Meal-Kit Leader HelloFresh Used Data Analytics to Dominate the Industry
Just amassing data doesn’t mean you are using it to grow your business
Starting in 2007 in Sweden, the meal-kit business was a good idea that was limited by Internet 1.0 and logistics. The promise, however, was real. By 2015, Blue Apron was the “pioneer of the meal-kit industry in the United States” and the darling of VCs and tech investors.
Initially raising $135 million, the sky seemed the limit. Led by a team of experienced investors and entrepreneurs, it would not be an exaggeration to say that Blue Apron created the multi-billion dollar meal-kit industry.
Fast-forward to 2023, Blue Apron is still a relatively strong company with sales a little shy of $500 million in 2022, but it’s the German company, HelloFresh (HF), that repurposed the way it used its data, permitting it to surge to industry dominance and grow to be ten times the size of Blue Apron in a few short years. Now the king of the meal-kit industry, sales for HelloFresh in 2022 were 7.6 billion euros.
Simply put, HF decided that the data would be used to retain customers rather than endlessly acquire more.
HelloFresh Created a ‘Data Culture’ to Better Retain Customers
Finding customers is difficult; retaining them is even more challenging. When customers choose your product line, the competition tirelessly takes them from you. Customer retention, a much more varied and complex process than customer acquisition, requires a data strategy focusing more on predicting what your current customers will want and less on trying to appease the whims and caprice of customers ever hunting for a better deal.
The meal-kit business revolves around selling and delivering pre-packaged meal boxes. Inside each box, the customer expects to find all of the ingredients required to make their meal of choice: fresh produce, meat, dairy, and everything must be precisely measured out. Somehow, HF, after defocusing on customer acquisition and focusing on retention, managed to master the logistics behind this troublesome product offering. The key to success in this business is freshness, giving consumers what they want, and on-time delivery.
Like any company, HF amasses tremendous amounts of information. But unlike in many companies, that information does not sit idle. It gets absorbed and turned into better menu offerings. As the Senior Director of Operations at HelloFresh, Adam Kalikow, put it:
“We all need to obsess about how to continue pulling high-quality talent into this industry, into the supply chain, to be able to leverage this wealth of data.”
To this end, HelloFresh works to cultivate a “data culture” throughout its organization, with the help of high-level talent capable of translating analytics and insight into a better experience for the customers ((How HelloFresh Is Using Data to Make a Better Customer Experience).
HF mastered this approach while Blue Apron tinkered. HF focused on data gathered from operations and used that for robust menu creation, considering what customers want today, tomorrow, and in a few years. While Blue Apron was chasing new customers, HF was focused on improving delivery to existing customers and simplifying its menus.
Frank Sanni, a fractional CMO and marketing consultant, told CMSWire that the customer experience is enhanced by offering the right product to the right person at the right time. “This takes many forms. For example, a retailer may offer a mother a new educational item for her child, or a bank may offer a lower interest rate to a high-value customer,” said Sanni. “A company may offer enhanced service to a customer who may be at risk of leaving the brand. A bookseller may offer the next logical volume to a customer who has been reading a series of novels.” Sanni said that all of these examples are done via computer modeling that looks at transaction history and uses predictive modeling to recommend the right offer at the right time (Using Predictive Analytics).
Blue Apron was amassing similar data to HF, but it was more focused on understanding why its customers chose a competitor and how to get them to switch. This difference is arguably one of the primary reasons HelloFresh dominates the industry today, and Blue Apron is a case of “what went wrong.”
The Data River
In many ways, HelloFresh is not a meal-kit industry but a tech company. Its internal tech team at 1000-strong, called HelloTech, is one of the most honed teams in data analytics in business today. While most companies can’t employ HF’s aggressive approach — hiring ten analysts is challenging enough — it does not mean that the company’s lacking such resources also shouldn’t be obsessed with how better to exploit the data they are accumulating.
HF understood that if it was going to dethrone the then-market leader Blue Apron, it would need to build its marketing strategy not so much around the short-term desire to get something for free but to look long-term and create popular menus that people were willing to pay for. Let the customers come to the menus and not the menu to the customer. HF made the recipe the driver of operations, and all the data flowed downstream from this creation process.
During the production of our meal kits data plays an important role in every stage of the process. Similar to a river the flow of data starts with a spring (the recipe creation) and after many currents and bends reaches the customer, with each stage having a significant downstream effect. When producing a meal kit there are multiple different stages where data gets generated, processed and used (The Data River).
During the first stage of development, the accumulated data is used to create new recipes. This process never stops. The data is analyzed and gleaned from the most important information for ensuring a satisfactory experience with the prepared meal. HF offers a very varied but, at the same time, predictable menu that permits both culinary exploration and the security offered by a favorite meal. Of course, HF didn’t invent this approach but has managed to massage it into lower operating costs.
Using historical recipe data (including data from existing recipes, operating costs, and customer satisfaction scores), new ideas are constantly being tried, taking into consideration seasonal nuances. HF has developed a library of 14,000 recipes worldwide, and all of them have been “data-tested.” If a menu does not hit certain criteria for success, it gets booted from the system.
However, the process of creating the ideal menu does not rest on its “plate (pun intended).”
A couple of months before a certain delivery week, the menu planning starts. The recipes are curated into a menu of between 18 and 45 recipes (depending on the market). The menu creation is powered by HelloFresh-developed algorithms, which strike a perfect balance between maintaining and increasing customer satisfaction (measured in recipe scores), lowering ingredient costs and maintaining diversity in our menu offering. Over the years, our tech-team has refined these algorithms to constantly lower procurement costs for HelloFresh while increasing customer satisfaction at the same time.
Thanks to the large team of data analysts and marketers at HF, creating the menu and then “sale” does not end the process of “data crushing.” The moment a new menu hits the HF site, team leaders can see how accurate their analyses are by tracking the sales.
While it may seem like the supply and demand process here is a standard in any company, and it is, however, in the meal-kit industry, whose success is both determined by freshness and precision of the menu, anything a customer does not like — and doubt in the ordering process (orders can be changed up to four days before delivery) — hits that the margins. Operating costs increase, and profit decreases.
The precision of the forecast is so important, and our algorithms are constantly refined. While our customers take just a few minutes to choose their recipes, in the backend, we combine their choices, their subscription data (how many active customers there are in a given week), and the delivery data (where and when do orders get shipped). At the end of this step, we know exactly how many boxes were ordered, how many meals, and how many add-ons were included. This data gets forwarded to production, where boxes are packed in one of our production facilities around the globe (The Data River).
The Last Mile Takes HF Back to the Menu Creation
After all is packed and ready to go, the value chain works to get the finished boxes to the customers. The moment that package leaves the hands of the producer, in this case HF, the waiting game begins. The customer is waiting for her purchase, and the company waits to hear that all went off without any hiccups.
In HF’s case, the company is constantly updating customers on the whereabouts of their delivery and its expected time. Customers are finally asked to rate the recipes they receive. The feedback and the historical order data get fed into the databases, and the production process begins anew with the recipe creation.
Of course, the early menus after HF’s initial launch were more customer-driven and culled in a hit-or-miss fashion. However, as the company grew and the data was accumulated, HF realized that it was easier to manipulate the data it was receiving to build a strong foundation around the menus rather than trying to predict the personalities of the ever-changing customer base. Customers come and go; they jump from competitor to competitor, looking for discounts and freebies. By building its foundation on its ever-evolving, customer-centric menus, HF pushed aside all major players.
Blue Apron, some have suggested, was addicted to customer acquisition. The company focused its success metrics on new customers because this also made the investors smile. It fits nicely into a pitch deck, and people get it. Blue Apron became the trailblazer for the industry, showing other companies how to deal with these ever-changing needs of the meal-kit customer base. Focusing its data analytics on customer acquisition, Blue Apron disregarded the data that showed that retention was going to be the path to success because everyone was on the hunt for the big funding ticket — and the IPO.
Brand loyalty in the meal-kit industry is low, so whoever has the best offer or menu will be the company of choice for the moment. The churn rate for Blue Apron was 70 percent. When HF saw this happening in 2018, it reworked its data strategy to focus on retention, and it learned that customers might try other companies occasionally. Still, if they can land on a mix of menus and products they like and — most importantly can expect to find time after time — they will stay with the company for the long term.
From 2018 onward, HF began focusing on retention, and Blue Apron continued to chase new customer acquisition.
“I used Blue Apron since I was getting $20 off 3 boxes. As soon as I stopped getting it, I canceled, and within a week, I got emailed another promo code to come back for two weeks. Did that and cancelled again, and now I have another promo code that is good for another 3 weeks.
I’m basically just paying $40 cause, at that price, it’s worth it with no intention of ever paying the full $60. How the heck is this company still in business (A Solution to Blue Apron’ Retention Problem)”
Once HF reordered how it exploited its data, focusing more on how to build existing customer satisfaction and drive more profit from them, Blue Apron’s days were numbered. Stuck in the “raising money” mindset, Blue Apron struggled to adapt to a retention strategy. By 2019, customers expressed more satisfaction with HF than Blue Apron.
The research firm asked respondents if they hold an overall positive or negative impression of a particular brand. Since January 2018, HelloFresh’s impression score climbed from 15 to 18. Blue Apron’s has decreased from 15 to 13. In addition, HelloFresh’s satisfaction score recently reached a peak of 26 while Blue Apron has yet to hit a score of 18 this year (HelloFresh Tops Blue Apron).
This inability to create and retain a loyal customer base prevented Blue Apron from making a profit. While it may seem like a pretty straightforward business axiom, subscription-based companies need to focus on retention and not endless acquisition.
While it should be noted that all meal-kit companies struggle with low retention rates, HF’s focus on creating a predictable menu and acquisitions of smaller players has helped it overcome some of the problems other companies face. HF was also able to keep its customer acquisition costs lower than other companies.
According to Adam Kalikow, Senior Director of Operations at HelloFresh, “Because of the business model and the data we collect from our customers, we’re able to demand forecast a lot more effectively than a typical retail or e-commerce store selling food. Over time, we’ve been able to build up a ton of data… and develop internal proprietary algorithms that we can apply to improve that forecasting (How HelloFresh Is Using Data to Make a Better Customer Experience).”
It is a simple lesson.
Where most companies cannot hire a team of 10, 100, or even 1,000 data analysts, many are trying to do precisely what HelloFresh’s tech team, HelloTech, does — master their data. If you are sitting around wondering if you are getting the most out of your data, then the chances are you aren’t.
