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Exploring The Marketing Potential Of Predictive AI

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Exploring The Marketing Potential Of Predictive AI

Success in business is all about being proactive – being able to anticipate what will happen in the future, and then using this information to your advantage.

And the key to doing this? Predictive AI.

It might sound futuristic, but using predictive analytics in business is nothing new.

Just ask Henry Ford, who used data science analysis in his business as far back as the late 19th century.

This same practice continued to develop in the 1960s, thanks to the growing popularity of computers.

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Fast forward to 2022, when predictive AI recorded a market size of $12.49 billion, and it’s evident just how much of a global phenomenon it’s become.

What’s more, it’s showing no signs of slowing down. Reports predict it will reach $38 billion by 2028.

This means that if your business isn’t using predictive analytics yet, it risks getting left behind.

What Is Predictive AI?

Before we explore the marketing potential of AI-powered predictive analytics, it’s helpful to understand what it actually is.

As the name suggests, it’s the use of artificial intelligence and machine learning to predict outcomes.

By analyzing historical data from your business using advanced algorithms, predictive AI can allow you to make more informed, data-driven decisions.

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It’ll also help you identify trends, forecast behavior, predict any impending challenges, and devise solutions for them too.

It’s here that AI systems and AI research can be a valuable tool for your business – analyzing complex data in minutes to help improve effectiveness and boost return on investment (ROI).

You’ll have the insights you need to move your business forward and deliver an enhanced customer experience, all through the power of AI.

Predictive AI Vs. Generative AI

So far, so good, but where do AI models like Midjourney and ChatGPT come in?

Now you’re talking about generative AIartificial intelligence platforms focusing on content creation rather than data prediction.

If predictive AI is about using historical data to predict patterns, trends, and behavior, then generative AI is about creation.

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And that means generating realistic images, content, music, and more, all with the help of machine learning.

Both rely on artificial intelligence, but where one focuses on prediction, the other focuses on generation, as the names of these AI models suggest.

The applications of each differ as well. Generative AI models are best suited to creative industries like film, writing, fashion, and art.

Predictive AI models are ideal for industries that rely on data analysis, like healthcare, finance, and marketing.

Both have their place, and both are seeing an increase in usage across various fields, with an expected annual growth rate of 37.3% projected between 2023 and 2030.

And it’s this surge in popularity that makes your understanding of predictive AI so vital.

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Because if you’re not already leveraging its potential, you can be sure that your competitors are.

The Benefits Of Predictive AI

Before you commit to using AI technology, it’s helpful to explore its benefits a little further.

While the benefits of generative AI are obvious (saving time and money on image generation and content creation, for one), the advantages of predictive AI are more varied:

1. Future Planning

Staying ahead of the game is all about having a competitive advantage, and this is exactly what AI tools like predictive AI can give you.

Using historical data to forecast trends and outcomes allows you to plan ahead and be proactive in your business approach.

2. Improved Efficiency

The better your predictive data and the more accurate your forecasting, the more you’ll be able to avoid repetitive tasks and errors, helping you streamline your business processes.

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3. Faster Decision-making

In marketing, decisions are all about data. The more accurate your data, the more informed your decisions will be.

That’s the advantage of predictive AI – giving you the data you need, when you need it, to make faster, more effective decisions.

4. Pattern Identifying

Have you ever wondered how to use your own data to look for patterns in order to identify opportunities, challenges, and solutions?

That’s what predictive analysis does for you, using machine learning to recognize patterns and guide your decision-making accordingly.

5. Trend Forecasting

Your data contains a wealth of knowledge, and that’s exactly what predictive AI has been designed to draw from.

By using mathematical algorithms, machine learning, data mining, and more, predictive analytics can use your data to predict customer behavior, events, and trends.

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Meaning you’ll be getting the valuable business information you need ahead of time.

The Applications Of Predictive AI

By far one of the biggest benefits of predictive AI, however, is the range of applications it’s suited for.

With its ability to improve productivity, increase revenue, and streamline processes, it has the power to impact a wide range of industries, such as:

Retail

From market trends to buying habits, predictive AI can follow the customer journey from beginning to end, analyzing it every step of the way.

The fast-paced nature of the retail industry lends itself to AI models perfectly – models that can analyze, adapt, and respond quickly.

Will certain products do better in the marketplace? Will certain incentives secure a sale? Predictive AI can answer all these questions and more.

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Healthcare

With so many patients and medical centers worldwide, the opportunities for collecting data in the healthcare industry are endless.

By using the significant resources and abilities of AI models, algorithms will be able to suggest treatments, offer personalized care, and even predict epidemics.

This is how AI can help not only improve diagnoses but save lives in the process.

Automotive

Thanks to AI, vehicle failures and recalls could become a thing of the past.

By using machine learning, predictive analytics will be able to detect failures in manufacturing before they occur.

Looking to the future, predictive AI could also go one step further, helping to develop automotive technology and driverless vehicles based on studies of driver behavior.

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Financial Services

With its ability to forecast trends and apply machine learning models across a host of transactions and customer interactions, predictive AI is a perfect fit for the financial industry.

It’s fast, accurate, efficient, and has the power to revolutionize the way the financial world works.

Using Predictive AI Tools

So what types of predictive AI tools are out there, and what exactly can they do? Let’s take a look.

Neurons

First up, there’s Predict AI from Neurons.

What’s remarkable is that it’s built on a database of eye-tracking data gathered from more than 120,000 people worldwide and more than 100 billion data points of brain responses.

With its foundation models built on these neuroscience studies, Predict can generate creative insights data in seconds. This allows it to increase conversions and accurately predict human behavior.

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Thanks to Predict’s innovative AI technology, you’ll be able to understand how and why customers respond to your brand and your ads.

Which in turn will help you build awareness and drive sales at the same time. Look forward to improved engagement and optimized creativity, too, all with the power of Predict.

Dragonfly AI

Although it may have started life as an app, today, the Dragonfly AI platform is known for its emphasis on content performance.

With a full product suite focused on visual predictive analytics, Dragonfly’s Studio desktop solution offers a range of AI tools.

Increase your ROI, test your performance, A/B test your creatives, and streamline your design process, too, all in one.

With a mobile app for iOS and a browser extension, it’s versatile and flexible, and leverages AI technology perfectly.

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All so that the right messages reach the right customers at the right time. Just the boost your bottom line is looking for.

Vizit

What is it about your marketing campaigns that drive customers to view and purchase your products?

That’s exactly the question that Vizit has been designed to answer.

Powered by award-winning AI, Vizit uses patented technology to simulate what your customers see and feel when they look at your products.

That’s because it’s estimated that 93% of customers use visuals to make their purchasing decisions. So the more you can understand how to capture a customer’s attention, the better results you’ll see.

With predictive AI based on millions of behavioral interactions, Vizit is able to measure your visual content and give you insights to help boost your performance.

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You’ll be able to test, learn and grow, all while seeing through your customers’ eyes. And with Vizit ensuring increased conversions of up to 45% and sales growth of 30%, it could be your most rewarding view yet.

Is Predictive AI The Right Tool For Your Business?

While there’s some discourse around the fact that the quality of generative AI, such as OpenAI’s ChatGPT, may be worsening, the benefits and applications of predictive AI are clear.

Machine learning and artificial intelligence aren’t the way of the future – they’re our present reality, and they’re only going to become more sophisticated as time goes by.

Will you let your competitors overtake you with their ability to predict market trends and customer behavior, or will you embrace predictive AI and explore its potential for yourself?

It’s a question only you can answer, and it’s one you’ll need to consider sooner rather than later in order to stay ahead of the pack.

That’s a prediction you can count on.

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WordPress Releases A Performance Plugin For “Near-Instant Load Times”

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WordPress speculative loading plugin

WordPress released an official plugin that adds support for a cutting edge technology called speculative loading that can help boost site performance and improve the user experience for site visitors.

Speculative Loading

Rendering means constructing the entire webpage so that it instantly displays (rendering). When your browser downloads the HTML, images, and other resources and puts it together into a webpage, that’s rendering. Prerendering is putting that webpage together (rendering it) in the background.

What this plugin does is to enable the browser to prerender the entire webpage that a user might navigate to next. The plugin does that by anticipating which webpage the user might navigate to based on where they are hovering.

Chrome lists a preference for only prerendering when there is an at least 80% probability of a user navigating to another webpage. The official Chrome support page for prerendering explains:

“Pages should only be prerendered when there is a high probability the page will be loaded by the user. This is why the Chrome address bar prerendering options only happen when there is such a high probability (greater than 80% of the time).

There is also a caveat in that same developer page that prerendering may not happen based on user settings, memory usage and other scenarios (more details below about how analytics handles prerendering).

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The Speculative Loading API solves a problem that previous solutions could not because in the past they were simply prefetching resources like JavaScript and CSS but not actually prerendering the entire webpage.

The official WordPress announcement explains it like this:

Introducing the Speculation Rules API
The Speculation Rules API is a new web API that solves the above problems. It allows defining rules to dynamically prefetch and/or prerender URLs of certain structure based on user interaction, in JSON syntax—or in other words, speculatively preload those URLs before the navigation. This API can be used, for example, to prerender any links on a page whenever the user hovers over them.”

The official WordPress page about this new functionality describes it:

“The Speculation Rules API is a new web API… It allows defining rules to dynamically prefetch and/or prerender URLs of certain structure based on user interaction, in JSON syntax—or in other words, speculatively preload those URLs before the navigation.

This API can be used, for example, to prerender any links on a page whenever the user hovers over them. Also, with the Speculation Rules API, “prerender” actually means to prerender the entire page, including running JavaScript. This can lead to near-instant load times once the user clicks on the link as the page would have most likely already been loaded in its entirety. However that is only one of the possible configurations.”

The new WordPress plugin adds support for the Speculation Rules API. The Mozilla developer pages, a great resource for HTML technical understanding describes it like this:

“The Speculation Rules API is designed to improve performance for future navigations. It targets document URLs rather than specific resource files, and so makes sense for multi-page applications (MPAs) rather than single-page applications (SPAs).

The Speculation Rules API provides an alternative to the widely-available <link rel=”prefetch”> feature and is designed to supersede the Chrome-only deprecated <link rel=”prerender”> feature. It provides many improvements over these technologies, along with a more expressive, configurable syntax for specifying which documents should be prefetched or prerendered.”

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See also: Are Websites Getting Faster? New Data Reveals Mixed Results

Performance Lab Plugin

The new plugin was developed by the official WordPress performance team which occasionally rolls out new plugins for users to test ahead of possible inclusion into the actual WordPress core. So it’s a good opportunity to be first to try out new performance technologies.

The new WordPress plugin is by default set to prerender “WordPress frontend URLs” which are pages, posts, and archive pages. How it works can be fine-tuned under the settings:

Settings > Reading > Speculative Loading

Browser Compatibility

The Speculative API is supported by Chrome 108 however the specific rules used by the new plugin require Chrome 121 or higher. Chrome 121 was released in early 2024.

Browsers that do not support will simply ignore the plugin and will have no effect on the user experience.

Check out the new Speculative Loading WordPress plugin developed by the official core WordPress performance team.

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How Analytics Handles Prerendering

A WordPress developer commented with a question asking how Analytics would handle prerendering and someone else answered that it’s up to the Analytics provider to detect a prerender and not count it as a page load or site visit.

Fortunately both Google Analytics and Google Publisher Tags (GPT) both are able to handle prerenders. The Chrome developers support page has a note about how analytics handles prerendering:

“Google Analytics handles prerender by delaying until activation by default as of September 2023, and Google Publisher Tag (GPT) made a similar change to delay triggering advertisements until activation as of November 2023.”

Possible Conflict With Ad Blocker Extensions

There are a couple things to be aware of about this plugin, aside from the fact that it’s an experimental feature that requires Chrome 121 or higher.

A comment by a WordPress plugin developer that this feature may not work with browsers that are using the uBlock Origin ad blocking browser extension.

Download the plugin:
Speculative Loading Plugin by the WordPress Performance Team

Read the announcement at WordPress
Speculative Loading in WordPress

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See also: WordPress, Wix & Squarespace Show Best CWV Rate Of Improvement

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10 Paid Search & PPC Planning Best Practices

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10 Paid Search & PPC Planning Best Practices

Whether you are new to paid media or reevaluating your efforts, it’s critical to review your performance and best practices for your overall PPC marketing program, accounts, and campaigns.

Revisiting your paid media plan is an opportunity to ensure your strategy aligns with your current goals.

Reviewing best practices for pay-per-click is also a great way to keep up with trends and improve performance with newly released ad technologies.

As you review, you’ll find new strategies and features to incorporate into your paid search program, too.

Here are 10 PPC best practices to help you adjust and plan for the months ahead.

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1. Goals

When planning, it is best practice to define goals for the overall marketing program, ad platforms, and at the campaign level.

Defining primary and secondary goals guides the entire PPC program. For example, your primary conversion may be to generate leads from your ads.

You’ll also want to look at secondary goals, such as brand awareness that is higher in the sales funnel and can drive interest to ultimately get the sales lead-in.

2. Budget Review & Optimization

Some advertisers get stuck in a rut and forget to review and reevaluate the distribution of their paid media budgets.

To best utilize budgets, consider the following:

  • Reconcile your planned vs. spend for each account or campaign on a regular basis. Depending on the budget size, monthly, quarterly, or semiannually will work as long as you can hit budget numbers.
  • Determine if there are any campaigns that should be eliminated at this time to free up the budget for other campaigns.
  • Is there additional traffic available to capture and grow results for successful campaigns? The ad platforms often include a tool that will provide an estimated daily budget with clicks and costs. This is just an estimate to show more click potential if you are interested.
  • If other paid media channels perform mediocrely, does it make sense to shift those budgets to another?
  • For the overall paid search and paid social budget, can your company invest more in the positive campaign results?

3. Consider New Ad Platforms

If you can shift or increase your budgets, why not test out a new ad platform? Knowing your audience and where they spend time online will help inform your decision when choosing ad platforms.

Go beyond your comfort zone in Google, Microsoft, and Meta Ads.

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Here are a few other advertising platforms to consider testing:

  • LinkedIn: Most appropriate for professional and business targeting. LinkedIn audiences can also be reached through Microsoft Ads.
  • TikTok: Younger Gen Z audience (16 to 24), video.
  • Pinterest: Products, services, and consumer goods with a female-focused target.
  • Snapchat: Younger demographic (13 to 35), video ads, app installs, filters, lenses.

Need more detailed information and even more ideas? Read more about the 5 Best Google Ads Alternatives.

4. Top Topics in Google Ads & Microsoft Ads

Recently, trends in search and social ad platforms have presented opportunities to connect with prospects more precisely, creatively, and effectively.

Don’t overlook newer targeting and campaign types you may not have tried yet.

  • Video: Incorporating video into your PPC accounts takes some planning for the goals, ad creative, targeting, and ad types. There is a lot of opportunity here as you can simply include video in responsive display ads or get in-depth in YouTube targeting.
  • Performance Max: This automated campaign type serves across all of Google’s ad inventory. Microsoft Ads recently released PMAX so you can plan for consistency in campaign types across platforms. Do you want to allocate budget to PMax campaigns? Learn more about how PMax compares to search.
  • Automation: While AI can’t replace human strategy and creativity, it can help manage your campaigns more easily. During planning, identify which elements you want to automate, such as automatically created assets and/or how to successfully guide the AI in the Performance Max campaigns.

While exploring new features, check out some hidden PPC features you probably don’t know about.

5. Revisit Keywords

The role of keywords has evolved over the past several years with match types being less precise and loosening up to consider searcher intent.

For example, [exact match] keywords previously would literally match with the exact keyword search query. Now, ads can be triggered by search queries with the same meaning or intent.

A great planning exercise is to lay out keyword groups and evaluate if they are still accurately representing your brand and product/service.

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Review search term queries triggering ads to discover trends and behavior you may not have considered. It’s possible this has impacted performance and conversions over time.

Critical to your strategy:

  • Review the current keyword rules and determine if this may impact your account in terms of close variants or shifts in traffic volume.
  • Brush up on how keywords work in each platform because the differences really matter!
  • Review search term reports more frequently for irrelevant keywords that may pop up from match type changes. Incorporate these into match type changes or negative keywords lists as appropriate.

6. Revisit Your Audiences

Review the audiences you selected in the past, especially given so many campaign types that are intent-driven.

Automated features that expand your audience could be helpful, but keep an eye out for performance metrics and behavior on-site post-click.

Remember, an audience is simply a list of users who are grouped together by interests or behavior online.

Therefore, there are unlimited ways to mix and match those audiences and target per the sales funnel.

Here are a few opportunities to explore and test:

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  • LinkedIn user targeting: Besides LinkedIn, this can be found exclusively in Microsoft Ads.
  • Detailed Demographics: Marital status, parental status, home ownership, education, household income.
  • In-market and custom intent: Searches and online behavior signaling buying cues.
  • Remarketing: Advertisers website visitors, interactions with ads, and video/ YouTube.

Note: This varies per the campaign type and seems to be updated frequently, so make this a regular check-point in your campaign management for all platforms.

7. Organize Data Sources

You will likely be running campaigns on different platforms with combinations of search, display, video, etc.

Looking back at your goals, what is the important data, and which platforms will you use to review and report? Can you get the majority of data in one analytics platform to compare and share?

Millions of companies use Google Analytics, which is a good option for centralized viewing of advertising performance, website behavior, and conversions.

8. Reevaluate How You Report

Have you been using the same performance report for years?

It’s time to reevaluate your essential PPC key metrics and replace or add that data to your reports.

There are two great resources to kick off this exercise:

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Your objectives in reevaluating the reporting are:

  • Are we still using this data? Is it still relevant?
  • Is the data we are viewing actionable?
  • What new metrics should we consider adding we haven’t thought about?
  • How often do we need to see this data?
  • Do the stakeholders receiving the report understand what they are looking at (aka data visualization)?

Adding new data should be purposeful, actionable, and helpful in making decisions for the marketing plan. It’s also helpful to decide what type of data is good to see as “deep dives” as needed.

9. Consider Using Scripts

The current ad platforms have plenty of AI recommendations and automated rules, and there is no shortage of third-party tools that can help with optimizations.

Scripts is another method for advertisers with large accounts or some scripting skills to automate report generation and repetitive tasks in their Google Ads accounts.

Navigating the world of scripts can seem overwhelming, but a good place to start is a post here on Search Engine Journal that provides use cases and resources to get started with scripts.

Luckily, you don’t need a Ph.D. in computer science — there are plenty of resources online with free or templated scripts.

10. Seek Collaboration

Another effective planning tactic is to seek out friendly resources and second opinions.

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Much of the skill and science of PPC management is unique to the individual or agency, so there is no shortage of ideas to share between you.

You can visit the Paid Search Association, a resource for paid ad managers worldwide, to make new connections and find industry events.

Preparing For Paid Media Success

Strategies should be based on clear and measurable business goals. Then, you can evaluate the current status of your campaigns based on those new targets.

Your paid media strategy should also be built with an eye for both past performance and future opportunities. Look backward and reevaluate your existing assumptions and systems while investigating new platforms, topics, audiences, and technologies.

Also, stay current with trends and keep learning. Check out ebooks, social media experts, and industry publications for resources and motivational tips.

More resources: 

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Google Limits News Links In California Over Proposed ‘Link Tax’ Law

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A brown cardboard price tag with a twine string and a black dollar sign symbol, influenced by the Link Tax Law, set against a dark gray background.

Google announced that it plans to reduce access to California news websites for a portion of users in the state.

The decision comes as Google prepares for the potential passage of the California Journalism Preservation Act (CJPA), a bill requiring online platforms like Google to pay news publishers for linking to their content.

What Is The California Journalism Preservation Act?

The CJPA, introduced in the California State Legislature, aims to support local journalism by creating what Google refers to as a “link tax.”

If passed, the Act would force companies like Google to pay media outlets when sending readers to news articles.

However, Google believes this approach needs to be revised and could harm rather than help the news industry.

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Jaffer Zaidi, Google’s VP of Global News Partnerships, stated in a blog post:

“It would favor media conglomerates and hedge funds—who’ve been lobbying for this bill—and could use funds from CJPA to continue to buy up local California newspapers, strip them of journalists, and create more ghost papers that operate with a skeleton crew to produce only low-cost, and often low-quality, content.”

Google’s Response

To assess the potential impact of the CJPA on its services, Google is running a test with a percentage of California users.

During this test, Google will remove links to California news websites that the proposed legislation could cover.

Zaidi states:

“To prepare for possible CJPA implications, we are beginning a short-term test for a small percentage of California users. The testing process involves removing links to California news websites, potentially covered by CJPA, to measure the impact of the legislation on our product experience.”

Google Claims Only 2% of Search Queries Are News-Related

Zaidi highlighted peoples’ changing news consumption habits and its effect on Google search queries (emphasis mine):

“It’s well known that people are getting news from sources like short-form videos, topical newsletters, social media, and curated podcasts, and many are avoiding the news entirely. In line with those trends, just 2% of queries on Google Search are news-related.”

Despite the low percentage of news queries, Google wants to continue helping news publishers gain visibility on its platforms.

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However, the “CJPA as currently constructed would end these investments,” Zaidi says.

A Call For A Different Approach

In its current form, Google maintains that the CJPA undermines news in California and could leave all parties worse off.

The company urges lawmakers to consider alternative approaches supporting the news industry without harming smaller local outlets.

Google argues that, over the past two decades, it’s done plenty to help news publishers innovate:

“We’ve rolled out Google News Showcase, which operates in 26 countries, including the U.S., and has more than 2,500 participating publications. Through the Google News Initiative we’ve partnered with more than 7,000 news publishers around the world, including 200 news organizations and 6,000 journalists in California alone.”

Zaidi suggested that a healthy news industry in California requires support from the state government and a broad base of private companies.

As the legislative process continues, Google is willing to cooperate with California publishers and lawmakers to explore alternative paths that would allow it to continue linking to news.

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