Case Study: Food Delivery App Increased ROI by 152% through Segmentation by Order Parameters

Rocket is a Ukraine-based international food delivery app launched in 2018. By the end of 2020, the company already operated in 27 Ukrainian cities and had 1M+ downloads. In December 2020, Rocket started operating in Cyprus and expects to launch in the Netherlands by March 2021. The company plans to extend its presence on the international market entering several other European countries.

With the help of our service, Rocket managed to create personalized communication strategies with different customer segments, improve their shopping experience and grow sales.

• After churn analysis we found out that churn of new users was cut by 40% thanks to triggered mobile pushes that were sent to app registrants who made no orders.
• Reactivation campaigns drove back 25% of users.
• The average customer check increased by 16% on average.
• The number of orders has increased by 65% since March 2020.
• LTV has grown by 12% and keeps on growing.
• ROI reached 152% and continues to grow monthly. ROAS brings on average $5 profit per $1 of investment.

Task

As an app-based service, Rocket uses Mobile Push as the main channel for customer communication. Since their customer base grew rapidly, different groups started to require a different approach. Rocket decided to implement customer segmentation and send personalized push notifications depending on the customer shopping behavior and order preferences.

The main tasks:

1. Convert more app users into paying customers.
2. Reactivate inactive customers.
3. Build relevant communication with loyal customers.
4. Retain customers and increase repeat sales.
5. Grow sales through personalized offers.
6. Increase customer lifetime value.

Since the company had much data that required maximum fast analysis, they needed well-though segmentation marketing and a proper customer data platform that would extract data from their app and use it to divide customers into segments and address them with relevant messages.

For this purpose, Rocket chose our service because our extensive functionality fit their customer segmentation strategies.

• Segmentation tools allow to send personalized mobile pushes to each user.
• Order data from a mobile app is processed in real time with minimal delay.
• Microsegments are built based on the corresponding order parameters.
• Segment and campaign management is automated and requires minimal manual correction.
• Reports with all the statistics are available on each campaign.

Strategy

We began to work with Rocket in January 2020. To fulfill their goals, we decided to use segmentation by app order parameters. Data on orders was instantly transferred to our service from their app and was available for segmentation.

Having implemented this approach, Rocket managed to:

1. Quickly integrate with our service. The necessary settings were made in the personal profile: the client set the mapping condition (phone number) and added the event orderCreated.

2. Get a full range of data operations:

• Collect and store contact data. A shopping history was obtained for every customer. We knew their names, location, order history, and preferences (meals, cuisine, price, order time).
• Implement behavioral customer segmentation based on one or several parameters.

3. Build complex segments:

• Work with active customers.
• Segment contacts by meal type, city, restaurant.
• Target segments based on the average check.
• Segment a loyal audience.
• Send personalized pushes based on customer preferences.

Solution

We built a separate segment and created different campaigns to fulfill each task.

1. Conversion of App Users into Paying Customers

This is a priority for any business. The registration phase should be strictly monitored as people get distracted by competitors, forget about the service, or simply need little encouragement to make the first order.

Rocket managed to take this process under control and converted 30% more registrations into orders. They sent a triggered mobile push to users who had confirmed their phone number but made no order over the last 90 days.

2. Reactivation of Inactive Customers

Our experience tells that you can return 20% to 55% of dormant customers by properly configuring reactivation triggers. In the first stage, Rocket set up a trigger to drive back customers who hadn’t used the services for more than 3 months. The segment was created taking into account the city and the app language in order to make a relevant personal offer.

3. Relevant Communication with Loyal Customers

Loyal clients are a core of your business who advocate your service and bring new customers. Communication with them is based on personalized offers and discounts to keep them interested in the company.

Long-time customers typically have established preferences. For food delivery clients, these preferences mostly apply to a cuisine or place. To meet the needs of each category, we built the following segments.

• Place fans regardless of the city who had made more than three orders at this place in the last three months. This segment received promotional content or discounts on orders at this particular place.

• Fans of a certain cuisine in a certain city who had made the corresponding orders in the last three months. People ordering Japanese, Italian, or Chinese cuisine often stick to their preferences, so this segment received discounts on orders of the corresponding cuisine.

4. Retention and Growth of Repeat Sales

To keep the conversation going with the existing customers, we built two segments.

The first segment included customers who made an order without a promo code (discount) for the period/all time in the city of N/in all cities. Such an approach is important as even the most loyal ones require occasional incentives to keep the interest going.

The second segment included customers who had intended to buy but hadn’t finished the order.

The workflow for this segment started in 2 cases:

• Customer made an order 24 hours ago and didn’t complete it;

• Customer made an order 5 days ago and didn’t complete it.

5. Sales Growth through Personalized Offers

To predict the next move of a particular customer and anticipate the demand, we used the following parameters:

• City and delivery address;
• Preferred cuisine;
• Previously ordered meals;
• Application language;
• Payment method;
• Order date.

Based on them, we built the following segments:

• Customers who had made N orders of N cuisine (Asian, European, etc.) for the period/all time in the city of N/in all cities.

• Customers who had ordered a meal of the N category (pizza, burger, sushi...) for a period/all time in the city of N/in all cities.

6. Customer LTV Growth

To increase customer lifetime value, we built the following segments:

• Customers who had made orders worth less than N for the period/all time in the city of N/in all cities.

Customers who had made orders worth more than N for the period/all time in the city of N/in all cities.

Conclusion

With the help of our service, Rocket managed to segment their customer base, build personalized communication and improve sales metrics:

As part of the future plans, the company intends to add web tracking to work with abandoned browses and carts, and geofencing to determine location and achieve better personalization.

This will enhance segmentation by adding new parameters for segment conditions:

• Contact information (name, surname, address, location, language, etc.);
• Campaign activity;
• Order data (city, place, meals, average check, etc.);
• Current location;
• Data for abandoned browses and carts.

For Rocket, mobile pushes are key for customer communication. However, the company plans to add Email and SMS to their marketing strategies using Advanced Segmentation by our service. It may increase their profit by 25%.

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