Riva

During my last semester of college, I worked part-time at Riva, a salary negotiations startup. I work with the CEO Ben Cook, who is a Duke alum.

Riva connects clients (who seek help with salary negotiations) with their suite of in-house coaches (who give the help). Coaches get paid based on the negotiated salary increase that they helped secure.

Ben constantly had his hands full, so my job in a nutshell was to offload some things off his plate that he just did not have the resources to get to. In other words, I was a do-it-all, just-figure-it-out type of intern. Below are two examples of projects I worked on during my time at Riva.

Price Structure Clarity

The “how we price” page used to direct to a “legal” page that was basically a wall of text. I was tasked with overhauling this page so we could communicate the concepts in a clear and concise way. My work eventually became the How We Charge page on the company’s website.

The original page detailed various compensation package scenarios and how Riva charges clients if there are non-salary componenents, multiple offers, etc. I used this as a template to rewrite the content to be neater. I also had the idea to include drop-down examples for additional clarification without sacrificing page length. Finally, I designated areas for graphics to visually break up the page to create a smoother reading experience.

Nitty Gritty of the Won Client Pipeline

Through this project, Riva ended up with a better strategy of interacting with clients. I took a look at our “Won” clients, i.e., those who went through the various marketing channels to actually sign up time with a negotiations coach.

Ben had some idea that a good amount of them drop off without any reason, but he wanted to get deep into the specifics of how they behave, for example:

• time from first contact to scheduling the first session
• time between each session, if there are multiple
• reasons for if a client is “Lost”
• proportion of those negoating for their current job vs. a new job
• amount of follow-ups from coaches
• average and median percent change for successful negotiations
• etc.

I aggregated and organized data from HubSpot and Stripe. We used these findings to optimize follow-up negotiations in HubSpot so that the coaches could stay top-of-inbox for the clients. Through this study, I also was able to discern the main reasons for if a client isn’t able to get a salary increase.