Cloud Technology is helping Grocery Delivery Apps optimize their operations – Here’s How

With more startups entering the on-demand delivery market, surviving the competition has become a priority for existing grocery delivery apps. 

There is no doubt that all grocery apps aim to grow by scaling their capacity. However, a rigid infrastructure with insufficient support tools can restrict the scalability of such companies. 

Below are some ways cloud computing is helping companies overcome these restrictions without compromising on the customer experience.

Quicker Delivery Routes

With the rising competition and consumer demand for speed, every grocery delivery app is facing multiple challenges in optimizing its operations. 

On one side, companies have started offering quicker delivery times to survive the saturated market. 

On the other side, more and more consumers adopting the on-demand delivery apps has put a strain on the available resources. This has created a new challenge for delivery apps to maximize their operational efficiencies to better fulfill the demand.

Cloud computing is helping delivery apps do just that with the help of route optimization. As more orders enter the pipeline at a single time, allocating delivery resources efficiently becomes more complex. 

With the help of data extraction, data analysis, and machine learning, cloud computing helps with prioritizing orders and finding the best routes. 

All on-demand grocery delivery apps have to assess, analyze and utilize real-time order data to optimize their delivery routes. 

Going through this data in real-time, ranking it to understand delivery times, allocate resources, and schedule prioritization for each order is impossible without supportive infrastructure. 

By carrying out these tasks on a central location that is also instantly scalable, grocery delivery apps are able to unwrap millions of data pieces every second without overwhelming their existing software.

AI-powered Automation

There is no doubt that delivery tasks are not easy to automate, given the human resources needed for each order fulfillment. Being labor-intensive and requiring multiple steps to delivery is one of the biggest limitations of modern delivery apps.  

High-level decisions like which order to prioritize first and how to allocate orders to each rider require a lot of real-time data. With the help of AI and data analysis, cloud solutions offer automated scheduling and task syncing that allow a more seamless flow of delivery. 

The AI infrastructure helps grocery delivery apps utilize the quick calculations that are driven by multiple factors, including order delivery time, fulfillment of the previous order, and rider availability at each distribution center.

Improved Scalability

Working with multiple distribution centers in different locations can make the delivery system more complicated. 

Without real-time data exchange between each distribution center and resource allocation system, quick delivery times cannot be achieved. 

Cloud computing solutions that are specifically designed around the needs of delivery apps and route optimization help track important factors that affect resource allocation.  

By making the data related to inventory levels, production capacity, available labor, and other resources readily available on a central location, cloud computing allows effortless scaling.

More and more grocery delivery apps are now able to scale seamlessly to other cities and countries without facing any allocation issues. 

This allows companies to focus on the customer experience and fulfill their service-level responsibilities without worrying about their backend capacity and resources.

By making the data related to inventory levels, production capacity, available labor, and other resources readily available on a central location, cloud computing allows effortless scaling.