Problem

Nearly 50% of the users we interviewed are unable to use our Tip Pooling product because it doesn't accommodate restaurants that calculate tips based on a percentage of sales. Many of these blocked users are from full-service restaurants, which have more complex tip pooling processes.

Expanding our product to address this gap will provide the automation they need to simplify their complex tip pooling processes.

Key metrics

~30% increase in Tip Pooling adoption

Research

We interviewed 20+ restaurants to better understand their current process and issues. The current method is very labor-intensive, with many using Excel spreadsheets to calculate tips, causing restaurant owners to worry about potential mistakes.

Common themes

Sales tip pools are more common in Full Service Restaurants

These restaurants used a sales-based model to incentivize Servers, as a higher tip means more money they get to takehome.

Using "total sales" isn't enough, people want to be more specific

Common scenarios include restaurants wanting to filter sales by specific categories. Example: Bartenders should only be tipped based on beverage sales.

With tips based pools, we usually say 1-2 calculations per restaurant. With sales based, they'll need many more.

There is much more nuance and specifics with Full Service Restaurants that they usually will have a higher number of tip pools because there are more roles and employees in their business.

Example of a restaurant's current tip process using Google Sheets

Ideation

Synthesizing test data

Our goal was to understand the details of the tip pooling processes in restaurants we couldn't serve. We used research methods like user interviews, watching sales demos, and tracking why prospects didn't activate our Tip Pooling product.

Ideating on a user flow to test

We sketched out the high-level usr flow to ensure it would integrate well our current system. The main question we aimed to answer was, "When is the best time to ask if they pool based on sales or tips?"

User testing

We built high-fidelity prototypes to test with six 7shifts users who are not using our Tip Pooling product.

Determining Minimal Viable Product (MVP)

Although the user-tested designs included Sales Percentage and Filtering capabilities, the PM decided to release incrementally to unblock customers and iterate quickly. For the first release, we will only planned for the Sales Percentage capabilities, and the designs were updated accordingly.

This changed once we conducted the private beta.

Learnings from Beta