TeeTurtle was founded in 2012 to create ultra-soft t-shirts for gamers, nerds, and pop-culture lovers. Preferring to outsource non-core strengths, TeeTurtle concentrates on what they do best -- designing quirky tees and building a hyper-engaged fanbase.

The Problem

A few months ago, TeeTurtle was preparing to renegotiate a new contract with its logistics provider. “Based on our research, we knew we were paying too much,” said Chuck Pack, Director of Marketing. “We’ve tried to renegotiate shipping rates in the past by leveraging the price cut that other companies could offer. Our existing partner simply pointed to their own low margins and said ‘This is the best we can do.’” This time around, TeeTurtle needed something more solid ⎼ they needed data.

The TeeTurtle team hypothesized that inefficiencies in the shipping process were the reason that their provider was unable to offer more competitive pricing, but they needed to be able to identify the specific pain points leading to this inefficiency.

Choosing the right tool for the job

Identifying these pain points involved joining two disparate data sources ⎼ Shopify order history and shipping costs ⎼ and segmenting them by destination, weight, and shipping method. This was a task that eluded the grasp of simple spreadsheets, so the team began the search for just the right partner.

“We look for partners that offer unconventional solutions that we can customize to fit our specific needs,” said Chuck. “RJMetrics is a very flexible platform, and we knew it was the right tool for the job.” First, TeeTurtle gathered the requisite shopping cart data using the RJMetrics Shopify connector. Next, they uploaded raw data files provided by the logistics company. With all the data in one place, they were ready to begin the analysis.

Chuck Pack, Director of Marketing

“The data clearly revealed the most efficient shipping method for us. Having RJMetrics on our side felt like a superpower."

To check his initial hypothesis, Chuck created a graph to track how weight affects shipping cost.


Immediately, the graph illustrated that TeeTurtle was consistently losing money on packages weighing over one pound. Additionally, wild variability in the cost of packages weighing over six pounds became apparent. Chuck’s hypothesis was correct: there was a frequent mismatch between weight and shipping method. This indicated that some packages were being shipped via unnecessarily expensive methods.

After Chuck segmented the data by shipping destination, he learned that the inefficiencies were exacerbated on international purchases. With this analysis in hand, TeeTurtle had a solid starting point for the negotiation process.

RJMetrics makes it easy to explore your data in an intuitive interface backed up by a lightning fast cache.

Data brings $100,000 savings

When TeeTurtle presented this analysis to the logistics provider, the tone of the conversation changed dramatically. Rather than negotiating rates, both sides set out to determine what the most efficient shipping method was for packages of any given weight and destination. Together, they developed more efficient shipping policies resulting in significant cost savings for both parties.

TeeTurtle renegotiated the contract with impressive savings:

TeeTurtle estimates that, over the next year, this new contract will save them $100,000. “The data clearly revealed where the problem was, and this leveled the playing field. Having RJMetrics on our side felt like a superpower.”