Mashable: How it uses the Parse.ly Data Pipeline
As a digital-only, startup media company, Mashable has always relied on data to help inform its editorial choices. Mashable had used another third-party data provider to store view log data. Accessing that data often took multiple days, a process that frustrated the data science team.
In 2016, Mashable integrated Parse.ly’s raw data pipeline with the goal of obtaining more granular information about its data. The Mashable team was able to push this data to BigQuery, its data warehouse, and scale its infrastructure to help uncover specific and actionable information to benefit its editorial team.
In this case study, you will learn:¶
- How content-level data benefitted the data science, editorial, and business teams
- How Mashable enriched data by combining data sets
- How the Data Pipeline alleviated the time cost of retrieving data
Download the Case Study
Here you go!
How audiences find articles, by topic
How audiences find articles varies by topic. Learn what implications this referral data has for your content strategy.
Exploring the impact of formats on audience metrics
Parse.ly investigates the success of video and other common media formats