Connect with us


5 Ways SEO Experts Are Winning In Local Search



5 Ways SEO Experts Are Winning In Local Search

This post was sponsored by Bright Data. The opinions expressed in this article are the sponsor’s own.

You know the story, every SEO professional is learning and using the same methods for building their SEO strategy.

So, how do you uncover hidden gems that help propel your local brand to the top of search engine results pages (SERPs)?

How do you elevate yourself from just a professional to an SEO expert?

Where do you get actionable insights that help you claim a top SERP position?

Expert digital marketers know that in order to win a top position on the SERP, they must understand how the SERP works.

The solution: Actionable search insights can be discovered with SERP APIs.

Being able to see what makes or breaks a top spot in a search will help you create a winning strategy.

Expert digital marketers are using SERP APIs, or SERP scrapers, to create:

  • Brand sentiment strategies.
  • Online reputation management (ORM) strategies.
  • Improved keyword ranking strategies to modify their positioning and increase their visibility in search engines.

Before you take your first steps toward a stronger local SEO strategy, let’s dive into what a SERP API is.


SERP APIs are automated tools that pull public web datasets from SERPs.

They focus on giving you web data from paid and organic search results of different keywords and queries typed into search engines.

SERP APIs can help you outrank your competition by:

1. Automatically targeting unique parameters, including:

  • Location (city-level targeting).
  • Language.
  • Filters.
  • Safe mode.
  • Device.

2. Automatically analyzing different search engine features, such as:

  • Maps.
  • Shopping.
  • Trends.
  • Hotels.
  • Flights.
  • News.
  • More.

These two automated public data sets help you:

  • Monitor your competition.
  • Uncover hidden trends.
  • Improve paid advertising campaigns.
  • Expose content gaps.
  • Understand how your content performs from region to region.
Screenshot from SERP API, October 2022

What Are SERP APIs Used For?

SERP APIs, especially automated ones like Bright Data’s SERP API tool, help you:

  • Easily uncover harmful ratings and bad press so you can repair your reputation.
  • Create an SEO keyword strategy that’s based on real-time web data, instead of historical.
  • Build out a content strategy that helps search engines understand your business and rank you higher.
  • Uncover the best backlinking opportunities.
  • Automatically gain insights and save time during SEO research phases.

1. Uncover & Repair Bad Reviews & Press To Increase SERP Rankings

You can use SERP APIs to manage the online reputation of your organization.

Worried about bad PR? Get alerted so you can get ahead of it.

Wondering if bad reviews are making your products appear lower on SERPs? Find out in seconds.

SERP APIs can help you and your team with Online Reputation Management (ORM).

How? By quickly scraping all public web data from search engines and seeing, at a glance, what pages rank highest – for positive and negative reasons – when searching for branded keywords or product keywords.

Your automated SERP API tool will show you how your brand is positioned to the public, and how its position is influenced by these factors.

From here, you can develop a superior strategy that counteracts any negative content with positive content – leveraging the insights pulled from the SERP web data to optimize your brand’s reputation and reach.

For example, SEO teams can see how their reviews and ratings compare against their competitors’ and monitor for any negative press or comments about their brand.

Using an automated SERP API can quickly show the types of websites that appear first in searches and whether or not they place the brand in a favorable position.

2. Build Your Strategy With Real-Time Keyword Research & Web Data

Traditional SEO tools rely on historical data to give you insights, providing results or data from a week ago or longer.

Often, they don’t give users the option to search by city or other detailed parameters. This becomes an issue for local SEO specialists, as search engine results for a keyword in Miami will appear differently than they will in Orlando.

It’s time to get ahead of your competition by creating your strategy from real-time web data.

How? SERP APIs have the ability to scrape public web data from search engine results pages in real time from any country, city, or location, making it perfect for international SEO and local SEO.

You’ll be able to build local SEO strategies and ORM strategies that improve your brand’s ranking position across locations in real time.

By using an automated SERP scraper you can:

  • Track the changes in local search engine results or rankings in relation to your competitors.
  • Uncover specific keyword, description, and link trends.
  • Optimize advertising campaigns.
  • Locate untapped backlink opportunities.
  • Duplicate data affecting search positioning.

3. Automatically See Search Trends & Discover Content Gaps

You can use SERP APIs to discover search engine trends and expose gaps in your content marketing strategy.

The web data collected from SERP APIs can identify new, trending content ideas – such as blogs, articles, or videos – that can help you create and manage high-quality content that generates organic traffic.

How? An automated SERP API can give you instant insights into what your 2023 content strategy should contain.

4. Get Instant Insights Into The Most Effective Title Tags, Meta Descriptions & Backlink Opportunities

SERP APIs retrieve titles, tags, and descriptions from SERPs.

This means you can see the content you need without surfing through hundreds of SERPs.

With this information, you can better optimize your pages so they appear higher up in searches than your competitors’ pages, products, or services.

How? By scraping competing results, public websites, and content, you can identify areas to improve your own title tags and meta descriptions.

You can also locate untapped backlink opportunities to further enhance their pages and ensure they appear first in trending search results.

The best part? You can do this automatically.

5. Automate Your SERP Scraping Tasks With SERP APIs

SERP APIs can automate the process of scraping SERPs.

If you’re a local business with many locations or an international SEO professional who uses local SEO strategy for international rankings, you know this too well: Many different elements can affect the results being displayed on a page, including location, search history, and device.

SEO agencies also have multiple clients, and it can take hours to perform a manual scrape for each one.

As a result, it’s not feasible to manually survey SERPs and return accurate, real-time results.

How? SERP scrapers allow you to automate and pull web data from countless sources at once, enabling your teams to gather large volumes of data at a faster pace and have greater visibility into their positioning in search results.

Many web data providers offer SERP APIs that require little to no experience to scrape web data from result pages.

These tools are specifically designed to target all major search engines.

Similar to data collection infrastructure, some tools even come with unblocking technology attached, and more importantly, the data provider will automatically update SERP APIs after search engines make changes to the results pages – ensuring accurate and uninterrupted real-time web data collection.

This is extremely important considering there are constant changes being made to the structure and algorithms of SERPs, and new features are being added to these pages more frequently.

Equip Your SEO Teams With Safe SEO Automation, Today

SERP APIs can provide you with the additional tools you need to optimize your strategies for ORM, localized SEO, content optimization, real-time rank tracking, and other SEO-related projects.

With the help of SERP APIs, gathering accurate, real-time SERP web data has become a significantly more manageable task and has provided SEO teams with a direct line to different audiences and SERPs across the globe.

Test Bright Data’s SERP API, now!

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address


5 Questions Answered About The OpenAI Search Engine




5 Questions Answered About The OpenAI Search Engine

It was reported that OpenAI is working on a search engine that would directly challenge Google. But details missing from the report raise questions about whether OpenAI is creating a standalone search engine or if there’s another reason for the announcement.

OpenAI Web Search Report

The report published on The Information relates that OpenAI is developing a Web Search product that will directly compete with Google. A key detail of the report is that it will be partly powered by Bing, Microsoft’s search engine. Apart from that there are no other details, including whether it will be a standalone search engine or be integrated within ChatGPT.

All reports note that it will be a direct challenge to Google so let’s start there.

1. Is OpenAI Mounting A Challenge To Google?

OpenAI is said to be using Bing search as part of the rumored search engine, a combination of a GPT-4 with Bing Search, plus something in the middle to coordinate between the two .

In that scenario, what OpenAI is not doing is developing its own search indexing technology, it’s using Bing.

What’s left then for OpenAI to do in order to create a search engine is to devise how the search interface interacts with GPT-4 and Bing.

And that’s a problem that Bing has already solved by using what it Microsoft calls an orchestration layer. Bing Chat uses retrieval-augmented generation (RAG) to improve answers by adding web search data to use as context for the answers that GPT-4 creates. For more information on how orchestration and RAG works watch the keynote at Microsoft Build 2023 event by Kevin Scott, Chief Technology Officer at Microsoft, at the 31:45 minute mark here).

If OpenAI is creating a challenge to Google Search, what exactly is left for OpenAI to do that Microsoft isn’t already doing with Bing Chat? Bing is an experienced and mature search technology, an expertise that OpenAI does not have.

Is OpenAI challenging Google? A more plausible answer is that Bing is challenging Google through OpenAI as a proxy.

2. Does OpenAI Have The Momentum To Challenge Google?

ChatGPT is the fastest growing app of all time, currently with about 180 million users, achieving in two months what took years for Facebook and Twitter.

Yet despite that head start Google’s lead is a steep hill for OpenAI to climb.  Consider that Google has approximately 3 to 4 billion users worldwide, absolutely dwarfing OpenAI’s 180 million.

Assuming that all 180 million OpenAI users performed an average of 4 searches per day, the daily number of searches could reach 720 million searches per day.

Statista estimates that there are 6.3 million searches on Google per minute which equals over 9 billion searches per day.

If OpenAI is to compete they’re going to have to offer a useful product with a compelling reason to use it. For example, Google and Apple have a captive audience on mobile device ecosystem that embeds them into the daily lives of their users, both at work and at home. It’s fairly apparent that it’s not enough to create a search engine to compete.

Realistically, how can OpenAI achieve that level of ubiquity and usefulness?

OpenAI is facing an uphill battle against not just Google but Microsoft and Apple, too. If we count Internet of Things apps and appliances then add Amazon to that list of competitors that already have a presence in billions of users daily lives.

OpenAI does not have the momentum to launch a search engine to compete against Google because it doesn’t have the ecosystem to support integration into users lives.

3. OpenAI Lacks Information Retrieval Expertise

Search is formally referred to as Information Retrieval (IR) in research papers and patents. No amount of searching in the repository of research papers will surface papers authored by OpenAI researchers related to information retrieval. The same can be said for searching for information retrieval (IR) related patents. OpenAI’s list of research papers also lacks IR related studies.

It’s not that OpenAI is being secretive. OpenAI has a long history of publishing research papers about the technologies they’re developing. The research into IR does not exist. So if OpenAI is indeed planning on launching a challenge to Google, where is the smoke from that fire?

It’s a fair guess that search is not something OpenAI is developing right now. There are no signs that it is even flirting with building a search engine, there’s nothing there.

4. Is The OpenAI Search Engine A Microsoft Project?

There is substantial evidence that Microsoft is furiously researching how to use LLMs as a part of a search engine.

All of the following research papers are classified as belonging to the fields of Information Retrieval (aka search), Artificial Intelligence, and Natural Language Computing.

Here are few research papers just from 2024:

Enhancing human annotation: Leveraging large language models and efficient batch processing
This is about using AI for classifying search queries.

Structured Entity Extraction Using Large Language Models
This research paper discovers a way to extracting structured information from unstructured text (like webpages). It’s like turning a webpage (unstructured data) into a machine understandable format (structured data).

Improving Text Embeddings with Large Language Models (PDF version here)
This research paper discusses a way to get high-quality text embeddings that can be used for information retrieval (IR). Text embeddings is a reference to creating a representation of text in a way that can be used by algorithms to understand the semantic meanings and relationships between the words.

The above research paper explains the use:

“Text embeddings are vector representations of natural language that encode its semantic information. They are widely used in various natural language processing (NLP) tasks, such as information retrieval (IR), question answering…etc. In the field of IR, the first-stage retrieval often relies on text embeddings to efficiently recall a small set of candidate documents from a large-scale corpus using approximate nearest neighbor search techniques.”

There’s more research by Microsoft that relates to search, but these are the ones that are specifically related to search together with large language models (like GPT-4.5).

Following the trail of breadcrumbs leads directly to Microsoft as the technology powering any search engine that OpenAI is supposed to be planning… if that rumor is true.

5. Is Rumor Meant To Steal Spotlight From Gemini?

The rumor that OpenAI is launching a competing search engine was published on February 14th. The next day on February 15th Google announced the launch of Gemini 1.5, after announcing Gemini Advanced on February 8th.

Is it a coincidence that OpenAI’s announcement completely overshadowed the Gemini announcement the next day? The timing is incredible.

At this point the OpenAI search engine is just a rumor.

Featured Image by Shutterstock/rafapress

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading


Warning: Unpopular SEO writing opinion



Warning: Unpopular SEO writing opinion

Unpopular opinion alert: Adding new blog posts may not help your site.

(No matter what that content marketing company told you.) 🙄

So many of my new clients — especially subject matter experts — don’t need new content (immediately).

They HAVE content — scads of it scattered across various platforms.

(Maybe that sounds familiar.)

What they DO need is someone to review their content and customer persona, pinpoint opportunities, and develop a baby-step approach to leveraging those older content assets.

Because there are always opportunities. 🔥

Before writing another word, ask…

  • Are you repurposing the content you have? Or are you writing it once and forgetting about it (which is so common)?
  • Is your customer/reader persona still accurate, or has your target audience changed post-COVID?
  • Do your sales pages showcase your benefits and speak to your customers’ pain points? Or are they flat and dull?
  • Does your content sound like YOU with a point of view? Or is there a massive disconnect between how you talk to clients and the words you use on your site?
  • When did you last take a peek at your old sales emails and email welcome sequences? Could updating those assets make you more money?
  • Isn’t it time to save time (and budget) and leverage your existing content?

If you need help untangling your content and messaging, let me know. I love creating content order out of chaos.

After all…


Warning Unpopular SEO writing opinion


What do you think? Leave your comment below.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading


Google Bans Impersonation In Ads




Google Bans Impersonation In Ads

Google bans impersonation and false affiliation in ads, enforcing policy changes in March.

  • Google bans impersonation and false affiliation in ads.
  • Policy enforcement starts in March.
  • Violators will be banned from Google Ads.

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading


Follow by Email