The ultimate guide to food delivery app marketing and growth

The online food delivery market is continuing to grow, with global revenue set to reach $483.9 billion by 2032, at a steady 12% CAGR. While the food delivery vertical was well-established before the COVID-19 pandemic, adoption skyrocketed globally during that period, transforming it into an everyday convenience for many consumers. Quick commerce (delivery in under 30 minutes) has also transformed consumer expectations, but speed alone isn’t enough to keep users engaged. With so many options available, customer loyalty has become the real battleground. To build a sustainable business, food delivery apps need to focus on more than just fast service—a strategic, data-driven marketing plan is essential to drive retention and long-term profitability.

Food delivery apps come in different flavors, with several distinct business models designed to meet specific consumer needs.

Restaurant-to-consumer

In this model, restaurants handle everything from order to delivery through their own apps. Chains like Domino’s and Pizza Hut have perfected this approach, retaining full control over customer experience and profit margins. However, smaller restaurants are also increasingly investing in this model to build direct relationships with customers and avoid aggregator fees.

Platform-to-consumer

Aggregators like Uber Eats, DoorDash, and Grubhub connect users with multiple restaurants. These platforms manage delivery and customer service while taking a percentage of each order. Competition in this space is intense, with platforms offering loyalty programs, exclusive deals, and even subscription models to win over customers and increase revenue.

Grocery delivery

Quick commerce has transformed grocery delivery, with services like Getir, GoPuff, and Instacart promising delivery in under 30 minutes. While the segment has seen mixed performance due to challenges around profitability, demand remains strong in urban areas where speed and convenience are key drivers of customer loyalty.

Meal kit delivery

Services like HelloFresh and Blue Apron deliver curated ingredients and recipes, combining the convenience of delivery with the satisfaction of home cooking. The market has shifted toward more flexible options, including single meals and customizable plans, to better meet consumer demand.

Building and marketing a successful food delivery app requires more than just a good idea, it demands a strategic approach, a deep understanding of the market, and a focus on user experience (UX). Artificial intelligence (AI) is now central to this process, enhancing everything from user personalization to operational efficiency. Here’s how to get started:

Market validation and defining your target audience

Start by identifying a gap in the market or a unique value proposition (UVP). What will make your app stand out—faster delivery, better pricing, or exclusive restaurant partnerships? Conduct competitor analysis and user research to uncover opportunities and pain points. Quick commerce and eco-friendly packaging are examples of trends that could give your app a competitive edge. Test your idea through surveys, prototypes, and focus groups to ensure you’re building something that meets real demand. AI can analyze market data to identify trends and predict potential demand across different regions, helping you refine your value proposition.

App development

Decide whether to build a fully custom app or use low-code/no-code platforms to save time and costs. A custom app offers greater flexibility but requires more resources, while low-code/no-code tools can accelerate the launch. For complex apps, like those involving delivery tracking and multiple interfaces (for customers, drivers, and restaurants), a custom build may be necessary. For simpler apps, a no-code platform could help you launch quickly and test the market with minimal investment. AI-based development tools can speed up coding and automate error detection, improving efficiency and reducing time to market. Ensure the app architecture is scalable to handle growing traffic and order volumes without performance issues.

Core features

A seamless user experience is essential for success. Start with intuitive onboarding and a clean interface. AI-powered personalization can suggest restaurants and meals based on user preferences and past orders, while machine learning can refine search results and improve order recommendations over time. Real-time order tracking is now an expectation, and AI can enhance it by predicting delivery times and adjusting routes based on traffic patterns.

Offering multiple payment options, including Apple Pay, Google Pay, and PayPal, helps reduce friction at checkout. Push notifications can improve order completion rates and keep users engaged with updates and promotions. Loyalty programs, such as points-based systems or free delivery thresholds, are effective for encouraging repeat orders. AI can help identify the most effective incentives by analyzing user behavior. Strong customer support—including live chat and quick refunds—is also critical for building trust. AI-powered chatbots can resolve common issues instantly, reducing customer frustration and improving satisfaction.

Monetization strategy

Define how your app will generate revenue. Most food delivery apps operate on a commission-based model, where a percentage of each order is retained by the app. Delivery fees can be charged to customers or split between the restaurant and the app. Subscription models, such as offering unlimited free delivery for a monthly fee, are gaining traction and encouraging customer loyalty. In-app advertising and premium placements for restaurants are also effective monetization methods. AI-driven dynamic pricing can adjust fees and delivery costs based on demand, helping you maintain profitability while staying competitive.

Tech stack and infrastructure

A stable and scalable infrastructure is key to handling large volumes of simultaneous orders and real-time tracking. Cloud-based solutions like AWS or Google Cloud offer the flexibility to scale up during peak hours. Your app should support secure payment processing through PCI-compliant gateways, and user data must be protected with encryption and GDPR-compliant protocols. Latency issues or failed payments can lead to customer drop-off, so performance optimization is critical. AI-powered infrastructure can predict server load and automatically allocate resources to maintain smooth app performance, even during peak hours.

Partner onboarding

If your app aggregates restaurants or grocery stores, a smooth partner onboarding process is essential. Create a dedicated portal where partners can upload menus, adjust pricing, and track orders in real-time. AI can analyze partner performance data to offer insights on order trends, customer preferences, and peak times, helping partners maximize their (and your) revenue. Providing training and responsive support ensures that partners remain engaged and satisfied with your platform.

Testing, soft launch, and post-launch strategy

Before launching fully, create a minimum viable product (MVP) with core features. This allows you to gather early feedback and identify pain points before investing further. A soft launch in a small, controlled market helps you test operational performance and user experience. AI-based A/B testing can evaluate different layouts, user journeys, and notifications to optimize engagement and conversion rates. Monitor metrics like conversion rates, session times, and order completion rates to fine-tune the app. Once the data shows positive engagement and minimal friction, you can scale to larger markets.

Leveraging data and insights

AI and machine learning can transform your marketing strategy by providing real-time insights into user behavior. Tracking session times, order completion rates, and drop-off points helps you understand how users interact with your app. AI can predict user preferences, allowing you to offer personalized recommendations and targeted promotions. If a user frequently orders from a particular cuisine type, you can suggest similar options or offer discounts on those meals. Data analysis also helps refine your ad spend by identifying which channels are driving the highest return on ad spend (ROAS) and customer acquisition cost (CAC). Regularly reviewing this data allows you to adjust your strategy, improve engagement, and increase customer retention.

Successful food delivery apps use a mix of organic and paid strategies to reach their target audience and build long-term engagement. As the market evolves, leveraging the right combination of channels is key to driving sustained growth and maximizing customer retention.
Here’s how to establish a winning multichannel marketing strategy:

App store optimization (ASO)

ASO helps your app rank higher in app store search results, increasing visibility and driving organic downloads. Start by researching high-performing keywords and incorporating them into your app’s name and description. Use compelling visuals—including screenshots and videos—to showcase the app’s key features and highlight your app’s UVP. Positive reviews also boost visibility, so consider prompting satisfied users to leave feedback.

AI can improve ASO by analyzing user behavior and adjusting search relevance based on performance data. Machine learning models can suggest new keywords, identify which visuals are driving the most engagement, and recommend optimizations to increase conversion rates. 

Social media and influencer marketing

Social media is a powerful tool for engagement and brand awareness. Visually appealing content works especially well for food delivery apps, since food is naturally shareable and eye-catching. Platforms like Instagram, TikTok, and Facebook allow you to showcase mouthwatering food photography, share user-generated content, and engage with followers through comments and direct messages.

Influencer partnerships remain an effective way to reach niche audiences and build credibility. For example, Uber Eats has successfully worked with food bloggers to promote the app to targeted demographics. Influencer takeovers and live content—like livestreaming an order experience—can increase engagement and app installs.

Tracking the right performance metrics is essential for evaluating the success of your app and optimizing your strategy over time. Here are the key performance metrics that food delivery apps should measure:

• Impressions: Impressions measure how many total users see an ad or listing. High impressions indicate good visibility, but low clicks or conversions could suggest a mismatch between the targeting or creative, depending on the channel and campaign goal.
• Click-through rate (CTR): CTR reflects the percentage of impressions that result in clicks. A high CTR indicates that your ad resonates with the target audience. If impressions are high but CTR is low, refining the messaging or visuals may help.
• Conversion rate: Conversion rate measures the percentage of users who complete a desired action—such as placing an order or signing up. If clicks are high but conversion is low, issues like complex checkout processes or limited payment options could be to blame. A/B testing can help identify and resolve friction points.
• Return on ad spend (ROAS): ROAS measures how efficiently your ad spend translates into revenue. A low ROAS suggests that targeting or ad creatives need improvement. DCO can help improve ROAS by automatically adjusting ad spend based on performance.
• Customer acquisition cost (CAC): CAC measures how much you spend to acquire a new customer. Lowering CAC is critical for long-term profitability. High CAC might mean weak targeting or expensive ad placements, requiring strategy adjustments.
• Contribution margin: Contribution margin measures the profit generated from each order after subtracting direct costs like delivery fees and commissions. A positive contribution margin means your app is generating profit on each order. A negative margin could mean delivery costs or promotions are cutting into profitability.

Adjust’s suite of solutions helps food delivery apps maximize growth by providing precise attribution, deep insights, and targeted engagement capabilities. You can attribute and measure every touchpoint—from the first ad impression to post-install events and activity. This enables you to identify the most effective channels and make changes to bids and budget in real-time. 

For food delivery apps, deep linking is particularly critical to both new UA and reengagement. With Adjust’s TrueLink, you can seamlessly funnel users to the exact in-app destinations where they’re most likely to convert.

Stay ahead of the competition with smarter insights and scalable engagement. Request a demo today to see first hand how we can grow your app business.