How Flickr uses Snowplow data to improve profitability

Background

Flickr, the largest photographer-focused community in the world, was founded in 2004 and has since grown to over 100 million registered users and offers free and paid accounts. In 2018, Flickr was acquired by leading photo management platform SmugMug.

Challenges

Prior to the SmugMug acquisition, Flickr was using Adobe Analytics to extract user data. With such a large number of free users, the potential to convert free users into paying customers was significant and would breathe new life into Flickr if successful. However, converting free users into subscribers is not an easy task. It requires detailed user insights so data and marketing teams can adjust the user journey to optimize conversion rates.

Solution

SmugMug’s data team had long used Snowplow’s Behavioral Data Platform (BDP) and quickly introduced Flickr to it after the acquisition. At first glance, Flickr recognized that Snowplow BDP was capable of collecting the rich, granular data needed to optimize the user journey for conversion in a way that Adobe Analytics could not. The organization recognized the opportunity to use Snowplow BDP to build predictive models to identify a set of circumstances that make it more likely that a free user will convert to a paying customer.

Since the platform’s launch, the company has reaped several benefits:

Analytics and Insights Sharing

Flickr uses Snowplow BDP for analytics and insight sharing. Snowplow data is pushed to Amazon QuickSight, where Flickr’s data team has created dashboards and tracking for employees. In particular, the marketing team uses these dashboards to deliver personalized product experiences that improve conversion rates and reduce customer churn.

We use Snowplow for analytics. We build dashboards, tracking, and we also have a data catalog. With Snowplow, we are able to collect data on subscriptions, passive and active engagement. I look at the data daily and share insights with the entire organization about what’s working and what’s not, and present it in our all-hands meetings.”

NINA NORIEGA-SAITO | PRODUCT MANAGER, FLICKR

Increased Data Confidence

Snowplow BDP provides Flickr with a great way to accurately understand user behavior. For the first time, the company can see the entire situation that leads to a particular user action. For example, Flickr can see how likely a user is to churn based on the number of photos uploaded or deleted.

By capturing state as well as events, we have much more confidence in the underlying data and can create a larger number of queries without using additional tools.“

NINA NORIEGA-SAITO | PRODUCT MANAGER, FLICKR

Funnel Conversion

Flickr’s product and design teams use Snowplow data to understand feature performance over time. This capability proved useful when the company launched a new version of its subscription checkout.

We were able to understand the conversion trends of the new checkout for different user personas. As a result, our product and design team decided to support more digital wallets like Apple and Google Pay because the data showed the need for a faster, more seamless payment method for our mobile users.“

NINA NORIEGA-SAITO | PRODUCT MANAGER, FLICKR

Propensity Modeling

Most importantly, Snowplow BDP has enabled Flickr to meet its desired use case of propensity modeling.

Propensity modeling is a type of statistical analysis that helps predict the probability of an event occurring based on a set of variables or factors. In the case of Flickr, Snowplow data is used to create propensity models to define a set of circumstances that make it more likely that a free user will switch to a paid Pro account.

Results

Using Snowplow data, Flickr has increased its conversion rate from free to paid users. It has also succeeded in creating a more personalized user experience, which has contributed to a reduction in the churn rate of paid users.

Crucially, these statistics represent a step in the right direction to increase Flickr’s profitability. And with Snowplow BDP, Flickr can introduce new use cases that will further improve the user experience and encourage more free users to opt for a paid Pro account.

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