Driving Intelligent, Scalable Digital Commerce for Enterprise Food Delivery

Industry

Food Tech

Services

Food Delivery App Optimization and E-Commerce

Business Type

Enterprise

Salesforce Solutions Used

Salesforce Commerce Cloud, Tableau CRM, Einstein AI, MuleSoft, Experience Cloud, Sales Cloud, Service Cloud
 

About The Solution

The client was looking to optimize their food delivery app. Their legacy software was using older technologies which were unable to keep up with the rising demands of the customers. They wanted to integrate Salesforce into their systems to make it optimized. We accessed their needs and planned a framework through which we would work together to create a functioning system.  

Background

The client wanted to bridge the gap between customers and restaurants. There were complaints of inaccurate delivery estimates and the app not being able to handle the rush hours. We designed a CRM with modern technologies and optimized features where they would manage their customers and other operations. With the help of Experience Cloud and Tableau CRM, we ensured that marketing insights are shared across the enterprise, allowing strategies where promotional campaigns were aligned with restaurant inventory and regional delivery capacity. 

The client was facing a critical disconnect between users and kitchens and needed a system that functioned as a command center necessary to synchronize the moving parts. Our solution enables automation and real-time analytics to streamline operations, reduce manual work for staff, and enable smarter, data-driven decisions on pricing and promotions.



Challenges

Here are the challenges that the organization was facing:

01
High Customer Churn

Inaccurate delivery estimates and generic marketing led to low retention.

02
Operational Friction

Logistics team and internal sales teams were using disconnected systems.

03
Data Fragmentation

Customer data was trapped in separate silos

04
Scalability Issues

The existing infrastructure struggled to maintain performance

05
Rush Hour Instability

The legacy infrastructure could not handle massive concurrent user spikes

Objectives

The core objective was to integrate Salesforce into their systems to make it optimized. Let us see in detail:

1
Bridge the Communication Gap
  • Unify logistics data to provide a single view of the order lifecycle
  • Establish a direct merchant-to-customer messaging channel
  • Achieve 100% real-time synchronization
2
Stabilize High-Traffic Performance
  • Ensure 99.99% system uptime during defined "rush hour" windows
  • Implement an API-led architecture to handle 5x transaction volume
  • Automate load balancing
3
Improve Delivery Accuracy
  • Reduce the variance between estimated and actual delivery times
  • Utilize Einstein AI to factor in kitchen load and courier availability
  • Implement dynamic routing to bypass traffic congestion
4
Enhance Operational Scalability
  • Decrease manual support ticket volume
  • Onboard new restaurant brands in hours rather than weeks
  • Automate 70% of logistics dispatching

Results

The results of our strategies and design
MetricBefore SalesforceAfter Salesforce
Delivery ETA Accuracy62% Variance94% Accuracy
Peak Hour System Uptime88.50%99.99%
Customer Support Volume1 in 4 orders1 in 20 orders
Order Conversion Rate3.20%6.80%
Merchant Onboarding Time14 Days6 Hours


Analysis

  • Salesforce AI: Einstein AI shifted the strategy from reactive to proactive by automating repetitive tasks and making customer service easier
  • Cloud UI: A modern cloud UI reduces technical debt significantly. Creating a user interface that is dynamically rendered and powered by cloud-based backend services
  • Retention: System focused on retaining existing high-value users and providing them with smoother experience and better customer service.
  • Enhances B2B synergy: Integrating cloud-based platforms that connect restaurants, delivery fleets, and suppliers through shared data 
  • Tableau CRM: Tableau CRM allowed managers to see "delivery hotspots". This integration enables data-driven logistics optimization, allowing managers to proactively reposition delivery fleets, adjust staffing, and reduce wait times 
  • Service Cloud’s: Service Cloud’s integration meant increase in service speed
Problem

Their legacy software was using older technologies which were unable to keep up with the rising demands of the customers. 

Solution

Automation and real-time analytics to streamline operations, reduced manual work for staff, and enabling smarter, data-driven decisions on pricing and promotions.

Result

Optimized workflow, better data management and utilizing a cloud-first architecture for a stable and secure platform.

Strategic Takeways

The new system helped fill quite the number of pain points the institution was facing. Here are a few strategic takeaways: 

  • Having a single view of the customer across marketing and service is the only way to reduce churn effectively.
  • Predictive intelligence is only useful if it’s tied to an automated delivery system
  • By providing merchants with their own data dashboards, you create a system that is hard to disrupt.
  • Utilizing a cloud-first architecture ensures that the platform remains stable

Conclusion

This case study shows how an integrated Salesforce ecosystem can revolutionize food tech operations. We helped our client create a unified platform connecting customers, restaurants, delivery partners and employees. The optimized platform not only solved the pain points but enhanced the foundation of a continuously evolving platform.

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