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Zero-Click Searches: How to Get Back Your Lost Google Traffic

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More than 50% of Google searches end without an organic click – and that’s a huge threat to our websites.

These zero-click searches are resulting in growing losses in both revenue and leads, making Google everyone’s competitor.

On February 26, I moderated a sponsored Search Engine Journal webinar presented Andreas Dzumla, CEO and Co-founder at Longtail UX.

Dzumla showed simple, proactive steps that marketers can take today to recover traffic lost to zero-click searches.

Here’s a recap of the webinar presentation.

The Rise of Zero-Click Searches

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The rise of zero-click searches is an issue of growing importance to members of the SEO and SEM community.

There was a time when all a search engine result page (SERP) pointed to 10 blue links with a few ads in between.

Nowadays, the SERPs are filled with other features that don’t lead to websites.

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In November 2019, Rand Fishkin highlighted the challenge that SEO pros are facing:

“The largest source of traffic on the web — free and paid — is becoming a walled garden, intent on keeping people on its own properties.”

This is happening to SERPs for various industries and verticals, including:

  • Hotels

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  • Finance: According to WordStream, the CTR of a #1 SERP result falls by 39% when a featured snippet is present.

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  • Automotive

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A similar scenario is happening on the PPC side.

On top of all the challenges in the landscape (including increasing competition and complexity, limited control with automation, and tech limitations and content creation for landing pages), paid search is likewise becoming a walled garden because of the “Amazonification” of the SERPs.

For instance, Google Shopping is attempting to provide a better experience for users.

Instead of having a number of links where users click through in order to go see different products here, now Google Shopping provides many more products in one click.

google shopping 5e5d3a189c1fa

While good for user experience, this also leads to some issues from an advertiser’s perspective.

There is more pogo-sticking and more competition on prices.

Plus, having all transactions done within Google means you’re paying for traffic but users never actually land on your website.

You’ll be unable to:

  • Promote brand experience.
  • Do list building and retargeting.
  • Do cross-selling.
  • Have a good margin.

Google is threatening to turn ecommerce websites into mere suppliers, by forcing us to compete on price alone (and even starts handling the checkout).

A Silent Threat: Google’s Competition with Websites & the ‘Amazonification’ of Search

Google’s competition with websites and the “Amazonification” of search is a silent threat for marketers. Here’s why.

SEOs Have Been Looking at the Wrong Metrics

It’s because SEO pros  have been looking at the wrong metrics:

  • Rankings
  • Visibility

BERT will only make things worse for marketers.

The effect of this algorithm to SEO came under the radar as most SEO tracking tools aren’t that good in the long-tail.

BERT will actually mean:

  • More featured snippets and better answer boxes.
  • Less CTR to websites.
  • Profit for Google.

PPC Pros Have Gotten Used to Spending More for Less

PPC pros have gotten used to spending more for less due to:

  • Increasing competition.
  • Dependence of product detail pages (PDPs).

The Blame Game

Instead of blaming Google, we need to be reminded of the following truths:

  • Google’s customers in SEO are not websites and digital marketers – but the searcher. In PPC, the serve digital marketers and the searcher.
  • Google tests SERP features algorithmically – so the numbers tell them they are right.
  • Google provides automated content and covers the long-tail because you don’t do it.

But when you think about it, Google isn’t entirely faultless.

  • Google’s own Analytics doesn’t tell you which keywords provide 97% of SEO traffic and revenue (“not provided”) – forcing search marketers to rely on visibility and rankings from third-party tools.
  • Google Search Console shows Impressions and Clicks only for top 1,000 KWs – and it’s not linked to Conversions and Revenue.
  • A Groupon study found that Google attributes up to 60% of organic traffic as “Direct”.

Solving the SEO Problem

Despite the challenges, there are solutions to get back your lost traffic from zero-click searches.

Rand Fishkin provided some solutions over at SparkToro, including (but not limited to):

  • Institutional action.
  • Strategic keyword selection: Done manually, this can be expensive, time-consuming and deliver an uncertain outcome.

But there is a better way to approach this: by having automation that will:

  • Target long-tail keywords at scale.
  • Know when you provide better content than Google.
  • Make informed decisions based on data.

1. Keyword Research with First-Party Data

First-party data beats third-party data any day of the week.

For companies that run Google Ads, this would be available in the Search Terms report.

However, SEMrush, Ahrefs, Keyword Planner and other tools are great if you don’t have first-party data.

2. Look at Brand vs. Non-Brand SEO

How much revenue your website made on non-brand SEO is something you can’t look up in any tool or in Search Console or Google Ads, but it’s an important area to help you plan on your strategy.

3. Keyword-Level ROI Insights for SEO & Test Keywords at Scale

Having a long-tail keyword strategy is crucial in order to compete with Google.

Creating better long-tail content and providing better UX than Google can reward you with better search visibility.

All these are now possible with platforms such as Longtail UX.

What You Can Do

In a Google world where half your on-SERP visibility is at risk, if you can “fail” cheap, you can keep winning.

To do this, start automating:

  • Page creation.
  • Custom user experience.
  • Contextual interlinking.
  • Measure SEO ROI at the keyword-level.

Solving the PPC Problem

Everyone else thinks that focusing on product detail pages (PDPs) in paid search is the key.

But there’s an alternative. Using automation, you can:

  • Let each keyword create their own matching landing page.
  • Let the landing pages create their own campaign structure.

These may result in better conversions and ROAS, among others.

Q&A

Here are just some of the attendee questions answered by Andreas Dzumla.

Q: When it comes to reporting, you mentioned that SEO’s should shift away from Rank and Visibility. What should be the metric(s) for reporting moving forward. Aside, from analytic tools like GA/Abode Analytics to measure those ordinary website metrics.

Andreas Dzumla (AD): Revenue and conversions, using Landing Page reports.

You can see your last 12 months – plus the opportunity for growth by implementing Longtail UX – by running the Scorecard at https://scorecard.longtailux.com/.

Q: Does the solution integrate with Shopify Plus and BigCommerce?

AD: Yes, Longtail UX works with Shopify Plus and BigCommerce.

Q: Automation is great for some tasks, but Google might penalize you if you don’t use it as they want you to – mostly around smart bidding. This is not a great fit for all campaigns. Low volume/high value conversions are best controlled manually IMO.

AD: We run hundreds of thousands of long-tail landing pages. No SKAG (single keyword ad group) run to those pages has ever gotten a penalty.

Q: What’s the critical mass needed for the long tail to be effective? I have a client site with only 100 pages.

AD: Automated – 1,000 pages.

Q: Does this affect professional services (veterinarian) like it does if you’re selling products?

AD: Yes, in fact lead generation websites often do better with Longtail UX because Google doesn’t put as many on-SERP distractions on non-product related searches.

Q: What is the approach to identify and reduce click fraud?

AD: We don’t deal with much of this, but it would be tough to get click fraud on a Longtail UX landing page.

We only run SKAGs at them, and they’re usually for keywords that get so little search volume that it would be hard for a competitor to find and defraud them. (Most of the keywords our customers target get <100 exact searches per month.)

Q: Is it not a risk to organic SEO rankings to have thousands of landing pages? Will these be crawlable or hidden just for PPC ads?

AD: Not a risk. We roll out pages for Organic SERPs at a rate of 20% of indexed pages on the website. All long-tail landing pages intended for collection of PPC traffic are noindex, nofollow. (So no need to worry about crawl budget in either case.)

Q: Where are the best places to get first party data?

AD: The Search Terms report from GA. The Longtail UX Scorecard shows you everything you need to know in about 30 seconds of work.

Q: Will automating the page creation process sacrifice design and UX for ranking/conversion?

AD: No. Longtail UX landing pages convert on average 50-100% higher than product detail pages.

From the perspective of the searcher, she’s just grateful somebody finally created a landing page to serve her very personalized search.

Q: Amazing statistics of how few SEOs look at keyword data. How are you determining clicks or revenue for featured snippets?

AD: That report comes from Tim Soulo at Ahrefs: https://ahrefs.com/blog/featured-snippets-study/

Q: You won’t see Search Terms reports unless you’re running ads.

AD: That’s right. To be a prospect for Longtail UX, you need to be running at least $20,000/month in paid search ads.

Q: How do you know an SEO long-tail landing page focus is going to be a better user experience than what could be generated in the Google Answer Box?

AD: You don’t! That’s why you testing thousands of long-tail landing pages – and then cutting the poor performers (a.k.a. “failing cheap”) is the name of the game today.

Q: Should we use Google Ads search term reports for SEO keyword research?

AD: Because Search Terms reports give you the exact keyword, the exact amount of traffic, the exact conversion rate, the exact amount of revenue… all stuff that the Organic report doesn’t give you. Then you can find those gold nugget keywords that need better matching content, products, reviews, etc.

Q: By automating landing pages at scale whats the balance with this vs. crawl budget?

AD: We recommend limiting the number of Longtail UX landing pages to 20% of your current number of indexed pages.

[Video Recap] Google’s Hogging Half YourTraffic: How to Get It Back

Watch the video recap of the webinar presentation and Q&A session.


Image Credits

In-Post Image: Longtail UX

All screenshots taken by author, March 2020

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Google’s Next-Gen AI Chatbot, Gemini, Faces Delays: What to Expect When It Finally Launches

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Google AI Chatbot Gemini

In an unexpected turn of events, Google has chosen to postpone the much-anticipated debut of its revolutionary generative AI model, Gemini. Initially poised to make waves this week, the unveiling has now been rescheduled for early next year, specifically in January.

Gemini is set to redefine the landscape of conversational AI, representing Google’s most potent endeavor in this domain to date. Positioned as a multimodal AI chatbot, Gemini boasts the capability to process diverse data types. This includes a unique proficiency in comprehending and generating text, images, and various content formats, even going so far as to create an entire website based on a combination of sketches and written descriptions.

Originally, Google had planned an elaborate series of launch events spanning California, New York, and Washington. Regrettably, these events have been canceled due to concerns about Gemini’s responsiveness to non-English prompts. According to anonymous sources cited by The Information, Google’s Chief Executive, Sundar Pichai, personally decided to postpone the launch, acknowledging the importance of global support as a key feature of Gemini’s capabilities.

Gemini is expected to surpass the renowned ChatGPT, powered by OpenAI’s GPT-4 model, and preliminary private tests have shown promising results. Fueled by significantly enhanced computing power, Gemini has outperformed GPT-4, particularly in FLOPS (Floating Point Operations Per Second), owing to its access to a multitude of high-end AI accelerators through the Google Cloud platform.

SemiAnalysis, a research firm affiliated with Substack Inc., expressed in an August blog post that Gemini appears poised to “blow OpenAI’s model out of the water.” The extensive compute power at Google’s disposal has evidently contributed to Gemini’s superior performance.

Google’s Vice President and Manager of Bard and Google Assistant, Sissie Hsiao, offered insights into Gemini’s capabilities, citing examples like generating novel images in response to specific requests, such as illustrating the steps to ice a three-layer cake.

While Google’s current generative AI offering, Bard, has showcased noteworthy accomplishments, it has struggled to achieve the same level of consumer awareness as ChatGPT. Gemini, with its unparalleled capabilities, is expected to be a game-changer, demonstrating impressive multimodal functionalities never seen before.

During the initial announcement at Google’s I/O developer conference in May, the company emphasized Gemini’s multimodal prowess and its developer-friendly nature. An application programming interface (API) is under development, allowing developers to seamlessly integrate Gemini into third-party applications.

As the world awaits the delayed unveiling of Gemini, the stakes are high, with Google aiming to revolutionize the AI landscape and solidify its position as a leader in generative artificial intelligence. The postponed launch only adds to the anticipation surrounding Gemini’s eventual debut in the coming year.

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Google Brings Bard Students Math and Coding Education in the Summer

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Google Brings Bard Students Math and Coding Education in the Summer

Google is stepping up its AI efforts this summer by sending Bard, its high-profile chatbot, to summer school. The aim? To boost the bot’s math and coding smarts. These developments are excellent news— when Bard first debuted, it was admittedly not a finished product. But Google is steadily plugging away at it, and have now implemented implicit code execution for logical prompts, and handy Google Sheets’ integration to take it to the next level.

Thanks to implicit code execution, Bard can respond to inquiries requiring calculation or computation with Python code snippets running in the background. What’s even more amazing is that coders can take this generated code and modify it for their projects. Though Google is still apprehensive about guaranteeing the accuracy of Bard’s answers, this feature is said to improve the accuracy of math and word problems by an impressive 30%.

In addition to this, Bard can now export directly to Sheets when asked about tables. So, you don’t need to worry about copying and pasting, which comes with the risk of losing formatting or data.

From the company’s I/O keynote address, it is clear that they are focused on making the most of what Bard can offer. As they continue to speak highly of the chatbot, we’re sure to expect more features and capabilities when the summer comes around.

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Google Bard vs. ChatGPT: which is the better AI chatbot?

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Google Bard vs. ChatGPT: which is the better AI chatbot?

Google Bard and ChatGPT are two of the most prominent artificial intelligence (AI) chatbots available in 2023. But which is better? Both offer natural language responses to natural language inputs, using machine learning and millions of data points to craft useful, informative responses. Most of the time. These AI tools aren’t perfect yet, but they point to an exciting future of AI assistant search and learning tools that will make information all the more readily available.

As similar as these chatbots are, they also have some distinct differences. Here’s how ChatGPT and Google Bard measure up against one another.

Which is better, Google Bard or ChatGPT?

This is a tricky question to answer, as at the time of writing, you can only use Google Bard if you’re part of a select group of early beta testers. As for its competition, you can use ChatGPT right now, completely for free. You may have to contend with a waitlist, but if you want to skip that, there’s a paid-for Plus version offering those interested in a more complete tool the option of paying for the privilege.

Still, when Google Bard becomes more widely available, it should offer credible competition for ChatGPT. Both use natural language models — Google Bard uses Google’s internal LaMDA (Language Model for Dialogue Applications), whereas ChatGPT uses an older GPT-3 language model. Google Bard bases its responses to questions on more recent data, with ChatGPT mainly trained on data that was available prior to 2021. This is similar to how Microsoft’s Bing Chat works.

We’ll have to reserve judgment on which is the more capable AI chatbot until we get time to play with Google Bard ourselves, but it looks set to be a close contest when it is more readily available.

Are Google Bard and ChatGPT available yet?

As mentioned, ChatGPT is available in free and paid-for tiers. You might have to sit in a queue for the free version for a while, but anyone can play around with its capabilities.

Google Bard is currently only available to limited beta testers and is not available to the wider public.

Banner of Google Bard intro from February 6.

What’s the difference between Google Bard and ChatGPT?

ChatGPT and Google Bard are very similar natural language AI chatbots, but they have some differences, and are designed to be used in slightly different ways — at least for now. ChatGPT has been used for answering direct questions with direct answers, mostly correctly, but it’s caused a lot of consternation among white collar workers, like writers, SEO advisors, and copy editors, since it has also demonstrated an impressive ability to write creatively — even if it has faced a few problems with accuracy and plagiarism.

Still, Microsoft has integrated ChatGPT into its Bing search engine to give users the ability to ask direct questions of the search engine, rather than searching for terms of keywords to find the best results. It has also built it into its Teams communications tool, and it’s coming to the Edge browser in a limited form. The Opera browser has also pledged to integrate ChatGPT in the future.

ChatGPT Google Bard
Accessible through ChatGPT site. Only text responses are returned via queries. Integrated with Google Search. You only need to change a Google setting to get your regular search results when using Google Bard AI, and vice versa.
ChatGPT produces answers from its trained database from 2021 and before. Google Apprentice Bard AI will be able to answer real-time questions.
Based on GPT (Generative Pre-trained Transformer). Based on LaMDA (Language Model for Dialogue Applications).
Service has a free and paid plan option (called ChatGPT Plus). Service is free.
Has built-in plagiarism tool called GPT-2 Output Detector. No built-in plagiarism detection tool.
Available now Still in beta test phase

Google Bard was mainly designed around augmenting Google’s own search tool, however it is also destined to become an automated support tool for businesses without the funds to pay for human support teams. It will be offered to customers through a trained AI responder. It is likely to be integrated into the Chrome browser and its Chromium derivatives before long. Google is also expected to open up Google Bard to third-party developers in the future.

Under the hood, Google Bard uses Google’s LaMDA language model, while ChatGPT uses its own GPT3 model. ChatGPT is based on slightly older data, restricted in its current GPT3 model to data collected prior to 2022, while Google Bard is built on data provided on recent years too. However, that doesn’t necessarily make it more accurate, as Google Bard has faced problems with incorrect answers to questions, even in its initial unveiling.

ChatGPT also has a built-in plagiarism checker, while Google Bard does not, but Google Bard doesn’t have the creative applications of ChatGPT just yet.

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