Google is bolstering its Google Analytics service with a new automated insights offering that uses machine intelligence to find meaningful and actionable data for brands and businesses. Google claims that it will highlight trends “among the thousands of metric and dimension combinations” in a quick and timely manner.
Google unveiled the new stream of AI-assisted insights last week and detailed a few examples of how it could benefit businesses such as retailers. It works by combing through data sets to provide recommendations and will also offer tips and get smarter by reacting to feedback and usage patterns.
“Go beyond simple reporting to view findings and insights automatically, in language you can read: our insight stream enables faster, more informed decision-making that can have real impact on your business,” Google Analytics product manager Ajay Nainani said in an official blog post.
Nainani said that retailers could benefit from the new feature during the upcoming holiday season, as the updated mobile app will now provide users with an idea of the popularity of different products throughout the busy festive period and tell them where ads and content will be the most effective.
In addition to these surface level insights, the automated service will also dig a little deeper by telling businesses with physical stores about local trends, such as where customers are hearing about them and how they are purchasing products and services. These insights should be particularly useful for both SMEs and large corporations.
Google has already rolled out the new feature to Android and iOS, and English-speaking users can access it by navigating to the Assistant screen. The tech giant has focussed its effort on mobile initially, but a web version is expected to arrive for Google Analytics, which is now part of the Analytics 360 Suite, in the near future.
The arrival of an AI-powered automated service on Google Analytics could be an important milestone for business intelligence, as it will finally enable marketers and key decision-makers to make sense of the growing mass of big data and source relevant information in minutes rather than the hours it may have previously taken.