Deep-dish Data Science: How Dodo Brands Uses AI for Dynamic Pricing


Andrey Filipyev, Chief Data Officer at Dodo Brands was able to balance peak hour rush with a strategy that used machine learning algorithms to offer discounts to customers that ordered early.  

Business leaders can look at technology to solve certain business challenges. But be prepared to take on new challenges that come with it, especially if people, processes and legacy systems aren’t aligned. 

When it comes to choosing partners and investing in technology solutions, Andrey Filipyev, Chief Data Officer at Dodo Brands has this to say, “The optimal approach is to appoint someone within the company responsible for integrating the transformation and comprehending the business. This person will develop the AI development strategy and strive to achieve the objectives. Following this, the company can collaborate with outsourcing firms or construct an in-house team, but having an expert in charge of transformation integration and business understanding is crucial.”  

Datatechvibe asked Filipyev about how enterprises could use data to drive innovation and product design. Here’s what he had to say;

Develop information system to automate 

Let me explain our business model. Dodo Brands operates via a franchise model in 17 countries, and we have an extensive network of partners to whom we provide our business model and technologies. Since the company’s inception, our headquarters has been developing its information system to automate all store processes, enable order creation via mobile app, and facilitate order tracking.

Establish the success parameter for your business 

Our goal is to provide excellent food service to our customers, and the quality of our service is determined by various parameters such as product quality, delivery speed, and convenience of communication channels like mobile apps. Delivery speed is a crucial parameter that directly affects customer loyalty. When customers order food for delivery, they expect it to be delivered quickly, at a reasonable temperature, and at a good price. However, during peak hours when the kitchen and roads are overloaded, maintaining a high level of service becomes increasingly challenging.

How AI drives price optimisation 

We can use two strategies to handle this challenge of peak hours with dynamic prices: increase the prices or decrease the number of order peaks. Many examples of increased costs during peak hours can be seen in ride-hailing services through apps.

At Dodo Brands, we decided against raising our product prices to solve the same problem. Instead, we utilised various machine learning algorithms to identify peak hours and offer discounts to customers who order before peak hours. For instance, if a customer orders pizza a little earlier, they can enjoy an extra discount on the product while still receiving the same quality. This approach reduces the number of orders during peak hours, thus reducing the workload on the store and allowing us to maintain a high level of service quality during peak hours. 

This B2C business model is a win-win situation for our customers and us.


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