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Carpe Doesn’t Sweat Data and Analytics with Daasity

How the antiperspirant brand uses Daasity to customize its analytics and make real time-business optimizations

When it comes to our data, it’s easier to say what we don’t use Daasity for.

Curtis Howland, Director of Marketing

Industry
Health & Personal Care
platform
Shopify Plus
Notable Integrations
Klaviyo, Attentive, Amazon Seller Central, Recharge, Zendesk, TikTok
Challenge
In-house data solution limits, including querying issues and extracting data from sources like Amazon Seller Central, hampered agile monitoring.
Results
  • Consolidated their data within a unified data and analytics environment
  • Saved over 50 hours per week on manual data work
  • Identified a $20k fulfilment overcharge
  • Freed up in-house capacity for dedicated analysis and strategic insights

Data Challenges

Carpe is a pioneering antiperspirant company committed to providing effective relief from excessive sweating. Their proven products, designed for maximum efficacy without irritation, are gentle enough for daily use and strong enough to manage even the most severe cases of sweating. Specializing in solutions for hands, feed, armpits, and more, Carpe caters to the needs of those seeking reliable and gentle antiperspirant options.

The data team at Carpe, despite strong analytical skills, grappled with the limitations of their in-house data solution. Difficultly in querying data and extracting information from key sources like Amazon Seller Central hindered agile monitoring of the company’s performance, highlighting the need for a more efficient data solution.

Before Daasity, our workflow primarily revolved around pulling all our orders and putting them in Excel. We’re a pretty data-heavy team, and I crashed my computer probably daily trying to do some analysis with 500,000 orders.

Curtis Howland, Director of Marketing

Data Solutions

After exploring various data solutions, Carpe opted to partner with Daasity for several key reasons: its high level of customizability - including the ability to write custom queries, a robust Amazon integration, plus the ability to query both Shopify Plus and Amazon data together.

Using Daasity, Carpe was able tt Utilizing Looker, the team crafted customized visualizations and conducted regular queries, particularly on Shopify Plus and Amazon data. Daasity also plays a pivotal role in automated reporting, delivering daily, weekly, and monthly KPI reports tailored to the specific data needs of each team, including marketing, finance, operations, and customer services.

We do a lot of tests onsite to try to increase certain metrics: subscription percentage, retention KPIs, and more. With Daasity, we can track all of those tests and quickly and concisely decide in which direction to go. That revenue and those learnings compound over time.

Sam Hannon, Analytics Manager

“We’re now able to react to changes in the data pretty much in real time. That is extremely valuable. As soon as a KPI changes, we have the ability to react and respond as soon as we possibly can. ”

Sam Hannon, Analytics Manager

The Results

By leveraging Daasity, Carpe has revolutionized their data and analytical efficiency. Enabling real-time tracking and reaction to data changes, the platform has heightened productivity for the analytics team. For example, the team analyzes how many new customers were acquired from Amazon out of their total orders daily. T

his efficiency fosters continuous testing and learning, driving iterative improvements in brand performance and workflow dynamics.

Daasity easily doubles my productivity.

Sam Hannon, Analytics Manager

Centralized

data and analytics alignment

Centralized

data and analytics alignment

50 hours

a week saved on manual data work

50 hours

a week saved on manual data work

$20k

fulfillment overcharged identified

Want to See Similar Results?

Reach out to schedule a personalized demo or try Daasity now for 14 days free!

Want to See Similar Results?

Reach out to schedule a personalized demo or try Daasity now for 14 days free!