The online food ordering trend is becoming more advanced in today’s digital ecosystem. Essentially, food delivery apps have become a consistent part of our everyday lifestyle. As a result, businesses are rapidly investing vast amounts in big data analytics. Basically, Big data boosts business strategy based on gathering data.
Furthermore, big data analytics helps collect real-time data, such as ordering frequency, repeated orders, road traffic, restaurant preferences, etc., and accurately estimate customer delivery time. Moreover, with big data, one can predict the impact of these factors on retaining customers, which helps take preventive measures to improve the customer database.
“Big Data Analytics reported at GrubHub that from 2013 to 2015, there had been a jump to 1 billion dollars from 46 million dollars in terms of Big Data investments in the food delivery business.
This rise has been exponential and is expected to continue. Apps have also enabled 5 million active diners and 30,000 take-ups out of restaurants to get daily services and orders.” (Quote from: techaheadcorp.com.)
How Analytics Used in Food Delivery App Development?
Data Analytics and Data Science are helpful across the food industry to measure customers’ satisfaction, pricing, brand value or popularity, quality of products, product popularity, market situation, etc.
- Food Delivery App Development — Image Credit: businessofapps.com; Thank you!
Evaluate Customer Behavior
By applying Big Data Analytics, you can measure the customers’ interest in your brand. In addition, your food delivery performance and customer comeback; can all be analyzed using Big Data Analytics software.
Big Data Analytics software help collect and interpret all the brand’s reviews and feedback received across various social media platforms. Twitter, Instagram, Facebook, and forum comment sites are the most common target social platforms. As a result, it helps CEOs and marketing experts make business decisions based on the provided data.
Enhance Delivery Time and Cost-efficiency
Determining and optimizing time and cost efficiency becomes hassle-free by introducing Data Science and analytics in the process. So, if any circumstances occur, a business can quickly decide how to respond to the current situation to make it favorable. Also, considering what a customer needs and wants encourages them to deliver on time and as expected.
The food delivery service and their customers should immediately get their food — hence — providing a win-win situation for all.
Location-based Data Analysis
Analytics tools are used to collect location-based data, such as user location, delivery time, and restaurant location. This data is used to optimize the delivery process by predicting delivery times, identifying areas and the times of high demand, and optimizing delivery routes.
Performance Analysis
Analytics tools are used to track app performance, including app crashes, response times, and server uptime. This data optimizes the app’s performance by identifying and fixing bottlenecks.
Increase ROI on Deliveries
Before, several big players in the USA, like Starbucks, McDonald’s, and others, leveraged big data analytics to enhance the customer experience. They gather data on what and when the customer makes their orders. The question is answered, “do they need personalized offers or not?”
These questions helps the services to deliver what customers need and what kind of food delivery they prefer. The data analysis helps companies to understand the trends and to build their learning (and earning) strategy according to the latest trend and preferences.
Market Basket Analysis
Market basket analysis is related to forecasting the most probable behavior of the customer. This analysis is carried out based on the purchase history and the items in the customer’s cart.
Based on the results of this analysis, combo deals can be advertised to customers, attracting them to purchase more and ensuring customer satisfaction by making their ordering decision easier.
Employing Smart Algorithms for Demand
Using a smart Big Data algorithm, a food delivery app can forecast the customer’s next order. It is easier than you think; by studying the earlier browsing of a user and observing their past order data, the food delivery app can forecast when the customer is likely to order again or not.
Case Study – How Dominos Pizza Leveraging Data to Increase its Number Count
Domino’s Pizza, introduced in 1960, is the world’s leading pizza delivery chain, with a substantial business in the delivery of pizza services.
Domino’s Pizza, one of the world’s largest pizza delivery chains, is known for its innovative use of technology to enhance customer experience and increase sales. With a presence in over 90 countries and more than 17,000 stores, the company constantly looks for ways to improve its operations and expand its customer base.
Adopting technology as a competitive mechanism helped Domino’s accomplish over 50 percent of all global retail sales in 2017 from digital channels, especially online ordering, and mobile applications.
In this case study, we’ll explore how Domino’s is leveraging data to increase its number count.
Challenges Faced:
One of the challenges that Domino’s faces are maintaining and expanding its customer base in a highly competitive market. The rapidly growing number of online food delivery platforms has created more options for customers than ever before.
To remain competitive, Domino’s must keep up with changing customer preferences and offer a differentiated experience. Additionally, the company needs to manage its supply chain efficiently to ensure its stores are well-stocked and meet customer demand.
Solution:
Domino’s has been investing in data and technology to address these challenges to enhance its operations and customer experience. Here are a few ways the company is leveraging data to increase its number count:
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Predictive Analytics:
Domino’s uses predictive analytics to forecast product demand and plan its inventory accordingly. By analyzing historical sales data and using machine learning algorithms, the company can predict which products will be in high demand and when. This allows the business to improve its inventory levels and mitigate waste.
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Customer Segmentation:
Domino’s uses customer segmentation to personalize its marketing efforts and offers. By analyzing customer data, such as past orders and preferences, the company can segment customers into different groups and target them with relevant offers and promotions. This adds value to customer loyalty and retention.
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Digital Innovation:
Domino’s has been at the forefront of digital innovation in the food industry. The company has developed its own ordering app. It helps customers who order Pizza from their mobile devices while sitting anywhere at any time. The app also features a GPS tracking system that lets users track their orders in real-time. Additionally, Dominos has experimented with robot deliveries in some markets.
Results:
Domino’s has improved its operations and expanded its customer base by in data and technology. In the first quarter of 2021, Dominoz reported global retail sales growth of 13.4%, with same-store sales growth of 13.4% in the US and 11.8% internationally. Additionally, the company reported a 14.5% increase in the number of stores globally, with 177 new stores opening during the quarter.
Cost of Building Food Delivery App
The cost of building a food delivery app can vary widely depending on several factors, such as the platform (iOS, Android, or both), the features and functionality of the app, the complexity of the app design, and the development team’s hourly rates.
On average, the cost of building a food delivery app can range from $20,000 to $100,000 or more. However, the cost can be significantly higher for more complex apps or if you choose to work with a high-end development team.
Additionally, ongoing costs such as server hosting, app maintenance, and updates should also be taken into account.
Several factors can affect the cost of developing a food delivery app, including:
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Platform:
The cost of building an app for iOS, Android, or both can vary depending on the platform.
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Features and Functionality:
The advan features and functionality you want to include in your app, the more time and resources it will take to develop, increasing the cost.
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Complexity:
Depending on the app’s complexity, the time can be evaluated take to develop, which can lead to higher costs.
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Design:
The design of the app can also impact the cost. A more intricate and custom design may require more time and resources to create.
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Development team rates:
The hourly rates of the development team can vary depending on their experience level and location.
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API integrations:
Integrating with third-party APIs, such as payment gateways, can also increase the cost of app development.
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Testing and quality assurance:
Testing and QA are critical components of app development and can impact costs.
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Ongoing maintenance and updates:
After the initial development, ongoing maintenance and updates are vital to keep the app running smoothly and up-to-date, which can also impact the overall cost.
Working with an experienced development team to help you navigate these factors and develop a high-quality app that meets your business needs and budget is important.
As such, it’s advised that you work with an experienced development team to ensure that your app is built to the highest standards and delivers the best possible experience for your users.
Conclusion:
A food delivery app such as Domino’s is an excellent example of how a company can leverage data and technology to enhance its operations and increase its number count. By using predictive analytics, customer segmentation, and digital innovation, the company has been able to stay ahead of the competition and expand its customer base. As the food industry continues to evolve, Domino’s dominates the market to continue its growth and success.
Simply put, analytics is used in food delivery app development to improve user experience, imp delivery processes, increase sales, and continuously improve the app’s performance.
Featured Image Credit: Photo by Erik Mclean; Pexels; Thank you!
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