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Why You Need To Be Using Google Ads Bid Automation

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why you need to be using google ads bid automation

Bid automation is one of the top debated topics in the digital marketing industry. It’s not a matter of why you should be using automation, but how you are using it to achieve your goals and amplify growth efforts. Over the last few years, Google has recommended that advertisers move to automated bidding strategies to “take the heavy lifting and guesswork out of setting bids to meet your performance goals.” Though automated bidding isn’t perfect, it is a tactic that advertisers need to utilize.

Why Use Bid Automation?

Bid automation takes into account numerous bidding signals that aren’t visible to advertisers and uses machine learning to set appropriate bids. For example, advertisers can set bid modifiers for the time of the day, but not the browser that the searcher is using. These hidden signals are invaluable to advertisers because they help to decipher user intent as part of the bidding process. Manual bidding is slower, uses fewer signals, and is not conducted in real-time. When advertisers give Google the correct parameters and enough data, automated bidding can work effectively.

Two of the more common bidding strategies are Target Return On Ad Spend (tROAS) and Target Cost Per Acquisition (tCPA). With each strategy, you input what your target ROAS or CPA is and Google will optimize for this figure. You can enter your target in the bidding section of the settings. Google will give you a recommended figure if your campaign has enough data.

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An advertiser selling car parts may set a tROAS of 500% in a widget campaign as this figure is necessary to achieve profitability. The axle campaign may be set at a 300% tROAS as sales volume is more important than efficiency. By using these strategies, you need to have conversion tracking in place and have a value setup for these conversions (whether the value is dynamic or static).

The more data you can provide Google the better so the system can make the most informed decisions. For example, Google recommends that for the tROAS bid strategy, you have at least 50 conversions in the past 30 days. With these targets, you should be realistic about the goals. Setting a $30 tCPA in a campaign where the average CPC is $60 is unrealistic.

Once you set these targets, it doesn’t mean that they can’t change. In fact, you should be consistently reviewing the targets and changing as necessary. For example, there may be a sale on widgets where sales volume is now the main goal and efficiency is second. Bid automation unchecked will hurt performance.

When making changes, review at least the last 30 days of performance and/or the previous year’s data. Let’s review a SaaS provider with a tCPA of $125. Over the last 30 days, the campaign has seen a CPA of $120, 200 conversions, and an impression share of 70%. When looking at the forthcoming 30 days the year before, we see a CPA of $150, 250 conversions, and an impression share of 80%. Though we’re currently under our tCPA, we have the potential to see additional conversions if we raise our target. Here’s a table of the additional number of conversions that we may see at various percentage increases.

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The higher we increase the tCPA, the more conversions we see and the higher impression share we will receive. Though Google takes care of all bidding, we’re fueling the automation strategy.

Other Considerations

Not all data should be included in your bidding strategies. You may have had a day where your conversion pixel wasn’t firing correctly. Or, there was an inflated number of conversions one day due to a once a year sale. You can create data exclusions to bar a day(s) worth of data so it will not negatively impact the bidding strategy.

Within the “Bid strategies” section is an option called “Advanced controls.” In the “Data exclusions” tab you can create the exclusion criteria. Here’s an example.

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Data exclusions should be used sparingly and aren’t meant to manipulate bidding strategies. They shouldn’t be used to exclude data from days where the performance was poor. They ensure that your bidding strategies are making use of correct data and nothing more..

Seasonality adjustments are another feature available in the advertisers’ arsenal. They are temporary bid adjustments that override the bid strategy during a period where you expect a higher conversion rate. Google’s recommendation is to apply a seasonality adjustment if the conversion rate will swing by at least 30% compared to what it is normally. A perfect example of this occurrence is on Black Friday. For most advertisers, the conversion rate will skyrocket on this day. Thus, seasonality adjustments overwrite the bid strategy to capture this demand.

Seasonality adjustments can be applied to all campaigns or solely specific ones. They can be set by the hour or for an extended period of time.

Final Thoughts

The core concern with automated bidding is that it takes control away from advertisers. The better way to look at is to understand the numerous benefits it has over manual bidding and the ways advertisers can guide the system.

PPChero.com

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

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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.

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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

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Google Implements Stricter Guidelines for Mass Email Senders to Gmail Users

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Beginning in April, Gmail senders bombarding users with unwanted mass emails will encounter a surge in message rejections unless they comply with the freshly minted Gmail email sender protocols, Google cautions.

Fresh Guidelines for Dispatching Mass Emails to Gmail Inboxes In an elucidative piece featured on Forbes, it was highlighted that novel regulations are being ushered in to shield Gmail users from the deluge of unsolicited mass emails. Initially, there were reports surfacing about certain marketers receiving error notifications pertaining to messages dispatched to Gmail accounts. Nonetheless, a Google representative clarified that these specific errors, denoted as 550-5.7.56, weren’t novel but rather stemmed from existing authentication prerequisites.

Moreover, Google has verified that commencing from April, they will initiate “the rejection of a portion of non-compliant email traffic, progressively escalating the rejection rate over time.” Google elaborates that, for instance, if 75% of the traffic adheres to the new email sender authentication criteria, then a portion of the remaining non-conforming 25% will face rejection. The exact proportion remains undisclosed. Google does assert that the implementation of the new regulations will be executed in a “step-by-step fashion.”

This cautious and methodical strategy seems to have already kicked off, with transient errors affecting a “fraction of their non-compliant email traffic” coming into play this month. Additionally, Google stipulates that bulk senders will be granted until June 1 to integrate “one-click unsubscribe” in all commercial or promotional correspondence.

Exclusively Personal Gmail Accounts Subject to Rejection These alterations exclusively affect bulk emails dispatched to personal Gmail accounts. Entities sending out mass emails, specifically those transmitting a minimum of 5,000 messages daily to Gmail accounts, will be mandated to authenticate outgoing emails and “refrain from dispatching unsolicited emails.” The 5,000 message threshold is tabulated based on emails transmitted from the same principal domain, irrespective of the employment of subdomains. Once the threshold is met, the domain is categorized as a permanent bulk sender.

These guidelines do not extend to communications directed at Google Workspace accounts, although all senders, including those utilizing Google Workspace, are required to adhere to the updated criteria.

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Augmented Security and Enhanced Oversight for Gmail Users A Google spokesperson emphasized that these requisites are being rolled out to “fortify sender-side security and augment user control over inbox contents even further.” For the recipient, this translates to heightened trust in the authenticity of the email sender, thus mitigating the risk of falling prey to phishing attempts, a tactic frequently exploited by malevolent entities capitalizing on authentication vulnerabilities. “If anything,” the spokesperson concludes, “meeting these stipulations should facilitate senders in reaching their intended recipients more efficiently, with reduced risks of spoofing and hijacking by malicious actors.”

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GOOGLE

Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

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Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

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While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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