As a Product Manager at UberEATS, what feature would you develop to enhance the average order value?

This question prompts you to adopt the perspective of a Product Manager (PM) at UberEATS and suggest a new feature aimed at enhancing the average order value, also known as basket size. The term 'basket size' refers to the total number of items or overall value that a customer includes in one order. This task requires you to grasp the product and its user demographics while devising an innovative feature that encourages customers to increase their spending in a single transaction. When formulating your response, keep the following essential points in mind: Understand the Context: Familiarize yourself with how UberEATS operates, its business model, and patterns in customer behavior. Be User-Centric: Consider what factors would motivate a user to place a larger order. What incentives or strategies could be introduced? Measure the Impact: Think about how the effectiveness of this feature could be evaluated and how it might contribute to a rise in average order value. Consider the Feasibility: Assess whether this feature can be realistically implemented given UberEATS' current capabilities and resources.

One potential way to enhance the average basket size is by introducing a "Bundled Meals" feature. This would enable users to buy meal combinations from various restaurants at a reduced price. For instance, we could create a bundle that includes a pizza, a drink, and a dessert from different eateries, offered at a lower cost than if the items were purchased separately. This approach could motivate users to spend more per transaction, as they would receive a broader selection of food at an affordable price. Additionally, the bundled combo could be tailored to individual user preferences and ordering history, making each combo more appealing and increasing the chances that users will add it to their basket.

UberEATS might consider implementing a feature called "Upgrades." This idea, which is quite popular in the gaming sector, could also be applied to a food delivery platform. For example, options like larger portion sizes, additional toppings, or extra side dishes could be offered as upgrades to the existing order, potentially at a modest discount compared to ordering them separately. As customers recognize the benefit of receiving more for just a little extra cost, they are likely to opt for these upgrades, thereby boosting the average order value. On the backend, an algorithm could be developed to recommend upgrades based on users' past orders and preferences, enhancing the personalization and effectiveness of this feature.