Uberflip is a content marketing platform.
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Uberflip and Looker team to bring more value and content to their customers.
- Streamlined internal and external data access with Snowflake, Matillion, Looker, and 4 Mile Analytics
- Eliminated 20% of the product team's backlog of requests for more complex analytics reporting by creating Uberflip Analytics with Looker
- Freed up 15%–25% more time for each customer success manager (CSM) by productizing analytics for customers with Uberflip Analytics, allowing them to focus on strategic projects and provide a great customer experience
- Developed an internal data science model to help predict customer renewals and track feature adoption
Toronto-based Uberflip is a content experience platform that empowers marketing and sales to create engaging, relevant content destinations quickly for every campaign, audience, and stage of the customer journey. Marketers use Uberflip to incorporate content into every touchpoint and create positive experiences by surfacing customers with the right content at the right time.
Uberflip provides business-to-business (B2B) marketers with the capabilities to leverage content more effectively for demand generation, inbound, account-based marketing (ABM), as well as sales and customer engagement efforts.
Uberflip employs Looker’s business intelligence and data application platform to embed analytics into their product as well as deliver data to their internal users. With Looker powering the Uberflip Analytics solution, customers can understand how content and campaigns are performing to optimize their marketing investments.
“We decided to turn those customer data requests into a product rather than having our CSMs manually create ad hoc reports for every request.”—Jon Laba, Product Manager, Uberflip
Determining a need to productize analytics due to process delays and limited flexibility
Previously, Uberflip relied on a homegrown data solution to meet various data requests from their customers as well as internal teams. The data science team had to manually tackle each request for data—taking time to prepare and clean data in order to build each report.
As Geoffrey Hunter, Ph.D. and Director of Data Science at Uberflip, explains, “It took a lot of time to prepare data for various teams. We’d have unannounced schema changes and have to validate data selection. From finding, preparing, validating, and delivering data, it sometimes took up to four and a half weeks to complete requests. Simple tasks were, in fact, quite difficult.” Additionally, it was difficult to test hypotheses or quickly validate data efforts without significant time investments from his team. As Hunter adds, “We could theorize what a dashboard could look like, but we didn’t know if it would be useful until we could look at it with context.”
In addition to internal requests, customers were demanding deeper insights into their content. When customers asked additional questions, their customer success manager (CSM) would make another request to the data team or try to manually create the report themselves. This accounted for 20% of the data science team’s already long queue, took 15%–25% of each CSM’s time, and ultimately meant customers couldn’t have a self-serve data experience or explore insights further in real time.
“Customers wanted to tell a story of how audiences were experiencing content. We quickly outgrew our previous metrics capabilities as more customers started asking to analyze the performance of content and campaigns in more complex and granular ways. This limited our customers’ ability to fully understand and quantify the impact of their content or their investment with us,” explains Jon Laba, Product Manager at Uberflip.
Uberflip knew there was an opportunity to deliver more value to their customers as well as to automate repetitive tasks to improve internal efficiency. The “aha moment” was when the team realized that they could productize analytics by embedding dashboards to build what their customers wanted, increase customer satisfaction, and unlock new revenue opportunities. “We decided to turn those customer data requests into a product rather than having our CSMs manually create ad hoc reports for every request,” shares Laba.
Uberflip needed an analytics solution to drive customer acquisition and value as well as automate external and internal data access as much as possible.
Building a powerful data stack
When setting out to build their data product, which would eventually become ‘Uberflip Analytics,' the product team decided to buy rather than try building their own data solution.
The Uberflip data science and product teams agreed that leveraging Looker’s data application platform would help meet their data needs while also helping to expand their product offering to customers. Both teams liked Looker’s modeling layer, LookML, which provides a collaborative yet governed approach to deliver trusted metrics at scale. They also appreciated the ability to maintain dashboard version control, while maintaining flexibility to customize. Additionally, the product team found that Looker‘s QA fit in with their own development practices, and the data science team liked how Looker would help to simplify their tech stack and processes, while providing additional functionality such as built-in integrations.
Uberflip chose to run Looker on top of Snowflake’s cloud data warehouse, which allows them to decouple the data from compute resources and share infrastructure with separate liabilities.
Uberflip uses Matillion as their ETL (extract, transform, and load) solution. “We wanted full ownership, and we wanted the software to run on our services. Matillion gives us the ability to get low-level control—maintaining our high levels of security and privacy,” says Laba.
The company leveraged the expertise of 4 Mile Analytics, a full-service consultancy specializing in creating custom data experiences with Looker’s data application platform. “It was great to have someone who was knowledgeable—and we could speak to them about Looker guidance,” explains Laba. “We learned a lot by connecting with other customers through 4 Mile Analytics, and we were inspired to further build and customize on top of Looker.”
“When I arrived at Uberflip our director of product at that time said our biggest need was a request for data and insights, which was 20% of our product backlog. We set a giant target to eliminate this backlog and deliver what our customers told us they wanted. With Looker, all of those customer needs are now satisfied, and it's easier to evolve our product as the needs of the customer and the broader market change.”—Jon Laba, Product Manager, Uberflip
Delivering embedded analytics to Uberflip customers
A key focus for Uberflip is helping their customers with go-to-market strategies, including content marketing, demand generation, ABM, and sales and customer engagement. Their platform enables customers to manage content experiences, accelerate the buyer-customer journey, and surface actionable insights from their audience.
Previously, 20% of Uberflip’s product requests came from customers wanting a richer, real-time understanding of content performance. To address these requests and enhance their audience intelligence capabilities, Uberflip leveraged Looker’s data APIs to embed analytics within their platform and create a new product offering: ‘Uberflip Analytics'.
As Laba shares, “When I arrived at Uberflip our director of product at that time said our biggest need was a request for data and insights, which was 20% of our product backlog. We set a giant target to eliminate this backlog and deliver what our customers told us they wanted. With Looker, all of those customer needs are now satisfied and it's easier to evolve our product as the needs of the customer and the broader market change.”
Today, Uberflip leverages Looker to embed analytics directly into their product, providing customers with real-time insights within the context of their platform. Additionally, the Uberflip team can now design and prototype dashboards with real customer data live on customer calls. This allows them to quickly support customer requests and put the customer in the driver’s seat.
Rahim Lalani, Product Marketing Manager at Uberflip, shares, “We can now build value-added services for customers around our analytics offering. Customers who are looking for a greater degree of data customization or one-to-one strategic support can opt for additional functionality. It’s a win-win. Our customers get the insights they need to make timely and actionable business decisions and we can unlock additional value from our offering.”
Laba adds that delivering access to data via Looker has helped significantly with customer retention and expansion, “Some customers had churned because of analytics in the past. Our customers now consider our analytics the strongest part of Uberflip. It’s all here.”
Driving value for Uberflip customers with real-time insights
For Uberflip’s customers, access to real-time analytics means they can immediately see how their marketing content is performing, make critical business decisions, and take action to optimize audience engagement. Uberflip Analytics offering gives their customers several out-of-the-box dashboards, including a Home dashboard that provides a bird’s-eye view of key engagement metrics such as sessions, page views, average time on page, and call-to-action clicks. Uberflip Analytics also comes with purpose-built dashboards grouped around four categories: traffic, content, calls-to-action (CTAs), and visitor behavior. These dashboards provide a real-time look into all aspects of content and campaign performance—enabling customers to make actionable decisions.
“These dashboards enable our customers to zoom into data like never before. Looker’s ability to contextually link dashboards allows our customers to start with a question and keep exploring in a self-serve manner that’s intuitive.” explains Lalani.
Uberflip’s customers have the ability to explore and generate custom reports based on anything of interest—for example, dozens of key performance indicators (KPIs)—and compare it to other campaigns to see how one campaign is performing against another.
“This level of granularity and ability to choose from hundreds of data points is something that’s really valuable for our enterprise customers. They want as much information as possible, and now they can do as much as they want with the information,” points out Laba.
“Looker replaced the manual work of our CSMs by putting together ad hoc reporting. We’ve turned that into a product rather than having them put it together every time.”—Jon Laba, Product Manager, Uberflip
Improving efficiency and transforming the customer experience with internal analytics
In addition to Uberflip customers, their internal teams are discovering value with improved access to data. Previously, when customers wanted additional or custom reports, they made the requests via their customer success manager (CSM). These requests could take months, with CSMs either submitting the request to the data team or manually creating reports themselves. Before Looker, this process was a massive time drain on CSMs—with as much as 15% to 25% of each CSM’s time spent on this activity. This manual process also meant there was no way to ensure that each clients’ report was created consistently.
“Looker replaced the manual work our CSMs had to do to put together ad hoc reporting. We’ve turned that into a product rather than having them put it together every time,” remarks Laba.
As Laba shares, “Looker eliminated the time CSMs need to spend on ad hoc reports; now that’s all automated. Today, our CSMs can focus on actual customer success. We have great operational cost savings. Customers don’t have to wait for ad hoc reports. And it enables our Customer Success team to provide trusted and consistent data to all customers. It’s really leveled up our customer success experience across the board.”
In addition to improving CSM efficiency, access to data has also improved the customer experience.
“Looker has given our Customer Experience (CX) team rich insights into our customer activities. We can understand what works well and things they could improve. It helps our CX team move from reactionary to a trusted advisor role,” adds Hunter. The team now leverages insights to have more strategic and personalized conversations with customers.
For example, the Uberflip CX team has created insights for industry benchmarks. For customers in particular industries, the CX team shares insights and metrics with existing customers about what they’ve seen work best for specific types of companies. They also share these aggregated insights with the sales team to help them better understand the challenges marketers face and be a trusted, data-first partner.
Uberflip has also seen its partners leverage the Looker solution to improve experiences. “One of our customers is an agency partner. They love being able to add their own value. They consult with their customers, build reports, and then deliver. We’ve seen customers use this to build reports and show their customers,” says Laba. “One report used ‘negative analytics’ to give our customers insight into content that was not viewed in a particular time range. This way they can make better strategic decisions about what is not worth future investment.”
Predicting a data-driven future
One of the biggest benefits of implementing Looker has been the creation of an internal data culture. “Since we have unified the data stack, we can have global definitions and then create dashboards and insights for the internal team to use,” says Hunter. The product team now has insights on how products are being used. They can rapidly design, prototype, and experiment with data to continuously improve their product market fit. The data science team appreciates that Looker lets them leverage big data with little operational output and achieve “fast time to value.”
One of the biggest wins for the data science team was leveraging Looker in a data model that has beaten human predictions for likely customer churn. “Looker allows us to easily bring together a ton of datasets in a seamless way across multiple different data sources to predict churn,” Hunter observes. “We are now using it for a model that predicts churn more accurately than human predictions. We’re rolling that out to CX and will extend it into renewals and feature adoption.”
With the successful customer churn model, Uberflip is exploring more use cases to optimize internal models and predictions. The data science team's next project with Looker is focused on continually optimizing internal data engineering processes, and the product team is exploring dashboards to showcase ROI. “With Looker as the global data lens for our company, we can all be on the same page as we continue to find new ways to provide value for our customers,” concludes Hunter.
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Uberflip is a content marketing platform.