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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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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.

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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Google Brings Bard Students Math and Coding Education in the Summer

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Google Brings Bard Students Math and Coding Education in the Summer

Google is stepping up its AI efforts this summer by sending Bard, its high-profile chatbot, to summer school. The aim? To boost the bot’s math and coding smarts. These developments are excellent news— when Bard first debuted, it was admittedly not a finished product. But Google is steadily plugging away at it, and have now implemented implicit code execution for logical prompts, and handy Google Sheets’ integration to take it to the next level.

Thanks to implicit code execution, Bard can respond to inquiries requiring calculation or computation with Python code snippets running in the background. What’s even more amazing is that coders can take this generated code and modify it for their projects. Though Google is still apprehensive about guaranteeing the accuracy of Bard’s answers, this feature is said to improve the accuracy of math and word problems by an impressive 30%.

In addition to this, Bard can now export directly to Sheets when asked about tables. So, you don’t need to worry about copying and pasting, which comes with the risk of losing formatting or data.

From the company’s I/O keynote address, it is clear that they are focused on making the most of what Bard can offer. As they continue to speak highly of the chatbot, we’re sure to expect more features and capabilities when the summer comes around.

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Google Bard vs. ChatGPT: which is the better AI chatbot?

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Google Bard vs. ChatGPT: which is the better AI chatbot?

Google Bard and ChatGPT are two of the most prominent artificial intelligence (AI) chatbots available in 2023. But which is better? Both offer natural language responses to natural language inputs, using machine learning and millions of data points to craft useful, informative responses. Most of the time. These AI tools aren’t perfect yet, but they point to an exciting future of AI assistant search and learning tools that will make information all the more readily available.

As similar as these chatbots are, they also have some distinct differences. Here’s how ChatGPT and Google Bard measure up against one another.

Which is better, Google Bard or ChatGPT?

This is a tricky question to answer, as at the time of writing, you can only use Google Bard if you’re part of a select group of early beta testers. As for its competition, you can use ChatGPT right now, completely for free. You may have to contend with a waitlist, but if you want to skip that, there’s a paid-for Plus version offering those interested in a more complete tool the option of paying for the privilege.

Still, when Google Bard becomes more widely available, it should offer credible competition for ChatGPT. Both use natural language models — Google Bard uses Google’s internal LaMDA (Language Model for Dialogue Applications), whereas ChatGPT uses an older GPT-3 language model. Google Bard bases its responses to questions on more recent data, with ChatGPT mainly trained on data that was available prior to 2021. This is similar to how Microsoft’s Bing Chat works.

We’ll have to reserve judgment on which is the more capable AI chatbot until we get time to play with Google Bard ourselves, but it looks set to be a close contest when it is more readily available.

Are Google Bard and ChatGPT available yet?

As mentioned, ChatGPT is available in free and paid-for tiers. You might have to sit in a queue for the free version for a while, but anyone can play around with its capabilities.

Google Bard is currently only available to limited beta testers and is not available to the wider public.

Banner of Google Bard intro from February 6.

What’s the difference between Google Bard and ChatGPT?

ChatGPT and Google Bard are very similar natural language AI chatbots, but they have some differences, and are designed to be used in slightly different ways — at least for now. ChatGPT has been used for answering direct questions with direct answers, mostly correctly, but it’s caused a lot of consternation among white collar workers, like writers, SEO advisors, and copy editors, since it has also demonstrated an impressive ability to write creatively — even if it has faced a few problems with accuracy and plagiarism.

Still, Microsoft has integrated ChatGPT into its Bing search engine to give users the ability to ask direct questions of the search engine, rather than searching for terms of keywords to find the best results. It has also built it into its Teams communications tool, and it’s coming to the Edge browser in a limited form. The Opera browser has also pledged to integrate ChatGPT in the future.

ChatGPT Google Bard
Accessible through ChatGPT site. Only text responses are returned via queries. Integrated with Google Search. You only need to change a Google setting to get your regular search results when using Google Bard AI, and vice versa.
ChatGPT produces answers from its trained database from 2021 and before. Google Apprentice Bard AI will be able to answer real-time questions.
Based on GPT (Generative Pre-trained Transformer). Based on LaMDA (Language Model for Dialogue Applications).
Service has a free and paid plan option (called ChatGPT Plus). Service is free.
Has built-in plagiarism tool called GPT-2 Output Detector. No built-in plagiarism detection tool.
Available now Still in beta test phase

Google Bard was mainly designed around augmenting Google’s own search tool, however it is also destined to become an automated support tool for businesses without the funds to pay for human support teams. It will be offered to customers through a trained AI responder. It is likely to be integrated into the Chrome browser and its Chromium derivatives before long. Google is also expected to open up Google Bard to third-party developers in the future.

Under the hood, Google Bard uses Google’s LaMDA language model, while ChatGPT uses its own GPT3 model. ChatGPT is based on slightly older data, restricted in its current GPT3 model to data collected prior to 2022, while Google Bard is built on data provided on recent years too. However, that doesn’t necessarily make it more accurate, as Google Bard has faced problems with incorrect answers to questions, even in its initial unveiling.

ChatGPT also has a built-in plagiarism checker, while Google Bard does not, but Google Bard doesn’t have the creative applications of ChatGPT just yet.

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