Zulily isn’t your typical online retail outlet-it’s all about discovery and a fun, exciting shopping experience. Our customers don’t come to us for a transactional purchase. They want to find the next great deal on designer shoes for themselves, a gift for a loved one, or a great kitchen item for their household.
The only way we can keep people coming back again and again-and keep building our business-is creating an incredible experience for each customer. And that takes data and analytics to make it happen. We have to be predictive and responsive with our data to create those lifetime relationships.
Analytics is central to our work at Zulily. We all rely on data to drive progress, even those in non-technical roles. Our data-driven culture didn’t just happen overnight. It takes a commitment to the technology, innovative approaches, and workflows to make it happen.
Our team has found the integration of Tableau and Google BigQuery to be a game-changer; in fact, we all feel like “data superheroes” with the tool. We are achieving many new ways to better leverage our data, uncover new insights, and save tons of time. Here are some of the lessons I’ve learned and how you can you’re your work more productive and effective and become that data superhero, too.
Make It Easy and Accessible
My main goal with the Tableau and BigQuery integration was to provide our business partners, like our marketers, with access to user-friendly and self-service views of data. I always want them to be able to consume any of the data on a daily or even intra-day basis for better decision-making and optimization.
Let’s take marketing for example. There can be a large gap with the technical skill sets required to consolidate, enrich, and analyze all of the complicated information from different channels-whether it’s Google, social media, email, and more. Tableau is an easy-to-use, self-service tool, and our entire organization uses it to visualize data. Plus, you can save so much time with the automatic updates of data and the fact that marketers can now make faster decisions with that up-to-date data.
And the best part for my team? We can do more meaningful work around strategies and experimentation for the marketing team instead of just manually creating reports for several hours each week.
Automate the Flow from Marketing Data Sources
So how exactly could we get to the point of delivering these new results? Our Zulily analytics function is quite unique because we actually do have all of our data centralized, and we support different teams across the organization. We also have a team that centralizes data from various marketing data sources-such as website engagement metrics, purchase information, and much, much more-into Google BigQuery. I can’t do my job without them, quite frankly.
My team takes this data to pull the statistical learnings, which is really helped by the Google Cloud infrastructure and embedding a handler query. The output is placed directly in BigQuery, and we use additional SQL and Python codes to construct reports, build up trajectories, and run statistical testing. From this, we create additional BigQuery tables to feed in Tableau. After that, our analysis and reports are now prepared, formatted, and available for marketers in Tableau. It’s a tremendous way to automate the data deployment, simplify the analysis, and deliver the easy-to-consume results to the end user.
Save More Time and Focus on the Customer
Time is a precious resource for both our analytics and the marketing teams. The automation with Tableau and BigQuery gives us much more time to focus on building loyalty with both new and existing customers.
We have now built a testing and learning culture because we can easily monitor results with Tableau. We can also react to customer behavioral changes on the fly and deploy any tactics that may show promising signals-all at a very large scale. And we are able to move very quickly based on dynamic information as well. It doesn’t matter whether it’s Cyber Monday or it’s a regular Wednesday.
With the integration and all of the tools available, analysts can use their day to really derive insights instead of querying everything. For example, it used to take me a whole day to query, summarize, and report out customer lifetime value. Now, I only spend an hour to investigate and share the same analysis with the same quality. That gives me even more time to save the day for other strategic marketing insights.
Hear more from Angela and learn about additional benefits of Tableau and BigQuery together by visiting the Salesforce + Google Virtual Adventure.