NEWS
YouTube Shares 3 Keyword Research Tips For Videos
YouTube offers advice on competitive keyword research for videos, and answers a number of other questions about its search and discovery algorithm.
In what has become a regular series on YouTube’s Creator Insider channel, a member of the search and discovery team fields questions from users in the first upload of the year.
One of those questions focuses on keyword research and how to gauge which video topics will resonate with users.
Here’s a recap of the questions and answers, starting first with the keyword research question.
YouTube Keyword Research
When researching which keywords to use in a video, what is a good way to gauge the likelihood that it will be surfaced in users’ recommendations?
YouTube recommends these three tactics for keyword research:
- Audience Insights
- Google Trends
- Competitive Analysis
Audience Insights
Within YouTube Analytics is an Audience Insights card that shows creators what other videos their audience is watching.
This can be a useful source for keyword research as you may discover new topics your viewers are interested in that you hadn’t considered before.
Creators should pay close attention to titles and thumbnails of videos surfaced in the Audience Insights card. Analyze the similarities as a way to guide the optimization of your next videos.
Google Trends
This one may be obvious to SEOs, but YouTube recommends Google Trends as a way to stay informed about which topics are popular right now.
With Google Trends you can enter multiple topics and compare their popularity over time to see which once is currently generating the most interest.
Let’s take two enormously popular topics on YouTube: Roblox and Minecraft. Which is more popular right now? Let’s take a look.
You can see how there was a time in September 2020 where the two topics were equally popular, but now the gap has widened and Minecraft is generating the most interest. It looks like Roblox is even declining in popularity.
If you have a few topics in mind and can’t decide which one should be the focus of your next video, Google Trends can help inform your decision.
Competitive Analysis
Another tactic SEOs are familiar with is competitive analysis. This involves entering keywords in YouTube’s search bar and seeing what you can learn from the most successful videos.
Analyze aspects such as titles, thumbnails, descriptions, intros, use of video chapters, ad placement, and so on.
Your goal is to determine not only what encourages users to click on the video, but what keeps them watching until the end.
Other Algorithm Questions
YouTube addresses several additional questions about its algorithm. Here’s a summary of everything else that’s discussed.
Upload Frequency
Is it better to publish videos regularly? Or is it acceptable to let large gaps of time elapse between video uploads?
Ideal upload frequency depends more on the viewers and how much content they’re willing to watch. There’s audiences who enjoy binge-watching content, and others who would prefer to watch a video every few days.
As it relates to YouTube’s discovery algorithm, there’s no single approach that’s going to work for all channels. The algorithm is designed to surface videos based on how users respond when they see those videos in their recommendations.
If you upload content on a regular basis, but those videos go unwatched by a majority of your audience, then that may impact how the algorithm surfaces your videos in the future.
YouTube recommends experimenting to see what works best for your specific audience. Then cater to their viewing habits based on what you learn.
Monetization
Is it true that monetized videos have a greater likelihood of being recommended over non-monetized videos?
YouTube’s search and recommendation system is not able to identify which videos are monetized and which ones aren’t. The advertising and discovery systems are separate from each other.
To answer the question – no, monetization has no impact on which videos are recommended to users. Channels can even turn off monetization temporarily without any impact to video performance.
Taking Breaks From Uploading
Is it okay for video creators to take breaks from uploading videos? Will a channel get hurt algorithmically if there’s an extended length of time between new content being published?
It’s perfectly fine for creators to take breaks. YouTube actively encourages it and cites data to back this up.
YouTube analyzed 40,000 upload breaks that lasted between 8 and 60 days. It found there’s no correlation between upload breaks and a consistent loss of viewership.
Many channels even received higher viewership after taking a break. YouTube’s study found 25% of channels that took a break grew their viewership by 50% after they returned.
There’s no algorithmic penalty for taking a break, and data suggests the longer the break the more positive the change in views. Creators should not feel pressured to upload daily or weekly.
If you’re trying to find an ideal time to take a break, YouTube notes that many creators take breaks in January because that’s when advertising budgets tend to run dry.
For more, see the full video below:
NEWS
OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models
OpenAI has today announced the release of fine-tuning capabilities for its flagship GPT-4 large language model, marking a significant milestone in the AI landscape. This new functionality empowers developers to create tailored versions of GPT-4 to suit specialized use cases, enhancing the model’s utility across various industries.
Fine-tuning has long been a desired feature for developers who require more control over AI behavior, and with this update, OpenAI delivers on that demand. The ability to fine-tune GPT-4 allows businesses and developers to refine the model’s responses to better align with specific requirements, whether for customer service, content generation, technical support, or other unique applications.
Why Fine-Tuning Matters
GPT-4 is a very flexible model that can handle many different tasks. However, some businesses and developers need more specialized AI that matches their specific language, style, and needs. Fine-tuning helps with this by letting them adjust GPT-4 using custom data. For example, companies can train a fine-tuned model to keep a consistent brand tone or focus on industry-specific language.
Fine-tuning also offers improvements in areas like response accuracy and context comprehension. For use cases where nuanced understanding or specialized knowledge is crucial, this can be a game-changer. Models can be taught to better grasp intricate details, improving their effectiveness in sectors such as legal analysis, medical advice, or technical writing.
Key Features of GPT-4 Fine-Tuning
The fine-tuning process leverages OpenAI’s established tools, but now it is optimized for GPT-4’s advanced architecture. Notable features include:
- Enhanced Customization: Developers can precisely influence the model’s behavior and knowledge base.
- Consistency in Output: Fine-tuned models can be made to maintain consistent formatting, tone, or responses, essential for professional applications.
- Higher Efficiency: Compared to training models from scratch, fine-tuning GPT-4 allows organizations to deploy sophisticated AI with reduced time and computational cost.
Additionally, OpenAI has emphasized ease of use with this feature. The fine-tuning workflow is designed to be accessible even to teams with limited AI experience, reducing barriers to customization. For more advanced users, OpenAI provides granular control options to achieve highly specialized outputs.
Implications for the Future
The launch of fine-tuning capabilities for GPT-4 signals a broader shift toward more user-centric AI development. As businesses increasingly adopt AI, the demand for models that can cater to specific business needs, without compromising on performance, will continue to grow. OpenAI’s move positions GPT-4 as a flexible and adaptable tool that can be refined to deliver optimal value in any given scenario.
By offering fine-tuning, OpenAI not only enhances GPT-4’s appeal but also reinforces the model’s role as a leading AI solution across diverse sectors. From startups seeking to automate niche tasks to large enterprises looking to scale intelligent systems, GPT-4’s fine-tuning capability provides a powerful resource for driving innovation.
OpenAI announced that fine-tuning GPT-4o will cost $25 for every million tokens used during training. After the model is set up, it will cost $3.75 per million input tokens and $15 per million output tokens. To help developers get started, OpenAI is offering 1 million free training tokens per day for GPT-4o and 2 million free tokens per day for GPT-4o mini until September 23. This makes it easier for developers to try out the fine-tuning service.
As AI continues to evolve, OpenAI’s focus on customization and adaptability with GPT-4 represents a critical step in making advanced AI accessible, scalable, and more aligned with real-world applications. This new capability is expected to accelerate the adoption of AI across industries, creating a new wave of AI-driven solutions tailored to specific challenges and opportunities.
This Week in Search News: Simple and Easy-to-Read Update
Here’s what happened in the world of Google and search engines this week:
1. Google’s June 2024 Spam Update
Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.
2. Changes to Google Search Interface
Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.
3. New Features and Tests
- Link Cards: Google is testing link cards at the top of AI-generated overviews.
- Health Overviews: There are more AI-generated health overviews showing up in search results.
- Local Panels: Google is testing AI overviews in local information panels.
4. Search Rankings and Quality
- Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
- Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.
5. Advice for Content Creators
- Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
- Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.
6. New Search Features in Google Chrome
Google Chrome for mobile devices has added several new search features to enhance user experience.
7. New Tests and Features in Google Search
- Credit Card Widget: Google is testing a new widget for credit card information in search results.
- Sliding Search Results: When making a new search query, the results might slide to the right.
8. Bing’s New Feature
Bing is now using AI to write “People Also Ask” questions in search results.
9. Local Search Ranking Factors
Menu items and popular times might be factors that influence local search rankings on Google.
10. Google Ads Updates
- Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
- Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
- tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
- WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.
These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.
Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again
Uppdated: It seems that today’s issues with Facebook haven’t affected as many users as the last time. A smaller group of people appears to be impacted this time around, which is a relief compared to the larger incident before. Nevertheless, it’s still frustrating for those affected, and hopefully, the issues will be resolved soon by the Facebook team.
Facebook had another problem today (March 20, 2024). According to Downdetector, a website that shows when other websites are not working, many people had trouble using Facebook.
This isn’t the first time Facebook has had issues. Just a little while ago, there was another problem that stopped people from using the site. Today, when people tried to use Facebook, it didn’t work like it should. People couldn’t see their friends’ posts, and sometimes the website wouldn’t even load.
Downdetector, which watches out for problems on websites, showed that lots of people were having trouble with Facebook. People from all over the world said they couldn’t use the site, and they were not happy about it.
When websites like Facebook have problems, it affects a lot of people. It’s not just about not being able to see posts or chat with friends. It can also impact businesses that use Facebook to reach customers.
Since Facebook owns Messenger and Instagram, the problems with Facebook also meant that people had trouble using these apps. It made the situation even more frustrating for many users, who rely on these apps to stay connected with others.
During this recent problem, one thing is obvious: the internet is always changing, and even big websites like Facebook can have problems. While people wait for Facebook to fix the issue, it shows us how easily things online can go wrong. It’s a good reminder that we should have backup plans for staying connected online, just in case something like this happens again.
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