As most of you know by now, in October we launched Foody a food ordering & delivery startup.
This is the 2nd major launch of our team after AtYourService and I now understand what all the fuss is about second time founders :)
I do not have words (maybe that comes with your 3rd startup) to describe how much better our work is in terms of quality and efficiency.
Now as you probably know, I am kinda of an Analytic nut.
The fact that food delivery is a very competitive market (at least 7 serious competitors) means it’s a great opportunity for me to go wild with my Analysis (yayyyy).
In the past I wasn’t sure if I should write such a transparent blog.
I say that because I will actually reveal stuff that gives us a competitive advantage, but at the same time we have such a strong culture of sharing, and not doing so would go against that.
So here I am sharing some of the competitive analysis we do (obviously can’t share everything, but hope I `ll be able to share more and more in the future).
Before I jump right in, i`d like to clearly state the following:
Monitoring the Market (especially in a tiny Market like Cyprus) is not easy and definitely not an exact science.
The data is not bullet proof and we know it.
This is true every time you do analytics with limited data, or every time you do analytics in a small market
My data is wrong.
Nevertheless, it’s better to have an estimation than not to.
At the same time, we constantly try to compare these numbers with numbers we get from other sources and all data we receive actually show we have a larger market share.
So I guess it’s time to make my first big claim!
Foody currently has about 63% of the Food ordering Market.
Let me tell you how I got that result
In order to monitor the Market I use 3 tools:
Tool #1 Google Keyword planner
I use the number of searches of the exact name of each competitor as an approximation of its traffic.
Why is this a good Metric
Google searches in general is a very good metric as a lot of returning users use search to find the website, i.e. write foody instead of the address and click on the first link.
It’s the only metric out of the 3 that cannot be manipulated, as it’s based on Google’s data on all internet searches, and not a tool that extrapolates based on a small number of users.
For each website I used 5 or 6 search terms — depending on their name.
Here is the raw list Avg monthly search for the months of November and December.
This information is public and you can confirm it in 2 minutes using the Google AdWords planner
The numbers paint a picture, but to make sense I have grouped them for each brand, and calculated the percentage of the total.
Tool #2 Alexa
Alexa provides a ranking for each website. It is the most widely used metric in Cyprus. I don’t like it very much because it can be manipulated up to a point, but it’s still a proxy of real use.
Alexa provides ranking, so to turn that into a market share, I assumed that if Competitor A is positioned at point 100 he has double the traffic from someone that is positioned at point 200.
This is not necessarily true, those differences are bigger near the top and smaller near the bottom but on average its a decent approximation:
Tool #3 SimilarWeb
I think similarweb is a great tool in larger markets (was very useful when we were monitoring Greece for AtYourService) but in Cyprus it’s a bit limited.
From our own experience, we can state that our actual traffic is multiple times higher than what mentioned. Nevertheless, it’s estimates are getting better with time
On the positive site, it’s the only monitoring tool that has bounce rate and time on page which are extremely valuable.
Tool #4 Mobile App data from App Stores
In my previous analysis I did not include mobile app data. The reason for doing that is that not all competitors have a mobile app but mentioning it in our footnotes as being something that needs to be included.
Every competitor has a mobile site, and the results of the mobile site are shown in the previous metrics which ignore customers through apps.
We ehm believe (or maybe know is a better word) that a very good percentage of orders come from mobile apps as they are mostly used by repeat customers.
To calculate the share of each competitor we use a basket of the following 4 metrics. Total Downloads (Android, IOS) Total Stars received(Android,IOS)
So the data look a little bit like this
And when we try to convert it into something more meaningful, we get this
I seriously doubt that anyone is still reading, but if you still are, all i can say is wow! :)
So what happens when we put all the data together?
I think that when you put the data together they tell a pretty consistent story, even with all their limitations.
Are these data air tight? Of course not — there will always be objections.
Of course, we always verify the data using different mechanisms (unfortunately can’t share more on how we do it) and data from other directions shows we have about 70% of the Market.
This is both good and bad.
Our goal (which we have outperformed every single month to date) is to achieve an additional growth of 500% till the end of the year.
The data clearly shows that this growth can only come by growing the total market — and that’s exactly what we plan to do :)
As a final note I would like to say that I would appreciate feedback from anyone — fellow analyst nuts, competitors who have a different opinion, interested on-lookers, as this can only help us improve.