Google recently provided its Performance Max best practices for advertisers in the tourism and travel industry.

The need for additional support tools outside of retail and ecommerce has been strong as Google continues to prioritize Performance Max and automation.

Google’s latest tutorials video provides key steps to setting up a successful Performance Max campaign for hotel properties.

The touted benefits of Performance Max for hotels are similar to other industries:

• The ability to reach users across the full range of Google inventory
• Expand brand reach with additional ad formats and channels
• Utilizing strategic inputs to help steer Google’s AI for maximum performance.

Step 1: Prepare the Account Settings

Before jumping into campaign creation, reviewing the Business Data settings is essential.

Navigate to “Tools & Settings” >> “Business Data” and choose the “Hotel Properties” feed.

This is where advertisers choose which hotels to choose from later on in the Performance Max campaign.

For marketers with few properties, use the “hotel picker” by choosing hotels from a map.

Image credit: Google, March 2023

If over 50 properties are used, there are three options to add them to the business data:

• Create a feed using Google Maps URLs
• Use hotels in the Hotel Center Account that is linked to the Google Ads account
• Use the Google API

Step 2: Select Campaign Settings

Now, it’s time to set up the Performance Max for Hotels campaign.

When creating a new campaign, select “Sales” as the objective, then a “Purchases” conversion action from the account.

After those selections, choose “Performance Max,” which will default to the hotel selection. The travel-specific enhancement will allow advertisers to select the data feed source (from step 1).

Image credit: Google, March 2023

One of the most critical components is selecting a bid strategy that aligns with the company’s objectives. Choose from either maximizing:

• Konverteringar (if all conversions are worth the same)
• Conversion value (if each conversion has a different value, such as other hotels providing different rates, etc.)

Google recommends setting a Target CPA (Cost Per Acquisition) or Target ROAS (Return On Ad Spend) from the last 30 days, comparable to other campaigns in the account with similar goals. This helps steer Google’s AI in the right direction from the start.

Finally, adjust other settings such as the ad schedule, start and end date, and budget.

Step 3: Customize Asset Groups

The first item to choose is a default logo that can be used for any hotel within the Performance Max campaign.

Each hotel that was selected in the campaign automatically becomes its own asset group (similar to an ad group for non-Performance Max campaigns).

Asset Group components

Each asset group is made up of the following:

• Website URL
• Images
• Logo(s)
• Videos
• Text headline(s)
• Text description(s)
• Call-to-action (CTA)

Image credit: Google, March 2023

Google’s AI will automatically copy assets from the chosen website. However, advertisers must review anything selected. Advertisers can also decide on the combinations used.

Google states that if no video assets are available, they will automatically create one based on other chosen image assets.

It’s essential to review automatically chosen assets because there’s always room for a margin of error – especially if a website is not up-to-date. Be sure to check the following:

• Grammar in headlines and descriptions
• Images and video are up-to-date and high-quality
• Logos are cropped correctly
• CTAs are aligned with website goals

Utilize Audience Signals

Advertisers also can create and upload their assets for more control. While this can be a bit more manual process, it’s better for marketers who want more campaign control.

Another critical item to add to the campaign before launching is audience signals. Start by adding any first-party or customer data available to help Google’s AI find more users most likely to book immediately.

Additional audience signals recommended to add are Google’s “In-Market” segments. Similar to first-party data, these signals steer Google’s AI to more bottom-of-funnel users ready to take action.

Image credit: Google, March 2023

Lastly, before launching, include additional assets (formerly ‘extensions‘) such as sitelinks, callouts, and calls to make the ad more prominent.

Once these items have been created and reviewed, the campaign can be launched!

Step 4: Optimize Campaign Performance

Google recommends evaluating initial campaign performance after a few weeks from launch. This is recommended because it lets Google test, optimize, and account for any potential conversion lags or delays where customers need extra time to book.

When optimizing the Performance Max for Hotels campaign, review the following regularly:

• Look for any ad or asset disapprovals that may be affecting performance
• Individual asset performance to improve creative
• Audience signals to ensure the most relevant ads are shown to the most relevant users

Google provides property-specific reporting for advertisers to help determine an indication of traveler demand across different locations. This is valuable information to marketers as it can help influence other non-Performance Max campaigns and where to shift priorities.

In addition to property-specific reporting, it supports the ability to segment by dimensions of ‘interest’ in the “Hotel” tab on the left-hand side of the interface.

Image credit: Google, March 2023

Performance Max for Hotels uses the same Brand Safety settings at the account level, found under “Content Suitability” in the “Tools & Settings” navigation.

Sammanfattning

As Performance Max continues to mature, so does its support for other industries outside of retail and ecommerce.

This step-by-step guide to setting up a Performance Max for Hotels campaign can help alleviate optimization pain points by checking off all the necessary initial inputs.

Over the years, we’ve seen some epic battles between search engine giants. We’ve watched as Google, Bing, and Yahoo have gone head-to-head, each vying for market share. Now, a new challenger has entered the arena–Bing’s chatbot AI. 

Launching this experimental tool last February 7, 2023 put Microsoft ahead of the race–and forced Google to take Bing seriously as a challenger for the future of search. 

But, the question is this: can Bing’s Chat AI take down Google Bard? Let’s probe further.

How Bing Chat AI Fares Now

Powered by OpenAI, Bing’s new chatbot was designed to deliver better search results and provide a new search experience for users–and it worked. 

Bing now has 100 million daily active users. While that seems like a tiny number compared to the millions that still use Google today, it’s enough to make them declare a “code red” with their own experimental chatbot, Bard.

On March 8, 2023, Yusur Mehdi, Microsoft’s Director of Marketing, shared that Bing surpassed its 100 million daily active users after their Chat AI was launched a month ago. Here’s what Yusur Mehdi has to say about their progress on Bing’s new addition:

“Of the millions of active users of the new Bing preview, it’s great to see that roughly one-third are new to Bing. We see this appeal of the new Bing as a validation of our view that search is due for a reinvention and of the unique value proposition of combining Search + Answers + Chat + Creation in one experience.

Secondly not only are we seeing growth in new users, but we are seeing engagement growing as more people are conducting more searches daily. “

What can we glean from this? First, that Bing has greatly benefited from its launch first-debug later strategy, which Google failed to establish as a pioneer in the AI chat field. Safe to say that Google lost ground when it delayed its Bard launch over Bing’s ChatGPT. 

And second, that Bing’s on the right track in reinventing the search experience. With more than a month of beta testing (and a few weeks of open testing for everyone who signed up for their waitlist), we can now take a better look at how Bing’s Chat AI performs.

How to Access Bing’s AI Chatbot

If you want to check it out yourself, you’ll find Bing’s AI Chatbot as a new feature on their search bar. It’s under the “Let’s chat” button or the “Chat” button at the bottom of the search box. You can also click the “Chat” option on the Bing homepage.

Doing so will bring you to the chatbot page. Here, you’ll see that it’s quite different from your typical search bar–and more like chatting with another person in something like Google Teams or Slack.)

I’ve been testing it out myself for the last two weeks, and I consider it to be a significant improvement over the functionality and user experience of ChatGPT. 

How Does Bing’s AI Chatbot Respond?

The ability to access the internet and current data is a significant improvement for New Bing. And New Bing takes this a step further by including sources and footnotes in search results, which addresses one key issue when you use ChatGPT.

It’s also content-aware, much like ChatGPT. It will remember your previous searches, so you can ask follow-up questions for more information on your topic of interest, without having to start over. However, there is a limit of up to 2000 characters per question.

New Bing also includes chat prompts for other search options. When users select a prompt, such as “What is the meaning of SEO? “, it also provides some follow-up questions, such as “What is online reputation management.” This can lead to a more engaging conversation experience that scrolls to a different area of the website.

After testing New Bing over the last few days, I’m finding that the results are pretty helpful when choosing a prompt after searching.

Recent Updates with Bing’s AI Chatbot

Following the weeks since its initial launch, Microsoft has introduced several updates to the AI chatbot. 

One of them is that it now offers replies in three different tones, in response to some of the earliest criticisms of the chatbot. 

The default is set to “Balanced,” which generally creates neutral responses that do not take sides on a specific topic. Other options are “Creative,” which generates more playful and original responses, and “Precise,” which generates the most concise and factual responses. 

Microsoft has also given another feature: the ability to generate images (which, at the time of writing, is currently a work in progress). Built on the DALL·E model, it allows users to generate images by typing the prompt “create an image,” followed by your instructions. 

Lastly, the search function on the chatbot itself is still limited to only 15 queries per session, and 150 queries per day. You can keep track of how many you have left in each topic at the bottom-right of the most recent response Bing provides:

How Does Bing Chat AI Compare to Google Bard? 

Building from the substantial amount of search behavior with ChatGPT, Bing comes out strong, showing a new paradigm of what users can gain from using a search engine.

At present, it also presents a new method of search that isn’t possible on Google, which means it can take some potential traffic away from Google–though that would only make a small dent in Google’s search volume.

And this isn’t to say that Google won’t contend with Bing. Google has long been the gold standard when it comes to finding information online. Its algorithm is sophisticated and efficient, able to sift quickly through vast amounts of data to provide relevant results in a matter of seconds. 

At the time of writing, Google has just opened up its waitlist for Bard–but has yet to share anything substantial about its AI chat results. All we’ve seen so far is a very basic walk-through of Bard, and it doesn’t show much. 

The one interesting thing that we do know is that Google wants Bard to improve on the Knowledge Graph Cards you often see in their SERPS, particularly when asking questions that have simple answers. 

They’ve also stated that Bard’s responses are designed to answer NORA questions – queries with No One Right Answer. This is different from the approach being used by New Bing. You can check out a preview of how this works on Brodie Clark’s Twitter thread.

Comparing the two at face value, I think that the approach used by Bing centers on publishers, whereas Google centers the content itself. But then again, as these two tools are still under development, we’ll just have to see how far they go with their implementation.

Can Bing Chatbot AI Take Over?

When it comes to the question of whether Bing AI Chat can take over Google Bard, there are several factors to consider. Both Bing Chat AI and Google Bard are chatbot technologies that use artificial intelligence to interact with users and provide information or assistance. Here are some points to consider:

• Användarupplevelse: The success of any chatbot is greatly influenced by its user experience. A chatbot is more likely to be effective if it is simple to use, offers reliable information, and can comprehend user queries. In terms of user experience, Google has a long history and a more well-established track record of excellence. Bing Chat AI is constantly developing, though, so it might be able to catch up in terms of user experience.

• Features and capabilities: Each chatbot’s features and capabilities should be taken into account. Google Bard is renowned for its capacity to comprehend complex queries and deliver precise answers. Also, it is compatible with other Google products, like Maps and Search. On the contrary, Bing Chat AI is still in its infancy and might not have as many features and functionalities as Google Bard might have.

• Integration with other services: Another important element in the success of a chatbot is its integration with other services. Because of its ability to interface with other Google services like Maps and Search, Google Bard has a significant advantage in this regard. Users now have an easier time finding information and receiving the assistance they require. The advantage of being created by Microsoft, which has a vast range of services and tools that it might interact with, is that Bing Chat AI is still developing its integration capabilities.
  
• Market share: Finally, market share is another factor to consider. Google is the dominant search engine, and Google Bard is built into its search results pages. This gives Google Bard a significant advantage in terms of visibility and accessibility. However, Bing Chat AI is also backed by a major tech company and has the potential to grow its market share over time.

It’s hard to say definitively whether Bing’s chatbot AI will eventually overtake Google Bard in terms of market share or popularity. However, one thing is certain—chatbots are becoming increasingly popular in search, and are already being used by some major companies like Amazon and Microsoft. 

As more companies begin integrating them into their customer service systems, they will likely become even more commonplace in the near future.

What Can We Learn From Bing’s Chatbot?

Bing is the first search engine to showcase what AI-powered features–such as a chatbot function–could mean for search. This means that it’s also the first to show just how difficult and unpredictable it is to work with new AI tools. 

Just take the beta tests with Microsoft’s Bing chatbot, which have been extensively documented by many over the past few weeks. This argument in particular is a good example of the surprises and mistakes it committed early on. 

But thanks to the open beta tests, Microsoft was able to put in additional content-generation safeguards, beefing up OpenAI’s own built-in restrictions. And as Microsoft learns its lessons, I’m sure that the rest of the Search Engine industry is following along.

Microsoft’s new AI also presents a novel way to search. It opens a new era of interacting with information online because it’s conversational AI that taps into both a huge search database and powerful AI language models.

That said, there is still the looming risk of potentially serious consequences–AI models, even one as complex and as tested as Bing’s chatbot, may not be able to reliably sort fact from fiction. And we’ve yet to see any AI who can do so. Bard, fueled by Google’s extensive resources and development, also presented misinformation on the day of its big reveal. 

Even so, there is now an open AI arms race amongst just about every Big Tech company. Meta just announced its intent to focus on generative AI, while Snapchat announced that it has an ongoing experiment with OpenAI, the same firm that Microsoft is working with for its AI-powered chatbot.

While I am interested to see where this takes us, I fear that the speed at which these companies are going might result in “experimental” features that are ultimately less credible or functional than standard search. 

So, as fascinating as these tools are, I’d have to caution users on how they take in and interact with the information these conversational AIs provide.

Key Takeaway

Bing Chat AI’s early release has the potential to change the search landscape and SEO as we know it. It even has the potential to catch up to tech giants in terms of user experience, features, and integration capabilities. 

But when it comes to Google Bard vs. Bing AI, the success of each chatbot will ultimately come down to how well it meets the needs of its users and how effectively it can differentiate itself in the market. 

While it had a good start, the outcome is still uncertain as Google Bard is yet to be released to the public. We can, however, glean some very interesting insights as to how AI can transform search from Bing AI’s beta testing to its initial release.

Only time will tell if Bing Chatbot AI will be able to successfully compete with its rivals, but there’s no denying that its capabilities make it a tool worth investigating!

Rendering is crucial to your website’s operations, enabling Google to retrieve your webpages, decipher the code, and understand its content and structure.

The rendering process then converts this code into a webpage with which users can interact.

Every webpage should be designed with the end person in mind, so choosing the most effective type of rendering is imperative when creating your website.

Each rendering technique has pros and cons, so in the first of our JavaScript series, we will cover server-side rendering (SSR).

Read on to discover what server-side is, how the server-side process works, and its advantages and disadvantages.

What Is Server-Side Rendering (SSR)?

Server-side rendering is where your site’s content is rendered on the web server rather than the browser. This server prepares an HTML file with user-specific data and sends it to the user’s machine.

The browser then interprets the content and displays the page, giving the user a fully rendered HTML page without waiting for JavaScript or CSS files to load.

Many think this method is favorable for SEO compared to client-side rendering, but let’s first see how SSR works.

The Server-Side Rendering Process

As we’ve discussed, server-side rendering enables website content to appear quickly by eliminating the need to download and run application code.

But how is your HTML rendered on the server in response to navigation?

• The user opens their browser and requests to open the webpage.
• The server creates rendered content in a viewable HTML file and sends it to the user. The CSS is also displayed on the browser, but the page is not yet interactive.
• Meanwhile, the browser downloads the JavaScript of the page, which is readily available on the server.
• The user can now interact with the site and the different elements.
• The browser implements the JavaScript (Document Object Model or DOM is fully rendered).
• The page is now fully loaded and can respond to the interactions of the user journey.

Many popular JavaScript frameworks, including Angular och React, use server-side rendering.

Social media giants such as Facebook and Twitter also use rendered content before it’s sent to the user.

But what are the unique pros and cons of using SSR? Here are the advantages and disadvantages:

The Advantages Of Server-Side Rendering

Faster Load Time

SSR only updates the parts of the HTML that need updating, so it generates faster page transitions between pages and much quicker First Contentful Paint (FCP).

Even users with slow internet connections or outdated devices can immediately interact with your webpages.

Remember, the less time a user has to look at a loading screen, the better for your SEO.

Easy To Index

Indexing SSR sites is much easier for search engines than client-side rendered sites. The content is rendered before the page is loaded, so they don’t need to run JavaScript to read and index it.

Ideal For Static Websites

SSR is excellent for static webpages as it’s faster to pre-render a static (or unchanging) page on the server before sending it to the client.

More Accurate User Metrics

SSR enables you to keep a healthy, optimized website by quickly and accurately gathering metrics.

Unlike client-side rendering, SSR will inform the server as your user moves from one page to another.

Evaluating how they navigate your site and interact with your content will help you continually improve the user interface (UI) and user experience (UX).

Excellent Social Media Optimization

SSR also optimizes your pages for social media.

This means you’ll get a nice preview with the page title, description, and image whenever you share your webpage’s content via social media.

The Disadvantages Of Server-Side Rendering

Higher Server Load For Bigger Applications

The server bears the full burden of the requests for users and bots.

Rendering bigger, more complex applications on the server side can increase the loading time because it is a single bottleneck.

Increase In Expenses

SSR can get complex and expensive when it becomes difficult to maintain and debug and is more prone to errors.

You’ll need to use your own company’s server to install an SSR application, which means higher running costs.

Compatibility Issues

SSR can be incompatible with some third-party libraries and tools, including JavaScript code.

Slow Page Rendering Inactivity

Even though the user can view the page right away, they must wait for the JavaScript download to complete before interacting with it.

Inefficient Caching

Efficient caching is important for data retrieval performance, but SSR means each page’s HTML is different.

It’s harder to catch this on a content delivery network (CDN), so users who load a page that hasn’t been cached on the CDN will experience a longer page load time.

Server-Side Rendering Frameworks

Delivering rendered content to the browser is vital for frontends on SSR applications to load quickly.

Many of the frameworks we’ve highlighted support running the same application in Node.js, rendering it to static HTML, and finally hydrating it on the client.

Some of the most popular frameworks used to support SSR for web development are:

• Angular Universal – used to render an angular application on the server side.
• Ember.js – a JavaScript framework focused on scalable single-page applications.
• Gatsby.js – a React-based framework that’s ideal for building static websites.
• Next.js – a JavaScript, open-source framework built on top of React.
• React – an open-source JavaScript framework and library for building reusable UI components.
• Vue.js – a JavaScript framework developers mainly implement to create interactive user interfaces.

Is Server-Side Rendering Better?

SSR is effective for boosting your SEO performance because it indexes your pages before they are loaded in the browser.

It benefits the organization that builds the web application by tracking engagement metrics to fuel constant improvement for the end client.

Ultimately, you need to decide how it stacks up to client-side rendering or dynamic rendering when choosing your web framework and architecture and the type of features you require.

Fler resurser: 

Featured Image: hanss/Shutterstock