Artificial intelligence, machine learning and neural networks are major buzzwords in the SEO community today. Marketers have highlighted these technologies’ ability to automate time-consuming tasks at scale, which can lead to more successful campaigns. Yet many professionals often have trouble distinguishing between these concepts.

“Artificial intelligence is essentially the term that defines the whole space,” said Eric Enge, president of Pilot Holding and former principal at Perficient, in his presentation at SMX Next. “Machine learning is a subset of that [AI] set around specific algorithms.”

Natural language processing (NLP) is another system that’s been used for SEO tasks in recent years. It’s primarily focused on understanding the meanings behind human speech.

“NLP is about helping computers better understand language the way a human does, including the contextual nuances,” he said.

With so many developing technologies available, marketers would be wise to learn how they can be applied to their campaigns. Here are three ways AI and its branches can automate SEO tasks at scale.

AI can address customers’ long-tail needs

Enge pointed to a customer search engagement study from Bloomreach that found that 82% of B2C shoppers’ experience is spent searching and browsing. This leaves room for plenty of long-tail searches, which are more niche in nature and, consequently, often overlooked by marketers.

Bloomreach’s own AI tool focuses primarily on extracting insights from this phase of discovery, Enge explained. It can identify site content that’s both underutilized and matches customer long-tail searches.

“AI improves pages by presenting more related pages that currently aren’t being linked to,” he said, “Or even potentially create new pages to fill the holes of those long-tail needs to create a better customer experience.”

Marketers can use AI systems to generate more relevant pages based on these long-tail interests. But, there are some caveats to be aware of.

“Just be careful not to create too many new pages,” Enge said. “There are certainly cases where too many pages can be a bad thing. But deployed properly, this can be very effective.”

AI can enable automated content creation

Enge shared some information about GPT-3, a popular AI language model, to demonstrate AI’s content creation capabilities. While impressive, he noted how a system like this can get out of control if there aren’t proper constraints.

“They [AI systems] currently don’t have any model of the real world,” he said. “They only have the data that they were trained on. They don’t have any perspective or context for anything, so they can make really bad mistakes, and when they write, they’re prone to bias.”

“The wonderful thing about the web is that it has all the world’s information on it — the terrible thing about the web is all the world’s disinformation is on it, too,” he added.

Despite these weaknesses, AI systems have a lot of promise. Continuous improvements in these technologies can help marketers scale content efforts to meet customer expectations.

GPT-3, in particular, has the ability to generate content in a variety of formats, allowing SEOs to focus more on optimization efforts.

“You can use it [GPT-3] to create new content,” Enge said. “You’re going to have to put in a lot of effort and bring a lot of expertise to the table to do it. It might be more cost-effective than writing from scratch, or it may not, depending on how good you are.”

AI can leverage deep learning to help establish topical authority

Having topical authority means your site is a perceived expert on a given subject. This is one of the factors many SEOs believe is vital for improving rankings, which is why so many have leveraged AI’s capabilities.

Enge pointed to seoClarity, which uses an AI tool called Content Fusion designed to help brands write with more authority, to highlight these deep learning capabilities: “The approach is to leverage deep learning to identify entities and words that help you establish authority in a topic,” Enge said. “It extracts intent, entities, terms and potentially related topics. Then they apply their machine learning models that are specific to your market space.”

The deep learning capabilities offer marketers a clearer view of their brand’s area of expertise, which can then be used to further develop their web properties. Establishing an automated deep learning system can provide them with fresh data to help demonstrate E-A-T (Expertise, Authoritativeness, Trustworthiness).

Every AI integration will look different, but each one has the potential to streamline your SEO efforts through automation and machine learning.

“There’s an incredible amount of stuff happening out there with AI,” Enge said. “Some of it you can take into your own hands if you’re willing to do the programming; in other cases, you can use tools. It’s up to you.”

Watch the full SMX Next presentation here (free registration required).

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Google has a new robots tag for when you use embedded content on your pages named indexifembedded. Google said with this new tag “you can tell Google you’d still like your content indexed when it’s embedded through iframes and similar HTML tags in other pages, even when the content page has the noindex tag.”

Why we care. If you embed content on your site and want to control indexing of the content on the page, now you have more control with this new indexifembedded robots tag. Give it a try and see if it helps you with any indexing issues you may have had with pages where you embed content.

Why a new tag. Google explained that sometimes publishers want the content on the page to be indexed and sometimes not, when they embed content. This new robots tag gives you more control over communicating those wishes to Google Search.

“The indexifembedded tag addresses a common issue that especially affects media publishers: while they may want their content indexed when it’s embedded on third-party pages, they don’t necessarily want their media pages indexed on their own,” Google said, “Because they don’t want the media pages indexed, they currently use a noindex tag in such pages. However, the noindex tag also prevents embedding the content in other pages during indexing.”

Noindex and indexifembedded. Google said this new indexifembedded tag works with the original noindex tag: “The new robots tag, indexifembedded, works in combination with the noindex tag only when the page with noindex is embedded into another page through an iframe or similar HTML tag, like object.”

The example Google gave was if podcast.host.example/playpage?podcast=12345 has both the noindex and indexifembedded tag, it means Google can embed the content hosted on that page in recipe.site.example/my-recipes.html during indexing.

Code examples. Here are code examples of how to implement it, the first is via normal meta robots tag and the second is via the x-robots implementation:

Other search engines. It seems Google is the only search engine to currently support this new robots meta tag.

Why use it? I asked John Mueller of Google why would anyone use this? I am still not sure I am convinced but this is what he said:

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Google has added a note to the product structured data help documentation to explain how to specify car markup and still have Product review snippet feature eligibility.

What is new. The note says “currently Car is not supported automatically as a subtype of Product.” You “will need to include both Car and Product types if you would like to attach ratings to it and be eligible for the Search feature,” Google said.

Code example. Google then provided this example in JSON-LD:

Why we care. If you are just using car schema or just using product schema on your car and automobile landing pages, you will want to make sure to use both. If you do not, any review snippets may not show up in the Google search results for your site and web pages.

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Semrush, the SEO toolset provider, has acquired SEO training website Backlinko, the company announced Wednesday, for an unannounced sum.

Why we care. Semrush’s acquisition will likely strengthen the company’s own SEO education hub, Semrush Academy. This could make Semrush a more robust source of SEO knowledge and may help it pull away from other toolset providers.

Additionally, Backlinko draws in 500,000 organic visits a month, according to the announcement. Semrush is likely to market to those users to drive them further down its sales funnel.

Why Semrush may have acquired Backlinko. “The desire to acquire Backlinko was fueled by Semrush’s commitment to inspiring both the current and next generation of digital marketers,” according to the announcement.

In an email sent to Backlinko subscribers, Brian Dean, founder of Backlinko, explained that he wanted to further scale his business, but had hit a plateau in terms of what he could do on his own. “Then, out of the blue, I got an email that changed everything,” Dean wrote, sharing that he was approached for this deal by Max Roslyakov, SVP of marketing at Semrush.

Some SEOs have speculated about other potential reasons for the acquisition: “How much was Backlinko worth to Semrush? Breaking down courses, traffic, and estimated MRR from converting that traffic. What if a competitor came in?” tweeted Victor Pan, head of technical SEO at HubSpot.

“That’s what makes the acquisition itself the joke about our industry — A leading, listed tool company, buying a site, purely for the links gained by publishing nonsense,” Peter Mindenhall tweeted, suggesting that one of the motivators behind the deal was the acquisition of Backlinko’s backlink profile. Mindenhall’s remark about “publishing nonsense” refers to the mixed reception that some of the guidance in Backlinko’s content has garnered from the SEO community.

The future for Semrush/Backlinko. “On joining Semrush, Backlinko founder Brian Dean and his colleagues will continue to grow the Semrush community by creating and curating original content for the Semrush Academy,” according to the announcement.

“As part of my agreement with Semrush, I’ll still be working on Backlinko for the foreseeable future on a part-time basis,” Dean tweeted.

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Much like a physical marketplace, the online search environment has both its successful businesses and those that fail to gain traction. Matt Colebourne, CEO of Searchmetrics, used the analogy of a “high street” — the main area of commercial or shopping — to describe the current state of search marketing in his presentation at SMX Next.

“Just as you have the winners and the losers in the physical space, you have the same in the digital space; page two of Google or any search engine is fundamentally the ‘backstreet,’” he said. “That’s where a lot less audience is going to end up.”

Marketers have long used search data to optimize their content so it meets user needs. But many fail to apply those same insights to inform decisions that impact the long game.

“A lot of companies make the mistake of optimizing for growth way too soon,” Colebourne said. “They settled for their current product set and their question becomes, ‘How can we optimize sales of what we have?’ Whereas the questions they should be asking are, ‘What are the sales that we could have? How much of our target market do we have right now?’”

Each day Google processes over 3.5 billion searches, which provides marketers with a wealth of data. Here are three reasons why analyzing this search data improves marketers’ decision-making processes.

Search data shows where your growth is coming from

“Currently, about 15% of search terms that appear on Google every month are new,” said Colebourne, “So, that starts to give you an inkling of the pace of change that we have to deal with. We see trends come and go in months, and some cases even weeks. And as businesses, we have to respond.”

Many organizations focus too much energy on driving growth while neglecting to determine where that growth is coming from. And in this digital age, there’s a good chance much of it is coming from search. This data offers marketers valuable insights, especially those relating to their industry segment.

“You have to understand how your industry and category is structured and ask the right questions,” he said. “If, for example, you sell specialty sports shoes, it doesn’t make a lot of sense to compare yourselves with Nike or similar companies who have much much bigger coverage, but may not be leaders in certain segments.”

It helps address your most significant decision-making challenges

Data — specifically search data — should be part of any company’s core decision-making process. To show how often brands use it, Colebourne highlighted a survey from Alpha (now Feedback Loop) that asked 300 managers how they made decisions.

“The question they asked was, ‘How important or not important is it to you to use data to make decisions?’” said Colebourne. “And I think nobody is going to be surprised by the results — 91% think data-driven decision-making is important . . . But the corollary to this question was, ‘How frequently or infrequently do you use that?’”

The answer was just 58%.

Clearly, knowing search data is valuable isn’t enough to be successful — marketers need to use these insights from searchers to make better business decisions. Otherwise, they’re going to miss out on a good source of traffic insights.

“65% of all e-commerce sessions start with a Google search,” Colebourne said. “I would argue that makes it a good source for decision-making. It’s a massive sample set, completely up to date, and it’s continually refreshed.”

Search data gives you more consumer context

“That [search] data — sensibly managed and processed — can show you the target market and provide you with the consumer demand,” said Colebourne. “It can show you if the market is growing or contracting.”

Analyzing search data can give marketers a clearer view of their consumers, especially for those groups they haven’t reached yet. Reviewing what people are searching for, how often they’re searching and how your competitors are addressing the challenge can make decision-making that much easier.

But more than that, marketers must look at the marketplace as a whole, using search data to inform decision-making.

“We’re all very focused on keywords and rankings and all these good things that we know how to manage,” Colebourne said. “But what we need to do is step beyond that and not just look at what we have or what competitors have, but look at the totality of the market.”

“Let’s look at the input search data to understand what the real demand is and how big this market is,” he added.

Watch the full SMX Next presentation here (free registration required).

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As a mortgage broker, one of the toughest challenges that you will face is acquiring new leads. That is why it is important to make the most out of every existing borrower relationship. 

But how exactly do you encourage past clients to turn to your team the next time they need mortgage services?

While there are many ways to accomplish this goal, customer relationship management software is the best option. A quality CRM platform will include robust tools that are designed to help you draw in repeat clients. Here are some of the ways that the right tool can make this happen.

Protect Your Brand Reputation

A high-quality CRM software will help you give borrowers a positive experience from start to finish. This is essential to a great brand reputation.

If you provide clients with a seamless loan experience, they will be more likely to do business with you in the future. On the other hand, poor communication or excessive processing times may cause them to seek out other loan officers the next time they need services.

Facilitate Post-Funding Communication

The average borrower will go years without needing mortgage services. During that time, they may forget which loan officer they worked with. That is why it is important for you to maintain regular communication post-funding.

CRM software gives you the ability to create automated follow-up campaigns that will help you keep in touch with past clients. You can reach out to them via SMS or email to ensure that your team is top of mind when clients need new loan products.

Send Out Customized Alerts

Another great way to attract repeat business is through birthday or home anniversary alerts. By simply sending an email or text message to clients on important days, you can let them know that they are a valued customer. 

Once you upload client data into your CRM software, you can enable automated birthday or anniversary alerts with the tap of a button. This means that you will never miss an opportunity to connect with your clients.

Notify Borrowers About Refinance Opportunities

CRM platforms can also help you to notify clients about opportunities to refinance their loans. Most homeowners will jump at the chance to save money. 

A great CRM software will send you notifications anytime one of your past borrowers is eligible for refinancing. You can then craft a custom email or text message that discusses just how much money they could potentially save.

Access the Leading Mortgage CRM

While there are plenty of mortgage CRM options available on the market today, none can compare to the cutting-edge BNTouch platform. Our software features an array of tools that you can use to nurture client relationships and draw in repeat business.

BNTouch offers solutions designed for independent mortgage brokers, large teams, and multi-location enterprises. With our powerful tools for marketing and processing, you can drive repeat business like never before. Ready to learn more? Book your no-obligation demo today!

The post New Year, New Financing: How CRM Tools Can Draw in Repeat Business appeared first on .

Google Ads is rolling out an updated Experiments page, the company announced Wednesday. In the new Experiments pages, advertisers no longer have to create a separate campaign draft and changes made to the original campaign are automatically synced to the experiment as well.

Why we care. This streamlined experiments workflow saves advertisers time by eliminating campaign draft creation. Similarly, the experiment sync feature is also a timesaver because advertisers may no longer have to manually copy changes over from their original campaigns, which can be particularly time-consuming when running multiple experiments simultaneously.

And, the ability to apply the changes from an experiment to the base campaign with just one click also makes implementation easier.

The new Experiments workflow. First spotted by numerous PPC professionals in December 2021, one of the main features of the new workflow is the ability to set up an experiment in a single step, without having to create a campaign draft.

During experiment setup, advertisers can designate how much of their original campaign’s budget and traffic they’d like to use and how long they’d like the experiment to run for. Performance can be monitored from the Experiments page and changes can be applied to the original campaign with a single click.

Automatically sync experiments. The new experiment sync feature automatically updates the trial with any changes made to the base campaign.

Sync is turned on by default whenever a new experiment is created. However, it can’t be turned on for trials that have been scheduled or are already running. All changes made by experiment sync are reported within the account’s change history.

The post Google Ads’ updated Experiments page sheds campaign drafts and adds experiment sync appeared first on Search Engine Land.

Google has updated the recipe schema markup help documents to remove all references to time ranges for food prep, cook time and total time as a supported field type. Now you need to specify a singular time, and no longer provide time ranges.

What changed. Google wrote that it “removed guidance about specifying a range for the cookTime, prepTime, and totalTime properties in the Recipe documentation. Currently, the only supported method is an exact time; time ranges aren’t supported. If you’re currently specifying a time range and you’d like Google to better understand your time values, we recommend updating that value in your structured data to a single value (for example, "cookTime": "PT30M").”

Old docs. the old documentation had references to using minimum and maximum time frames for the range of time it takes to prepare and cook the dish. Here is an old screenshot from the totalTime field about the mix and max ranges:

Now there are only references to using a singular and fixed time without any ranges.

Why we care. If you use recipe schema markup on your pages and have time ranges in that markup, you will want to adjust those ranges to use singular and fixed times. One would assume the Search Console reports will soon show errors for the use of ranges but you should jump on this and modify any uses of ranges in your markup.

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