PartnerStack doubled data team output by 2.5x

PartnerStack helps partnership teams easily scale their program revenue by automating a variety of partner referral and sales motions in a single dashboard.
Software Development
Company size
Data stack

Data requests were getting lost and going unanswered for the PartnerStack data team. By using Secoda, they've increased data team output and democratized data exploration for the company.

PartnerStack and Their Data

PartnerStack is changing the way the world sells software, working with companies like Secoda to grow and improve through ecosystems.

The data team at PartnerStack has one goal: to democratize data for the entire company as it grows. Brendan McDonald, Data Operations Manager at PartnerStack, is spearheading this goal. He and his team of analysts work hard to empower other teams in the company to: 

  1. Make better, high growth decisions;
  2. Track the results of their actions and activities; 
  3. Improve their performance.

As a unit, the data team fields all of the PartnerStack data requests. They make sure that the workload for these is evenly distributed, and that they never disrupt the bigger data projects that the team might be working on. 

Typical data requests that Brendan and his team would be all over the board– it was typical for finance teams to ask for metrics, context, and data surrounding revenue and earnings, for the product team to make requests around usage and in-app behavior, the customer experience team to ask for customer churn metrics, the list of diverse requests is endless.

The Problem

When Brendan joined PartnerStack three years ago, the entire company was only 20 employees. Since then, the team has grown to over 200, and with that growth came an increasing demand for data. The data team grew to try to meet these demands, but a glaring problem began to arise. Data requests from the rest of the company came with such urgency and from so many different platforms that the team began to lose track of the requests, some never being completed. 

In addition to the lost, untimely data requests, the data team was struggling to establish momentum with their bigger picture data projects that was essential for them to complete on top of external requests from the team. Like many startups, there was no process in place to track and collaborate on these data requests, resulting in lost requests, no metrics on how long these requests took to complete, and multiple interruptions from receiving data requests via direct message. 

As the data team doubled in size, managing the incoming requests effectively became a priority for PartnerStack. In order to complete their larger data initiatives, the team needed a tool to manage data requests, understand how their team was interacting with the data, and distribute the workload of data requests evenly.

The Solution

Enter Secoda. The PartnerStack team was in search of a solution to effectively manage data requests and the analytics to be proactive in data knowledge for the rest of the team. 

Using Secoda’s Questions to manage, track, and respond to data requests.

  • One place for requests and questions: the Questions feature in Secoda provides Brendan and the PartnerStack data team one place to receive and manage requests from the rest of the team. No more interruptions from Slack messages or missed requests.
  • A searchable repository of past questions: recording responses to data questions means that users with similar problems can search to see if their question has already been answered before submitting a request of their own. 

Leveraging User Analytics on Secoda to create better documentation.

  • Curated dashboards and documentation for business users: Secoda keeps track of the data resources that users at the company use the most– so the data team can see which questions, documents, and tables are the most useful. 
  • Feedback loop for better documentation: By understanding which data resources are the most valuable to the PartnerStack team, Brendan and the data team can be proactive and add more context to those resources, meaning less redundant data requests down the line.

The Results

The PartnerStack team now has a process in place for fielding data requests, and SLA’s (service-level agreement) that mean no more interruptions on Slack, increased data team capacity, and better data discovery for the business data users across the company. 

  • Standardized data requests: Using an SLA document that outlines how to submit a data request and when to expect getting it back, Brendan and the PartnerStack data team no longer have their work days interrupted with an urgent data request, and can evenly distribute the workload of completing these requests. This has cut down the average time it takes to finish a data request to less than 5 days.
  • Streamlining work for data analysts: With one place for all of their data requests and a searchable repository of past data questions, the PartnerStack data team is able to focus on their bigger, internal data projects. This has doubled the output of the data team and made scaling up easier. 
  • Self-serve data discovery for team members: One place for all company data knowledge and insights into how the rest of the company interacts with this knowledge means that Brendan and the PartnerStack data team can build better dashboards and truly democratize data. This has resulted in over 100 different documented resources.

Who is Secoda Ideal for? 

For Brendan, Secoda is a clear solution for any data team that has to handle ad hoc data requests from the rest of their company. If you’re finding that the number of requests that your data team handles is increasing, or that you have no metrics or benchmark for how long it takes to answer these requests, it’s probably time to give Secoda a try.

This is because Secoda provides a space for all data requests and questions that arise in the same place that data documentation lives. It also provides powerful insights into how users interact with data resources, so data teams can start to spot trends and be proactive.