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How Food Delivery Apps Benefit from Big Data Analytics

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Food Delivery App Development


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:

  1. 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.

  2. 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.

  3. 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:

  1. Platform:

    The cost of building an app for iOS, Android, or both can vary depending on the platform.

  2. 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.

  3. Complexity:

    Depending on the app’s complexity, the time can be evaluated take to develop, which can lead to higher costs.

  4. 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.

  5. Development team rates:

    The hourly rates of the development team can vary depending on their experience level and location.

  6. API integrations:

    Integrating with third-party APIs, such as payment gateways, can also increase the cost of app development.

  7. Testing and quality assurance:

    Testing and QA are critical components of app development and can impact costs.

  8. 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!

Neha Malhotra

Neha Malhotra is a brand and content strategist by profession. With a profound experience in IT, she writes about new disruptive technologies and innovations. She has authored blogs on various digital platforms.

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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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