Digital Marketing: latest News from the World – January Part 5
Welcome to our blog, where innovation meets strategy in the dynamic realm of digital marketing! In this post, we’ll examine the latest developments and emerging trends that are transforming the digital landscape. From recent updates in social media algorithms to AI-powered marketing techniques, these changes offer exciting possibilities for brands and marketers.
Get ready to learn how these advancements can revolutionize your campaigns, broaden your reach, and boost your ROI. We’ll analyze the key developments shaping the future of digital marketing, offering detailed insights to help you stay ahead in this rapidly evolving field. Don’t miss this comprehensive look at the current trends and news that are at the forefront of digital marketing!
Update to evaluate your quality in Google
Google has released on January 23, 2025 an update to its Search Quality Raters Guidelines, a fundamental document that serves as a reference for the external evaluators hired by the company.
These evaluators are tasked with analyzing the quality of Google’s search results, providing valuable information on how the platform rates content and what factors it considers essential to improving the user experience.
While their evaluations do not directly influence the ranking of websites, their ratings provide key insights that help Google refine its search algorithms. Recently, Google has released a major update to these guidelines, introducing significant changes that SEO professionals should be aware of and take into account.
In this article, we will explore in detail what these guidelines are, what has changed in the latest update and how these adjustments can impact search engine optimization strategies.
What are the Search Quality Raters Guidelines?
The Search Quality Evaluator Guidelines is an internal Google document that serves as a guide for external evaluators hired by the company. These evaluators are tasked with analyzing and rating the quality of search results, providing feedback that helps Google understand how its algorithms work and identify areas for improvement.
Although these evaluators do not have the ability to directly change the ranking of websites, their ratings are critical for Google to adjust and refine its ranking systems.
The primary goal of these guidelines is to ensure that search results are useful, relevant and of high quality for users. Through raters’ comments and evaluations, Google can determine what type of content best meets users’ needs and how to optimize its search engine to provide a more satisfying experience.
In addition, these guidelines serve as a reference tool for content creators, allowing them to self-assess whether their material meets the quality standards that Google values.
In short, Google’s Search Quality Evaluator Guidelines not only guide evaluators in their work, but also provide valuable insights for SEO professionals and content creators, helping them to align their strategies with Google’s expectations and ultimately improve their visibility in search results.
What has changed in the new updated Search Quality Evaluator Guidelines?
The latest update to the Search Quality Evaluator Guidelines, released on January 23, 2024, has introduced significant changes, many of them focused on fighting spam and improving the clarity of the document. These adjustments reflect Google’s commitment to content quality and user experience. Here are the most relevant changes:
1. Focus on spam and page quality
Updated Page Quality sections:
The Lowest and Low quality pages sections have been revised to better align with Google’s spam policies. This includes the addition of illustrative examples to help evaluators identify low-quality or spammy content.
New subsections on spam and low-quality content:
4.6.3. Expired Domain Abuse: Replaces the previous section on automatically generated content.
4.6.4. Site Reputation Abuse: Replaces the previous section on non-value-added copied content.
4.6.6. MC Created with Little to No Effort: New section addressing low quality content, with no originality or value to users.
2. User Experience Changes
Filler as a Poor User Experience:
The section on distracting ads has been replaced with a new subsection that focuses on filler content that detracts from the user experience. This reflects a greater emphasis on overall page quality and user satisfaction.
3. Expanded guidance on search intent (Needs Met Ratings).
- Guidance on how to evaluate minor interpretations and users’ search intentions has been expanded.
- New examples have been included to clarify these concepts and help evaluators make more accurate decisions.
4. Scoring range update and other minor changes.
- Updated scoring ranges: The scoring system has been revised to ensure that evaluators follow the guidelines consistently and accurately.
- Removal of obsolete examples: Removed examples that are no longer relevant.
- Correction of typographical errors: Improved clarity and accuracy of text.
- Updated browser requirements: Technical adjustments to ensure that evaluators use up-to-date tools.
Social Network
Threads also joins the announcements
For the past 18 months, the same number of months that Threads has been live, Meta’s alternative to X has been happily emancipated from advertising. However, Meta’s subsidiary has decided to call time on its advertising abstinence and is already experimenting with introducing ads on Threads.
Adam Mosseri, head of Instagram, recently announced that Meta has started a “small test” to show advertising on Threads. Once this social network is more or less consolidated, Meta has made the determination to start monetizing it with ads.
As Mosseri explained, advertising will make its way into the user’s feed in the form of posts with images that will be interspersed between posts of an organic nature. For the time being, ads on Threads will only reach the eyes of a small percentage of the social network’s users in the United States and Japan.
Meta’s intention is to kick-start Threads advertising in these two countries with the support of a few advertisers. “We know there will be a lot of feedback on how Threads ads should take shape and we want to make sure that their look & feel is similar to that of organic posts and provides a home for relevant and interesting content,” emphasizes Mosseri. “We will closely monitor this initial small test before a more massive launch to ensure that Threads ads are as interesting as organic content,” he says.
In bringing advertising to Threads, Meta will rely on its powerful advertising infrastructure. And advertisers will be able to expand their existing campaigns to Threads without the need to upload ad hoc content or additional resources. All they need to do is check one of the boxes in Meta’s ad manager.
Meta’s ad testing on Threads will be restricted to the US and Japan
Meta will also experiment with its “inventory filter” on Threads, a tool that allows advertisers to control the level of sensitivity of the organic content next to which their ads are placed. This tool will prove particularly important for brands in the coming months, as Meta announced a few weeks ago that it would relax its content moderation policies in the United States, where the company will dispense with fact-checking organizations.
Although the advertising test undertaken by Meta on Threads is small in size, the company will presumably have a fairly easy time convincing advertisers who already trust Facebook and Instagram to also place their trust in its particular replica of X, which already has 300 million users worldwide.
The emergence of advertising on Threads has been speculated for several months now. In November last year, rumors surfaced that ads would debut on Threads in January. Even at that time Meta said, however, that it did not expect to earn truly significant revenue from the sale of advertising on Threads until the end of 2025.
Digital Marketing
Google launches Meridian: a new open source marketing mix model
Google announced the global launch of Meridian, an open source marketing mix model (MMM) designed to enable marketers and advertisers to measure the impact of their cross-channel strategies and their influence on key outcomes, such as sales growth. The tool, which has already been used successfully in a limited availability period starting last year, is now generally available globally.
What is Meridian?
Meridian is a Marketing Mix Model (MMMs), also known as the “4Ps” of marketing: Product, Price, Place (Distribution) and Promotion. Developed by Google, it aims to modernize the measurement of advertising impact. Being open source, Meridian offers a transparent and customizable solution, allowing users to adjust the code according to the specific needs of their business. In addition, it incorporates innovations such as video reach and frequency analysis, along with calibration of results based on real-world experiments. These features enable more accurate and actionable analytics, providing reliable data that facilitates strategic decision making.
In addition, Meridian improves ad budget management by analyzing campaign performance based on key performance indicators (KPIs) and incorporating detailed data from Google. Backed by a network of certified partners, the tool integrates technological innovation with a data-driven approach, providing solutions to address today’s marketing challenges.
Key Features
As marketers face the increasing complexity of measuring the impact of their multichannel strategies, due to fragmented media consumption and changes in privacy, Marketing Mix Models (MMMs) are gaining relevance. In turn, they help measure how strategies impact key outcomes such as sales. According to a Kantar study, 60% of U.S. advertisers already use MMMs, and 58% of non-users are considering implementing them.
In this context, Meridian is distinguished by four main characteristics:
- Innovation: it introduces new methodologies to obtain more accurate and useful results, considering factors such as the results of experiments and the frequency of exposure to ads.
- Transparency: being open source, it allows users to review and adapt its inner workings to fit their specific business needs.
- Action: not only provides data, but helps turn it into strategic decisions by identifying the most effective channels and optimizing budget efficiently.
- Education: includes guides and expert support so that users can maximize the tool’s potential and improve their campaigns.
With these features, Meridian redefines the way marketers measure, analyze and optimize their strategies. As such, Google has launched a partner program with more than 20 certified agencies, such as Analytics Edge, to provide global support. These partners help implement Meridian, optimize investments and customize metrics for each business. In addition, they gain access to more detailed MMM data for Google media.
Case Study
Finder, an Australian finance company with a presence in the UK, US and Canada, has customized Meridian to suit its needs: “At Finder, our mission is to help people make better financial decisions and we try to apply that approach to everything we do, including our own marketing. With Meridian, we now have much more confidence in our ability to measure the impact of our investments. This has allowed us to go from investing time and resources in building linear regression models from scratch, to an agile, world-class solution that our team can still own and manage. The insights we’ve gained have reinforced the additional value that YouTube drives beyond what is visible with standard conversion tracking,” commented Jennifer Snell, General Manager of Marketing and Loyalty at Finder.
With Meridian, Google is looking to modernize marketing measurement by offering a transparent, innovative and actionable tool. It aims to optimize and maximize the impact of campaigns, as well as facilitate a better understanding of their value, integrating advanced methodologies and fostering collaboration in an increasingly complex environment.
Study reveals Google AI Overviews appear in 74% of problem-solving searches
Did you know that Google AI Overviews can influence your digital visibility? According to the source, they appear in 74% of problem-solving searches and 30% of total searches. In this article we tell you how they work, in what type of queries they are most frequent and what steps you can take to optimize your content.
AI Overviews are not so common, but very influential
The new study indicates that AI Overviews were only shown for 29.9% of the 10,000 keywords analyzed. However, they represent 11.5% of the total search volume. This data reveals that, while they are not present in all queries, they can grab much of the user’s attention when they do appear.
These previews reportedly occur most frequently in medium-volume search terms – between 501 and 2,400 monthly searches – where 42% showed AI Overviews. On highly competitive words, they don’t trigger as much. To dig deeper, you can review the data section in our research area.
User intent and industry make a difference
The study highlights that queries based on questions or designed to solve problems trigger AI Overviews the most, at 74% and 69% respectively. On the other hand, navigation-type searches – looking for a specific brand or website – rarely trigger these views.
The Telecom category tops the list with 56% of keywords associated with AI Overviews, while Beauty & Cosmetics barely reaches 14%. This suggests that certain sectors, with more complex processes, could benefit from creating content aimed at resolving user queries.
Generic terms outnumber brand terms
According to reports, 33.3% of non-branded searches display AI Overviews, compared to 19.6% of those that include branded terms. This pattern seems to indicate that users are looking for more comprehensive information or advice before making a purchase.
For brands, appearing in these early AI Overviews can shape user perception at an early stage. At the same time, it could lengthen the purchase cycle, as people consume more data before deciding. If you’re interested in content strategies for these phases, check out our article on marketing funnel.
Impact on traditional organic results
Once the user clicks “Show more” within the AI Overview on desktop, the page scrolls about 220 pixels down. On mobile devices, barely one or two organic listings are seen without scrolling. This forces SEOs to look for additional methods to stand out.
If your goal is to not get left behind, it pays to ensure your presence in both AI Overviews and organic results. Otherwise, you run the risk of losing visibility in an interface that devotes more and more space to these AI overviews.
Relationship with positioning and Featured Snippets
The report notes that a high search ranking increases the chances of appearing in AI Overviews, but it is no guarantee. About half of the pages that rank high are also included in these summaries, although others that are not in the Top 10 may also come up.
As for Featured Snippets, having one means more than a 60% chance of appearing in an AI Overview. Even so, the correlation is not absolute. This picture points to the importance of comprehensive optimization, covering traditional SEO and efforts in generating authoritative content.
The role of trust and YMYL topics
Sites recognized for their expertise, especially in areas of finance and health, tend to appear in AI Overviews more frequently. This confirms that credibility and quality are determining factors for Google to show your content in quick answers.
In contrast, popular forums such as Reddit and Quora, despite having high rankings, are seen less in these overviews. According to the research, Google prioritizes sites with more verified and reliable information, reducing the presence of user-generated content.
Conclusions and future perspectives
Although AI Overviews are found in less than a third of searches, their influence is especially felt in queries focused on solving specific problems or doubts. If your industry involves a lot of analysis or high-value details, you are likely to see increased competition to appear in these views.
SEO specialists should prepare strategies that encompass optimization for Featured Snippets, authoritative content and deep understanding of user intent. As Google improves its language models and collects more data, the spaces reserved for artificial intelligence could expand, increasingly impacting the way digital marketing is done.
artificial intelligence
Microsoft, Google and Perplexity integrate DeepSeek R1 model into their platforms
DeepSeek-R1 is an artificial intelligence (AI) model developed in China that is attracting the attention of the scientific community and the technology sector. The development is positioned as a cheaper and more accessible alternative to algorithms with advanced reasoning capabilities, such as OpenAI o1.
The algorithm, created by the startup DeepSeek, has a performance similar to that demonstrated by the most advanced system of the firm led by Sam Altman when solving mathematical, chemical and coding problems, according to a technical paper published in the journal Nature. The model achieves 97% accuracy in solving math challenges evaluated with the MATH-500 benchmark and outperforms 96% of human participants in the Codeforces initiative’s programming tests.
DeepSeek-R1 amid tensions between China and the United States
The program, like its U.S. counterpart, processes requests through “thought chains” that emulate human reasoning processes. It was trained based on the operation of the V3 chatbot, also from DeepSeek, using reinforcement learning techniques, where engineers rewarded the system for arriving at a correct answer and describing its “thinking” in resolution processes. The researchers also used an “expert mixture” architecture, which enables the model to decide which processing networks to activate for each task.
The methodology resulted in a training cost of about $6 million, according to some experts. The figure is significantly less than the more than $60 million that Meta spent to train its Llama 3.1 model. The savings in computing resources drastically reduces access prices for users. Using DeepSeek-R1 costs one-thirtieth of what it costs to use OpenAI o1.
Mario Krenn, director of the Artificial Sciences Laboratory at the Max Planck Institute, points out that “an experiment that cost more than £300 with OpenAI o1 can now be done for less than $10. This is a dramatic difference that will influence future adoption [of the Chinese algorithm].”
DeepSeek-R1 has been released under a Massachusetts Institute of Technology license as an “open-weight” tool. This means its thought chains are accessible to researchers and the model can be reused without restriction. It is not fully considered an open-source product, because its training data is not available. Despite this Marco Dos Santos, a computer scientist at the University of Cambridge, says that the program’s accessibility “allows a better interpretation of the model’s reasoning processes.”
Experts point out that DeepSeek-R1 has been built despite strict export controls imposed by the United States. Former U.S. President Joe Biden earlier this month unveiled a program to further limit the shipment of artificial intelligence chips and base models to China and other countries. François Chollet, AI researcher and creator of the Kera deep learning library, emphasizes that “the fact that DeepSeek-R1 is coming from China shows that resource efficiency is more crucial than mere computational scale.” For his part, Alvin Wang Graylin, global vice president of HTC, concludes that “the advantage the U.S. once perceived itself to have has shrunk. Both nations must take a collaborative approach to developing advanced AI rather than perpetuating the current sterile arms race competition.”
Latest Tech and Digital Marketing Updates
📌DeepSeek: the Chinese AI that has revolutionized everything. This startup has developed a super-efficient and economical open source AI model. A bombshell that has had a huge impact on Wall Street, affecting giants such as Nvidia or Microsoft.
📌Google clarifies of this SEO thing. John Mueller has confirmed that alt text should prioritize accessibility before SEO. While it may benefit SEO, accessibility is the key to optimizing this element.
📌YouTube’s algorithm in 2025. They have updated their recommendation system, integrating AI and new satisfaction metrics such as likes and polls. In addition, they can highlight older videos if topics of interest resurface.
📌Performance Max is improved. Google updates this tool: campaign-level negative keywords for all advertisers, adjust campaigns by age and device type, high-value customer targeting, and improved reporting.
📌Buzz of the week. In order for TikTok not to have to shut down the app in the U.S., it will have to be sold. Well, the names that have sounded like candidates have been: youtuber MrBeast, Elon Musk, investor Michael O’Leary and Perplexity AI.
📌I want to grow… then I’m expanding! Wetaca, after 10 years of success in Spain, are ready to make the leap to Germany. Tip: first optimize your local market, plan digital strategies and build a solid base to expand.
📌More news about DeepSeek R1. Microsoft has also integrated it into the Azurem catalog and, in addition, it leads downloads in the App Store.
📌X wants to be good for everything. They have teamed up with Visa so that the social network can also be a payment platform. This would arrive this same year.
📌Record figures. For the first time, the price of ads in the 2025 Super Bowl will exceed $8 million (for 30 seconds of advertising). Next to nothing.
📌The winners of the TikTok Spain awards. The TikTok Star of the year is @elefutbol, the TikTok Pro is @almucarrion, Public Figure of the year @lamine.yamal and the video of the year “@juanki.municio and his grandfather go to the Euro Cup final”.
📌Alibaba also wants the best AI. They have launched a new AI model, and they claim that it is better than those of OpenAI and DeepSeek. It’s called Qwen 2.5 Max.
📌One of the collaborations of the moment. Adidas and the artist Bad Bunny, to shape the Ballerina Benito.
