The Role of Data Science and Data Analytics in Food Delivery Startups
By: Henny Jones
Tags: Big Data Analytics, Food, Big Data, Data Science, Startup

The Role of Data Science and Data Analytics in Food Delivery Startups Henny Jones Follow Jul 29 · 5 min read

Photo by fabio on Unsplash

Over a decade, there have been cut-throat competitions in food industries. However, every owner is finding their way to step on top of this competition. In that, food industries started adopting the latest technologies to enhance their services. Advanced technology such as Data Analytics and Data Science is top on the list.

The only food industries are trying to understand consumer behavior, taste, and preferences. When the users order food online or order in a restaurant, they expect to get delicious food- at a reasonable price and set pretty high expectations of the food. With the food industry, there is an evolution in food delivery apps. According to a study, 60% of consumers judge food based on food quality.

To match the expectation of the users, Data Science and Data Analytics come into the picture and play a vital role in it. The enterprises are leveraging Data Analytics to discover precise food industry analytics to increase their business, be aware of the trends, and decrease expenses. Data science supports identifying the customer’s needs precisely. It assists organizations in collecting and analyzing data which helps to detect trends and patterns.

The innovations bring creative solutions to problems troubling the industry while producing positive developments in the food industry. Moreover, the usage of technology is more needed for food delivery startups. Because they need more data to know about customer demand and preferences regarding food delivery, according to a report, the food delivery market is expected to rise to $5 billion in 2019; by 2023, it will reach $15 billion.

Following are the reasons food delivery startups use data science and data analytics:

1) Enhance Delivery Time and Cost-Effective

One of the reasons why the food industry is escalating is because of food delivery. The food chain delivering restaurants to customer’s places made the customer experience more manageable and efficient. However, food delivery has a complicated issue to solve as it includes a scale between securing a good customer experience while keeping high productivity in delivering orders.

Data Science and analytics help them to optimize time and cost. So, if any circumstances occur, they know what to do and encourage them to deliver on time and as expected. The food delivery or the customers should not wait for their food for a long time. Hence, it is a win-win situation for all.

2) Evaluate customer behavior

Big Data Analytics and Data Science are known for the data which can help them predict customer behavior. Every food delivery startup has a social media platform where they upload, post about new offers, and everything. However, if something takes place, the first one to be a target is social media. You cannot simply ignore the customer sentiment on social media. It is the first place where they will criticize.

Applying Big Data Analytics, you can measure the direction of the customers towards your brand. Your food delivery performance and customer reaction; all can be analyzed by utilizing Big Data Analytics software.

Big Data Analytics software will gather and analyze all the brand’s remarks across various social media platforms like Twitter, Instagram, Facebook, and others. You can then make your business decisions based on the provided data.

3) Increase ROI on deliveries

It has been proved by the survey that food delivery gives a better return on investment. Being a startup food delivery company, it is essential to know about the expected return on investment. Several decisions are based on the data by applying data science and analytics.

Before, several large companies in the USA like Starbucks, McDonald’s, and others have leveraged big data analytics to refine the customer experience. They gather data on what and when the customer orders- do they need personalized offers or not. It helps them to provide what customers need and what kind of food delivery they like to have.

The data analysis helps them to understand the trend and act accordingly to the latest trend and preferences. If you are a startup food delivery company, you need to adopt this method to grow successful.

4) Location-based Promotion

Every food delivery delivers food to a certain distance. The reason is obvious that the food delivery person cannot be everywhere and if the person went ahead, he or she will not be able to deliver food on time.

The benefit of Big Data Analytics is that it enables the food-tech company to target customers by creating use of real-time location and at the right time. The location-based promotion has several better advantages and real-time data, and the tracking that companies get from it is leading.

Food delivery companies have applied location intelligence to determine zone-wise cancellation rates, discover the proportion of demand and supply of food and delivery managers in an area and get an idea of delivery and restaurant step sizes and their differences.

5) Following Smart Algorithms for Demand

By applying a smart Big Data algorithm, a food delivery app can forecast the customer’s next order. It is simpler than you think; by analyzing the earlier browsing of a user and observing their past order data, the food delivery app can predict when the customer is probable to order again or not.

Through adopting predictive analytics, a food delivery app can predict accurately how many customers will order, especially during a particular time of the day or week, and from where and what.

The predictive analytics algorithm can tell what customer is likely to want and in which area of the city or state, the food is ordered the most. It gives you a perfect idea of where your food delivery is going and it is a hit or fails among the customers.

Wrapping Up

It will become essential for startups and food delivery companies to employ Big Data Analytics and Data Science with the rising demand for food delivery. From delivery rate, food preparation time to delivery routes- several things can be covered by applying Data Science and Data Analytics.