Case Study: Powering Community at Poshmark

Case Study: Powering Community at Poshmark

Poshmark Logo

The Challenge:

Poshmark needed more visibility into their customer support KPIs, with less manual effort. In order to properly staff the team and maintain its high level of customer service, accurate current and historical support data is essential.

The Solution:

Using Nexla’s Data Operations platform, Poshmark was able to integrate its customer support data from and leverage Looker to build intuitive dashboards—with no engineering required.

The Results:

  • No more manually updating spreadsheets
  • More time spent on customer support
  • Availability of long term and rich data with all attributes of every single case to inform strategic planning of support functions

“I was happy to find a software solution to solve the problem. It allows us to scale without disrupting anything else,” Barkha Saxena, Vice President, Analytics, Poshmark

Powering Community at Poshmark

Poshmark is the largest social marketplace for fashion where anyone can buy, sell and share their style with others. Poshmark’s mission is to make shopping simple and fun by connecting people around a shared love of fashion, while empowering entrepreneurs to become the next generation of retailers. Recognized as the go-to shopping destination for millennials, Poshmark’s community of over three million Seller Stylists help shoppers discover the perfect look from over 25 million items and 5,000 brands.
Because community is so critical to the business’s success, Poshmark strives to provide the best possible customer support. Proactive monitoring of support KPIs is key to this effort. An understanding of long term trends is also important to appropriately staff the support team.

The Pain of Data in Silos

Poshmark’s support data existed in the portal, but it was not integrated with Poshmark’s core Business Intelligence tool, Looker. The data wasn’t provided in the format required, so the team updated Excel sheets manually. All this led to significant hours wasted per week across all agents, and created the possibility of a human error in manual work.
There was a need to enable access to support KPIs through Looker so that all executive and business stakeholders have single-point access to core KPIs. Specifically, Poshmark’s executive team needed access to check on the number of cases, how they are pending, resolution time, and first response time. Given Poshmark’s focus on providing world-class community support, this information needed to be easily accessible on-the-go via phone.

The Magic of One Source of Truth

“No data engineers were disturbed during the integration of this API.”

The combination of Nexla and Looker was uniquely suited to help Poshmark achieve its objectives. Nexla made it easy to integrate and monitor customer support data via the API, and then send that data to Poshmark’s Redshift database. Integration took less than a day and allowed the data engineering team to continue to focus on other priorities. Once the data was flowing, Poshmark was able to create Looker dashboards and analyses to provide the executive team and other business stakeholders access to critical support data through their core BI platform.
“Prioritization is always a challenge at a growing company. It can be hard to complete integrations in the time we would like,” said Barkha Saxena, VP Analytics at Poshmark. With Nexla, they were able to integrate the API in a few hours, instead of days or weeks. No data engineers were disturbed during the integration of this API. “I was happy to find a software solution to solve the problem. It allows us to scale without disrupting anything else,” Saxena said.
With one API integrated and the data flowing, Poshmark sees many uses for the Nexla platform. The monitoring and alerting features ensure the analytics team is always aware of any data breakages. Poshmark plans to use Nexla for more API integrations so they can “set it and forget it” and never worry about gaps in historical data again.

A Data Driven Future

Now that Nexla is connected to the data sources Poshmark wants to analyze, the team can more easily build customer service dashboards to appropriately staff their team. Armed with access to raw event-level data, the analytics team plans on using this data to work on many initiatives such as estimating the value of customer service (by measuring the changes in customer LTV as a result of a customer touch point), analyzing support data by different dimensions, and user/order tags to identify opportunities to continue to provide highest level of service to their community. All this, while improving their special Poshmark community experience.
This new access to support data from Nexla in Looker will allow the Poshmark team to stop wasting time manually updating spreadsheets, and instead continue to invest in their special Poshmark community experience.

Interested in learning more? Get an introductory demo to Nexla.