customer experience,Google Analytics Features Put Marketing Objectives Into Action

Gathering data and providing that information to top-level executives is no longer the be-all, end-all job objective of marketers.

Actually translating that data into actionable items that improve your brand health management and, ultimately, increase sales is. 

Testing Engine Beefed Up

Google Analytics says it has produced new tools in its Content Experiments Platform that will help. Its goal is making analytics actionable with a Google Analytics A/B testing engine that is as strong as ever, Google announced today in a blog post.

“Analyzing data to gain insights into your business and marketing efficacy is just step one,” Russell Ketchum, Google Analytics product manager, wrote in the blog post. “Taking action on that data is the all too important next step.”

According to Google, its Analytics users who have linked their accounts to AdSense can now select AdSense Revenue as an experiment objective.

Once set, Google Analytics Multi Armed Bandit optimization algorithms will shift traffic among the experimental variations to achieve maximum revenue in the shortest amount of time, according to Google. The goal of a "multi-armed bandit" is to find the best or most profitable action.

Google’s also added an advanced option to allow even traffic distribution across all experiment variations, it announced.

"Using this feature bypasses the programmatic optimization that Google Analytics provides so it isn’t right for everyone," Ketchum wrote. "If you have an experiment objective that can’t be entirely captured by a content experiment objective, then this new feature might be right for you."

Aim for Better Data Grouping

Google Analytics has been busy with updates the last few weeks. The search giant upgraded its Advanced Segmentation with more granular controls as to how visitors can be grouped. Essentially, it’s all about matching relevant information for organizations side by side with the ability to make strong comparisons (i.e. matching up paid traffic data with historical data).

Another new tool, Data Driven Attribution, includes algorithmic models, looks at the customer journey and generates values to each marketing touchpoint.