GOOGLE

Will Google Address Advertisers’ Transparency Concerns?

Published

5 years ago

November 15, 2019

will google address advertisers transparency concerns

An overwhelming majority of Hanapin’s State of PPC and Machine Learning survey respondents said that lack of transparency and lack of control were their biggest worries for the role of AI and Machine Learning in advertising. Below are a number of other worries from survey respondents:

Some of the other worries are also correlated to the transparency and control piece, further proving how skeptical we are of machine learning and/or ‘smart’ features.

Personally, I don’t think Google is going to give advertisers more transparency and control when it comes to machine learning.

As we’ve seen in the past, the algorithms tend to improve over time. When the algorithms improve, the performance gets better. When performance is on par with what we were manually producing previously, we adopt more of Google’s automation, despite the lack of transparency and control. That process has worked for Google in the past, so why try anything new?

Where did this strategy come from?

I’ve never worked for Google, so this is purely an educated guess.

I believe Google has 2 main options here:

Give advertisers more transparency and control with smart features while ALSO improving machine learning to drive better performance from ‘smart’ features.
Continue giving us broad descriptions of what ‘smart’ features are doing on the back end (requiring no extra work/money) and focus SOLELY on machine learning to improve the algorithms as fast as possible.

Think about how much time it would take to explain to advertisers how the algorithm on the back end of every “smart” feature is working (transparency). My assumption is that it’s MUCH faster, and cheaper, to focus ONLY on machine learning, improve the algorithms, and drive acceptable performance faster than if Google’s focus was split. When the performance reaches the point where it’s on par with what we’re able to achieve manually, there’s no good business reason for advertisers to not adopt that feature. It’s achieving the same or better performance, minus all of the extra work on our end. So we put down our pitchforks and adopt smart bidding, for example. Google wins, but we’re not mad anymore because the ‘smart’ features are working. Transparency and control are now moot points, at least when it comes to smart bidding.

The same goes for giving advertisers more control. We could NEVER process as many data points as a modern-day machine. So why, in the short-term, would Google invest time and money in a dozen levers we can pull to influence bids when in a few months or years the algorithm will get better results than humans can achieve? At that point, we’ll be okay adopting a feature with fewer controls because it’s hitting our performance goals. It just doesn’t make business sense, from a purely financial standpoint, to invest time and money in levers that advertisers can control.

Sure, Google may lose trust or loyalty from hundreds of advertisers by using this strategy. But have we stopped using Google’s advertising platforms as a result? I have yet to meet an advertiser that has stopped using Google Ads in order to make a point about transparency. And even if they exist, their ad spend was probably a drop in the bucket for Google.

All of that being said, I wonder if we’ll reach a tipping point? Will Google introduce a feature that’s lacking so much transparency that the majority of advertisers refuse to use it, at all?

Do you think something like this has already been introduced?

Food for thought!

PPChero.com

GOOGLE

Google Warns About Misuse of Its Indexing API

Published

2 days ago

September 12, 2024

Max

Google Warns About Misuse of Its Indexing API

Google has updated its Indexing API documentation with a clear warning about spam detection and the possible consequences of misuse.

Warning Against API Misuse The new message in the guide says:

“All submissions through the Indexing API are checked for spam. Any misuse, like using multiple accounts or going over the usage limits, could lead to access being taken away.”

This warning is aimed at people trying to abuse the system by exceeding the API’s limits or breaking Google’s rules.

What Is the Indexing API? The Indexing API allows websites to tell Google when job posting or livestream video pages are added or removed. It helps websites with fast-changing content get their pages crawled and indexed quickly.

But it seems some users have been trying to abuse this by using multiple accounts to get more access.

Impact of the Update Google is now closely watching how people use the Indexing API. If someone breaks the rules, they might lose access to the tool, which could make it harder for them to keep their search results updated for time-sensitive content.

How To Stay Compliant To use the Indexing API properly, follow these rules:

Don’t go over the usage limits, and if you need more, ask Google instead of using multiple accounts.
Use the API only for job postings or livestream videos, and make sure your data is correct.
Follow all of Google’s API guidelines and spam policies.
Use sitemaps along with the API, not as a replacement.

Remember, the Indexing API isn’t a shortcut to faster indexing. Follow the rules to keep your access.

GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

Published

3 months ago

June 30, 2024

Entireweb News Bot

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.

AI

Exploring the Evolution of Language Translation: A Comparative Analysis of AI Chatbots and Google Translate

Published

7 months ago

February 26, 2024

Max

A Comparative Analysis of AI Chatbots and Google Translate

According to an article on PCMag, while Google Translate makes translating sentences into over 100 languages easy, regular users acknowledge that there’s still room for improvement.

In theory, large language models (LLMs) such as ChatGPT are expected to bring about a new era in language translation. These models consume vast amounts of text-based training data and real-time feedback from users worldwide, enabling them to quickly learn to generate coherent, human-like sentences in a wide range of languages.

However, despite the anticipation that ChatGPT would revolutionize translation, previous experiences have shown that such expectations are often inaccurate, posing challenges for translation accuracy. To put these claims to the test, PCMag conducted a blind test, asking fluent speakers of eight non-English languages to evaluate the translation results from various AI services.

The test compared ChatGPT (both the free and paid versions) to Google Translate, as well as to other competing chatbots such as Microsoft Copilot and Google Gemini. The evaluation involved comparing the translation quality for two test paragraphs across different languages, including Polish, French, Korean, Spanish, Arabic, Tagalog, and Amharic.

In the first test conducted in June 2023, participants consistently favored AI chatbots over Google Translate. ChatGPT, Google Bard (now Gemini), and Microsoft Bing outperformed Google Translate, with ChatGPT receiving the highest praise. ChatGPT demonstrated superior performance in converting colloquialisms, while Google Translate often provided literal translations that lacked cultural nuance.

For instance, ChatGPT accurately translated colloquial expressions like “blow off steam,” whereas Google Translate produced more literal translations that failed to resonate across cultures. Participants appreciated ChatGPT’s ability to maintain consistent levels of formality and its consideration of gender options in translations.

The success of AI chatbots like ChatGPT can be attributed to reinforcement learning with human feedback (RLHF), which allows these models to learn from human preferences and produce culturally appropriate translations, particularly for non-native speakers. However, it’s essential to note that while AI chatbots outperformed Google Translate, they still had limitations and occasional inaccuracies.

In a subsequent test, PCMag evaluated different versions of ChatGPT, including the free and paid versions, as well as language-specific AI agents from OpenAI’s GPTStore. The paid version of ChatGPT, known as ChatGPT Plus, consistently delivered the best translations across various languages. However, Google Translate also showed improvement, performing surprisingly well compared to previous tests.

Overall, while ChatGPT Plus emerged as the preferred choice for translation, Google Translate demonstrated notable improvement, challenging the notion that AI chatbots are always superior to traditional translation tools.

Source: https://www.pcmag.com/articles/google-translate-vs-chatgpt-which-is-the-best-language-translator