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It’s been two weeks since the official roll out of Google’s new Search Analytics API for the Search Console, and webmasters have had more than enough time to get accustomed to the new system. Now, the search giant made another announcement regarding the eventual withdrawal of support for CSV download scripts.
The phasing out of CSV support will be a gradual process, with October 20th being the final day that scripts will continue to work. This more than three month period should give webmasters ample time to migrate their scripts towards the new Search Console API. But, why would Google withdraw support from CSV download scripts when options such as Python have served webmasters well enough in the past?
It all begins with the prior rollout of the Search Analytics API. According to Google, they decided to introduce the Search Analytics API because of the positive feedback on the Search Analytics feature in the Google Search Console.
What makes the new API special is that it allows SEO services to run queries over their Google search data and see how often their properties appear on search data through various filters.Webmasters can greatly improve their property’s search performance by knowing how the traffic changes over time, where it’s coming from, and which queries are most likely to show their properties.
The best part of the new API is that webmasters who have experience with using any of Google’s other APIs, or any existing Search Console APIs will be able to use the new system easily. In fact, many of the example codes available still use Python as the basis, since this is the most common script that webmasters can relate to. In fact, the existing guide for running a sample query with the Search Analytics API still uses the Python client library and script to help guide webmasters without experience in the new tools.
This is understandable considering how new the Search Analytics API is; webmasters are still experimenting with the codes that can work best for their properties. Webmasters are, however, still encouraged to build their own recipes with the API, and satisfy their need to classify new information.Many webmasters even see the phase out as an additional stimulus on Google’s part to push webmasters to explore new avenues and stop depending on CSV scripts.
But, the question still remains, if CSV scripts are so ingrained in the process, why phase it out in the first place?
The biggest problem with continuing support for CSV scripts is that they use the data from the Client Login API instead of the Search Analytics data that the new API provides. This on its own, however,wouldn’t have been enough to push Google to pull the plug on CSV scripts.What really convinced the search giant to withdraw from CSV was the support webmasters gave the Search Analytics API, depreciating the value of the former.
The Search Analytics data is simply more accurate in the sense that it provides a bird’s eye view of search trends across different platforms over time. The comparative ability is what sets Search Analytics apart from other tools, as webmasters andinternet marketers can easily follow the trends of their traffic through Google Search Console. This is something Python and other similar scripts are simply unable to do, because the codes were written at a time when alternative platforms – such as mobile – weren’t as big a factor as they are now.
This isn’t to say that CSV scripts and Python are problematic to begin with; Google has been supporting their downloads since 2011, which says a lot about the quality of the codes. Google simply found a way to streamline their data and provide webmasters with more accuracy in the presentation of the data on their own Search results and traffic over time.
There’s little reason to continue supporting a tool when there’s a superior alternative that’s readily available and easier to access. Only having a single tool also sets a standard that everyone in the industry can follow that will simplify discussion, and save on resources.Focusing everyone’s efforts on one tool puts them on equal footing in terms of data analysis, and automatically puts everyone on the same page when new changes occur in the future.
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