In online marketing, there are always discussions about whether and how you can successfully integrate content marketing on your own blog or website. Here, two Google algorithms appear repeatedly in the discussion: Panda and Hummingbird. Although these two algorithms belong to Google’s company secrets, Google itself also gives hints repeatedly on how good (!) content can be written.
Google has wanted to bring about a change in thinking since 2013 (and increasingly since 2017): Content should be of high quality, instead of pure information now also contain applicable knowledge and banish pure SEO optimized texts and articles in search results. Of course, the keywords that specify the article and let it be classified continue to play a weighty role. But keywords and backlinks will lose importance soon. Furthermore, Google has declared war on article spammers. Thus, Google introduced further criteria, so that the article quality – from view of Google – rises. Google speaks in this connection of reader-specific criteria. With this specification, knowledge-oriented elements are to be integrated in contributions, reports, and articles, which have a added value for the reader.
Optimization possibilities for Panda and other Google (AI) algorithms
However, some interesting optimization opportunities can already be worked out today, on the one hand through information provided by Google itself, and on the other hand through the experience of bloggers.
Make sure that your website is filled with informative and above all relevant high-quality content. Panda initiates a check for the absence of errors (links) and the quality of in-depth content). This makes pure enumerations of product features with high keyword density “bad” content for Google today and in the future. Why In-Depth Content? Google explains that just such articles contain a significantly higher half-time value of information than classic, optimized articles and information. Thus, these articles partly remain in the search results for a few years and thus remain on the crucial first page of the search results.
Google thus places a strong focus on editorially well-researched and edited articles with the above-mentioned criteria. Panda can thus reward the work of an editorial team based on a long-term strategy. If customers and readers of their content can rate it or share it socially, Panda will have this noted positively in its rating. This again raises the quality criteria of their content marketing. Here, the provision of white papers and e-books will play a far greater role in the future than is the case today. E-books will replace digital PDF documents.
Social media, such as Twitter, Facebook or Google+, can no longer be ignored today. The recommendation procedures of these social networks lead to viral information structures and rating systems. Make sure that there is a possibility to use just this social distribution of their information. Panda 4.0 explains that with a high acceptance in these media, their brand value will also be communicated much better (quality criterion: brand value).
Critical evaluation of Google’s algorithm
Despite the criteria that have become known for improving the quality of information and Google’s efforts to offer optimized content to all Internet users in the future, critical voices on Google’s information strategy remain rare or even go unheeded.
Google will also present this year on the Google I/O and the developer conference a main emphasis of its research and development achievement of the next years as the goal an AI intelligence from the house Google global in the Internet to implement.
For this, Google of course needs the free (!) assistance of all people who deal with information, knowledge and procedures of information and knowledge networking. Critically it is to be noted further that we follow as editorship ever more the algorithms of Google and not the writing and reading habits of humans. Some critical editorial offices therefore demand that by disclosing the mechanisms of these algorithms by Google, Yahoo, Microsoft and others, it should be possible to distinguish egoistic goals of these algorithms (see NSA affair) from objective methods.
I can only agree with this. We write for humans and not for AI algorithms and BigData infrastructures.