Imagine you have a supermarket. What would you give to know exactly what is going to be bought say next Friday at 18:00? Or perhaps how the recent MasterChef Australia’s TV program, where they made pancakes, will affect your milk and flour sales tomorrow? Better yet, what if you could know exactly what the best time to start your spaghetti marketing campaign is?
These and many other questions is what the Helsinki based startup, Avansera, is attempting to answer, while going head-to-head with top industry analysis companies.
Talking to Cormac Walsh, the CEO of Avansera, makes one understand the intricacies of the industry and how backward it seems to be. One of the examples Walsh provided was that at the moment most analytics that fast moving consumer goods (FMCG) stores get are in form of huge tables that you have to spend countless hours analysing to make any sense of.
Who does it? Well, almost nobody. Walsh tells us that it is common practice that a budget for such reports is set by the managers, so you kinda have to buy them. The problem is – getting any real answers that you can immediately act upon.
So instead of providing these managers with countless tables, one needs to give them well analyzed answers and clear actions. As Walsh put it: “We do not want to be insulting, we just know that they have no time. We need to cut away the 99.9% of big data and deliver a 0.01% of it.”
To get this data, Avansera is using their product – Ostosnero, which is a smart grocery shopping list. This means that when people, right after watching MasterChef Australia, start adding milk and flour to their shopping lists, and Avansera can analyze the change in the quantity of flour and milk compared to an average day.
They also know when people go shopping, since they use the app to check things off once in the shop. This allows them to predict, to a good degree of accuracy, how much milk and flour will be bought say next Friday at 18:30.
Yes, you still need quite a few users to make it accurate, but probably a lot less than you think. Statisticians can estimate the amount of minimum data points needed and in this particular case it is about 3 000. So with just 3 000 people, Avansera would be able to predict all of the above extremely accurately.
In the process, no personal data is collected, they do not even need to know your sex or age, as all of that can be deduced from your behaviour. In fact, everything can be deduced from it and that might be a little scary – the power of big data.
With this approach, Avansera can really stick it to the current players in the market as they usually need to collect the data using good old questionnaires. The industry standard is 5 000 respondents so if you want to find out something very specific like “Do buyers in a particular target market prefer strawberry yoghurt or a vanilla one?”
To answer that, the current procedure involves finding 5 000 people, meet them, ask them a bunch of questions and compile the answers. You can probably imagine how many man hours it takes just to get the answers, not counting the data input, the analysis, etc. With Avansera – this is almost free, allowing them to gather and sell the information at a fraction of the cost. Not to mention other problems with current methods of data collection, such as the “Observer Effect”.
Currently, they already have over 500 users on Ostosnero. However the idea is to push hard on marketing and achieve the benchmark number of 5000 people. It helps that in addition to Ostosnero, Avansera can gather data online, from retailers or even from other apps that are providing a similar grocery shopping list apps.
So this can decrease the overstock, prevent undersupply and when you start adding a lot of other data into the mix such as calorie counts, weight – a lot more.
Avansera has previously received an investment from Reaktor Polte and was recognized by the Code_n competition, being the only finalist from Finland.
Top Image Courtesy of Shutterstock // Supermarket
