7 Potential Future Search Signals

What Google and Bing might use to rank search results going for­ward.

Lisa Lacy By Lisa Lacy. Join the discussion » 0 comments

Unfor­tu­nate­ly for dig­i­tal mar­keters, there is no yel­low brick road that leads direct­ly to good search rank­ings. How­ev­er, at SMX Advanced recent­ly, Rand Fishkin, the so-called Wiz­ard of Moz, looked into his crys­tal ball to pro­vide some insight into what may mat­ter to search engines and impact rank­ings in the future.

Smart mar­keters who want to stay ahead of search algo­rithms and be found by con­sumers at crit­i­cal moments know they need to watch where Google is going.

It’s very pos­si­ble these sig­nals are pure­ly spec­u­la­tive, but I think there is inter­est­ing evi­dence and/or patent appli­ca­tions from search engines sug­gest­ing it might hap­pen now or in future,” Fishkin said.

Here’s a look at Fishkin’s take on some more spec­u­la­tive rank­ing sig­nals, as well as his insight into what Google and Bing might use to rank results going for­ward.

1. Usage Data Of Pages & Sites

Fishkin uses the exam­ple of a query for “cloud com­put­ing” and points to Google Chrome and Android device usage as per­haps ele­ments that are already inform­ing Google of what con­sumers are search­ing for. In this par­tic­u­lar exam­ple, a site with few­er vis­its per day ranks high­er because Google is send­ing searchers to the page with greater vis­i­tor loy­al­ty and engage­ment, he said.

And in anoth­er search for “silk flow­ers”, he notes this type of rank­ing input could be behind the strong per­for­mance of pop­u­lar brand sites like Michaels and Ama­zon in queries where clas­sic SEO ele­ments are lack­ing, like poor key­word tar­get­ing and rel­e­vance, as well as few links, because the sites prob­a­bly have stronger traf­fic and engage­ment than their com­pe­ti­tion.

2. Accuracy vs. Popularity Of Information

Fishkin point­ed to a query for “do vac­cines cause autism” and not­ed the web­site www.howdovaccinescauseautism.com ranks #2, which he said was ini­tial­ly trou­bling until he clicked on the link and dis­cov­ered the site says, “They fuck­ing don’t.”

It makes you proud of the Inter­net,” Fishkin said. “By look­ing at mul­ti­ple data sets, you real­ize an algo­rithm could deter­mine the con­sis­ten­cy of accu­ra­cy shown by a giv­en web­site and poten­tial­ly boost rank­ings based on that.”

3. Query Structure As An Anchor-Text-Like Signal

Not­ing this par­tic­u­lar sig­nal is “high­ly spec­u­la­tive,” Fishkin said how we con­struct search queries may be a fac­tor that deter­mines rank­ings in the future.

In oth­er words, many searchers are using query struc­tures in a par­tic­u­lar fash­ion that could con­nect brands and mod­i­fiers to key­words, which, he said, opens an oppor­tu­ni­ty for mar­keters.

For exam­ple, a search for “sun­glass” could bring up sug­gest­ed results for the brand “Sun­glass Hut.”

What’s more, pop­u­lar search­es around a brand could indi­cate asso­ci­a­tions that man­i­fest in rank­ings input, he added.

4. Brands As Entities, Entities As Answers

Brands are increas­ing­ly becom­ing enti­ties in Google’s Knowl­edge Graph, Fishkin said. And in many com­pet­i­tive SERPs, there seems to be a cor­re­la­tion between brand drop­downs and high­er rank­ings.

I see folks say­ing brands aren’t some­thing Google talks about, but enti­ties are,” Fishkin said. “Brands are becom­ing what Google clas­si­fies as enti­ties.”

In oth­er words, Google can see peo­ple also search for not just a giv­en query, but a spe­cif­ic enti­ty, which is “at least sub­tly show­ing some brand bias,” Fishkin said.

He also not­ed there is a strong cor­re­la­tion between brand drop­downs and high­er rank­ings.

Using the exam­ple of a search for “Seat­tle real estate mar­ket,” he points out that real estate web­site Zil­low is so tight­ly con­nect­ed to the key­words and asso­ci­at­ed with the query that it appears in the sug­ges­tions drop­down.

You just want to be what peo­ple asso­ciate with the query,” Fishkin said. “Now you own your traf­fic,” which, he added, is a poten­tial SEO tac­tic for the future.

Google Sug­gest also shows brand queries that earn strong con­nec­tions to URLs. Even some gener­ic queries – like for “maps” or “toys” – bring up brand­ed domain sug­ges­tions for Google Maps and ToysRUs.com.

Fishkin uses the exam­ple of ask­ing a room­ful of peo­ple – like, say, the SMX crowd – about what results they expect for a giv­en query, like, “tech news,” or, “New York best restau­rants,” and how it is fair­ly easy to pre­dict which brands will rank high­ly and then say­ing, “Yup,” upon see­ing expect­ed results.

In fact, Fishkin said the best way for brands to rank in 2018 is to “find a way to be the first, ‘yup,’ that every­one yells out in the room.”

5. Tracing The Visit Path To An Answer

Google wants to dis­am­biguate the query path to get con­sumers to com­ple­tion faster, Fishkin said.

In oth­er words, if Google sees that many peo­ple who per­form these types of queries – like for “best ramen noo­dles,” “instant noo­dle brands,” “tasti­est pack­aged noo­dle,” etc. – even­tu­al­ly end their queries on the top­ic after vis­it­ing instant noo­dle review site The Ramen Rater, Google might use the click­stream data to help rank that site high­er, even if it doesn’t have tra­di­tion­al rank­ing sig­nals.

6. Weighting Elements Of User Experience

Since launch­ing its Pan­da algo­rithm update, Google has tried to sur­face not just qual­i­ty con­tent, but high-qual­i­ty web­sites, which is why Pan­da can hurt a site with good con­tent by hav­ing lots of bad con­tent on it as well, Fishkin said.

And if Google isn’t already doing it, it is at least think­ing about how to mea­sure UX and rank sites that do it bet­ter high­er, he added.

7. Replacing Flawed Humans With Deep Learning Machines

Fishkin also points to a shift from human-cre­at­ed algo­rithms to machine learn­ing, which he said “changes the equa­tion for how we are think­ing about SEO.”

In machine learn­ing, a com­put­er is giv­en images from across the Inter­net and trained to rec­og­nize and qual­i­fy said images and com­pa­ra­ble images as pic­tures of, say, cats.

Deep learn­ing takes it one more step, Fishkin said.

We give the machine a bunch of pic­tures and we don’t have to give it cat­e­go­riza­tion, but it fig­ures out these things should be cats,” Fishkin said. “That’s super pow­er­ful and sug­gests if Google can do that for YouTube videos and images, why not for rank­ing ele­ments? Replace YouTube with the Web and cats with any giv­en search query, and it’s not hard to imag­ine Google cre­at­ing a deep learn­ing rank­ing algo­rithm.”

For exam­ple, Fishkin said that when he search­es for “Paul Gra­ham,” Google knows that based on his his­to­ry, he is prob­a­bly look­ing for Paul Gra­ham the pro­gram­mer and not the pho­tog­ra­ph­er.

And, in the future, even Google’s search qual­i­ty engi­neers may have no idea why some­thing ranks or whether they’re using a par­tic­u­lar fac­tor in the rank­ing algo­rithm, Fishkin said. The machine will sim­ply ask, “What algo­rithm pro­duces results that searchers engage with best?” and then make it, he said.

For Google, It’s All About User Experience

In addi­tion, accord­ing to Fishkin, Google seems to be going down what he calls “a strange path” in which total searchers, num­ber of searchers, and search­es per searcher are going up, so he ques­tions whether Google is sac­ri­fic­ing ad impres­sions to make searchers hap­py and whether Google is will­ing to take away queries that pro­vide rev­enue.

In the end, Fishkin said he thinks Google is think­ing long term.

They want addict­ed searchers pro­vid­ing data about them­selves so they can charge more per ad unit,” Fishkin said. “Face­book has shown Google that more data about users yields more dol­lars per impres­sion and click. I think Google will chase bet­ter UX to almost any extent in order to keep searchers and get data, even at the cost of their exist­ing mod­el.”

In oth­er words, Fishkin said Google cares about user expe­ri­ence almost more than mon­ey and could be sac­ri­fic­ing rev­enue direct­ly to pro­vide a bet­ter expe­ri­ence, which he calls “pret­ty inno­v­a­tive and brave.”

Face­book has shown that by hav­ing all that data, it can charge more for impres­sions and clicks than Google can, which is scary to Google. That’s why there are so many algo­rithms around users, user expe­ri­ence, click­stream mod­els,” Fishkin said. “It’s pre­dict­ing people’s hap­pi­ness. If you keep chang­ing to bet­ter the user expe­ri­ence in order to keep searchers, you can keep col­lect­ing data. Google will chase bet­ter UX to almost any extent.”

What’s your take on Fishk­in’s poten­tial future search sig­nals?

Lisa Lacy

Written by Lisa Lacy

Lisa is a senior features writer for Inked. She also previously covered digital marketing for Incisive Media. Her background includes editorial positions at Dow Jones, the Financial Times, the Huffington Post, AOL, Amazon, Hearst, Martha Stewart Living and the Dian Fossey Gorilla Fund.

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