example.org.