This post isn’t for the easily offended. If you’re the type of person who puts 2 and 2 together and gets 5, I suggest closing this tab and reading no further.
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I was chatting with Oytun, our Turkey country manager, this past weekend, because I’ve been quite concerned about what’s going on in Turkey. I was worried about our team’s safety and well-being (in addition to being concerned about the well-being of the world in general). Oytun reassured me that Turkey is a resilient country, that it always bounces back in about 2 weeks, and that I shouldn’t be worried.
That thought stayed with me, and I figured that our traffic data in Turkey should very easily be able to prove the hypothesis that Turkey bounces back in two weeks. After all, the frequency of eating out is a fair indicator of how a country is reacting to a particular terror attack or situation.
For those not in the know, here’s some context on Turkey. The country has seen more than its fair share of unrest in recent times. Since the start of 2016, they’ve suffered a series of attacks and events that have put the country on high alert. Istanbul alone has seen three violent attacks, and been at the centre of an attempted military coup.
Every time one of these events occurs, we see a country that reacts the way any country in its place would: businesses pull down their shutters, people stay indoors, security measures are beefed up, and day-to-day life is disrupted. Sitting helpless thousands of miles away, it’s terrifying – all we can think of is the safety of our colleagues, and pray that normalcy will be restored soon.
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Something that’s amazed us is how – every time, and without exception – our team carries on with business as usual (while taking all necessary precautions, obviously). We can put this down to their incredible resilience and work ethic.
But what about the rest of the city? Does it actually take Istanbul as a whole just two weeks to get back up on its feet and get back to life?
One rarely gets to see that from an outsider’s perspective (and we were curious), so we started digging through Istanbul’s traffic patterns on Zomato. Here’s what we found:
Our website traffic in Turkey drops by as much as ~50% in the immediate aftermath of an event, but recovers to its original point within ~10-15 days.
Here’s some data to illustrate this better.
Attacks in Ankara (March 13th) and Istanbul (March 19th): The attacks in Ankara on the 13th of March had a strong effect on traffic in Istanbul, causing a sharp dip in traffic. Just six days later, on the 19th of March, Istanbul was hit by attacks. However, the effect it had on traffic was nowhere nearly as dramatic. By the 27th of March – just two weeks after the attack in Ankara – traffic in Istanbul had returned to the point it was at just before the attacks.
Attempted military coup across Turkey, July 15th-16th: Between military-imposed curfews, widespread protests, and the declaration of a three-month state of emergency, Turkey seemed to be in complete disarray. By the end of the 16th of July, our traffic in Istanbul had dropped to almost nothing. But by the 30th, it had recovered the gap and then gone on to grow to 6% higher than it was on the 14th of July.
Interestingly – but not entirely surprisingly – delivery restaurants gained more share of the recovering traffic (compared to dine-out restaurants) after these events. Dine-out restaurants’ traffic was also near normal within two weeks. What does that tell us? That slightly fewer people want to head outdoors to eat in the wake of any unrest, simply because it’s safer to stay indoors.
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The hypothesis was right: two weeks.
It takes Istanbul two weeks to bounce back from events that have rocked the city. It speaks volumes of the fortitude of the Turkish people, and their ability to get on with their lives.
When I mentioned this to someone yesterday, they argued with “Yeah, but many cities bounce back from adversity. What makes Istanbul unique?” To be honest, we don’t have a benchmark to compare Istanbul to – and we hope we never do. No city, and nobody, should have to suffer what Istanbul has in recent times.
This post is simply a salute to a city with immense courage; a city that refuses to take things sitting down. But more than that, it’s a tribute to my colleagues in Istanbul, whose unyielding and eternally positive spirit is an inspiration to us all.
This milestone achieved by our online food ordering team is dedicated to our mates in Turkey. Our thoughts are with our team and everyone in Turkey – the people who show an undying spirit in the greatest moments of adversity.
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“Will we get there? Will we not?” – Everyone at Zomato
Before the start of July, we knew that if we did our job well, we could grow our online food ordering business to a million orders a month in July. We kicked our planning into gear, and made sure that we did enough to get there. We came up with a plan – a day-by-day prediction of our order volumes for the entire month.
The first time we circulated a projection chart within the team was at end of day on the 3rd of July. This is what that chart looked like:
A few days later, we were pleasantly surprised to see that things were going according to plan:
I’ll be honest – such things don’t really happen too often at Zomato. We are usually over-ambitious, and often fall short of our own expectations. This time, us meeting our expectations was a result of two things – 1) setting realistic expectations (even though the expectation would need us to stretch ourselves), and 2) the team doing a great job and smashing out results one day after the other.
In general, my predictions have never been spot-on. So much so, even when I wanted just one kid, I got twins 🙂
The fact that July had five weekends certainly helped our cause. Finally, at 8:23 pm on the 31st of July, we hit the million-order mark for July – and then we racked up another 20,000 orders before the night ended. This is what the chart looked like at the end of last night:
The average order value (AOV) of our orders is holding well at ~Rs 480, and our unit economics have improved by 10% since the last time we wrote about it. We now make Rs 23 per order as contribution margin compared to Rs 21 two months ago. Our customer retention has also improved sharply; in fact, our cohorts are now looking even more like a smile – a shape that lets me sleep well at night.
Note that this cohort is for returning users – not orders from returning users. Orders from returning users cohort looks even more exciting because of the ever-increasing frequency from retained users.
Congratulations to our entire team, which has worked super hard to get here. But this is just the start, and we’re going to power on keeping in mind – what got us here, will not take us there.
We have a confession to make. Over the last two years, we’ve been so busy with our international expansion and our manic focus on winning delivery, that we let the basic USP of our core product – search and discovery – suffer a fair bit. Our own app feels a bit outdated to us, and we’re now beefing up (no pun intended!) our engineering and product teams to get our app back to being one that’s delightfully enjoyable to use and explore.
We’re starting with something our users have complained about for so long – “You know so much about me now. Why do I still see the same restaurants and recommendations as everyone else? Show me stuff you know I will like. Don’t be a dumb f**king app.” (Yup, users don’t mince their words when they care about you so much).
Listening is a very important trait. So we’ve made personalisation one of the top priorities for our product and engineering teams, and we are now working on building personalisation into various aspects of Zomato. Needless to say, we are starting with the online food ordering product, but we will very soon bring personalisation to our main search and discovery product as well.
To start with, we are drawing on data and behavioural patterns to personalise your ordering experience on Zomato, and making crafting your meal from all those extensive fifteen-page menus waaay easier.
First, we’re tackling the big question:
Where should I order from?
Earlier, restaurants in the online ordering flow used to appear based on factors such as popularity, and distance from your physical location. The problem was, this made the list of restaurants static, and you’d likely have to scroll endlessly to find that one place you really love ordering from. To overcome this, we’ve added a layer of personalisation that helps us put the restaurants you are most likely to order from right at the top of the stack. How do we know which ones to show you first? Your search, browsing, and order history on Zomato offer some very strong indicators, such as your cuisine preferences, how much you spend on orders on an average, and what you typically order at a given time of day. The algorithm also factors in how you’ve been using Zomato in general, and shows places you may not have ordered from yet, but might like to try (for example, your bookmarks).
This has improved our DAU ⇒ Checkout conversion on the Order app by a whopping 2.5% (and made us feel like we’ve been living under a rock all this while).
And then, we have the bigger question:
What should I order?
We have done two things to solve this problem.
First, we simply reorganised the dishes on each menu page for a restaurant, and put the ones you are most likely to order at the top. For example, if we notice a pattern of someone consistently ordering non-vegetarian dishes, we push non-vegetarian dishes to the top of every menu page on all restaurants that person views, so there’s less scrolling to get to dishes they might want to order.
Secondly, and most importantly, we made the Recommended tab on menus super smart by putting dishes we know you are most likely to order in it. These dishes are picked on basis of your past order history, other users’ order history, and corresponding order ratings received for those dishes. Our aim while designing this tab was to ensure that you are able to build an entire meal for two from that one tab, without having to swipe at all. It literally takes seconds now. I, for one, have placed my last six orders this week using just the Recommended tab. There’s some simple machine learning behind these recommendations, and we hope you’ll love this nifty new feature.
As expected, both of these changes have significantly reduced the time it takes to build an order – as of now, we’re seeing orders being placed 21% quicker, and we will further improve that number.
Like we said earlier, these are just baby steps towards making Zomato more personal and loved. We are going to get smarter, and will make up for all the work that we didn’t do for you over the last couple odd years.
There’s still a lot more to come, and we can’t wait for you to see it.
For years, our top priority at Zomato has been to ensure that we remain a trusted resource for the millions of people who use Zomato every single day.
An important part of this priority is to keep biased content out of reach of our users. There are a number of automated checks, which learn and get smarter over time. In addition to that, our neutrality team ensures that we are constantly watching for new ways in which people try to game the system; this knowledge is fed back to our engineering team, which makes sure that we always stay one step ahead of business owners who write good reviews for their own business, and bad reviews for their competition.
Over the past year or so, with the growth of popularity of Zomato as a restaurant discovery product, we’ve seen a rise in the number of people creating biased content – a few agencies spread across the world are now offering services to artificially boost restaurant ratings on Zomato, and individuals are offering to write positive reviews for restaurants ‘as a service’. And business owners are happily buying into this, because of the lure of a higher rating on Zomato. For the most part, this doesn’t work. When it does, it means that someone somewhere has figured out a way to get smarter than the system that we have created.
We are constantly working on making sure that we are smarter than the folks who want to game the ratings on Zomato to make a quick buck. Over the last few months, we have been working to completely overhaul our bias-detection algorithms. On Thursday, 9th June 2016, we are rolling out a strong new anti-bias algorithm that will help clean up biased reviews retroactively, and also put sophisticated new bias checks in place for the future. While we can’t divulge too much (for obvious reasons), we’d like to highlight some of the key things that will change.
This is our Panda update, so to speak. Here are the details of what’s changing –
Less deletions, more hiding. One might assume that deleting biased content from Zomato is the easiest thing to do. It is, technically, but anyone smart enough to try and game the system in the first place, will also be smart enough to identify patterns in what gets deleted and what doesn’t. So from now onwards, we will be deleting fewer biased reviews (but we will still delete the obviously biased ones), and algorithmically hide such reviews where they won’t be seen by most users. This will ensure that the user experience doesn’t get hurt, and spammers don’t have a clue.
User credibility scores. The new algorithm takes a fundamentally new approach to user credibility, and significantly increases the confidence level with which we can predict a user’s bias in their reviews. The new credibility scores assigned to users increase or decrease their ability to affect the restaurant’s overall rating. Credibility now factors in users’ behavioural patterns on Zomato over a period of time, as well as the quality of a user’s content. There’s enough NLP and manually curated historical data in place for us to cluster users into various ‘bias’ categories.
Moderation history. For ease of explanation, we’re going to use one of the oldest (and slightly more dramatic) cliches in the book – it takes many good deeds to build a good reputation, and only one bad one to lose it. What this means is, if a user has a history of having their content flagged and moderated, their ratings will automatically carry far less weightage in a restaurant’s overall rating. While Zomato is an open platform where we encourage people to write honest and unbiased reviews, we take abuse and bias very seriously, and will do what it takes to keep Zomato free of it.
Recency and decay. Everybody makes mistakes, and consistency is not always a given. Business owners have often complained that they still get “punished” for a bad review which they received 5 years ago, and their streak over the last 2 years has been very good. Fair point. Going forward, the effect of older ratings and reviews on a restaurant’s aggregate rating will taper off over time, giving users a better idea of what they could expect at a restaurant if they were to visit today.
Those are, in a nutshell, some parts of the new anti-bias algorithm. If we tell you more, or give you more details, we’d be doing a disservice to our users by disclosing more than we should to the people we are fighting to keep Zomato bias-free.
Starting tomorrow, some restaurants may benefit from having a lot of biased, low-value content hidden from plain sight, while some may see their rating reduce due to lower ratings from (in)credible users. We hope users and restaurant partners alike will understand and appreciate that this is being done to improve the overall quality and credibility of ratings and user-generated content on Zomato for the long term.
We’ve always told every business owner we have ever gotten in touch with – “improve your business, delight your customers, and the ratings will take care of themselves”.
However, since you got to this point in this post, there’s one important point to remember. Zomato ratings are not simple averages. You cannot calculate the average of the ratings and reviews that you get and say “this rating doesn’t make sense”. And then there’s normalisation. Or classroom ranking as some people call it. For a city, we forcibly fit all restaurants and their ratings on a normal distribution curve. In short, there’s a lot that goes on under the hood to make sure that you get a true sense of what you can expect.
There’s plenty more to come that will help make Zomato an even better and more useful product. Over the years, we’ve kept working on ways to keep the bias out, and it’s something we will continue to do. Folks who try to beat the system will always try and find new ways to do it, so it’s important that we evolve faster – and this is a strong step in that direction.
Let’s face it – some things just go really well together. Shahrukh and Kajol. Rainy days and a great book. Or Pepsi and a delicious meal. We can’t really make the first two happen on demand, but for the third, we’ve got it covered for you.
We met the Pepsi team a couple of months ago to discuss interesting ways to partner. The very first few ideas were simple and dumb – for example, we went as far as asking ourselves “should we give a free Pepsi to customers who place an order above Rs 500”? We’re tired of “free”, so we decided that we need to dig into our creativity to find something more appealing for the user, and target a product integration towards customers who would value the product at the price it sells for. Not for free. At Zomato, we don’t love people who love only free.
Finally, we found the answer. And today, we’re super excited to announce the new Pepsi integration into the Zomato app, which makes it ridiculously easy to add a Pepsi to your online orders on Zomato when you need your cola fix.
The next time you’re ordering online on Zomato (from a restaurant that serves Pepsi, of course), you’ll see the little Pepsi icon and an Add button in two places – in the ‘Recommended’ tab on online ordering menus, and inside your cart. From here, you can just go ahead and add as many bottles as you’d like to order.
For a customer placing an order, having an easy way to add a drink from within the cart means less effort swiping to the ‘Beverages’ section, which usually sits at the very end of the menu.
As far as brand integration goes, this is massive for both Zomato and Pepsi. For one, the context in which the Pepsi brand is appearing couldn’t be more perfect. People open Zomato when they’re hungry or thirsty, and this puts the product right in front of a large, targeted audience specifically looking for things to eat and drink. Moreover, adding a drink to a food order is almost second nature – in the past month alone, with the summer at its peak, 72% of all online orders placed on Zomato included a drink.
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Your app will need an update for you to see this integration. If you use the Zomato app for ordering, both iOS and Android apps (download now at www.zomato.com/mobile) already have this feature; it will be rolled out for our standalone Order apps over this week.
In terms of traditional advertising metrics, this integration gives an average of 40k targeted eyeballs to Pepsi everyday. And the Zomato restaurant finder apps (where this is live already), have seen a 140% increase in Pepsi orders. We’ll have more concrete results to share on what this has done for us, and for Pepsi, in a few weeks’ time.
Until then, here’s to making your orders on Zomato a little bit sweeter!
In earlier posts, we spoke about what our online food ordering business has taught us, and how we built the transactions DNA at Zomato over the past year despite having been a content-centric business so far. In this post, we will zoom in and look at the unit economics of our online ordering business in India, and how things look for us in the future.
Before we go on, let’s show you how order volumes stack up during various times of the day, and days of the week.
We look at our unit economics on a monthly basis. Now, if you slice out the peak volume on Sunday, those four hours obviously have extraordinarily great unit economics. But the trick of the trade is to make your unit economics work over an entire month/week, which factors in multiple peaks and troughs.
In the month of May, we processed a total of ~750,000 orders, continuing to grow at an average of 30% month-on-month. We’ve grown our online ordering business in a sustainable manner, focusing on high average order values, consciously avoiding the discounting route, and putting a great customer experience at the core of everything.
Of the ~750k orders last month, 80% of the orders were fulfilled by restaurants themselves (where we don’t do the delivery for them) – we call these Type A orders. 20% of the orders were fulfilled by us, through our last-mile logistics partners – we call these Type B orders. Keep this nomenclature in mind as you read on; this blog post analyses both Type A and Type B orders separately.
Here’s how everything stacks up for us.
The tldr; version of unit economics is in this chart below (all numbers in INR):
Note: In an analyst call a few days ago, we had said that the loss per order for Type B orders was Rs 2. That was because until last week, we used to average out our total processing/support cost over all received orders. However, now we have now started calculating processing/support cost separately for Type A vs Type B orders, and the loss per order for Type B orders comes out to be Rs 9.1
If you want to know more about the thinking behind each of these numbers, and how these are calculated, please read on.
Average Order Value (AOV)
AOV (sometimes also referred to as average ticket size or basket size) is the average value of an order during a period of time. AOV can be pre-discount, or post-discount, depending on how you look at it. Having said that, you can only gauge the real value of the business you are building if you consider the AOV post-discounting. Customers acquired through discounts are almost always going to be discount seekers, and not building that into your long-term unit economics means you are not being honest to yourself.
Our AOVs (post all possible ways to consider discounting) are Rs 480 for Type A orders, and Rs 375 for Type B orders.
Zomato doesn’t do much discounting by itself. Less than 2% of our orders are discounted by us, while 27% of our orders are discounted by the restaurants themselves. When restaurants discount something, we don’t call it discounting, we call it ‘pricing’. Just like airlines, or hotel prices, because restaurants push discounts on Zomato themselves to drive demand, using the Zomato for Business app (which they use frequently for review notifications, etc.).
Even this real-time pricing is built into the average order values for Zomato. Effectively, this formula is what holds true (and should hold true) if you are honest to yourself about your average order values –
(average order value) * (number of orders) = (total amount of real money transacted on the platform)
Take-rate/Commission/Gross Margin
This is the percentage of the total bill amount that the restaurant pays us for bringing them the delivery orders through our online ordering service. We have a variable commission rate for most of the restaurants on our network; the commission rate depends on the delivery experience for each order as rated by the customer – the better the experience, the lower the commission. While it might seem counterintuitive to do this as against charging a flat commission rate, it incentivises restaurants to provide better experiences, which leads to better customer retention.
For us, this is averaging out to 8.2% in the most recent month for Type A orders, and 18.2% for Type B orders (which includes an extra 10% for delivery).
Here’s the math for this.
Type A orders, commission – AOV * Take Rate = Rs 480 * 8.2% = ~Rs 40
Type B orders, commission – AOV * Take Rate = Rs 375 * (8.2% + 10%) = ~Rs 68
This means that we have Rs 40 to play with for Type A orders, and Rs 68 to play with for Type B orders. That’s our gross margin on each order, on an average.
For type A orders, we need to make sure that the total order processing cost – including payment gateway fee, order processing fee, support cost – is less than Rs 40 per order.
For type B orders, there’s an extra cost we incur per order which is the delivery cost, and we need to make sure that the sum of order processing cost and delivery cost is less than Rs 68.
Now, let’s talk about Delivery cost.
Delivery cost
Applicable to us only for Type B orders, this is the cost incurred to deliver a single order. This is a loaded cost, which means it includes salaries for delivery staff, the equipment and vehicles they use, as well as training and administrative costs. We pay Rs 50 to our delivery partners per order on an average (more on that later).
But it costs our delivery partners Rs 62 to fulfil an order they receive from us. An important point to note here – despite our business being extremely spiky, our delivery partners (Delhivery and Grab) are able to work in a relatively cost-efficient way because they can do e-commerce and grocery deliveries during our lean times (when food ordering is not at its peak). So Rs 62 is extremely good already. There’s room to make it better, and we are together working on predictive tech to make route planning better for delivery personnel so that this cost can come down to around Rs 50 per order.
Another important point to note – Rs 50 will eventually only be possible if you are able to keep delivery personnel busy during lean periods for food orders (which they do by serving e-commerce and grocery). Oh, and by the way, this math doesn’t factor in the very high recruitment cost of delivery personnel because of sky-high attrition.
We are thankful to our delivery partners to work with us to grow this part of the business. If we were to do this ourselves (and we’ve had the urge to do it multiple times), we would end up ruining the unit economics for the entire company in one shot. Because of the spiky nature of the business, the delivery cost would work out to ~Rs 105 per delivery. Of course, in some dense areas, during peak times, this can be much lower. But over a month, over all the markets you serve, it makes no sense at all, and you will lose more money than you can ever imagine recovering in any way possible.
And we haven’t yet gotten to the order processing and support costs yet, which is next.
Processing and Support Cost
Processing cost includes the telco data fee we incur when we automatically transmit a new order over to the restaurant. However, sometimes the device at the restaurant’s end has a bad signal, and we have to then make an SOS call to them to get the order processed. Our network is designed to have 95% automation, but it ends at 80% automation because of data/battery issues at the restaurant’s premises. Obviously, automation is way cheaper, easier, and quicker than making a call to relay an order.
Then there’s the support cost, which is what we incur when something goes wrong, and the customer raises an issue with our support team.
For Type A orders, we only have a two-way conversation to handle – between the customer and the restaurant. For Type B orders, we have a three-way conversation to work with – the customer, the restaurant, and the delivery partner’s person who is on the road.
Our total processing and support cost for Type A orders adds up to Rs 18.4 per order. For Type B orders, it adds up to Rs 27.4 (primarily because of the three-way calling, which adds more support agent time, and tariff to the cost stack). Three-ways aren’t always a good thing.
Six months ago, our support cost was about Rs 50 per order – we’ve managed to bring this down to current levels with automation, and by making hundreds of micro improvements. There is no silver bullet to bring this cost down – you have to keep chipping away at this cost bit by bit. And that’s what makes this business exciting and endless. Save a rupee per order, and the unit economics start looking way better than they did before.
Another thing this cost includes is the payment gateway fee, which is not borne by the restaurant separately (35% of all our orders are now paid for online). The number of restaurants accepting online payments on Zomato has gone up drastically in the past six months. In addition to a smoother product experience for customers, it also significantly drives down the cost associated with cash collections, and prevents pilferage – something that is very hard to control with a large delivery fleet, even if you own it.
A founder of a now-defunct local grocery startup once told me that their entire net revenue got wiped out due to cash pilferage at the hands of delivery personnel. Interestingly, he wasn’t taking that into account when calculating unit economics, and was adding these costs in the corporate overhead line item of “Miscellaneous”.
Net Contribution Margin
Net contribution margin = (AOV * Take Rate – Delivery Cost – Processing Cost)
This is what contributes towards the overall profitability of the business, and has to, over time, offset the fixed cost of the business.
Customer acquisition cost (CAC)
This is the marketing cost. This is beyond unit economics and fixed costs. How much CAC you incur, depends on how much money you are willing to spend to acquire each customer into your transaction funnel, and at what pace.
India’s CAC to LTV (life time value for a customer) ratios are very bad. Some companies are even acquiring a transacting user for as high as Rs 1200. Why’s that so high? We pay extremely high prices to various marketing channels in addition to discounting for customer acquisition.
Also, most e-commerce/transaction businesses have a traffic problem. They need to spend large amounts of capital to re-engage customers i.e. getting them to transact again on the platform. On that note, the Priceline group spent $2.8bn last year on online marketing, and Amazon spent $3.8bn. Unless customers visit the platform for something else (e.g. content, reviews, photos, and sharing) and then naturally move into the transaction flow, it is very hard to drive high re-engagement rates for commerce platforms. And that’s exactly what makes it easy for us at Zomato – our classifieds business, where we have 8.5 million monthly uniques in India alone. And so far, less than 3% of them are ordering from us. There’s massive room to grow before we think of paying big $$$s for marketing.
Fixed Cost
Sales teams, engineering teams, analytics and business teams. This cost stays fairly the same over time if you are adequately staffed here. Over time, the total net contribution margin should become more than the fixed cost, which will give you…
Profit.
This might have needed explaining in 2015. Not anymore.
We came across a Facebook post from a long-time user of Zomato who, after gaining adequate popularity and trust as a reviewer on Zomato, started offering positive reviews as a service to restaurants.
Typically, we don’t react to people who slander Zomato and claim we resort to unfair practices to make money. But we are reacting today, because we’ve received calls from the media about covering this incident, and that puts everything we do to maintain the sanctity of Zomato in a bad light.
As they say, a lie can travel halfway around the world while the truth is putting on its shoes.
We deleted this user’s profile because our neutrality team had proof that this user was resorting to unfair practices. Here are screenshots of the conversation between the user and a restaurant owner.
They were sent to us by the owner of the restaurant – one of the most honest business owners we have worked with (and believe us, that isn’t always the case).
In his post, the user is clearly telling the restaurant that he will write a positive review for the place. This means the review was going to be biased. As a result, we cannot trust any of this user’s reviews, and cannot let our vast community of users read or trust any of his reviews either. With that in mind, we decided to delete Prateek’s profile.
As we always do when removing a profile, we sent an email to Prateek, telling him why we were going to delete his profile –
Despite this, Prateek says in his Facebook post that we never informed him about his profile being deleted.
It pains us to see this post, mostly because of the glaring gaps and false accusations in his story. For the benefit of everyone who refers to – and trusts – reviews on Zomato, we’d like to clarify a few things anyway. We’ll address each point he makes in his post individually.
“A new restaurant (is about to open up or) opens up in a locality. Either it approaches Zomato, or Zomato approaches it for enlisting on the portal.”
This is true. Restaurants pay nothing to be listed on Zomato.
“Zomato’s Area Sales/Marketing Manager pays the restaurant a visit. Asks the owner/manager if they’d want a good rating & reviews for the restaurant since it drives business in return. Most of us do refer to Zomato to look for the ‘best restaurants’ in a particular area, so it makes sense for a restaurant to be there.”
We have a content/data collection team that collects and lists restaurant information. If a Sales Manager visits a restaurant, it’s because a new restaurant is a potential advertiser (for the banner ads you see on Zomato). The code of ethics for our sales team does not let them talk about reviews to a potential advertiser, and we maniacally enforce this policy. Even a benefit of doubt here is always given to the organisation, and not to the sales person.
“If the restaurant owner is financially well-off, he gives in to Zomato’s monopoly and pays up to get “good ratings”.
Restaurants cannot pay for a rating under any circumstances (unless, of course, they’re paying users who are resorting to unfair practices). We have enough eyes and ears out there to manage the menace.
“Now, Zomato’s “verified reviewers” (you know the ones with blue & white stars on their DPs) come into picture here. Zomato invites these guys to do review under the pretext of “Zomato Meetups” or whatever godforsaken name. These guys eat to their heart’s content for free, and subsequently reward the restaurant with high ratings and positive reviews.”
Meetups are our community engagement activities where we invite Zomato reviewers – having a Verified profile is not a prerequisite for this – for a meal at a restaurant. Yes, the restaurant hosts these meetups, and users do not pay for their meals. However, whether or not these users write reviews (let alone positive ones) is entirely up to the users themselves. It is made very clear to restaurants that this is an exposure opportunity for them among regular users, and that they are not allowed to ask for reviews.
“Also, by the way, Zomato’s uses its own (corrupt) “algorithm” to rate restaurants. The ratings are not simply calculated as “No. of Ratings divided by No. of Users,” Zomato provides its own ratings to most restaurants (based on the deal it strikes with them.)”
A restaurant’s rating is based on the ratings it gets from users. Zomato does not provide its own ratings to restaurants, because that would inherently violate the neutrality of Zomato as a platform – more on this soon. Prateek is right when he says that ratings are not absolute (# of ratings divided by # of users). Ratings on Zomato factor in the credibility and trust a user has built with us over time, and are then spread on a normalised distribution curve; you can read about it in detail here on our blog: http://blog.zomato.com/post/114022437961/simplifying-ratings-for-a-better-dining-experience
“Now, thanks to Zomato’s “rating” and credibility thanks to the reviews by Zomato Verified Reviewers, the restaurant starts attracting customers and business becomes good. Until, after a while, Zomato pays them a visit again.”
A restaurant will attract new customers if it offers a great dining experience. Simple. Zomato acts as a discovery platform for these restaurants, and reviews written by Zomato users help others decide where to eat.
“Why did they delete my account? Because I was doing reviews independently, and not as a Zomato Verified Reviewer. Restaurants would directly invite me over for free meals (thanks to my good following on Zomato & Instagram) and I would in turn honestly review their restaurants on the Zomato app. Zomato obviously gets a whiff of it.”
Anyone is welcome to review restaurants independently. It doesn’t matter whether one is a Verified reviewer or not. The problem arises when one starts offering positive reviews on Zomato as a service – which was the case here. We got to know of it because restaurants Prateek wrote to sent us screengrabs of his conversations with them, which we have attached above as proof.
“Now, since my reviewing doesn’t reap any monetary benefits for Zomato, it decides to delete my account instantly without ever once notifying me. A bad example, but it’s a case of a big shark eating up a smaller one to get bigger and for future profits.”
Reviews definitely add value to Zomato, but we expect them to be fair and neutral for them to be useful to other users. If you are approaching restaurants offering positive reviews in exchange for free meals, that is in direct violation of our review guidelines and policies. This has got nothing to do with monetary benefits. It has got everything to do with honesty and trust.
“On the day Zomato deleted my account, I had 6,000+ followers and 250+ reviews. It felt as if I had lost a huge part of the work I had accumulated over the last 2 years. I was an absolute Zomato lover as well as an evangelist; probably that was another reason why kept mum about this.”
Deleting a profile is something we don’t love doing, especially when we know a considerable amount of effort has gone into building it. But when we know that someone is resorting to unfair means, we will do everything to maintain the sanctity and trust of the platform we have worked hard to build over the last 8 years.
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That’s all and more than what we have to say about this. We are a responsible platform, and will continue to be so – at any cost.
“In God we trust. All others must bring data.” – Captain Glimmergut
A few days ago, Tony Stark was looking at a restaurant page on the Zomato app, and he exclaimed –
“There
are so many buttons on this page. What do you want me to do? Should I
write a review? Or upload a photo? Or should I check-in? Or mark this as
been there (oh wait, have I been there)? How is that different from a
check-in? This sucks. I’m leaving. Jarvis, can you please figure this
out for me?”
Our data scientist, the caped superhero, ranted –
“Tony,
you’re too used to making Jarvis do everything for you. And most things
suck for you anyway. You suck too, I’m way cooler than you. I feel we
should cut the number of actions on a restaurant page down to what
matters and what works. My gut tells me people do loads of check-ins
(because it’s easy, and everyone likes to show off where they’re
eating), and upload lots of photos, but don’t write many reviews.
Reviewing a restaurant is fucking hard. But I’m being stupid. I think
I’m losing my superhero ability of using data to beat Jarvis. I’m going
to go look at the data and see what our users actually do and don’t do,
before I choose to do or not do something.”
Here’s what our data
scientist, who gave himself a new name – “Captain Glimmergut” – has to
say about the revelations he’s had from looking at the data.
“In
the past week, 9k users checked in on Zomato, and made a total of 16k
check-ins across the world. In the same week, 32k users wrote more than
60k reviews. Whoa. That’s a million reviews every four months! And we
haven’t even started pushing our leaderboards. In the same week, 20k
users uploaded 170k photos. That’s more valuable than f**king Jarvis!
170k photos! I think our next target should be Pinstagram. They also
changed their logo to some rainbow-coloured disaster last week. I think
we have a good window of opportunity.
Hold on. So people write 4 times more reviews on Zomato than they check-in? And that is in spite of
our marketing teams and sales teams actively working on pushing
check-in campaigns. Wow. That’s a lot of work for very little outcome.
Maybe we should focus on what our users already do, or want to do. Like
uploading beautiful photos on Zomato. To do that though, I agree that we
will have to improve our photo uploads on the app, and the quality of
our filters. But anyway, let’s actually push photos. And reviews. Let’s push stuff that actually moves stuff. F**k check-ins.
Product team, can you please kill check-ins from our next app update?”
Product
team – “Done. We trust God, but you gave us data. Doing this for our
new iOS app today, other platforms shall be done soon. We’ll move all
our users’ check-ins to their ‘been there’ list along the way. High-fives
for giving Tony one less thing to whine about.”
An HSBC analyst report marked down our valuation from $1b to $500m. For starters, this is very different from all the markdowns so far where investors have marked down their own investments. But given all the media reports, I got a lot of questions from people at Zomato about what’s going on. Here’s an email I sent to everybody at Zomato (2100 people currently across the world) to allay their concerns and answer their questions. Read on.
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Hello all,
You must have woken up today to Google Alerts with mentions of Zomato’s valuation being marked down by HSBC. As you already know, the media is all over it, and we are trending on Twitter.
Since the report isn’t public, and we all get troubled by where we are and where we are heading, here’s some context and detail around the HSBC report.
Overall statements in the report
In the report, it clearly says – “Why do we differ from consensus?”. That means that this report is an outlier, and there are enough analysts, VCs, and founders out there who have called us “the only defensible Indian unicorn”, and have said “there’s multiples more inherent value in Zomato” about us.
The report claims that we have low market share. Our internal data shows that we drove a large percentage (>50%) of business to some of the biggest restaurant names in the country. Our traffic in India, our home market, also grew 8% in April 2016 over March 2016. We have over 8.5 million monthly uniques in India alone – very few Indian companies can claim that much traffic share in a single category. Also, we are currently present in 23 countries, and we are the market leaders in 18 of them.
Our food ordering business
It claims that we need to heavily invest in building last mile logistics on our own, and win in the order business to defend our advertising business. Now, delivery is a small part of our advertising business. Most of our ad revenue comes from the dining out and nightlife categories. Our search and discovery business is a big funnel for our transaction businesses though. We are able to divert traffic to transactions businesses (ordering, and table reservations) without any additional customer acquisition cost – a unique advantage that cannot be contested. At present, ~3% of our monthly unique customers are ordering on Zomato, so the room for growth within our existing user base is massive.
It also claims that we will need to invest in our own last mile logistics to hit profitability in online food ordering. We already know that the unit economics of owning a food delivery fleet can never work out.
To give you a little perspective on where we are at, we hit 33,000 online orders yesterday – at our average order values, it makes us the largest player (and only profitable players on a unit economics level) by GMV (there’s a blog post coming soon about our food ordering economics). We already are profitable in the order business at a unit economics level, and the overall online ordering business will hit profitability when we get to an average of 40,000 orders a day. We should get there in the next 3-6 months. Also, there isn’t any food delivery company in the world which owns its last mile logistics fleet, operates at scale, and is profitable. These assumptions and statements in the HSBC report make it look like they’re coming from someone who doesn’t – and hasn’t bothered to – understand the space well.
US operations
It claims that the US is an overcrowded market, and we will not be able to make inroads into the US. HSBC, because it never spoke to us, doesn’t know that we didn’t acquire Urbanspoon for its US presence. We acquired it for Australia and Canada, and our traffic is kicking ass in these two markets. We are monetising the traffic in Australia already, and Melbourne and Sydney are already in the top 5 revenue generating cities for us across the world.
Ad sales profitability
It says that we will need to build sales teams in a lot of countries going forward, and it will increase costs. However, all our countries already have large sales teams, which don’t need to grow any time over the next 12-14 months.
It says that ad sales based models in the US haven’t been able to scale and grow significantly. True. But Yelp, our largest counterpart in the US, is showing extremely positive signs on great sales execution – the last quarter’s results have been great, and their stock is up ~75%. On that note, we have significantly healthier margins in our ad sales business than pretty much anyone most people know. Case in point, Japanese companies – Hotpepper, Tabelog, Gurunavi are very large businesses in our space operating solely in Japan, and churn out hyper profitability in just the ad sales business. Even The Economist called our business model one with “mouth watering margins” in an article about us last month.
I have more to add here. Our revenue has doubled over the past 9 months. Costs have been rationalised. Burn is down 70% from the peak – it was high because we were experimenting with various business models and geographies, which we have cut down drastically – and we are now focused on the large opportunity in front of us in our core business and core markets. We do not need to raise another round of funding to sustain the business, or steer it to profitability. The advertising model has huge headroom for growth. More than 95% of the restaurants in our core markets have yet to be monetised. Mobile, which is over 50% of our traffic, is yet to be monetised seriously – the new product which will be out before the end of the May will completely change the face of mobile app monetisation for us. Fifteen out of the eighteen countries where we are traffic leaders are yet to see serious monetisation efforts. Apart from this, there is humongous scope for growth through increase in revenue per client, and retention rates.
Overall profitability
The report then goes on to say that it is unlikely we will hit profitability in our markets in the near term. But we already have, and we made an announcement when it happened. An example for you in real numbers – the Philippines. Our revenue in the Philippines is 1.5x of the total cost of the operation. When I say “total cost of operation”, I literally mean cashflow. And our Philippines team is using its profits to charge its growth going forward. We are aiming to hit overall profitability (without compromising on growth) at an overall company level in the next 6-12 months – depending on how well we execute in the near future. And we will re-invest those profits in our business to grow further, and faster.
Also, my thoughts on valuations – nobody who knows our business has marked down our valuations. In fact, our existing investors are bullish about us, and are willing to back us further, if needed. And they have categorically said that our valuations are justified. Especially because we are more than doubling year on year, and the next year looks even more exciting for us. But external perceptions of valuations are determined by the state of the market, and the availability of facts to the person who is analysing these numbers.
Having said that, we have a lot of work to do to justify the faith (not the valuation) our investors have put in us. We need to continue producing high quality work, innovate on our product, build and scale our new businesses to a point where they become meaningfully large and highly profitable contributors to our overall business.
The Economist in its coverage on us also says – “India has surprisingly few brands that are recognised abroad….consumer marques from India ring few bells internationally. Newcomers in its ebullient startup scene are mostly focused on the 1.3 billion-strong home market. So Zomato … counts as an exception.”
No pressure. There’s that much more to live up to, and win.
There’s something that we say often – “we are only 1% done”. We are truly 1% done, and if we continue to focus on execution, the noise will die down very soon.
We recently shared some of our learnings from our online ordering business. This post takes a step further back, and looks at how we rewired our DNA from that of a media content/media business to that of a transactions business.
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We’ve been in the content business for what feels like aeons now. And while it comes with its own unique challenges, the content business is quite different from the transactions business. The content business comes with small allowances for errors. You get more chances to experiment and make mistakes, and you can afford to take a two-day break to focus on something else if you need to, without things falling apart. The transactions business, however, is a completely different animal. If you take your eye off it for a minute, things can get out of hand very quickly.
Most of our transactions business had to be built from scratch, and needed a tectonic shift in how we thought about and approached our business. Moving Zomato from a predominantly content/media DNA to that of transactions was easier said than done – more so because we needed to find a way for both these parts to coexist as part of our global business and product.
Here are the three simple (and at the same time radical) things we did to build the DNA of our transaction business, from the ground up –
We put together a solid (and mostly new) team.
It’s no secret – finding the right people is half the battle won. Given the razor-sharp focus and intense effort the online ordering business needs, we assembled an independent team dedicated to kickstarting and growing it. We put together a crack team of engineers, product managers, and designers to give the product shape, and used that as a foundation to build on top of.
A few months down the line, we had Pankaj, our co-founder take over the business to drive things even faster. With his deep understanding of Zomato as a product, and a data-driven approach to business, we have been able to significantly grow order volumes, improve our retention cohorts, customer support and satisfaction, as well as market the order business in a cost-effective way.
We built a standalone app to begin with.
Rolling out an independent app for online ordering – Zomato Order – was the first time we ever unbundled an app for a specific feature instead of integrating it into the main Zomato app. Doing this helped us quickly learn our way around an entirely new business, make the mistakes we needed to, and fix them quickly. It also meant our engineering teams could work on independent development and release cycles, which allowed us to keep testing and tweaking without having to ship heavy updates too often. Once we knew our tech for it was stable, Zomato Order became an SDK we could bake seamlessly into the main Zomato app with relatively little effort.
We moved the Order team to a separate floor in our office.
While the end customer being served is likely the same, our Content and Transaction businesses have very specific – and distinct – things to focus on. To ensure our still-growing Transactions team wasn’t distracted by any of the Content business’ priorities, we separated the two teams and moved them to independent floors. In fact, they even ate lunch separately so they could continue thinking and exchanging notes about what they were working on while they ate, as our teams usually do. Bringing in and maintaining single-minded focus takes a little extra discipline, but the long-term upside is more than worth it, especially in a business with very narrow margins for error.
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Today, we’re processing ~28,000 orders a day across India and UAE – our two primary focus markets for online ordering. And while our advertising business still accounts for the lion’s share of our revenue, our online ordering business is rapidly gaining significant share.
In our next post, coming up in a few days, we look at The Unit Economics of Food Delivery in India and UAE.
Life at DTU 