Is your company looking for ways to spend less time and money driving traffic to your websites? GPO’s Brian Rutledge and Marchex’s Brian Craig (a.k.a. Brian-squared) present a proven and effective solution in the webinar, “How to Increase Revenue from Local Business Pages,” for boosting revenue from web traffic.
The two industry leaders will explain how Search Engine Optimization (SEO) remains the key driver of site traffic, and how you can leverage SEO to drive quality traffic without breaking the bank.
And yes, SEO remains a driver. As Hubspot points out…
Organic search equates to 94% of all web traffic, and the first position on Google search results has a 34% click-through rate for desktop and 35% percent for mobile.
Brian-squared will explain how tracking calls from organic local pages can deliver an exponential digital reward.
If you’re a franchise or multi-location business that utilizes local web pages as part of your digital marketing strategy, you may be able to boost performance from these pages.
Sign up today!Join Brian-squared on February 19, 2020 at 10:00 AM PT (1:00 PM ET) to learn how you can:
Optimize inbound call traffic to business websites
We are both fascinated and intimidated by artificial intelligence. We feed AI by seeding search engines with billions of queries every day. We even try to teach AI to flirtand end up with weird but endearing pickup lines like, “You’re so beautiful that you say a bat on me and baby,” and, “You look like a thing and I love you.” But — we also stiffen at the thought of AI stealing our jobs.
As digital marketers (and especially at GPO), we rely on Google’s AI-powered algorithms to get our content and ads in front of the right users at the right time, even if the user’s query isn’t an exact match to the words in the content. We expect the search engine to understand the purpose and value of our content. Most of the time, it does. BERT’s goal is to help when it doesn’t.
To understand BERT, you need to understand NLP
Computers are great at reading text but not good at understanding language.
Natural language processing (NLP) works to bridge the gap between reading and understanding.
Researchers have already developed NLP models that help computers understand specific types of language. Examples of successful NLP include entity recognition (being able to tell the difference between a person, time, organization, location, monetary value, etc.) and sentiment analysis (recognizing attitude and tone).
Moz’s Britney Mullerexplains that each piece of successful NLP is like a kitchen utensil. Your whisk is excellent at whisking, but don’t ask it to chop. Likewise, your food processor can slice and dice and grind, but don’t expect it to grill a sandwich like a panini press!
BERT is the one kitchen utensil that does it all — the Swiss Army Knife of kitchen tools!
So, what’s BERT?
Instead of looking at the meaning of words one-by-one and in consecutive order, BERT looks at words in relation to all the other words in a sentence.
“BERT models can therefore consider the full context of a word by looking at the words that come before and after it,” notes Google.
Here’s an example of a search engine result page (SERP) that Google tested with and without BERT.
As a human, if you saw the query, “2019 brazil traveler to usa need a visa,” you’d probably recognize that a Brazilian wanted to travel to the U.S. and needed a visa. Before BERT, Google wouldn’t get that. It would return a news article about U.S. citizens traveling to Brazil.
BERT, however, grasps the nuance and placement of “to” and serves a result for tourists traveling to the United States — just what the searcher wanted!
Going forward, Google estimates that BERT will impact one in 10 searches in the U.S., and primarily improve long-tail conversational queries where prepositions and context are pivotal to accuracy.
What does that mean for you? Next time you ask Google if you can pick up medicine for someone at the pharmacy, Google will show you a result titled “Can a patient have a friend or family member pick up a prescription,” instead of general results about filling prescriptions.
That said, BERT still needs some fine-tuning.
BERT’s great, but not perfect
BERT is still far away from understanding language and context in the same way that we humans can understand it, believes Allyson Ettinger, Natural Language Processing researcher at the University of Chicago.
Ettingerfound that the BERT model “struggles with challenging inferences and role-based event prediction–and it shows clear failures with the meaning of negation.”
BERT can’t understand what things are NOT. For example, BERT knows that a Robin is a bird. Great. But when asked to predict what a Robin is not…BERT also predicted a bird.
BERT struggles with layered inferences, too. For instance, you can search for “what state is south of Maine,” and you’ll get results for South Portland, Maine, when the answer you wanted was “New Hampshire.”
Can you optimize for BERT?
Nope. There’s no magic potion for pleasing BERT. You can’t optimize for it, but you can write towards it.
“The only way to improve your website with this update is to write really great content for your users and fulfill the intent that they are seeking,” recommends Muller.
Similar to theJune 3 algorithm update (and most other broad core algorithm update), BERT is about improving relevance and enhancing Google’s ability to connect search queries to the right content. It’s not about targeting specific websites or verticals.
Google’s recommendation echoes Muller’s:
Google believes you should be able to search in a way that feels natural to you. BERT gets us one step closer to AI having a real degree of language understanding, and leaps and bounds closer to seeing SERPs that are so relevant to our query that we can’t help but say, “You look like a thing and I love you, Google.”
The study also finds that the same query on the same search engine generates a different rank in mobile and desktop 79% of the time.
That means that while you may have visibility on page one of Google when searching a key phrase on desktop, you likely won’t see the same results when you search on mobile and vice versa.
For listings in positions 1-20, 47% had mobile and desktop rankings that were not the same, reports BrightEdge.
So what? Google has already indicated that the mobile-first index is imminent, and not in a “somewhere over the rainbow” kind of way. Having a responsive site is the first of many steps in having a truly optimized mobile user experience. The next step? Understanding the intent behind customer’s mobile searches vs their desktop searches.
How are your customers using mobile to find you? Once you can identify and differentiate between desktop and mobile demand, you can produce separate mobile and desktop content that resonates on multiple devices. And where organic visibility or CTR differs between devices, you can use your knowledge to optimize for the device that’s more important to your customers.
This is one reason we differentiate and track desktop vs mobile organic traffic and engagement—to provide you with a clearer picture of how well you’re reaching your mobile customers. If you’re ready for a deeper dive into device-specific keywords and traffic, send us a note. We’re here to help you build the mobile foundation you need for the future!
It may be easy to think that to achieve favorable search results on Google, Bing or Yahoo, simply putting up a video, blogging or posting to Facebook and Twitter will get the job done. However, to achieve optimal results, the combination of search marketing, organic search engine optimization, and social media necessitates a cohesive strategic vision. Moreover, this vision is not an end-game approach, but rather an ongoing and flexible process. The need for flexibility stems from the constantly shifting changes in search algorithms and consumer behavior. We are often asked at Get Page One how each of these components operates in tandem to reach results.
While the answers are not always simple, search engines begin the course of online visibility through a complex combination of factors. More than just heading tags, anchor text, backlinks and advertisements, each component in the search process works together to develop placement on search engines, where the best place is, of course, top visibility. Ideally, through the progression of increasing views and interaction, organizations convert search results into consumer demand and new sales.
In a sense, it is akin to a professional baseball team playing for a World Series title. Each element, from pitching and hitting to defense seemingly operate separately. However, these components do not win championships by operating independently. The manager must know when to bunt and steal bases and when to pull the starting pitcher and rely on the bullpen.
Likewise, search marketing, SEO, and social media marketing all seemingly function as separate entities. Yet, each has its own objectives. Choosing the right keywords, effective use of ad elements such as targeting and call-to-action, engagement through social networks and measuring results are just a few pieces of the puzzle.
On the Internet, you want to be in the right place at the right time, when the consumer is looking. Each building block in the practice of search marketing helps to realize this goal. Optimal search results typically occur when each building block combines within a comprehensive strategy. Therefore, like a World Championship baseball organization, achieving top Internet ranking is a team effort.