How Fake Orders Are Screwing Up The Food Ordering Business

In 2015, foodtech was the most celebrated sector with investors funding amounting to ~$300 Mn. Then came the downturn in 2016 which witnessed the closure of startups like Dazo, SpoonJoy and several others. The recent news of the $15 Mn Swiggy funding is being touted as a somewhat cautious sign of reviving confidence in the sector.

I believe the food sector has got its due course correction and from now on, will increasingly give rise to newer innovative models and entrants, while current ones will move towards stabilisation.

Fake Orders: Bane Of Foodtech Industry

Being an integral part of foodtech, my numerous interactions with Foodpanda, Zomato, and Faasos have unearthed a niggling issue that still plagues the online food delivery players — fake orders.

Fake orders are those orders which are intentionally done to either hurt the player (by other competing players) or are done by testers who test various websites for bugs/errors. To make clearer, fake orders are not those orders which happen due to a customer changing their mind post placing the order, and voluntarily cancelling the order.

In fact , even players like Dominos and Pizza Hut, (which receive more than 60% of their orders over the phone) have been experiencing fake orders too. Although fake orders are prevalent across ecommerce businesses, they are scarier for foodtech companies since food is perishable and can’t be sold to some other customer later. And, in most cases, can’t be stored beyond a certain time.

On the basis of my interactions, the fake orders ranged anywhere from 5–10% of total orders received by the online food delivery players. These orders hurt the most as in most of the cases, the kitchen has done their part of making a sumptuous meal and delivery boy has reached the delivery address to realise that there are no takers for the order at that address.

All the resources including the chef’s effort, ingredients used, cooking process, packaging, delivery boy’s effort , fuel consumed etc. have been utilised already, finally leading to nothing. Bigger chains such as Dominos, McDonalds etc. have policies wherein they discard/throw away these unowned orders and don’t sell them again.

However, some smaller kitchens who can’t afford such luxuries decide to resell them and in some cases without even telling their customers, further leading to dissatisfied customers and a fall in repeat purchase. They might have won the battle but lost the war.

Every foodtech company or internet kitchen has a few basic metrics to track: number of orders, cost of acquisition, repeat frequency, and average ticket size.

Of these, the number of orders is the most important metric for foodtech companies, which gets reported to investors to prove that their product is scalable. Some companies report their numbers net of cancelled orders, however, some do this correction at the time of auditing of financials. This over-reporting or wrong reporting is a cause of concern for VCs/investors, which also came out publicly in the case of foodpanda.

Measures Taken

Most of the companies don’t take this as a serious enough issue, however, everyone agrees that they face this issue on a daily basis. I checked up with few companies on what measures do they deploy for the same:

Customer registration : Some players have a mandatory customer registration process prior to placing the order. However, there are exceptions to the case with leading players such as Freshmenu and all restaurant websites built by Limetray.

OTP confirmations : Most bigger players use OTP confirmations to authenticate the customer. However, some believe it is a hindrance in terms of user experience as there are delays in SMS delivery which leads to drops in orders.

Call centres : Bigger companies such as Freshmenu, Faasos, Dominos etc. deploy call centres to confirm orders before processing the same. Ironically, calling and confirming every order just questions the genesis of online order as a business model.

Banning customer: Very few internet kitchens have gone to the extent of banning such users from placing any order on their platform. However, platforms such as Zomato, foodpanda, and Swiggy are not in a position to take such a stern action.

On-demand food ordering does more than 1.1 Lakh orders a day, with an average ticket size of INR 200; which takes the daily gross order value to INR 2.2 Cr a day, and INR 700 Cr annually. Even if I take a conservative estimate of 5% fake orders, it translates to a mind-boggling figure of INR 35 Cr annually. Along with the industry, this figure also continues to grow year over year.

Breakthrough Ideas To Counter Fake Orders

Usage of 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 order history) that are beyond a threshold score to be passed on to call centres for confirmation.

Common keywords for bug testers : Bug testers are a critical resource to developers as they help build a more secure online world, whether in terms of customer information or transaction security. These bug testers have no interest in food or harming the company by placing fake orders. However, in their process of finding bugs, they place such orders which are not real.

In order to avoid getting misguided by them, companies can assist bug testers through their console area of source code by mentioning: “Use code “BUGFOODIE” in case you are trying to gatecrash to help us save food.”

Tracking real-time bounce of emails : Most of the food ordering portals send a confirmation/receipt mail to the email id used for placing the order. Companies should have real-time monitoring for whether the mail has bounced to the recipient, which is a good indicator of a fake transaction.

[Chirag is the co-founder of Ketchupp. A coder at heart, he is an execution-oriented guy with experience in technology, finance & strategy. Apart from being a voracious reader, Chirag loves beer & biryani.]

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