What is it?

Ad-Set is a casual retail simulation in prototype. The design is intended to illustrate the chaotic reality in the seemingly mundane environment of a retail store. In this game, the player takes on the role of a retail clerk responsible for setting advertisements to meet sales objectives. The player has a primary sales goal to reach a particular dollar amount before the timer runs out. They also may complete a secondary objective, selling a specified number of a particular item, to extend the amount of time to reach the primary goal. In addition to the timer, the player must also be aware of the amount of stock of each item. If a customer attempts to purchase an item that is out of stock, the customer will become dissatisfied and leave the store without making a purchase.

The player is able to move about the store freely. They may interact with the ad signs around the store to change which item is being advertised on that sign. As a customer approaches a sign, the customer will become interested in the advertised item and seek to purchase it. The player may also interact directly with customers whom are not already seeking a product in order to lead them to an advertisement. Shopping carts are also placed around the store. The player may interact with these carts to move them about and block aisles, preventing customers from traveling those paths.

My Role

I was the sole designer and developer for this game. All features and mechanics were designed and programmed by myself.

Notable Features

• Customer AI with state-machine structure
• Unity navmesh pathfinding and use of dynamic navmesh obstacles
• Overlay and World-space UI elements

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Development Cycle

Ad-Set was designed and prototyped over the course of one month. During this time, all features were designed, documented, and implemented into the working prototype. The project also consisted of weekly, structured playtests to gather data on the prototype. Playtesters were asked to complete a questionnaire about their experience, bugs, and general feedback. This data was then analyzed and used iterate upon the design.