New potential for Google Shopping along the customer journey through MUM

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Reddi1
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Joined: Thu Dec 26, 2024 3:10 am

New potential for Google Shopping along the customer journey through MUM

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MUM is exciting for Google because it gives them new starting points for Google Shopping. When it comes to product-based searches, Google has lost a lot of ground to the large e-commerce marketplaces such as Amazon, but also to smaller specialist providers such as Otto or Zalando. Users who are in the preference phase of the customer journey often search directly for the product on Amazon, for example. This is difficult for Google from an economic point of view, because these users or commercial searches generate the most clicks on ads. Google seems to be having a hard time getting users back here, even though Google has now reopened the shopping search for free product listings.

Most Google users use Google for information-oriented searches in the awareness phase. However, Google is currently losing out to competitors in the preference phase at the latest.


7-stage customer journey model by Aufgesang , © Olaf Kopp

The examples presented by Google make it clear that Google wants to provide users with valuable information in the early stages of the customer journey (awareness and consideration). With the new design ukraine phone number data of the SERPs and the shopping search, Google wants to inspire the user, provide an overview and support them in the purchase process. In other words, accompany them completely through the customer journey so that Amazon and co. also come away empty-handed when it comes to product searches.

This shows that Google has given up the direct battle for product searches in the preference phase and is concentrating on its real strengths: organizing and processing the world's knowledge in a user-friendly format. The big e-commerce platforms cannot keep up here.



MUM: The future of Google search and what SEOs can learn from it
MUM is the next piece of the puzzle for Google on the way to becoming a purely semantic search engine that increasingly understands the context of search queries and content and thus the search intent and relevance of content and content passages.

The development of a usable quantum computer is still a thing of the future, so Google must focus on more efficient technologies such as MUM in order to use the currently lacking computing power for big-scale machine learning. This way, Google can develop its own search systems more quickly without having to take the lack of performance on the hardware side into account. You could say that software development is currently overtaking hardware development.

A breakthrough for commercially usable quantum computers is predicted for the year 2029. We can assume that by then Google Search will be a completely semantic search engine. In other words, keyword-text matching in Google Search will then finally be a thing of the past.

In summary, it can be said:

Google search becomes even more user-centric
Even more semantic
Even more user-friendly, as fewer and fewer clicks are needed to get answers
Even more performant, which primarily benefits Google resources
The Google indexes, which were previously divided into individual languages ​​and countries, will increasingly merge
More and more entities can be recognized via MUM and provided with attributes, relationships to other entities and placed in a thematic context.
Entity types such as publishers or authors can be assigned to more and more content types or media formats, which drives thematic classification and evaluation with regard to EAT.
Marking up content with structured data will become less and less important in the future, as Google requires less and less structured data through natural language processing.
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