Artificial intelligence also makes it possible

[sharminakter]

Google Analytics, on the other hand, offers built-in AI features such as Insights and Recommendations. Insights are unusual or significant changes, emerging trends, and other information about your site or app. Recommendations, on the other hand, include customized suggestions that help you get the most useful and accurate information and take advantage of new, relevant features as they become available. You can learn more about Google Analytics’ AI features, for example, on Analytics’ own YouTube channel .

Real-time measurement
AI can track campaign performance in real time, allowing an expert to make necessary changes quickly. For example, if a particular marketing message is not producing the expected results, AI can detect this trend and the expert can make changes to the campaign accordingly.

to automatically drive these changes, for example in Google Ads, but not everything should be left to AI alone, and human assessment is always needed.

For example, in Google Ads, AI aims to maximize results latvia phone data and does not take into account how a website ranks in organic search results. This can lead to media budget being spent on clicks that would have been received without advertising if organic traffic had dropped. You could say that an expert sees the big picture, while AI focuses on the specific task and detail.

“An expert sees the big picture, while artificial intelligence focuses on the specific task and detail.”

Read more about how artificial intelligence is changing Google Ads.

Building a dashboard
Artificial intelligence also comes in handy when more complex code is needed within the tools for measurement. For example, we have built our own tracking code for Google Ads campaigns using ChatGPT, so that we can get information about advertising that is not directly available from the tools. ChatGPT also works as a good code checker if errors are detected in the measurement.