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Posted by TheMozTeam
With the new year in full swing and an already busy first quarter, our 2019 predictions for SEO in the new year are hopping onto the scene a little late — but fashionably so, we hope. From an explosion of SERP features to increased monetization to the key drivers of search this year, our SEO experts have consulted their crystal balls (read: access to mountains of data and in-depth analyses) and made their predictions. Read on for an exhaustive list of fourteen things to watch out for in search from our very own Dr. Pete, Britney Muller, Rob Bucci, Russ Jones, and Miriam Ellis!
People Also Ask boxes exploded in 2018, and featured snippets have expanded into both multifaceted and multi-snippet versions. Google wants to answer questions, it wants to answer them across as many devices as possible, and it will reward sites with succinct, well-structured answers. Focus on answers that naturally leave visitors wanting more and establish your brand and credibility. [Dr. Peter J. Meyers]
Optimizing for voice search will still be no more than optimizing for featured snippets, and conversions from voice will remain a dark box. [Russ Jones]
This is barely a prediction. If your 2019 plan is to finally figure out mobile, you're already too late. Almost all Google features are designed with mobile-first in mind, and the mobile-first index has expanded rapidly in the past few months. Get your mobile house (not to be confused with your mobile home) in order as soon as you can. [Dr. Peter J. Meyers]
Expect Google to find more and more ways to replace organic with solutions that keep users on Google’s property. This includes interactive SERP features that replace, slowly but surely, many website offerings in the same way that live scores, weather, and flights have. [Russ Jones]
Featured Videos, Video Carousels, and Suggested Clips (where Google targets specific content in a video) are taking over the how-to spaces. As Google tests search appliances with screens, including Home Hub, expect video to dominate instructional and DIY niches. [Dr. Peter J. Meyers]
We’ve seen the start of interactive SERPs with People Also Ask Boxes. Depending on which question you expand, two to three new questions will generate below that directly pertain to your expanded question. This real-time engagement keeps people on the SERP longer and helps Google better understand what a user is seeking. [Britney Muller]
Google will continue asking more and more intimate questions about your business to your customers. Does this business have gender-neutral bathrooms? Is this business accessible? What is the atmosphere like? How clean is it? What kind of lighting do they have? And so on. If Google can acquire accurate, real-world information about your business (your percentage of repeat customers via geocaching, price via transaction history, etc.) they can rely less heavily on website signals and provide more accurate results to searchers. [Britney Muller]
In Moz’s recent State of Local SEO report, the majority of respondents agreed that Google’s focus on the proximity of a searcher to local businesses frequently emphasizes distance over quality in the local SERPs. I predict that we’ll continue to see this heavily weighting the results in 2019. On the one hand, hyper-localized results can be positive, as they allow a diversity of businesses to shine for a given search. On the other hand, with the exception of urgent situations, most people would prefer to see best options rather than just closest ones. [Miriam Ellis]
Look to see more of the local and maps space monetized uniquely by Google both through Adwords and potentially new lead-gen models. This space will become more and more competitive. [Russ Jones]
Google and Amazon have been moving towards voice-supported displays in hopes of better monetizing voice. It will be interesting to see their efforts to get displays in homes and how they integrate the display advertising. Bold prediction: Amazon will provide sleep-mode display ads similar to how Kindle currently displays them today. [Britney Muller]
I expect we’ll see a greater focus on the analysis of SERPs as Google does more to give people answers without them having to leave the search results. We’re seeing more and more vertical search engines like Google Jobs, Google Flights, Google Hotels, Google Shopping. We’re also seeing more in-depth content make it onto the SERP than ever in the form of featured snippets, People Also Ask boxes, and more. With these new developments, marketers are increasingly going to want to report on their general brand visibility within the SERPs, not just their website ranking. It’s going to be more important than ever for people to be measuring all the elements within a SERP, not just their own ranking. [Rob Bucci]
2019 is going to be another year in which we see the emphasis on individual search queries start to decline, as people focus more on clusters of queries around topics. People Also Ask queries have made the importance of topics much more obvious to the SEO industry. With PAAs, Google is clearly illustrating that they think about searcher experience in terms of a searcher’s satisfaction across an entire topic, not just a specific search query. With this in mind, we can expect SEOs to more and more want to see their search queries clustered into topics so they can measure their visibility and the competitive landscape across these clusters. [Rob Bucci]
I recently conducted a small study in which there was a 75% correlation between organic and local pack rank. Linked unstructured citations (the mention of partial or complete business information + a link on any type of relevant website) are a means of improving organic rankings which underpin local rankings. They can also serve as a non-Google dependent means of driving traffic and leads. Anything you’re not having to pay Google for will become increasingly precious. Structured citations on key local business listing platforms will remain table stakes, but competitive local businesses will need to focus on unstructured data to move the needle. [Miriam Ellis]
A Google rep recently stated that about one-third of local searches are made with the intent of reading reviews. This is huge. Local businesses that acquire and maintain a good and interactive reputation on the web will have a critical advantage over brands that ignore reviews as fundamental to customer service. Competitive local businesses will earn, monitor, respond to, and analyze the sentiment of their review corpus. [Miriam Ellis]
We’ve heard from Mozzers, and now we want to hear from you. What have you seen so far in 2019 that’s got your SEO Spidey senses tingling? What trends are you capitalizing on and planning for? Let us know in the comments below (and brag to friends and colleagues when your prediction comes true in the next 6–10 months). ;-)
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Posted by TheMozTeam
This post was originally published on the STAT blog.
We all know that featured snippets provide easy-to-read, authoritative answers and that digital assistants love to say them out loud when asked questions.
This means that featured snippets have an impact on voice search — bad snippets, or no snippets at all, and digital assistants struggle. By that logic: Create a lot of awesome snippets and win the voice search race. Right?
Right, but there’s actually a far more interesting angle to examine — one that will help you nab more snippets and optimize for voice search at the same time. In order to explore this, we need to make like Doctor Who and go back in time.
Back when dinosaurs roamed the earth and queries were typed into search engines via keyboards, people adapted to search engines by adjusting how they performed queries. We pulled out unnecessary words and phrases, like “the,” “of,” and, well, “and,” which created truncated requests — robotic-sounding searches for a robotic search engine.

Of course, as search engines have evolved, so too has their ability to understand natural language patterns and the intent behind queries. Google’s 2013 Hummingbird update helped pave the way for such evolution. This algorithm rejigging allowed Google’s search engine to better understand the whole of a query, moving it away from keyword matching to conversation having.
This is good news if you’re a human person: We have a harder time changing the way we speak than the way we write. It’s even greater news for digital assistants, because voice search only works if search engines can interpret human speech and engage in chitchat.
By looking at how digital assistants do their voice search thing (what we say versus what they search), we can see just how far machine learning has come with natural language processing and how far it still has to go (robots, they’re just like us!). We can also get a sense of the kinds of queries we need to be tracking if voice search is on the SEO agenda.
For example, when we asked our Google Assistant, “What are the best headphones for $100,” it queried [best headphones for $100]. We followed that by asking, “What about wireless,” and it searched [best wireless headphones for $100]. And then we remembered that we’re in Canada, so we followed that with, “I meant $100 Canadian,” and it performed a search for [best wireless headphones for $100 Canadian].

We can learn two things from this successful tête-à-tête: Not only does our Google Assistant manage to construct mostly full-sentence queries out of our mostly full-sentence asks, but it’s able to accurately link together topical queries. Despite us dropping our subject altogether by the end, Google Assistant still knows what we’re talking about.
Of course, we’re not above pointing out the fumbles. In the string of: “How to bake a Bundt cake,” “What kind of pan does it take,” and then “How much do those cost,” the actual query Google Assistant searched for the last question was [how much does bundt cake cost].

Just after we finished praising our Assistant for being able to maintain the same subject all the way through our inquiry, we needed it to be able to switch tracks. And it couldn’t. It associated the “those” with our initial Bundt cake subject instead of the most recent noun mentioned (Bundt cake pans).
In another important line of questioning about Bundt cake-baking, “How long will it take” produced the query [how long does it take to take a Bundt cake], while “How long does that take” produced [how long does a Bundt cake take to bake].

They’re the same ask, but our Google Assistant had a harder time parsing which definition of “take” our first sentence was using, spitting out a rather awkward query. Unless we really did want to know how long it’s going to take us to run off with someone’s freshly baked Bundt cake? (Don’t judge us.)
Since Google is likely paying out the wazoo to up the machine learning ante, we expect there to be less awkward failures over time. Which is a good thing, because when we asked about Bundt cake ingredients (“Does it take butter”) we found ourselves looking at a SERP for [how do I bake a butter].

Not that that doesn’t sound delicious.
So, what are we to make of all of this? That we’re essentially in the midst of a natural language renaissance. And that voice search is helping spearhead the charge.

As for what this means for snippets specifically? They’re going to have to show up for human speak-type queries. And wouldn’t you know it, Google is already moving forward with this strategy, and not simply creating more snippets for the same types of queries. We’ve even got proof.

Over the last two years, we’ve seen an increase in the number of words in a query that surfaces a featured snippet. Long-tail queries may be a nuisance and a half, but snippet-having queries are getting longer by the minute.
When we bucket and weight the terms found in those long-tail queries by TF-IDF, we get further proof of voice search’s sway over snippets. The term “how” appears more than any other word and is followed closely by “does,” “to,” “much,” “what,” and “is” — all words that typically compose full sentences and are easier to remove from our typed searches than our spoken ones.
This means that if we want to snag more snippets and help searchers using digital assistants, we need to build out long-tail, natural-sounding keyword lists to track and optimize for.
When it’s finally time to optimize, one of the best ways to get your content into the ears of a searcher is through the right snippet formatting, which is a lesson we can learn from Google.
Taking our TF-IDF-weighted terms, we found that the words “best” and “how to” brought in the most list snippets of the bunch. We certainly don’t have to think too hard about why Google decided they benefit from list formatting — it provides a quick comparative snapshot or a handy step-by-step.

From this, we may be inclined to format all of our “best” and “how to” keyword content into lists. But, as you can see in the chart above, paragraphs and tables are still appearing here, and we could be leaving snippets on the table by ignoring them. If we have time, we’ll dig into which keywords those formats are a better fit for and why.
You could be the Wonder Woman of meta descriptions, but if you aren’t optimizing for the right kind of snippets, then your content’s going to have a harder time getting heard. Building out a voice search-friendly keyword list to track is the first step to lassoing those snippets.
Want to learn how you can do that in STAT? Say hello and request a tailored demo.
Need more snippets in your life? We dug into Google’s double-snippet SERPs for you — double the snippets, double the fun.
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