How HelloFresh Uses Big Data to Cook Up Delicious Home Dining Experiences
Big data is a major driving force in almost every industry on the planet in 2018, and meal box delivery service HelloFresh is using it to cook up some great home dining experiences for their customers.
Berlin-based HelloFresh was founded by Dominik Richter, Jessica Nilsson, and Thomas Griesel in 2011 with the financial assistance of startup incubator Rocket Internet. The HelloFresh business model revolves around selling and delivering pre-packed meal boxes. These boxes each contain the exact ingredients needed to make a particular meal, including fresh produce, meat, dairy, and pre-measured seasoning. The meal kit is then rounded off with full illustrated instructions on how to prepare the meal with the ingredients provided.
Today, HelloFresh operates all over Europe and the US, and employs over 2,000 people. The company is valuated at over $2.9 billion and holds the #49 spot on the Fortune Unicorn List.
HelloFresh has millions of customers, all over the world, and therefore has access to vast quantities of data which it can use to make sure the right information is being put in front of the right people - at the right time. This data application, combined with leveraging the power of Google Keyword Planner, ranges from predicting which foods are likely to be popular at certain times of year, to creating unique food and ingredient combinations.
For example, during the Christmas period, HelloFresh may see an increase in searches for recipies involving turkey, ham, or sweet potatoes. It can then use this information to flexibly adjust offers and promotions. However, the data can also be used for less general applications. For example, a customer's account data may reveal they regularly eat fish on a Friday, and so will be targeted with bespoke appropriate offers in time for that day. The data can also be used to analyze food trends on a nationwide scale to drive offers.
"November sees searches for turkey- and pumpkin-related recipes increase due to Thanksgiving, for example, so HelloFresh can alter its offering in the US to reflect that ahead of time," said Karl Villanueva, Head of Paid Search and Display at HelloFresh. "It's not something you just have an idea of, you can back it up with data on how many people are looking for these ingredients at this time, so it provides a seasonality score. If Pho is trending in the United States, that gives an indicator that's a recipe that people might be interested in because they're eating it in a restaurant but might like to learn how to cook it at home."
Not content with promoting established and popular recipies, whether seasonal or trending, HelloFresh is also looking to use data to find ways for people to try new flavor profiles they may not have previously considered.
This would normally be carried out in a kitchen by chefs, who may spark off new industry trends when they hit on an unusual yet delicious food pairing. However, HelloFresh wants to do this itself by using data to combine what it already knows about how certain flavors go together to procedurally generate new, interesting and (hopefully) delicious recipe ideas for HelloFresh customers.
"You could really look at the chemical properties of food," says Villanueva. "It's something that's easy to do if you have a few pairings, take their flavor profiles, then try to figure out which flavors work well together. But, you can't try and mix everything in a massive kitchen. You want to take it scientifically and say, based on our data, that we know these go well, so which other flavors can we find that will work as well? We're essentially able to provide new food pairings that people may not have thought of by themselves, so we can push the boundaries of which dishes and ingredients pair well together."
Big data has many applications for companies in practically every field. HelloFresh is using its data to not only target trending food to the right people, but also try and set a few new trends at the same time.
The final word goes to Karl Villanueva.
"The end goal is to change the way people cook. There's a large rediscovering cooking element there that we find very interesting. Data about [customer] preferences is at the core of company operations."
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