Case studies

How KoStop became the hottest spot among UC Berkeley students

The challenge

Berkeley is a tough market to break into from outside. Students are loyal to the spots their friends already go, and there's a long list of restaurants in walking distance competing for the same dining decisions. KoStop had the food and the menu, but no presence in the student social graph.

The blank-spreadsheet question was: how do you become the place a Berkeley student takes their friend to for lunch — when neither the student nor the friend has heard of you yet?

The playbook

The Splash Party adapted for a student market means working through the social structures students already trust: clubs, friend groups, and tightly-bound communities. The campaign:

• Reached out to 10 student clubs. Each got a coordinated invite with tracked codes, framed around the club's specific cohort.
• Concentrated the event into a single window. 70 guests inside 2 hours isn't an average — it's an intentional density designed to make the restaurant feel like the place to be that afternoon.
• Captured every attendee. Each tracked code went with a known student, a known club, and a known meal. The campaign didn't end when the party did — the data did the next round of work.
• Designed for spillover. Student club events are inherently social — attendees post their own content, tell roommates, and bring next week's lunch group.

The numbers

• 10 student clubs represented at the Splash Party.
• 70 guests in 2 hours — concentrated, not spread out.
• A new ongoing lunch rush at KoStop after the event, driven by the student traffic the party introduced.

Why this kind of moment compounds

A single Splash Party in a student market isn't a campaign — it's an introduction. Once 70 students from 10 clubs have had a meal at your restaurant, the word-of-mouth network does the rest of the work. The lunch rush after the event isn't accident; it's the predictable second-order effect of seeding a connected community with a memorable shared experience.

The math is straightforward: the cost of bringing 70 known customers in once is far lower than what it would cost to acquire them through generic ads over several months. And the lunch rush they brought back amortizes the campaign cost across every subsequent visit.