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Modern Data + AI Integration:Strategies and Architectures

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Announcing Snowflake and Redshift Integration with Nexla

Nexla supports Snowflake integration and Redshift Integration

Nexla is happy to announce that Amazon Redshift integration and Snowflake integration are now available. With a simple configuration in the Nexla UI, stream your data from tables in Redshift or Snowflake. You can also map attributes to tables to send data to Redshift or Snowflake. Snowflake or Redshift integration has never been easier.

Integrating more data sources into your analytics database can unlock sophisticated analyses. That’s exactly what happened when Poshmark chose Nexla to easily integrate customer support data into Redshift. In this post, we explain how we teamed up with our partner, Looker, to help Poshmark enable more advanced analytics.

Poshmark Powers Customer Support with Nexla, Redshift, and Looker

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.

Redshift Integration Enables More Advanced Analytics in Looker

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.

Redshift integration with Nexla and Looker

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.

A Data-Driven Future

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.

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
  • Leveraging user/order tags to identify opportunities to continue to provide highest level of service to their community
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.

Easing data integration pains is our passion, and we’re glad to be able to help Poshmark continue their business successes. In this case study, learn more about how Poshmark streamlined its data operations to maintain its top-notch level of customer support with less manual work.

Download the Poshmark case study here.

Check out Looker’s post here.

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