Trending November 2023 # Top 20 Enterprise Search Engine Applications & Case Studies # Suggested December 2023 # Top 19 Popular

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54% of information workers across the globe complain about interrupting their work to look for information, insights and answers.

This article gathers the most common 20 use cases under three main categories: General processes, industry-specific and business function applications.

General search engine applications

Some common enterprise search engine applications include:

1.) Knowledge management: Search engines can help organizations manage and search through their knowledge bases, such as articles, manuals, and technical documents. Consequently, employees can quickly access relevant information and improve productivity.

2.) Customer support: Search engines can help customer support teams rapidly find solutions to common customer issues by searching through support articles, user forums, and other resources.

3.) Business intelligence: Enterprise search engines can be used to mine large datasets for insights and trends, helping organizations make data-driven decisions.

4.) User search behavior: Search engines can help understand user search patterns and information usage. This way, organizations can identify knowledge gaps and improve information sharing.

5.) Ensuring security: Companies can deploy search engines to check all customers against lists of individuals monitored by law enforcement agencies to ensure none of their customers is a public threat.

6.) Contacting experts: Search engines can filter by using attributes and experience to identify experts. Experts are critical as they may hold 42% of institutional knowledge.

7.) Intranet search: Search engines can be useful for locating information in shared drives and databases.

8.) Identifying suspicious activities: Search engines can connect to the system’s router, switch, and web server logs or VPN and check for suspicious behavior, such as:

Enterprise search engines can be applied to a wide range of industries, including:

9.) Healthcare: Healthcare providers can use search engines to quickly access patient records, medical literature, and other relevant information. For example, Mayo Clinic, a leading healthcare provider, deployed a search engine to help its physicians and researchers access patient data, medical literature, and other relevant information quickly and easily.

10.) Legal: Law firms and legal departments can use search engines to manage and search through case files, contracts, and other legal documents.

11.) Finance: Banks and financial institutions can use search engines to search through customer data, financial reports, and other financial information. For instance, Goldman Sachs implemented a search engine to help its traders and analysts search through financial data quickly and efficiently.

12.) Information technology: IT departments can use search engines to manage and search through technical documentation, knowledge bases, and other resources.

13.) Manufacturing: Manufacturing companies can use search engines to manage and search through technical documentation, production data, and other relevant information.

14.) E-commerce: Online retailers can use search engines to help customers find products based on their search queries and other criteria, such as price, availability, and customer ratings. For example, Airbnb, an online marketplace for vacation rentals, used a search engine to help its users find and book vacation rentals more easily.

15.) Education: Educational institutions can use search engines to manage and search through research papers, textbooks, and other educational resources.

Business function applications

Some use cases for enterprise search engines contains:

16.) Information management: Enterprise search engines can help organizations efficiently search and manage large amounts of data, including documents, images, and videos.

17.) Sales and marketing: Enterprise search engines can search through sales and marketing data, such as customer information, sales reports, and marketing materials, to identify trends and opportunities.

18.) Human resources: Search engines can help human resources departments manage and search through employee records, resumes, and other relevant information.

19.) Research and development: Enterprise search engines can explore research papers, patents, and other scientific data, helping researchers identify relevant information and make discoveries.

20.) Compliance and risk management: Search engines can help organizations search through compliance documents, regulatory requirements, and other risk management data, making it easier to identify and mitigate risks.

8 Search Engine Related Ipad Apps

Aside from Twitter and Social Networking apps, another interesting set of apps available right now on the iPad App Store are search-related. I scoured through the App Store to get the most significant of these search-related iPad apps – and found 8 of them. Here are 8 search-related apps that you might want to check out.

Zillow Real Estate Search

This iPad app lets you view photo galleries of home’s on the iPad’s large screen and tap, swipe, pinch and drag to see Zestimate home values , homes for sale, homes for rent, and more. The app also lets you filter searches by price, beds, baths, and other filters, search by monthly payment, view full-screen color photos, save searches, get push notifications, email homes to friend as well as share homes on Facebook. (Free) iTunes link.

If you need to find local businesses and other related information while on the move, you might want to get this app from the iPad App Store. This app features local business search, GPS location, maps and driving directions. It lets you view business websites and videos, save business details to your Contacts and sort items alphabetically or by distance to your current location. (Free) iTunes link.

Meta Flavor Restaurant Search

This is a pretty useful app for searching and comparing millions of restaurants and dishes. It lets you search by cuisine, restaurant’s name, and even by ingredient. The app also remembers your preferences and makes smart recommendations the next time you use the app. (Free) iTunes link.

Search Maestro (For Google)

Simply put, this iPad app lets you do Google searches on your iPad. It allows you save your searches and then browse them later. It also lets you save web pages, browse the internet fast, view current page in Safari and view searches even while your iPad is offline. (Price: $1.99) iTunes link.

DishFinders

Like Meta-Flavor, this app lets you search for specific dish and discover what other people have to say about this dish. You can browse through all the dishes that have been reviewed on a particular restaurant as well as submit your own reviews. The app also encourages users to share their dishes including photos of the finish product. (Free) iTunes link.

Searcher

Searcher is a fast web search tool for your iPad. It currently supports chúng tôi chúng tôi chúng tôi Wikipedia, chúng tôi chúng tôi chúng tôi chúng tôi YouTube, Twitter, Wolfram Alpha, Yaho and chúng tôi for translation. (Price: $1.99) iTunes link.

QuickFind

QuickFind is a pretty straightforward search tool for your iPad. It lets you search popular multiple sites at the same time. The app utilizes the iPad’s huge screen to come up with two column interface where the right column serves as display for your web browser. (Free) iTunes link.

JobServe Connect

One of the few, if not the only Job search tool available for your iPad. This app lets you search for jobs from a global database of over 40,000 job openings. It also lets you apply for a job quickly. And if you register for an account at Jobserve, you can view your latest jobs applied for, save and run searches, and get useful candidate messages from your online Jobserve account. (Free) iTunes link.

Top 5 Challenges Of Enterprise Seo

What makes enterprise SEO unique from a general knowledge in SEO?

The complexities.

A larger company has the technical challenges of a complex site architecture to getting budget for the tools and help needed to be successful.

I have seen many SEO professionals come from consulting or agency environments who have strong technical, content, and general knowledge of SEO.

What they lack, however, is the ability to work with other teams or understand the complexities that enterprise organizations face.

Without the experience of working in-house in such an environment, any SEO professional will struggle to gain credibility or make any sort of impact – resulting in a stagnant outcome with no signs of growth.

Here are the top five challenges any SEO might face when working in an enterprise environment:

Complex technical challenges.

Getting buy-in.

Priority for the business.

Tracking effectiveness.

Budget for tools/help.

If you can navigate through these challenges then support from the organization – all the way from the top down – will become strong, allowing for the overall health of the company’s SEO to flourish.

1. Complex Technical Challenges for SEO

When it comes to technical SEO for enterprise organizations, the level of complexity increases tenfold.

Sites that don’t focus on the technical aspects of SEO will often fall short no matter how excellent content, brand recognition, or link authority is.

When a site has 90% of its pages throwing errors around redirect chains, improper or self canonicals, duplicate titles, JavaScript issues, etc. are less likely to get results than their competitors who have only 20% (or less) of those issues.

New projects that are launched are less likely to gain traction in the search results or may struggle to ever get indexed at all.

Larger organizations consist of multiple engineering teams working on several aspects to a site and often on different platforms.

When entering into an enterprise environment, it’s good to understand that your first few months are going to be about learning:

How a site is structured.

How the engineering teams work.

How SEO can play a part.

From the use of subdomains/subdirectories, pushing chúng tôi files, generating chúng tôi identifying pages that need or have noindex tags, pagination, JavaScript implementation, how canonical tags are generated, pagination, infinite scrolling, Ajax calls, and so much more.

All of this may be common knowledge, however, working in the enterprise environment with a large site managed by multiple stakeholders that have business decisions that could impact SEO adds a level of complexity that is a challenge to navigate.

When dealing with the complexities of technical SEO in an enterprise environment, an SEO must not only be knowledgeable but be willing to listen.

A strong enterprise SEO can look at data, analyze crawl reports and web logs, and know who to talk to in order to understand the history of the work that has been done for SEO.

A good SEO should be able to make authoritative decisions while maintaining humbleness as trial and error tests present the best results.

By focusing 30% of the team’s effort on technical SEO fixes and mitigating additional issues, an enterprise site will have greater success.

2. Getting Buy-in

Ask any SEO and they will tell you how obvious it is why companies should invest time and money into SEO.

With a little effort from engineering, some tweaking by the content teams, and a small investment in SEO experts any company could make money with very little overhead.

Unfortunately, not all organizations see it that way.

Whether it’s a lack of understanding of what SEO is or what all that goes into SEO companies don’t often see it as a worthy investment.

SEO professionals should know that working within an organization doesn’t make it any easier to get work done for SEO.

Calendars could be filled with meetings all day but a discussion might come up in a meeting where stakeholders decide that SEO isn’t important and the SEO wasn’t in the room.

Later they find out that after a project was launched the company could have benefited greatly from considering SEO.

The key to getting buy-in for SEO is for an SEO to get to know as many people as possible in the organization from the top down.

Even when it doesn’t seem like someone will ever need or ever work with SEO, it’s still good to get to know them and their role.

One of those people could be in a meeting the SEO is left out of when a group decides that they don’t need SEO. In which case they would be able to speak up for SEO in their absence.

Additionally, any successes the team can have for SEO are always a good way to get organizational buy-in.

Find some pages or a section of the website that could use some changes to help improve SEO and report on the growth that you have accomplished.

This will show stakeholders and decision-makers that some work for SEO can increase traffic and revenue.

They will have more respect for SEO as well as the team that works on SEO and will want the same for their projects and responsibilities.

Getting buy-in from key stakeholders on what it takes to get work done for SEO is one of the biggest struggles any SEO faces in a larger organization.

From convincing the CEO that SEO can increase the bottom line, all the way down to getting engineering teams to spend the time to make their JavaScript crawlable by Google, SEO pros can spend a lot of time getting buy-in.

3. Priority for the Business

I will, at times, refer to SEO as the red-headed stepchild (a phrase used to describe a person who is neglected, mistreated, or unwanted) of the business.

Many companies know that they can benefit from SEO, but don’t understand enough about it to make it a priority.

Organizations that end up in this hole of lack of support, or understanding for SEO, have a difficult time digging themselves out and therefore reaping any benefit from SEO.

While getting stakeholders to buy-into SEO, it’s also important to push to establish SEO as one of the important priorities for the business as a whole.

By communicating with the business showing small, or even large, wins a team can establish SEO as a priority and align with what the business has planned for.

Aligning with the business isn’t always an easy task, and not all organizations are transparent when it comes to communicating what is a priority to the SEO level.

By focusing on getting to know teams and stakeholders within the organization the SEO team could become part of the conversation when there are talks about priorities for the business.

While getting SEO established as a priority for the business is a struggle, the benefits can be astronomical for both the business and the SEO team.

4. Tracking Effectiveness

Many times I have worked with agencies that report on their wins by showing keywords that have moved up in rankings, or pages they have worked on appearing higher in the search results.

The biggest struggle that SEO will often have within a large organization is reporting. Most enterprise businesses expect SEO to impact revenue.

While ranking changes and increases in traffic are nice, everything boils down to how much the company makes.

Tracking keywords to revenue is virtually impossible.

Calculating can be a complex estimation based on formulas with an understanding of what pages showed up for which keyword searches, with a count of keywords to that page, cut by percentages of Google traffic from organic from how much that page generated in revenue.

It’s a formula that isn’t always doable for each business, especially in times where there are multiple pages that appear in search results for a keyword.

The best way to track SEO’s effectiveness is to understand what is important for the business.

Some businesses are happy with free signups and might have a revenue value associated with them.

Working with data scientists and understanding hurdles associated when reporting for SEO is one of the biggest struggles an SEO faces in a larger organization.

5. Budget for Tools/Help

One of the biggest struggles I have faced in all my years as an SEO and working for many enterprise organizations is getting support and budget to hire help (agencies, consultants, or staff) and the tools needed that can handle large complex systems.

Hiring agencies that have the technical knowledge, experience, and understanding of what it takes to manage SEO for large organizations are few and far in-between, and they don’t come cheap.

Getting budget support for the expert help needed takes a lot of hard work and scrappiness from the SEO (or team) that is in place.

SEO professionals shouldn’t be expected to know everything there is to know about all aspects of SEO.

Some are more versed in content, or some may be more technically savvy.

Some may have a good sense for navigating the red tape of the organization but aren’t strong in content or technical. In that case, hiring a consultant or an agency to help to make the team even stronger would lead the business into a strong SEO presence.

The best way to approach this is for the existing team to not be afraid to speak up and let their coworkers know when they aren’t strong in an aspect of SEO.

Most organizations will respect this and support the hiring of an agency or consultant that specializes in that part that is lacking.

If SEO has shown wins from technical fixes and mitigation then an expert or agency that can help put a content roadmap together with a growth plan would make sense.

The key is to show stakeholders that there can be success with one aspect of SEO and that there is potential for growth from others. In the end, everyone will benefit.

At the enterprise level, well-known tools like Moz, DeepCrawl, and Keylime Toolbox aren’t able to handle the complexities or the massiveness of enterprise sites.

For larger organizations, tools that are capable of handling complex sites, and that have the staff of support that know what SEO professionals at that level face, require big budgets.

Getting budget approval for these tools can often be a struggle, but when the support comes in and the tools are being utilized, SEO greatly benefits in the long term.

The key is to start small with the more widely known tools and focus on a smaller part of a site.

Use the data found to gain some wins while expressing that there are tools that are helping, but there are struggles due to their limited capabilities to manage larger sites.

When SEO brings in several billion in revenue for a business and the team is asking for a tool that is a very small fraction of that, the return on investment makes sense.

Summary

The challenges that enterprise SEO professionals face are definitely unique.

But these aren’t impossible impossible to overcome.

By understanding that enterprise SEO has its own struggles and having the patience and experience to navigate through them, any SEO in a larger organization can have a successful career and the business will benefit in the long run.

Featured Image Credit: Paulo Bobita

Search Engine Marketing (Seo And Ppc) Trends 2023

How has 2023’s Google search algorithm updates affected your business this year?

Did you know there’s been nine confirmed Google updates (so far) this year? Three of these were ‘core’ updates and two specifically affected how mobile sites are indexed and presented to users through usability and design.

However, there has also been some interesting developments with Google paid search platforms, announced earlier this year at Google Live.

2023 Google algorithm updates (so far) include:

“Brackets” core update – March 2023 – According to Danny Sullivan’s Twitter page, @searchliaison, some sites may have seen drops or gains, stating: “There’s nothing wrong with pages that may now perform less well. Instead, it’s that changes to our systems are benefiting pages that were previously under-rewarded….”

Zero-result SERP test – March 2023 - This was a mediocre update, which was quickly terminated after a week of testing. For date, time, and conversion calculations that only require one concrete answer, Google started displaying zero search results with a “see all results” and displayed the answer on a short knowledge card.

Mobile-first index – March 2023 – Finally rolling out after months of build up and announcements on the importance of an optimal mobile experience, Google started migrating sites after a year and a half of testing.

Unnamed core update – April 2023 - Confirmed by Google but not named, this improved certain site ranking or had little or no negative impact. They stated this type of core update happens several times a year.

Snippet length drop – May 2023 - Earlier in the year, meta descriptions in SERPs had been increased to 300+ characters, allowing for a more descriptive sentence or two about the nature of the content. However, this has been reverted back to approximately 150-160 characters. Although it gave copywriters and SEOers more space to place with and potentially increase real-estate on SERPs, I fear it gave less experienced marketers a chance to “keyword stuff” instead of providing concise descriptions.

Video carousels – June 2023 - Video in SERPs is taking an interesting direction. Video carousels have been rolled out on desktop after having been tested and featured on mobile SERPs and in knowledge panels over a year ago.

Mobile speed update – July 2023 - Officially confirmed, Google now uses page speed as a ranking signal in mobile search ranking. This comes with the understanding mobile users are on the move, in a hurry and need answers quickly. This initially is set to just affect pages that deliver the slowest experiences to users and only affect a small percentage of queries.

Chrome security warnings (full site) – July 2023 – This was no shock to marketers since Google has repeatedly stressed the importance of secure sites, with many warnings throughout the year that non-HTTPS sites would be penalized and warning messages would appear to users.

“Medic” core update – August 2023 - Widely reported by Moz and confirmed by Google, their broad core algorithm update in August caused numerous fluctuations in ranking and traffic across many verticals. However, it seems those that were hit hardest by the update were in health and fitness.

Google’s updates show that they’re continually getting smarter with indexing and what they believe is quality content. However, looking over this year’s confirmed updates shows a key pattern – speed and security are important. But before SEOers start looking for the newest innovations, optimizing their site to reflect the latest update the basic’s need to be right as David Sayce, digital marketing consultant and director of Paper Gecko explains:

“Google (and the other search engines) can only get smarter, the way they crawl, index, and display information. Gathering more information on search intent (or at least having a better understanding of the intent).

Quality will continue to be a factor with speed and security continuing to be key. Older websites that may not have been updated in some time will continue to suffer.

Personalization will continue to increase, as will the information delivered directly from search through featured snippets

Voice search will continue to be the next big thing. Whether 2023 is the year, only time will tell.

Mobile (non-desktop) and AMP will continue to increase, as users gather information on the go.

Predictions are difficult, and each year we see a couple of key points like voice or AI mentioned, as 2023 is the year these hit some form of critical mass.

How important is mobile SEO?

There is a clear direction for brands to really start and take seriously mobile experiences, and how these are delivered to users that need quick and easy answers to their questions.

SEO expert, Dawn Anderson MSc DigM, Pg Dip DigM (IDM), Fellow IDM, Managing director, Move it Marketing, also agrees:

“2023 will be a year where tying in your SEO strategy harmoniously with other channels and strategies for both retention and acquisition will be crucial as we move further into the era of ‘assistive search’. We are moving into a stage of ubiquitous computing so joining up the cross-device journey in SEO and tying this in with both blazing fast speed and seamless and frictionless UX as users seek to solve problems and complete intent-driven tasks will be our challenge into the future. Voice Search will continue to evolve and emerge as new formats such as ‘speakable’ and Google’ Dialogflow bank of Google Actions question and answer knowledge grows, feeding into the possible responses for both Actions and Conversational Search. Finding ways to make this work for SEO will be the challenge commercially. Furthermore, meeting the back and forth app and mobile web consumer experience harmoniously with SEO will also present challenges possibly met through PWAs (or further enhancements on this which emerge). It’s no surprise that Google’s mobile search UI is becoming increasingly app-like. Our challenge is to make that step between our sites and apps seamless too.”

What SEO and PPC techniques can we expect businesses to start adopting in 2023?

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Where does SEM fit into the B2B customer lifecycle?

Organic search and paid search techniques are used in the REACH stage of a customer lifecycle – content created should be answering initial search queries and whetting user’s appetite for products or services.

Is voice search important?

The type of queries users ask is a great reflection of their stage of awareness of the problem they have. Content creators need to think about what type of content they are providing to users. Top of funnel content should educate and entertain users if they are still in the initial awareness stage, whereas the bottom of the funnel content should inspire and convince users of the quality of the product. Different types of queries include:

Answer to a question/problem based

The question itself/explicit and direct

Description of the problem/symptom based or detailed

Description of cause/symptom based

Brand name or product parts/direct and educated

Informational queries/awareness stage, or uninformed

“The biggest trend in search and on the web in 2023 is likely to be voice search. Anyone with a smartphone is now only seconds away from performing a voice search, and then refining that search with another – increasing their user-intent and propensity to take action. With comScore predicting that by 2023 50% of all searches will be voice-led it’s clear this is a hugely growing market.

The most prolific users of voice in search are new parents (those who often struggle to have a spare hand) and baby boomers (who use the device as a ‘valet for daily life’ according to Google). In essence, those who use voice-assistant device, which these two categories of users mainly fall into, aren’t your typical early adopters – they aren’t your millennials who we may expect to see at the forefront of the charge, instead its your everyday user able to see the benefit and practical promise of voice” – Andy Kinsey, Head of Search at Smithfield Agency

What are the E-A-T Google quality signals?

Following the August 1st update, it’s important more than ever to start creating content that follows E-A-T signals – shows expertise, is authoritative, and is trustworthy. Gaining commercial ‘spammy’ backlinks to increase DA and improve ‘authority’ is not the way.

However, over the last year, I’ve seen too many sites producing content “for the sake of producing content”, outreaching for backlinks to that content and believing that a 600-word article that is 400 words of fluff is good enough to engage readers, give them detailed answers to their questions, and believe Google will rank it high in SERPs. Over the year, I would say some sites have become lazy in their content.

Search is no longer just Google, Bing and Yahoo

“Google it”. A key phrase from people who don’t know the answer to a question. Our go-to place for getting an answer is Google (and other search engines) as they’ll always have the answer is a site has provided the content. What people tend to forget is that Google does not know the answer, Google shows the answer it thinks is the most relevant to what the user has asked, based on content from other sites. It directs you to where you need to be, but what about other sites that offer a search functionality?

Head of Marketing at Ahrefs, Tim Soulo, sums this up perfectly:

“The year 2023 is the perfect time to realize that ‘search presence’ doesn’t imply Google alone. You should start expanding your efforts towards every big platform that have search functionality.

Can people find you on YouTube?

Can they find you on SlideShare?

What about Apple App Store or Google Play Store?

What about eBay and Amazon?

What will they hear when they ask questions to Alexa, Google Assistant and Siri?

What about Facebook, Twitter, and Instagram? Those platforms have search functionality too.

For a very long time, Google used to be the only gateway to whatever you wanted to do online, so people used to start browsing the web exclusively from Google homepage.

However, that’s not to say Google is a dying engine – far from it. It’s still the most used search engine on desktop and mobile, holding the largest market share.

Amongst their latest developments included:

Cross-device reporting and remarketing in Google Analytics - combines data from users that use your site across different devices.

With these new developments, local businesses are sure to benefit in 2023. As I reported earlier in the year:

Local ad campaigns will, inevitably, become smarter.

Matt Janaway, CEO of Marketing Labs, explains how this will affect 2023 paid search strategy:

One of the trends I see year after year across a few marketing channels is the use of machine learning and how this will improve the customer experience. To help visualize how AI and machine learning can be applied across the customer lifecycle, Smart Insights has created its RACE machine learning diagram.

Byron Tassoni-Resch, SEM Manager at Deliveroo and Founder at the comparison website for digital marketing tools and platforms GrowthSupermarket, states including machine learning into your PPC bidding strategy is the next trend in paid search.

That said, with any kind of change to your campaigns, I recommend you test it first before rolling it out to your entire account. Then, once you have implemented an automated bidding strategy, make sure that you give it enough time to gather data before you start making changes to your input variables! If you do however want to make some changes, don’t increase your variables by more than 10%-15% (either up or down) because if you do, the algorithm will have to start from the beginning again and it’s likely your performance will suffer in the short term.”

We’re interested to see what is going to be included in your SEM strategy for 2023 – give us a tweet to discuss new innovations you want to share.

If you want a full overview of all channel trends, Dr. Dave Chaffey’s post, 8 business-critical digital marketing trends for 2023, is a great place to start!

Top 10 Applications Of Object

Watch out for these top 10 applications of object-oriented programming using the python language

When organizing a program, object-oriented programming (OOP) groups together similar characteristics and behaviors into distinct objects. Objects are conceptually comparable to a system’s parts. Consider a program as a type of factory assembly line. A system component processes some material at each stage of the assembly line, turning raw materials into finished goods in the end. An object has both behavior, such as the action that each component of an assembly line does, and data, such as the raw or pre-processed materials at each stage. In this article, we’ll know about the top 10 applications of object-oriented programming using python language.

About OOP in Python: The programming paradigm known as “object-oriented programming” offers a way to organize programs so that individual objects are composed of properties and behaviors. An approach for modeling physical, real-world objects, such as cars, as well as relationships between objects, such as between businesses and employees, students and teachers, etc., is called object-oriented programming. Real-world entities are represented by OP as software objects that have certain data attached to them and are capable of carrying out specific tasks. Another popular paradigm for programming is procedural programming, which organizes a program similar to a recipe by offering a series of steps (in the form of functions and code blocks) that must be followed to finish a task. The main lesson learned from this is that Python’s object-oriented programming revolves around objects.

Let us know the

top 10 applications of Object-Oriented Programming:

In parallel programming, an issue is split up into smaller subproblems that can all be worked on simultaneously utilizing different computing resources. OOPs, are utilized to streamline the procedure by improving the network’s capacity for approximation and prediction.

When creating client-server systems, OOPs principles are quite helpful. To construct Object-oriented server internet, or OCSI, applications, the IT infrastructure is created using Object-oriented client-server systems.

OOP can be used to reduce the amount of work required in manufacturing and designing applications. It can be applied, for instance, when creating flowcharts and blueprints. So, it makes it possible to produce these flowcharts and blueprints accurately.

OOP is helpful in hypertext and hypermedia. It aids in laying the framework for hypertext and hypermedia

Simulation and modeling systems are imitations of the real-world product. The system’s workings can be checked and analysed using object-oriented programming.

OOP helps users to minimize the work required and can be applied in both application design and manufacturing. For example, it can be applied when creating flowcharts and blueprints. The ability to precisely construct these flowcharts and blueprints is therefore made possible.

OOP is beneficial in hypermedia and hypertext. It assists in establishing the foundation for hypertext and hypermedia.

Systems used for simulation and modeling are an emulation of real-world products. Using object-oriented programming, the operation of the system may be examined.

The conventional form of storing data, known as the relational model, saves every single piece of data in tables made up of rows and columns. Today, every single piece of data is stored and processed in object-oriented databases.

It is beneficial in computer-aided design (CAD), which uses workstations or computers to assist in the creation, modification, analysis, or optimization of a design.

How Search Engine Algorithms Work: Everything You Need To Know

Often I find myself focusing on specific strategies to perform specific functions.

How do I write compelling copy to rank on voice search?

What structured data produces easy wins?

Things like that.

These important questions are often covered here on Search Engine Journal in very useful articles.

But it’s important to not just understand what tactics might be working to help you rank. You need to understand how it works.

Understanding the structure that the strategy is functioning in is paramount to understanding not just why that strategy is working, but how and what it’s trying to accomplish.

Previously, we discussed how search engines crawl and index information.

This chapter will explore the basics of how search algorithms work.

What Is an Algorithm? A Recipe

If you ask Google what an algorithm is, you’ll discover that the engine itself (and pretty much everyone else) defines it as “a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.”

If you take anything from this definition, it’s critical to understand what it is not in our context here.

An algorithm is not a formula.

We’ll go with a favorite of mine:

Roast beef

Horseradish

Yorkshire pudding

Green beans

Mashed potatoes

Gravy

(That’s right, we Canadians eat more than poutine and maple syrup, though both are awesome though probably not together.)

The roast beef needs to be seasoned and cooked perfectly.

The seasoning combined with the roast would be an example of a formula – how much of each thing is necessary to produce a product.

A second formula used would be the amount of time and at what temperature the roast should be cooked, given its weight. The same would occur for each item on the list.

At a very basic level, we would have 12 formulas (6 items x 2 – one for measurements and the other for cooking time and duration based on volume) making an algorithm set with the goal of creating one of Dave’s favorite meals.

We aren’t even including the various formulas and algorithms required to produce the ingredients themselves, such as raising a cow or growing potatoes.

Let’s add one more formula though – a formula to consider the amount of different foods I would want on my plate.

So, we now have an algorithm to accomplish this very important task. Fantastic!

Now we just need to personalize that algorithm so that the rest of my family also enjoys their meal.

We need to consider that each person is different and will want different amounts of each ingredient and may want different seasonings.

So, we add a formula for each person. Alright.

An Algorithm of Algorithms

What the heck do a search algorithm and a dinner table have in common?

A lot more than you think.

Let’s look at just a few of the core characteristics of a website for comparison. (“Few” meaning nowhere near everything. Like not even close.)

URLs

Content

Internal links

External links

Images

Speed

As we witnessed with our dinner algorithm, each of these areas is divided further using different formulas and, in fact, different sub-algorithms.

It might be better if we think of it not as an algorithm, but as algorithms.

It’s also important to keep in mind that, while there are many algorithms and countless formulas at play, there is still an algorithm.

Its job is to determine how these others are weighted to produce the final results we see on the SERP.

So, it is perfectly legitimate to recognize that there is some type of algorithm at the top – the one algorithm to rule them all, so to speak – but always recognize that there are countless other algorithms and generally they’re the algorithms we think about when we’re considering how they impact search results.

Now, back to our analogy.

We have a plethora of different characteristics of a website being rated just as we have a number of food elements to end up on our dinner plate.

To produce the desired result, we have to have a large number of formulas and sub-algorithms to create each element on the plate and master algorithm to determine the quantity and placement of each element.

Sound familiar?

When we’re thinking of “Google’s algorithm” what we’re actually referring to is a massive collection of algorithms and formulas, each set to fulfill one specific function and gathered together by a lead or, dare I say, “core” algorithm to place the results.

So, we have:

Algorithms like Panda to assist Google in judging, filtering, penalizing and rewarding content based on specific characteristics, and that algorithm likely included a myriad of other algorithms within in.

The Penguin algorithm to judge links and address spam there. But this algorithm certainly requires data from other pre-existing algorithms that are responsible for valuing links and likely some new algorithms tasked with understanding common link spam characteristics so the larger Penguin algorithm could do its job.

Task-specific algorithms.

Organizing algorithms.

Algorithms responsible for collecting all the data and putting it into a context that produces the desired result, a SERP that users will find useful.

So there we have it. That’s how search algorithms work at their core.

Why Search Algorithms Use Entities

One of the areas of search that’s getting some decent attention lately, though which is under-emphasized, is the idea of entities.

For context, an entity is defined by Google as:

“A thing or concept that is singular, unique, well-defined and distinguishable.”

So, in our dinner analogy, there’s me. I’m an entity.

Each member of my family is also their own entity. In fact, my family unit is an entity unto itself.

By that token, the roast and each ingredient that goes into it are also their own entities.

So is the Yorkshire pudding and so is the flour that went into making it.

Google sees the world as a collection of entities. Here’s why:

At my dinner table, I have four individual entities that would have the state “eating” and a host of entities being consumed.

Classifying us all in this way has a lot of benefits to Google over simply assessing our activities as a series of words.

Each eating entity can now have assigned to them the entities that are on their plate (roast beef, horseradish, green beans, mashed potatoes, Yorkshire pudding but no gravy for entity xyz1234567890).

Google uses this type of classification to judge a website.

Think of each entity sitting at the table as a page.

The global entity that represents us all (let’s call this entity “Davies”) would be about “roast beef dinner,” but each individual entity representing an individual (or page in our analogy) is different.

In this way, Google can easily classify and judge the interconnectedness of websites and the world at large.

Basically, search engines aren’t responsible to just judge one website – they must rank them all.

The entity “Davies” is seen to be about “roast beef dinner” but the entity next door (let’s call this entity “Robinsons”) is about “stir fry.”

Now if an outside entity known as “Moocher” wanted to determine where to eat, the options can be ranked to Moocher based on their preferences or query.

Where (in my opinion) the real value in entities lies is in what happens the day after. We have some leftovers.

By processing the entity “roast beef” with a different formula and adding the entities bread, cheese, and onions, we have:

How Search Algorithms Use Entities

OK, it may not seem obvious how important this is in understanding search algorithms and how entities work in this way.

While understanding how Google seeing what a website is about as a whole has obvious value, you may be asking why it’s relevant for Google to understand that my roast beef and beef dip are related and in fact – are drawn from the same core entity.

Let’s consider instead Google understanding that a webpage is about roast beef. Let’s also consider that another page links to it and that page is about beef dip.

In this scenario, it’s incredibly important that Google knows that roast beef and beef dip are drawn from the same core entity.

They can assign relevance to this link based on the connectedness of these entities.

Before the idea of entities entered search, engines were left to assign relevance based on word proximity, density, and other easily misinterpreted and manipulated elements.

Entities are far more difficult to manipulate.

Either a page is about an entity or it’s not.

Through crawling the web and mapping common ways that entities relate, search engines can predict which relationships should carry the greatest weight.

So, How Do Search Algorithms Work?

Alright, we’ve covered a lot of ground and you’re probably getting hungry. You want some takeaways.

Context Matters

It’s important to understand how algorithms function to apply context to what you’re experiencing/reading.

When you hear of an algorithm update, it’s important to know that what is being updated is likely a small piece of a very large puzzle.

Knowing this assists in interpreting which aspects of a site or the world are being adjusted in an update and how that adjustment fits into the large objective of the engine.

Entities Are Super Important

Further, it’s critical moving forward to understand that entities:

Play a massive role in search algorithms today.

Have their own algorithms.

Will play an ever-increasing role over time.

Knowing this will help you understand not just what content is valuable (how close are those entities you’re writing about?) but also which links are likely to be judged more favorably.

It’s All About User Intent

Search algorithms work as a large collection of other algorithms and formulas, each with its own purpose and task, to produce results a user will be satisfied with.

In fact, there are algorithms in place to monitor just this aspect of the results and make adjustments where ranking pages are deemed not to satisfy user intent based on how users interact with it.

Included in this are algorithms designed specifically to understand entities and how entities relate to each other in order to provide relevancy and context to the other algorithms.

Image Credits

Beef Dip: Adobe Stock

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