Can machine learning make anyone a better PPC marketer?

Can machine learning make anyone a better PPC marketer?

The beauty of artificial intelligence (AI) lies in its constant evolution over time. When combined with a statistical approach as audacious as machine learning, artificial intelligence can become an instrumental tool in just about any task you can find.

One of the fields in which artificial intelligence and machine learning have shown great potential is digital marketing, specifically PPC or Pay-Per-Click marketing. Although the current machine learning processes of AI still cannot surmount the overall rigor of analysis and strategy of human PPC teams, the current breed of PPC artificial intelligence machinery performs a good deal of tasks that make PPC marketing faster, easier, and more efficient.

What is Pay-Per-Click Marketing?

Pay-Per-Click (PPC) marketing is a digital marketing model in which advertisers pay a fee every time one of their ads is clicked and visited online. This is a good way to lead people into pages that you want them to visit, instead of just relying on organic clicks.

One of the most popular and effective models of PPC is search engine advertising. Advertisers bid for ad placements on sponsored links when their keywords are used, and a successful bid can make your ad be the first thing that people see when they try to search for what they’re looking for online.

If you want to launch a successful PPC campaign, you have to consider a lot of factors. You have to know the right keywords for your campaign, organize those into ad groups, and set up efficient and optimized landing pages to encourage conversion. Although paying for clicks might seem expensive at first glance, a quick conversion of those clicks into sales will definitely make your PPC campaign worth it.

How Does Machine Learning Factor into Pay-Per-Click Marketing?

As it stands, there is still room for improvement when it comes to PPC marketing. Wading through millions and even billions of data can be difficult and time-consuming for PPC marketing teams. However, the introduction of AI and machine learning can elevate this marketing strategy into an even more effective version of itself!

Here are some ways AI and machine learning can help boost your PPC digital campaign into an even higher level:

  • Smart Bidding

As mentioned, advertisers need to successfully bid for their keywords in order to have an effective digital marketing strategy. With the vast number of keywords available, it can be incredibly difficult to choose the most strategic ones for your campaign.

With AI’s Smart Bidding, its machine learning processes can optimize your strategy and use performance goals like target cost per acquisition (CPA), enhanced cost per click (CPC) and maximize conversions to dwindle down the number of keywords into the most efficient and cost-effective ones. Artificial intelligence would be able to use industry performance data, historical data, and user behavior patterns to make good use of the results of their keyword searches.

  • Effective Audience Targeting

Not everyone who uses your keywords are ready for conversion. To make good use of your PPC ads, you need to target people who are ready to convert their online queries into sales. Thankfully, AI and machine learning can help advertisers find the best people to market to. Artificial intelligence factors in the user’s search history and similar audiences, and utilizes the custom intent audiences function to find the best people to boost your ads to.

  • Life Event Targeting

With life event targeting, you can target and exclude users who are going through certain life events in your digital ad market. This is an extremely exciting feature made possible by artificial intelligence, as this can help you direct your ad to a certain demographic who are readier to buy your items and stray away from users who might not be the best people to market your goods to. For example, if you are in the real estate industry, you can target newly-weds who are ready to buy their new homes and filter out newly-graduated students who might be looking to only rent their next homes.







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AI and Machine Learning: Paving the Way for a More Effective PPC Campaign

There are various ways in which artificial intelligence and machine learning can help optimize your PPC ads. They not only make you spend on ads smarter, but they also increase your conversion rates massively. Smart bidding, effective audience targeting, and life event targeting are just some of the most exciting things that AI has to offer. Apart from these, they also allow you to track in-store visits with location extensions and get additional visibility into conversion paths to optimize user searches for your ads online.

Of course, while AI and machine learning are showing incredible potential, they still cannot totally replace PPC marketing teams at the moment. However, the addition of machine learning in PPC gives PPC marketing teams more time to focus on higher level priorities like data analysis and strategizing your company’s next move in digital marketing.

If you want to ride on the wave of the next big thing in PPC, embracing the benefits that artificial intelligence and machine learning have to offer is the way to go!

Machine Learning Ad Targeting

Of the many innovations that are set to change the marketing and advertising industry, machine learning in artificial intelligence seems to be the most revolutionary. With machine learning in your company’s strategic toolkit, you’ll find your campaigns taking leaps and bounds beyond the imagination of both the industry and your competitors.

The Potential of Machine Learning in Advertising

You may have heard of machine learning and artificial intelligence before. For many creative professionals, they may sound overly-technical. At its heart, machine learning simply means using a computer that has been programmed to learn and adapt as it processes new data. This ability allows the program to identify problems, create predictions, plan new protocols without the direct input, or even supervision of anyone else. This system is based entirely on one initial algorithm.

With the words “data” and “predictions” alone, you can see how machine learning can elevate ad targeting in marketing. Turning data from different sources into actionable data for design and promotion is at the cornerstone of marketing. The way marketers target and deliver ads require the application of information to future scenarios, and that’s where machine learning ad targeting steps in.

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Performance Analysis and the Profit Potential

One of the first and most important ways machine learning elevates ad targeting is through more efficient performance analysis. Traditionally, performance analysis metrics and tools can be difficult to scale and inefficient to perform comprehensively. After all, marketing campaigns, successful or otherwise, tend to be complex operations.

Machine learning can perform equally complex analyses of performance in a way that is scalable and efficient. There are different performance metrics and models that a computer can intuitively and accurately apply. For example, a campaign based on click-through rates can be assessed, as well as those based on install rates and drive conversion.

Accurately assessing the impression from each activity is crucial. Even better, machine learning models are predictive. They can use this data to predict conversion probability or click-through conversion probability of current and future campaigns.

This has amazing profit potential when it comes to ad revenue. Even a 0.1% improvement in the accuracy of a production process can yield hundreds of dollars in additional earnings.

Accurate and Efficient Ad Targeting with Machine Learning

Marketing campaigns rely on resonance and relevance, especially online. As such, the targeting and placement of digital ads are often designed based on the profile of target consumer groups.

Traditionally, consumer group clustering requires lengthy conversions and processing of data from multiple sources. The power of machine learning allows marketers to sift through overwhelming online data. More importantly, machine learning can more efficiently aggregate data mined from different service providers.

In contrast, data on consumer groups and behavior are sometimes incomplete because analysts can’t see the big picture, or can’t correlate certain data points in time. Machine learning can build statistical models that can transform dynamic data into relevant information from marketing in an instant.

Having an algorithm that can learn and pinpoint consumer clusters for you is one of the biggest advantages you can have to make your digital marketing campaigns more targeted and responsive.

2 Comments

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