The 3 Types of SEO Reports You Should Be Building in 2020 - Search Engine Journal

The 3 Types of SEO Reports You Should Be Building in 2020 - Search Engine JournalThe 3 Types of SEO Reports You Should Be Building in 2020 - Search Engine JournalPosted: 06 Jul 2020 10:12 PM PDTThis is a sponsored post written by Supermetrics. The opinions expressed in this article are the sponsor's own.SEO reports come in many shapes and sizes, which is why it's important to start building yours with a clear goal in mind.Do you want to:Track your website's organic visibility in the SERPs?Get content ideas?Identify ideas for paid search campaigns?Figure out which link-building tactics have been generating the best results?In this post, we'll walk you through three must-build SEO report types that will help you stay competitive in 2020 and beyond.Report #1: Website Health AuditBefore you do anything else, you'll want to understand your website's overall health in terms of on-page SEO (internal) and referring domains (external).This report will function as the fo…

As Potential Federal Probes Loom, Google Faces Smaller Antitrust Suits - Adweek

As Potential Federal Probes Loom, Google Faces Smaller Antitrust Suits - Adweek

As Potential Federal Probes Loom, Google Faces Smaller Antitrust Suits - Adweek

Posted: 24 Jun 2020 02:38 PM PDT

Key insight:

A suit filed this week in a San Jose district court alleges Google violated the Clayton Act by leveraging its market power to charge inflated prices for digital ads.

The plaintiffs are three small-business owners who allege they had to overpay for ads and are seeking relief for all advertisers and publishers using Google's ad-tech services. The suit, Devaney v. Google, comes less than a month after a similar class-action complaint, Grand Atlas Tours v. Google, was lodged in the same San Jose court. 

Like the Devaney case, Grand Atlas Tours alleges that Google, through years of acquisitions, has amassed a digital-advertising monopoly that forces advertisers and publishers alike to overpay for its services.

Meanwhile, a separate suit filed in Atlanta last year by a YouTube competitor Inform Inc. makes similar allegations and asks for Google's assorted enterprises—from search advertising and ad servers to Android and Chrome—to be separated.  

These smaller suits may fizzle out, however. In 2015, two class-action antitrust cases accusing Google of using Android to peddle its own software were thrown out for insufficient evidence of "antitrust injury." In other words, the plaintiffs couldn't show that Google's allegedly anticompetitive practices left consumers worse off.

But the recent lawsuits could still foreshadow troubled waters ahead as the potential of federal antitrust probes loom.

Similar to the reported Justice Department and state AG probes, the smaller antitrust suits focus on Google's ad business, rather than its mass-market products. That narrows the meaning of "consumer" to just advertisers and publishers, potentially creating sturdier ground for establishing antitrust injury.

On Tuesday, a day after the Devaney case was filed, Google separately published two blog posts detailing how its ad-tech infrastructure works. One post claims how publishers retain "over 69% of revenue" in Google Ad Manager. The blog posts follow previous attempts by Google to refute claims that it crimps competition. Still, the Mountain View, Calif.-based company pockets approximately 30% of all U.S. digital ad spend, according to eMarketer.

Plaintiffs in the Devaney case argue Google's aggregate market share matters less than its information advantage throughout the ad-tech stack. Google can funnel advertisers to its display and video products because of the firm's deep pool of user data and offering on both the demand and supply side, the complaint notes. Moreover, ads on Google-owned properties like YouTube can only run via Google's ad infrastructure.

The Devaney complaint goes on to cite a recent paper from the Omidyar Network, a nonprofit backed by prominent technologists, laying out the antitrust case against Google. "Google now performs every function that connects advertisers to publishers," the report argues.

While early indications suggest the Justice Department is focusing on Google's ad business, the public-facing rationale has emphasized the alleged role of Big Tech firms in curbing speech.

On Sunday, Attorney General William Barr told Fox News that tech companies are able to "quickly galvanize people's views because they're only presenting one viewpoint," Barr argued. "One way this can be addressed is through the antitrust laws and challenging companies that engage in monopolistic practices," he added.

Welcome to the Predictive Marketing Era - MarTech Today

Posted: 24 Jun 2020 12:00 PM PDT

Ginny Marvin, editor-in-chief at Search Engine Land

Artificial intelligence, machine learning, deep learning, neural networks. These are all part of the digital advertiser's lexicon now as the algorithms power so much of the tactical mechanics of our campaigns. The purpose? To serve that ad combination on that impression at that bid to that audience member to achieve the campaign goal with greater efficiency and efficacy than we marketers could do manually. All by training algorithmic models to understand patterns and predict outcomes based on gobs of historical data.

Google, Microsoft, Facebook and all the other digital advertising platforms are using data and algorithms to identify intent and predict customer needs, behavior and marketing outcomes.

This is the Predictive Marketing Era. And it is changing how performance media strategists and managers work and the skills they and their teams need to prioritize to become smarter, nimbler and more effective PPC marketers. This was the topic of my keynote during our virtual SMX Next event on Tuesday (available on-demand with registration).

Companies have been using predictive analytics for things like anticipating inventory needs, pricing optimization and fraud prevention for years. Machine learning is now pervasive in many marketing tools, including media buying, with ad creation and serving, bidding and targeting increasingly powered by algorithms.

Search marketing, specifically, is evolving from keyword buying to audience buying to predictive intent buying, with automated campaigns served across surfaces based on predicted outcomes. Search marketing is no longer just about buying the right keyword at an efficient cost-per-click.

Now add accelerant. Lots of people have noted that COVID-19 has acted as a trend accelerator. We are certainly seeing that in digital advertising and marketing. The introductions of Facebook Shops and free listings in Google Shopping were both fast-tracked due to COVID, for example, as consumers' shopping behavior trended further online. Many of the consumer habits formed in these months aren't going to disappear.

And machine learning and artificial intelligence are at the heart of nearly every new feature in digital marketing. Ads are served wherever and whenever the systems anticipate the desired outcome. Keywords and/or audiences often play a role, but the platforms are now using data and algorithms to identify intent and predict or anticipate customer needs, behavior and marketing outcomes. As I wrote after Google Marketing Live last year, the company's new campaign types deliver ads across multiple channels — to own every aspect of the customer journey, from the top to the bottom of the funnel.

The idea of running Search and Display together in one campaign will still make many advertisers shudder. But most of the new campaign types don't give advertisers the option to opt out of channel inventory. That, Google will say, was a tactic necessary in a pre-machine learning powered world. Machine learning may be overhyped, but it underpins nearly every aspect of campaigns and will continue to grow in importance.

Understand how the systems are designed to work. To visualize how much of paid search uses machine learning now, we color-coded Search Engine Land's Period Tables of PPC Elements. It's critical to understand how these elements are designed to work before deploying them. Learn as much as you can about how these AI and ML systems are designed to work, what we know about the signals they use, their benefits and shortcomings.

The algorithms aren't perfect. The models train on data, and those inputs matter (there are numerous examples of the unintended consequences of algorithmic bias). A healthy dose of skepticism will help you identify when things aren't delivering the outcomes that matter to your business. But this requires understanding how an element is designed to work.

Take the seasonality adjustment feature, for example. Many people started using it in their Google Ads campaigns at the beginning of the COVID-19 pandemic. Seasonality adjustment was not designed to be used during a sustained period of change, though.

Take data stewardship seriously. None of this works without data. PPC pros are in a position to help inform data strategy in their organizations. In many ways, search marketers have been at the center of understanding how to use data to do better marketing and get better results.

How can you ensure you have systems and processes in place to catch early indicators and be able to segment and activate your own data quickly in your own campaigns? How can you build more direct relationships with users to give you more control and insights as browsers crack down on third-party cookies?

How can your own data or other data sources be used to improve pattern recognition and outcomes in your own campaigns — in ways that respect user privacy and regulations?

Focus on user experiences. Ideally, in the Predictive Marketing Era the algorithms prioritize good user experiences as experiences that are predicted to have the best outcomes based on historical data are weighted more heavily. I spoke last year at SMX Advanced about the relationship between branding and performance, and this also speaks to experience. Direct to consumer brands have put in stark light the importance of branding and experience on performance outcomes.

Pay attention to story, ad creatives, landing pages, retargeting experiences, and your visuals.

See the bigger strategic picture. Particularly with the algorithms increasingly dictating where and to whom ads are served in the Predictive Marketing era, strategic skills are going to be far more valuable than tactical or mechanical skills.

I'd argue that marketing fundamentals matter even more now. This requires a shift in focus to revenue optimization instead of simply channel optimization.

As customer journeys get more complicated, focus on the experiences you're creating based on intent, not on the channel. To do this well takes strategic, creative thinking and planning.

If we're not looking at the bigger picture, we can miss the interplay of marketing efforts and their combined impact on the bottom line. This might also require focusing on new key performance indicators and metrics.

Think about ways you can internalize Predictive Marketing into every aspect of your work to anticipate behaviors and outcomes, from the data you use to the experiences you create to the ways you're measuring success.

Original URL:

About The Author

Ginny Marvin is Third Door Media's Editor-in-Chief, running the day to day editorial operations across all publications and overseeing paid media coverage. Ginny Marvin writes about paid digital advertising and analytics news and trends for Search Engine Land, Marketing Land and MarTech Today. With more than 15 years of marketing experience, Ginny has held both in-house and agency management positions. She can be found on Twitter as @ginnymarvin.

Apple's privacy changes represent 'tectonic shift' for digital ad industry -

Posted: 24 Jun 2020 01:18 PM PDT

Trade groups respond
Apple's announcement drew criticism from both the Association of National Advertisers and the American Association of Advertising Agencies (4A's). In a joint statement today, the groups said that "Apple's actions appear to continue a damaging pattern that began with its Safari web browser and will now extend to its mobile app ecosystem."

Both groups said the changes will impact publishers and mobile app developers, adding that ad personalization, measurement and other capabilities that marketers require to reach consumers will "cease to function."

"Advertising revenue funds vital news-gathering and reporting and supports the development of innovative products and services," said Alison Pepper, exec VP of government relations at the 4A's. "Cutting off this critical income stream for mobile app publishers and developers will hurt an already struggling news industry and countless small businesses and developers who will be forced to find new sources of revenue to fund their operations in order to survive."

The Interactive Advertising Bureau's Tech Lab acknowledged Apple's intentions. "By moving IDFA to 'opt-in' and announcing other privacy-related changes, Apple apparently aims to educate users and offer choices, instead of making decisions for them," Dennis Buchheim, president of the Interactive Advertising Bureau Tech Lab, told Ad Age. "But they're still taking an entirely proprietary approach, and consumers need predictable privacy across all experiences, operating systems, and browsers—which necessitates open standards."

Impact on targeting

The IDFA feature is essentially a way for advertisers to target Apple users and measure engagement, says Brian DeCicco, exec director of customer strategy at Mindshare.

"What IDFA can do for marketers is twofold," says DeCicco. "It can determine which actions a user takes in an app and connect those actions to an IDFA profile." The second, DeCicco says, allows marketers to capture consumer interaction with digital ads and attach it to an IDFA. "This helps you understand engagement and measure performance of an ad campaign," he says.

The changes to IDFA will impact even some of the largest ad platforms. Facebook, for instance, is widely regarded as among the biggest and best when it comes to getting consumers to install apps. The company offers two technologies—App Event Optimization (AEO) and Value Optimizations (VO)—for finding new users for mobile marketers.

Without IDFA, however, brands will face an uphill battle acquiring iOS users through AEO and VO technologies—something Facebook has built into a multi-billion dollar business, according to one person with knowledge of the matter.

"Will those specific product lines have an impact on Facebook? Yes, [IDFA changes] will have an impact," says Wagman, the MediaLink exec.

Direct-to-consumer brands hoping to go from being the 400th most popular app to the 25th will use AEO and VO to capture that growth, according to Wagman. "Or it is a tactic agencies will use to drive more downloads for the Home Depot app, [for example]" he says.

A Facebook spokeswoman told Ad Age in an emailed statement that it's working with its partners to better understand Apple's latest updates and how they affect businesses and people. "We share the industry's desire for more transparency and controls in the way ads run online, while ensuring personalized advertising continues to deliver value to both people and businesses," Facebook said.


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