Do you know the real importance of Big Data in the Food Industry? Knowing your audience is important, even fundamental for any kind of business. In this article we will analyze the best practices and the best data-driven strategies (marketing, but not only) for the food industry. Food and Beverage is a large and complex sector that embraces a number of very different players, some of whom are interconnected. The ecosystem includes both small producers and large multinational brands, players who cater to everyone and those who target a specific niche; then there are the distributors, clubs, restaurants both small and large, and retail chains.
Can we identify a lowest common denominator that concerns all aspects of this sector? The answer is, yes. It is this: all sides of the Food and Beverage Industry have a strong impact on the lives of individuals. They are therefore very delicate, and subject to a high rate of variability. And, they are unpredictable.
After all, this is something that affects almost all sectors, but in the food industry the impact of the individual is really central. Translated: This makes understanding the audience in the most precise, in-depth, and functional way, an absolutely urgent manner for brands, restaurants, store managers and marketers in general. Knowing one’s audience is one of the oldest mechanisms of commerce and advertising. In this case, however, we are talking about a potentially immense audience of customers.
How is it possible to track such an audience, to “know it”? Can it be done? Yes. Thanks to digital, and by putting the most advanced tools to work, brands can have an in-depth knowledge of their audience. In concrete terms, we are talking about the analysis of Big Data, the digital traces that we all leave online. Starting from this analysis, we have to build a data-driven marketing strategy. There is no strategy and tools that are valid for everyone. It is a matter of applying these technologies in a way that is intelligent, precise and, above all, functional to one’s own processes and goals. Here, the goal is to address the individual in a truly tailor-made, one-to-one dialog.
According to a Nielsen report, 63% of marketers in the United States believe that data-driven is among the most important and decisive marketing tools available. And what is certain is that this centrality will grow more and more in the future. But, if we look specifically at the world of Food and Beverage, what are the most effective strategies and best practices in this field?
The importance of Big Data in the Food Industry: 5 strategies
Below we will look at five. We will start with a quick glance at the production front (i.e. optimization and cost reduction) and we will go as far as the frontier of real personalization, up to loyalty. As we go along, you’ll see that all of these aspects are, in fact, linked.
1. The starting point: optimization and cost reduction
Before we turn to the world of marketing, let’s start from the ground up: production optimization and cost reduction.
Data analysis in this field is incredibly valuable. We’re not just talking about historical data which can help us identify inefficiencies and areas for improvement in the process (also thanks to technologies like the Internet of Things, a potentially endless new source of information). The data analysis also helps us be able, to a certain extent, to “predict the future”; here we are already in a territory halfway between production and marketing.
Let’s get straight to the point, with an example from Denmark. The Salling Group (the former Dansk Supermarked Group) is the country’s largest retailer and has been a pioneer in the use of data from a predictive point of view. Its constantly updated analysis systems make it possible to track the preferences of customers entering its stores almost in real time. Based on this, the company is able to determine the purchase and storage volumes it needs. It’s worth emphasising that this is a business that deals with an enormous selection of products, more than 1.4 million customers a day, and a significant volume of fresh products (which requires a certain delicacy in managing the freshness of its stock).
The advantages of a data-driven approach and how this can result in efficiencies in costs, user satisfaction, and waste reduction are easy to see. But, importantly, this enormous amount of valuable data is used by the company (and its marketing departments) to make strategic decisions with a level of awareness and potential for success that was previously unthinkable (For more on this case, see here).
2. Understanding and Predicting Sentiment
Sentiment is the index that measures what is “said”—whether positive or negative—about a brand or a product. In the case of a product, this can be generic or very specific, depending on the specific context. For example, you could look at what is being said about the topic of “red wine” in the global context, what is being said in one specific geographical location about a specific vintage, or you could look at what is being said about a specific brand of red wine.
Learning how to analyze this in order to better understand market trends and to be able to make decisions accordingly, is fundamental. In short, analyzing data allows you to offer products and services to your customers before they realize that they are exactly what they want. And, it allows you to do so by tightening the focus on increasingly specific segments at a geographical or demographic level, based on previous preferences and on a series of metrics that can (and must) be combined.
3. Finding the right mix
Finding the right mix in data analysis means, first of all, focusing and combining the right metrics.
But it also means getting the right data, in the right places, and at the right times with an omnichannel perspective: mobile, desktop, tablet; but also knowing how to track the best keywords on search engines, social networks, and specialized platforms.
One thing must be kept in mind: there is no single perfect mix that is applicable to everyone; it’s about finding the right one, the most functional one, for your business and your purposes.
4. Going for personalization? Yes, you can
The real purpose of a data-driven approach is to know as much as possible about your audience of customers, both potential and real customers. The next step is to divide this audience into many segments, in clusters based characteristics that you define. These specific slices of the audience will be intercepted with tailor-made messages, with the right “voice,” in the right place, at the right time.
But can it go further? Yes. And that’s exactly what companies like Doxee, who specializes in marketing and personalized Customer Service, do. It’s about really getting to know who you’re dealing with, person by person. Track individual customer journeys, and monitor all touchpoints, and, consequently, build personalized communications that are tailored to each customer
The big brands are all realizing the power of personalization; even in the Food and Beverage sector. McDonald’s, for example, has launched its app, through which you can access discounts and tailor-made offers, but also “talk” with the brand with a view toward improving the service. Then there is the retail giant, Kroger, with over 120 billion in sales and almost half a million employees. The company has implemented an efficient data collection system where they were able to use to generate more than 6 million unique and personalized offers to customers in 2017 (For more information, see here).
5. Loyalty: the real target
In this post, we started from the use of Big Data for production optimization and cost reduction (but also, at the same time, for a better knowledge of customer behavior). Then we moved on to marketing dynamics, and finally to the frontier of personalization. So why did we decide to close with loyalty?
Loyalty is the real objective to which all companies must aim (but also the most difficult one); those in the Food and Beverage sector are absolutely no exception.
According to an in-depth analysis by Bain & Company, winning a new customer costs 6 to 7 times more than keeping a loyal one. In short, it is the numbers themselves that “scream” the importance of loyalty. And, certainly, the best way to build customer loyalty is, again, to get to know the customer’s characteristics, behaviors, and needs.
At this point, it is hardly surprising that, according to a 2017 survey conducted by Gartner, as many as 81% of marketers from all sectors expect Customer Experience to be the main focus of marketing challenges over the next three years. And today, there is no satisfying Customer Experience without personalization.