Data mining technology has led to some important breakthroughs in modern marketing. Even major companies like HubSpot have talked extensively about the benefits of using data mining for marketing. One of the most important ways that companies can use data mining in their marketing strategies is with SEO.
Data mining is especially useful in the context of offsite SEO. Offsite SEO involves identifying linkbuilding opportunities, which is a lot easier with data mining tools. Local companies can also use data mining tools to identify canonicalization opportunities.
Data mining is going to be the life of many offsite SEO strategies in the future. Smart companies will find creative ways to utilize it effectively.
Why Offsite SEO is Important and Data Mining Can Be Crucial to Making it Work
We are going to get into the nuts and bolts of using data mining to optimize your offsite SEO strategy. However, it is important to first get an understanding of offsite SEO.
Many businesses pay attention to on-site SEO to enable them to increase their website visibility. They prioritize on-site SEO actions such as title tags and meta description optimization, website speed, quality content, and streamlining of site navigation. All these strategies are essential. But it’s important to note that some Google ranking factors are not found on your page. You must adopt off-site SEO strategies in your digital marketing in order to drive website traffic and business growth.
Off-page SEO consists of all activities that take place outside your website to help boost your search engine rankings. Off-site SEO signals, such as backlinks, tell search engines what other internet users think of your site. They also make your website authoritative and trustworthy. For instance, if there are so many valuable websites linking to your content, Google and other search engines will perceive that you have quality content that genuinely interests internet users.
Data analytics technology has helped companies make the most of their off-page SEO strategies. Companies like Moz have developed tools like MozBar that use sophisticated analytics algorithms to better understand the quality of the sites that companies can use for linkbuilding opportunities. These analytics algorithms help assess the spam scores and authority of different websites.
Implementing an off-page SEO strategy requires a significant level of skill and planning, so it is good to have sophisticated data mining and analytics tools at your fingertips. For internet users to know that your site can potentially offer what they want, your site’s domain has to be relevant, compelling, and memorable. You may have launched your site using any domain name available at the time. But if you want your business website to have a great impression on users, you must purchase a domain name that potential customers and other websites will easily recognize and link to. As a result, you may consider selling your current domain name. Saw.com, a domain brokerage firm, emphasizes that ”a domain appraisal is crucial because your domain could be more valuable than you think.”
One of the best ways to use data mining to help with offsite SEO is to identify sites to link to. One of the best strategies for accomplishing this is to use data mining tools from services like SEMRush to see the sites that your competitors are getting links from. This will help you explore sites that you might want to get links from as well. If you want to work with bloggers to help build links, then using big data can help with your outreach strategy.
Off-page SEO is not restricted to linking. In this article, you’ll learn more about using data mining for link and non-link-related off-site SEO strategies that will give you the website traffic you desire.
1. Backlinking
Backlinking is integral to off-page SEO because search engines use them to indicate content quality. There are various types of backlinks, classified by how they were earned. They include – manually built links, natural links, and self-created links. Manual links are those acquired through deliberate link-building activities, such as getting customers to link to your content or asking influencers to share your website’s content. On the other hand, natural links are those you earn without necessarily taking action. For instance, if your content contains relevant stats you obtained yourself, other website owners will likely link to your content when referencing the data you published.
Self-created links are those you create through practices, such as adding backlinks in online directories, press releases with optimized anchor texts, or blog comment signatures. However, to avoid being blacklisted by search engines, it’s best to limit the number of self-created links. Instead, focus on creating quality content that can earn you natural links. Generally, links that contribute immensely to your SEO efforts are those that provide the most equity. Some of the equity signals that search engines consider are the authority of the linking domain and page, the trustworthiness and popularity of the linking site, and the anchor text used on the linking site.
As we stated, identifying linkbuilding strategies is one of the best ways to apply data mining technology. One trick is to use data mining tools that aggregate searches from Google to identify sites that accept guest posts. You can also use data mining tools like SEMRush to reverse engineer other companies’ linkbuilding strategies.
2. Social Media Marketing
The idea behind social media marketing campaigns in off-site SEO is to create a reference to your website from a different place on the web – be it a link or a mention. The majority of consumers in today’s market use mobile devices, and they visit social media platforms every day. In fact, social media plays a pivotal role in how most people use the web to search for answers. The number of shares you get from your social channels may not affect your search ranking. Still, you can leverage your social networks to engage with your target audience.
Use your social networks to put your brand and its offerings in front of prospective customers. In the process, you increase the reach of your content. When you have real engagement and social media shares, you get more links and mentions. Also, when you respond to customers’ queries on social media, you build brand advocacy and promotion that potential and existing customers will discover in their sales journey.
You can also use data mining tools to identify companies to partner with on social media. The process is the same as with identifying companies to submit guest posts to, but the tools are different. You can use data mining algorithms on platforms like Hootsuite to find influencers to work with.
3. Strategic Guest Blogging
Well-implemented guest posting on other sites in your industry can contribute to your off-site SEO because it puts your brand in front of a totally new audience. Again, data mining tools help you find these opportunities. You gain more brand recognition and build authority in your industry. You may also get linked and unlinked brand mentions through guest posts. Of course, unlinked mentions are not as powerful as backlinks, but they are still helpful in your site’s SEO.
Incorporate Data Mining into Your Offsite SEO Strategy
Data technology is invaluable to modern SEO. We have talked about the benefits of using analytics to identify onsite SEO issues. However, data mining technology is just as important when it comes to improving your offsite SEO strategy. You will need to use data mining tools like Hootsuite and SEMRush to make the most of your strategy.
The world has changed drastically in recent years. Some of the biggest changes have been driven by advances in blockchain and bitcoin technology.
Blockchain and Bitcoin Have Become Important for the Modern Economy
Changes in the economy can definitely be tough to keep up with. After all, there are so many changes that happen on a regular basis. This means if you are someone who is a business owner or an entrepreneur, you are going to have to be on your toes. You need to be calm and collected while always being tuned in. Since being a business owner is such a demanding role, it means a lot of people do not to attain the success they once desired. Failure is a common thing in the world of business. However, the people who are dedicated to having success will be able to prevail through tough times and make a living for themselves.
Of course, as the world changes so quickly, there are many different things that can affect a business. One recent example of this would be the Covid-19 pandemic. This was a negative thing for businesses as it even caused many to close permanently. Another example that isn’t necessarily negative is cryptocurrency. This is something that has soared in popularity in the last couple of years. Of course, being a financial aspect, how has it affected business around the world? Here are some of the ways it has.
The cryptocurrency sector was made possible with the advent of blockchain. The same anonymous inventor created both of these earth-changing technologies.
It is important to be aware of the different ways that bitcoin and blockchain is changing the world of business and take the appropriate steps to incorporate them into your business models.
Examples of the Benefits of Blockchain and Bitcoin in Modern Business
There are a lot of lot of companies that are starting to find ways to leverage blockchain and bitcoin. Some of the biggest examples are listed below.
PayPal
PayPal is one of the biggest ways in which people can pay for goods and services. If you are a business owner, there is a good chance that you will use PayPal in your business. After all, why wouldn’t you? It is a safe and secure way to complete transactions, and it is appealing to many different members of the public. PayPal allows its users to complete transactions using Bitcoin and other forms of cryptocurrency. This means that if you accept PayPal, then there is a good chance a lot of your profit is going to come from Bitcoin. If you want to keep an eye on the value of crypto, this is something that can easily be done. Head to okx.com. Here, you can check out the value of Bitcoin as well as many other cryptos.
PayPal also recognizes that blockchain is a huge gamechanger for their industry. They have even hired a blockchain chief to incorporate the technology into their business model correctly.
Shopify
If you do your business through Shopify, then you are also going to be likely to accept some Bitcoin at some stage. Shopify is another site that accepts crypto as a form of payment. A lot of first-time business owners rely on Shopify to sell their goods and services, meaning that Bitcoin has had a major influence on them.
Shopify is also finding clever ways to use blockchain in its business model. One of the biggest ways they leverage blockchain is through the use of NFTs.
Appealing to a Niche
Being invested and interested in the world of crypto is actually something that can benefit business owners. Not every business is going to be accepting of the likes of Bitcoin. This means that there can be a gap in the target audience. If you are one of the few businesses that actually accept Bitcoin, then you could be appealing to a niche. People who like using Bitcoin as payment might be more likely to choose your business, thanks to the unique properties you offer.
Blockchain and Bitcoin Are Changing the Modern Economy
Data security and cybersecurity have often been treated as two fields separate from one another.
In reality, they are the two sides of the same coin.
Both have a major role in protecting information that’s circling within an organization.
Cybersecurity is focused on improving the systems, protocols, and tools that guard the company (and information) against hacking exploits.
Data security is more about safe storage and prevention of compromised access that might lead to a breach or altered and misused data within the network.
With 125 million cases of reported data breaches in 2020, organizations have learned the hard way that they have to up their cybersecurity to prevent stolen and leaked information.
In 2022, after two years of investing heavily in security, the number of recorded data breaches has gone down by 56%.
With all the security tools that exist on the market, how have companies built up their security that works for their specific needs?
The truth is that the secret lies in trial and error.
Or skipping the error altogether and investing in specialized tools for regular testing and assessment such as Breach and Attack Simulation.
What Is Breach and Attack Simulation?
Breach and Attack (BAS) is a security tool that continually launches simulated attacks. Its goal is to uncover vulnerabilities that might lead cybercriminals straight into an organization.
The software utilizes artificial intelligence to test people, security tools, and systems against common and new attack vectors.
Therefore, the tool is automated and can be configured to test chosen attack vectors 27/7.
Simulating attacks on chosen vectorsAnalysis of the data following an attackPresenting key data on the dashboard for IT teams
When simulating attacks, BAS determines whether the security points of the company could hold their own against real hackers.
During the analysis stage, the tool compares the attack surface with its previous state. Also, it assesses whether the current security would be successful in defending the infrastructure from exploits.
The results of the testing and evaluation are presented on dashboards that give analysts a comprehensive overview of security.
The report is risk-based, which means that it aids IT teams to remedy vulnerabilities by prioritizing high-risk flaws within the network.
After teams patch up weaknesses in the system based on the findings, all steps are repeated to assess the strength of security and find the space for improvement.
What Exactly Does It Test?
Simulated attacks are targeted at versatile attack vectors within the company to mimic the methods a hacker might use to breach the system.
Every company has a unique infrastructure, security, and needs. Depending on the organization, the BAS tool is calibrated differently for testing.
Common attack vectors include:
Phishing emailsMisconfigured tools
Social engineering techniques such as phishing are common, which is why most companies invest in basic cybersecurity training for their employees. Awareness can help prevent attacks and scams that are targeting less tech-savvy teams in the company.
BAS can continually run in the background to test whether your employees might click on a malware-infected link or attachment in their emails.
With increasingly complex infrastructures, errors in environments such as the cloud are quite common. BAS tests whether they pose an immediate threat to the company.
The system has to be tested against well-known and new exploits. To prevent zero-day exploits, the tool is regularly updated with the latest findings on the MITRE ATT&CK Framework.
MITRE is a digital library that depicts numerous exploits and the latest hacking methods that have previously compromised other businesses.
Strengthening Security After Testing
Simulated attacks are running continually in the background and testing the surface to isolate high risks that could lead to a data breach of a company.
IT teams use the data on the dashboard to make informed decisions in their next steps.
Once they’re presented with severe risks and flaws that have been registered within the system, they have to patch up flaws that have the potential to escalate into incidents.
Strong and updated security protects the most valuable assets of the company — including information within the system.
Layered Cybersecurity Guards Data
As mentioned, companies have a plethora of cybersecurity tools to choose from. They’ve been adding more and more to protect the range of software they use for work as well as endpoint devices of their remote workers.
An overwhelming number of security solutions has created complex systems that can be difficult to manage.
Breach and Attack Simulation guides understaffed and overworked teams towards improving security and strengthening it in the weakest places.
Detailed analytics and forensic reports highlight the high-risk issues. Instead of being bombarded with alerts all the time, IT teams get a summary of open weaknesses and suggestions on how to patch critical flaws.
Essentially, BAS creates a map of the most vulnerable points that need patching up as soon as possible to keep hackers from the information within systems.
It utilizes the power of AI to compare and test security postures and leaves parts of the management to automation.
Protecting Data in an Ever-Changing Attack Surface
An attack surface (a complete software environment that has possible points that could be targeted by threat actors) can change in minutes.
With every new hacking method that is out there in combination with regular software updates and configurations, the attack surface shifts.
Such changes might leave the system vulnerable to hacking exploits and lead to compromised access or successful phishing attacks that enable cybercriminals to obtain sensitive information.
Therefore, BAS has an integral role in tracking these frequent changes that might compromise data within the system.
The tool aids companies to be one step ahead of hackers everywhere.
Not unless you live in the most remote part of this world or somewhere underground, chances are that you have heard something about Artificial Intelligence (AI). But how does AI technology help eCommerce brands optimize for mobile?
Artificial Intelligence is becoming a big part of how different industries operate. The popularity of smart devices, security checks, research in the healthcare industry, and self-checkout registers are just a few examples of areas where AI is prominent.
The eCommerce industry has not been left behind. eCommerce business owners are looking for ways to use AI to improve their customers’ experience, increase sales, and streamline operations.
Here are a few ways AI technology helps eCommerce brands optimize for mobile;
Consumer Data Analysis
AI technology allows eCommerce brands to develop personalized and targeted marketing messages by analyzing consumer data from their eCommerce apps. However, these messages are created to fit into the requirements of a mobile app.
Brands obtain consumer patterns and trends from their eCommerce apps using AI. They also gain insights into the preferences of their customers using their mobile apps. This allows them to design the apps to match these preferences.
With such data, they know the kind of ads and targeted messages to send to each of their customers. They are also able to identify the right marketing times for such messages, allowing them to have a constant flow of traffic into their eCommerce mobile applications.
Automation
Advancements in technology have played a major role in pushing businesses towards automation. Today, tasks that would take days only need a couple of minutes to be completed. This is because of automation.
With new trends such as dropshipping in the eCommerce industry, we are seeing companies such as Spark Shipping using technology for eCommerce dropshipping automation. This requires AI technology to identify and give insights into different metrics.
Using AI, eCommerce dropshipping business owners can identify what their customers want when they visit their mobile applications. This information can be used to display the products that a customer is most likely going to buy.
Voice Search
Voice search is reshaping digital marketing in different industries. There is a lot of potential for eCommerce brands that want to use AI to implement voice search in their eCommerce applications. Using AI, eCommerce brands can learn about customer preferences, instructions, requests, queries, and interactions.
Using this data, they can segment and profile all users who access their eCommerce mobile applications. Using emerging technologies, they can streamline voice search ensuring that customers’ voices are easily recognizable.
Immediately after a returning user introduces themselves, the app can bring products that that particular user wants to see. They (customers) can interact with the mobile app without having to type anything. This is all made possible by AI technology.
Adding a Personal Touch with Chatbots
A chatbot can be defined as a computer program that is used to streamline conversations between eCommerce applications (or any other web application) and their customers.
Powered by AI, eCommerce brands can use chatbots to handle multiple tasks in their eCommerce businesses. For instance, you can use chatbots to automate all order processes in your mobile application.
When it comes to customer service, AI has learned everything about the operations of your app. This means that these chatbots can answer any question from your customers. All this happens in your app, without your intervention.
Dynamic Pricing
Initially, running an eCommerce business meant that you had to manually change your product prices whenever the need arose. Today, you can use AI to automatically change these prices instead of keeping fixed ones.
When a customer visits your eCommerce mobile app, they expect reasonable prices depending on the market. If you decide to do this manually, you are going to waste a lot of time, and the chances of errors will be very high.
In addition to dynamic pricing, AI technology can also be used to determine the consumers who need a discount even before converting. This way, you will make sure that price cuts are only available to customers who will make a purchase.
Artificial Intelligence is going to change every other industry in the next few years. As you can see above, eCommerce brands can use this technology to optimize their operations for mobile.
Data science is a very complex field that requires the insights of professionals from many different disciplines. One of the fields of professionals that are so important for data science projects are Python developers.
What is the Python programming language? Why is it so important in the data science profession?
What Is Python?
Python is a powerful programming language that is widely used in many different industries today. There are 8.2 million Python developers in the world today! That figure is growing as more teams need them to work on projects involving data analytics, AI and similar technologies.
Python developers are in high demand, and as a recruiter, knowing the roles and responsibilities of a Python developer is essential to finding the best candidates for your open positions. You will have a better understanding of the importance of using Python to create data science applications, which will make it easier to hire the right candidates.
In this blog post, we will outline the key roles and responsibilities of a Python developer and provide tips for recruiting them. So, if you’re looking to add a Python developer to your team, read on!
Python is a versatile scripting language that was first released in 1991. Python is used in many different fields today, including web development, software development, scientific computing, artificial intelligence, and more. Python is known for being easy to read and write, as well as being very reliable. Due to these benefits, it is an ideal programming language for the data science profession.
What Does a Python Developer Do?
A Python developer is responsible for writing code in the Python programming language. They may work on web applications, desktop applications, or back-end systems. Python developers typically work in a team of developers, and their job may also include working with databases, debugging code, and providing support to end users.
Python Developer Roles and Responsibilities
Let not waste any more of your time and get straight to some of the most common Python developer work roles and responsibilities.
Common roles and responsibilities of a Python developer include:
Developing back-end components for data science applicationsConnecting applications with third-party web servicesCreating scalable, testable, and efficient code which is necessary for handling programs that compile large datasetsIdentifying and fixing bugs and performance issuesWriting documentationCoordinating with other developers and data scientists
You can probably understand how these functions make Python the perfect programming language for creating AI and big data applications.
What are some of the requirements a Python developer working on big data applications should have? Here are the most common ones:
Strong experience with Python programming and an understanding of big data frameworks it will work withExperience with popular Python frameworks (Django, Flask, etc.)Experience with object-oriented programmingStrong problem-solving skillsExcellent communication and collaboration skillsExperience with version control systems (Git, Mercurial, etc.)
Python Developer Interview Questions for Data Science Teams
Data science projects are very complex. You can’t afford to hire the wrong team members. Therefore, you have to interview your candidates carefully.
What to ask your Python developer during an interview? We have collected a list of technical and cultural interview questions to ask your python developer.
Python Developer: Technical Interview Questions
What is Python?What are the benefits of using Python?What is your background on big data applications?What are some of the key features of Python?What is your experience with Python?What are some of the most popular Python frameworks?What is your experience with object-oriented programming in Python?
Python Developer: Cultural Interview Questions
Tell me about a time when you had to solve a difficult problem?What is your approach to problem-solving?Tell me about a time when you had to work with a difficult codebase?What is your experience with writing documentation?Tell me about a time when
That’s it for this article! Hope we’ve helped you figure out what are some of the common roles and responsibilities for a Python developer helping create big data projects. Good luck in hiring the best candidate!
Cloud technology is changing the future of business in many different ways. Countless companies have discovered the benefits cloud computing has to offer. As a result, 60% of companies have migrated to the cloud.
One of the many benefits of cloud technology pertains to human resource management. A growing number of companies are storing employee data on the cloud, which makes it easier to handle certain HR tasks.
In order to appreciate the benefits of using the cloud for HR management, it is necessary to understand the importance of human resource management in general. Keep reading to learn more.
What is Human Resource Management?
Human resource management is the process involving recruiting and selecting candidates while also providing them with training and development. Human resource management also decides on the appraisals of the employees’ performance and the compensation for the same. They maintain the proper relations with the employees and ensure the safety and healthy environment for the employees, which is in compliance with the labor laws of the land.
Since HR is so important, companies use the latest technology to handle it. This is one of the reasons that cloud technology has become so important in HR. The cloud helps with workforce planning and HR analytics, although there are still some challenges here that companies need to avoid.
HR management mainly deals with essential workplace functions like organizing, planning, directing, and controlling. It focuses on managing human resources for the organization and is responsible for their training, development, and maintenance. The HR department helps the organization achieve its social objectives.
HR management is a multidisciplinary subject that studies various fields like psychology, management, communication, and sociology. In recent years, it also involves new technology investments such as cloud computing.
It also helps in promoting teamwork. HR department handles every factor surrounding employees and manages the functions like job analysis, selection of the candidates, training, providing benefits and incentives, career planning, and maintaining discipline among the employees. It also communicates with the employees at all levels and maintains compliance with local as well as state laws.
What is the importance of Human resources?
Human beings have a great capacity, and no product or service can be produced without participation. It is a basic resource for the production of anything. Every business or organization desires to have skilled and professional people to make their business a success. It should be no surprise that many startups are investing in cloud HR technology to deal with these issues.
The management basics include the five ‘M’s, which are men, machines, money, methods, and materials. Human resource management is the branch that deals with the men. Humans are not easy to manage as each person is different from the other. In the other ‘M’s, men play a key role and have the power to manipulate the other ‘M’s.
People run businesses; a business cannot run by itself. The success of a business lies in its employees and managing them is what human resource management is all about.
Scope of human resource management
Human resource management includes a wide range of factors, so it’s necessary to classify it under the following subheads:
Personnel management – It is also called ‘direct manpower management,’ and it includes the most basic functions of human resource management like:HiringTrainingInduction and orientationTransfer, compensation, and benefitsLayoff and Termination
Labour relations – HRM focuses on improving the relationship between labour and organization. It addresses the grievances and settles the disputes to maintain harmony.Employee welfare – This mainly focuses on the working condition of an employee and includes factors like the safety and health of the employees.
As human resource management play a key role in recruiting and training professionals, an organization needs to increase its skills and expertise through senior management courses. The growth of an organization depends on how well the employees are assigned to their roles, and human resource management is responsible for the same. A well-organized and skilled human resource management department ensures an organization’s steady and consistent growth.
What Benefits Does the Cloud Bring to HR Management?
There are a lot of great reasons companies are investing in cloud technology for HR management. Here are some of the biggest benefits:
You can take advantage of SaaS human resource management tools that are only available on the cloud. Many cloud-based tools help with payroll administration, recruiting, benefits administration and talent management. You can track performance of employees more easily by storing records of their work on the cloud.You can use cloud-based tools to automate many workflows.
The benefits of using cloud computing in human resource management cannot be overstated. A report by Deloitte highlights some of the most pressing benefits of cloud HR.
Big data technology is becoming more important than ever for modern business owners. One study by the McKinsey Institute shows that data-driven organizations are 19 times more likely to be profitable.
There are many benefits of using big data to run a business. One of the most important advantages is that big data can help with marketing.
Big Data is Essential for Modern Marketing Strategies
Running a business isn’t easy, especially when it comes to marketing. However, if you want to continue to draw in new customers and clients, continuous marketing is a must. The good news is that big data can help with this. The McKinsey Institute report showed that data-driven businesses are 23 times more likely to acquire customers.
The good news is there are ways to use big data to simplify and boost your efforts to guarantee success. If you are looking to boost your marketing efforts as a data-driven organization, then you should follow these crucial tips.
Big data has revolutionized marketing. Giving you insights into how your current methods are working, your customers, and increasing brand awareness, big data can play a crucial role in your success.
The main types of big data you’ll want to capture include:
Customer dataOperational dataFinancial data
By collecting and analysing customer data, you’ll get a much better idea of who your target audience is. This can help you to figure out the best places to advertise and market your services, as well as determine your brands tone of voice. Having a strong understanding of your target audience is crucial in marketing. After all, if you don’t know who you are marketing to, how can you expect to receive results?
Operational data refers to the way the business runs, including shipping and logistics, and customer relationship management. Data has become very important for improving customer service. When you have a clear picture of the way the business is run, improvements can be made to improve performance. This in turn will boost customer satisfaction, leading to more word-of-mouth referrals.
Financial data such as pricing, sales, and margins, helps you to budget more effectively. You will also see where your budget is being wasted, allowing you to switch to more profitable marketing methods.
The more data you collect and analyse, the more targeted and effective your marketing will become.
Update Your Aesthetics – how things like flooring help with marketing (makes good impression etc)
In business, it’s important to make a great first impression. This is difficult to do if the aesthetics of your brand aren’t on point.
Start with your digital aesthetics such as your logo, web site, and social media presence. Does your branding match your business? Having clean, clear aesthetics can help you to appear more authoritative and professional.
It isn’t just your digital presence that you need to worry about. How your physical premises are laid out will also make a difference to your marketing efforts. Firstly, it determines a customer or client’s opinion of the business if they visit your premises. Secondly, the aesthetics of your business can impact morale, motivation, and productivity.
Everything from the type of flooring you have installed to how much light enters the premises can make a difference. When it comes to the flooring of your business it should be comfortable, practical, and aesthetically pleasing. It doesn’t have to cost a fortune to update the flooring in your business. There are companies that offer up to 65% off commercial flooring.
These are just some of the ways aesthetics matter in business. If you want to make a good impression, start by giving your online or offline a presence a makeover.
Leverage big data for local community engagement
Giving back to your local community is a great way to boost your marketing efforts. Customers and clients generally love brands who use their profits for good.
It could be sponsoring a local sports team, organizing a charity fundraiser, or planting trees and greenery to help improve air quality and aesthetics. Don’t forget to advertise the ways you give back to the community on your social media platforms. Getting involved in your local community could help you to attract a lot of new customers, as well as keep existing ones coming back for more.
It might seem like big data wouldn’t help much with local community engagement. However, there are creative ways to tap data to learn more about your target consumers. This allows you to focus on identifying charities and engagement opportunities that allow you to be seen be your target customers.
Use Big Data for Reputation Management
You need to use data mining to improve reptation management. You can use data scraper tools to find positive statements customers and experts have made about your company. Then, you can showcase these testimonials on your website.
Do you have glowing testimonials you can show off to potential clients? These days consumers need to trust a business before they buy from them. Testimonials and positive reviews can help to put their mind at ease, making them more likely to make a purchase.
You should showcase your testimonials wherever you can, including on your website, social media pages, and in email signatures. Don’t forget to encourage your customers to leave them too. Having a constant stream of positive reviews will do wonders for your brand.
Use Data-Driven SEO
To continuously attract new clients and customers, you need to work on your SEO. Making it easier for you to be found by search engines, the right SEO tactics can boost website traffic, convert more leads into customers, and improve your bottom line.
It can take a lot of work to develop and implement a successful SEO strategy. If you need to, bring in the professionals. SEO companies and freelancers can help you to achieve better rankings with minimal effort on your part.
There are a lot of benefits of using big data in SEO. You can use data-mining tools to identify keywords that are likely to appeal to your target demographic. There are also data-mining tools that can help you identify links to competitor websites, so you can reverse engineer their linkbuilding strategies.
Offer competitions and giveaways
Giveaways and competitions tend to attract a lot of attention. If you are trying to bolster your marketing efforts, think of a giveaway or competition that your audience will love.
Advertise your offer on social media, asking participants to like, share, and comment on your post. This will boost its visibility to others, making it easier for customers to find you. Limited time giveaways and competitions work best, and you can offer everything from discounts to free products.
Make the most of social media
Social media provides a ton of opportunities for marketing your brand. However, it’s important to focus on just one platform at a time when you are just getting started.
Find out where your ideal audience hangs out, then focus on marketing your business on that channel. With social media you can run paid ads, post valuable content, gather fans and followers, and boost brand awareness.
There are over a billion people using social media sites, giving you access to a huge audience. If your business doesn’t yet have a strong social media presence, now is the time to build one up.
You can’t take an ad hoc approach to social media, though. You are going to need to invest in social media analytics tools that will help you make more nuanced insights. You can use your data to guide your decision-making process, so yo can create the best content, post at the right times and engage with the right networks.
Use Big Data to Think Outside of the Box
Like everything in business, the best results often come from thinking outside of the box. Big data technology will make this a lot easier. You need to use analytics tools to make observations that you can use to make more informed decisions. When you invest in big data, you can come up with innovative ways to market your business. Look at what your competitors are doing and identify ways to improve on their strategies.
There are tons of ways to boost your marketing efforts with big data technology. The above methods are some of the most effective things you can try out to start seeing bigger, better results. Consistency and continually tracking your efforts with data analytics tools are key to your success.
Data created by humans found on the Internet and on computers isn’t always accurate. Typing, scanning, taking pictures, or recording done by humans aren’t always reliable. But what if there are sensors on machines that collect data and are capable of communicating with other machines? What if there’s some kind of protocol that makes medical and personal gadgets, appliances, and other electronics send and receive data from each other?
Such a system would mean people can, for example, accurately track what’s in their inventory. Or what part or item in their shop needs to be replaced, replenished, or repaired. As the sensors in the devices collect the data, it means the data is more accurate and more reliable.
This system was made possible with the arrival of the Fourth Industrial Revolution. It brought with it the Internet of Things (IoT), robotics, artificial intelligence, and other emerging disruptive technologies.
An Overview Of MQTT
Smart TVs, smartwatches, and other ‘smart’ appliances and gadgets that can send and receive messages with each other are now as common as cookies on websites. Collectively, these intelligent devices that can collect data through sensors and send them to other devices are known as the Internet of Things (IoT).
How do devices do this? Their ability to communicate with each other is made possible by a messaging technology called Message Queueing Telemetry Transport (MQTT). It’s an IP-based lightweight messaging system that provides support to IoT. It enables controllers, sensors, and other gadgets or devices to ‘talk’ with each other. Additionally, it supports equipment that isn’t always online, like automated devices equipped with microcontrollers.
The MQTT messaging protocol was created in 1999 by IBM’s Andy Clark and Eurotech’s Arlen Nipper. It started as a proprietary protocol used primarily in the oil and gas industry that later became an open-source protocol. The MQTT is designed to work in low-bandwidth networks. This characteristic is ideal for machine-to-machine communication and IoT devices with a small digital footprint. It works not only in low bandwidth networks but also in high latency environments.
The MQTT is used in various industries, like manufacturing, health, telecommunications, automotive, and others. It’s now recognized as the standard for IoT messaging. This messaging system, working on the publisher/subscriber principle, is operated using an MQTT server. Both the sender and receiver don’t need to be connected directly to one another.
Data from sources are published and received by clients subscribed to receive such data. The publishers and subscribers’ relationship works like this:
Publisher (data source) transmits data or message on a Topic.Client subscribes to a Topic to receive messages.The server matches publishers to subscribers.The message is discarded if no matches are found.
This arrangement is similar to a radio or TV broadcast—you can only view the transmission from the channel you’re tuned in to. In MQTT, data sources ‘publish’ the data, and recipients get it because they’re registered subscribers.
MQTT Architecture And Data Transmission Protocol
Designed to be a simple publish / subscribe protocol for lightweight devices, MQTT is composed of two primary components: the broker / server and the client.
1. MQTT Broker/Server
The computer running the piece of software that receives messages from data sources or publishers is called the broker or server. The server/broker then sends data from the sources to its correct destination, the subscribers. The software can be installed on a cloud-based broker / server using proprietary or open-source software, an on-site desktop PC, or a Raspberry Pi. But if you’re working with IoT projects that you can control over the Internet, using a cloud-based server is more suitable.
A server can manage MQTT clients of up to thousands connected simultaneously, depending on the implementation. Scalability and integration are, therefore, essential considerations when selecting an MQTT server. A server also has other capabilities besides receiving and sending messages, such as the following:
Security
An MQTT needs to be secured. It should require robust usernames and passwords from its clients. In addition, the transmission control protocol connection should be encrypted with Secure Sockets Layer (SSL) and Transport Layer Security (TLS). These security measures should ensure the message’s security and privacy during transit.
Quality of Service (QoS) Level
Quality of Service (QoS) Level is an agreement between the source of messages and the intended receiver. This agreement defines a specific message’s guarantee of delivery. There are three levels of QoS in MQ Telemetry Transport:
At most once (0)
At this level, delivery isn’t guaranteed. What this level guarantees, at most, is ‘best-effort’ delivery. The message is neither stored nor re-sent, and recipients send no acknowledgment of receipt. This Quality of Service level is used when the Internet is reliable and data needs to be quickly delivered.
At least once (1)
The message is guaranteed to be delivered to the subscribers at least once. The publisher stores the message until the recipient sends an acknowledgment of receipt. The server also acknowledges the message sent by the publisher, letting the client know that the message was received. The message will be sent again if the client doesn’t receive an acknowledgment.
The acknowledgment tells the subscriber-client that all messages pertaining to the topic to which the client is subscribed had been published. While messages being received are guaranteed at this level, duplicate messages can happen if the acknowledgment of receipt isn’t received on time.
Level 2 is used if the client needs to receive all messages on a subscribed topic. However, many commercial servers don’t support Level 2 because it’s comparatively slow and a resource hog.
Exactly once (2)
Level 2 is the highest Quality of Service level in MQ Telemetry Transport. Each message is guaranteed to be received once by the subscriber. It’s also the safest, albeit slowest, of the three QoS levels. While Level 1 can cause duplication of messages, Level 2 guarantees that data is received only once.
This guarantee is provided by two (at least) ‘request and response’ flows between the publisher and subscriber, which indicates that message is received. Once the subscriber confirms that the message is received, the publisher can discard the data packet. If the publisher fails to receive a ‘message received’ signal from the subscriber, the message will continue to be sent until the message is acknowledged.
High QoS levels are more reliable but involve high bandwidth requirements and higher latency, which can slow down data transmissions. This level is used when quick message delivery isn’t necessary and if duplicate messages can cause issues.
There are two sides to message delivery when it comes to QoS: from the publisher to the server and from the server to the subscriber. The source / publisher of the data or message sets the data’s QoS level every time data is sent to the server. The server then sends the data to the subscriber clients according to the clients’ QoS level, which was set at the start of the subscription process. If the client’s QoS is set lower than the publishing client, the server will send the data with the lower QoS.
This characteristic allows MQTT to provide added messaging qualities of service, ensuring that the data is sent according to the client’s requirements.
Store and Forward
Certain MQTT messages can be stored and forwarded to subscribers even when a subscriber- client isn’t available to receive the messages. These messages are called ‘Store and Forward Topics’ to which clients can subscribe. A client subscribed to the Store and Forward feature can receive the stored data when the subscriber becomes available to receive the messages.
For this feature to function efficiently, the MQTT server needs to do the following:
Track each subscriber’s Client IDTrack the identifiers of the last message sent successfully to each client.
The MQTT broker automatically deletes expired messages unless configured to retain them. The broker stores configured topics in case future clients subscribe to them. The messages will then be delivered to subscribers in the order that the messages were received originally.
2. MQTT Clients
The MQTT clients can be publishers and subscribers. The labels ‘publisher’ and ‘subscriber’ refer to clients that publish messages or subscribed to receive messages. In MQTT, the publish / subscribe functionalities can be implemented in the same client. Clients can perform different functions like subscribe, unsubscribe, publish, connect, and disconnect at the communication stage.
Moreover, these clients can be any device or app, ranging from a microcomputer to a full-pledged cloud-based broker / server equipped with various bells and whistles. The client can be a compact device with a bare minimum library and limited resources and connects using a wireless network.
Suffice it to say, any device capable of running MQTT through a TCP/IP stack can be a client. The MQTT’s implementation is streamlined and straightforward, traits that make MQTT ideally suited for small devices that use minimal resources.
Conclusion
Message Queuing Telemetry Transport (MQTT) is the technology that makes smart home appliances, smart gadgets, and other Internet of Things (IoT) devices ‘talk’ and share information with other machines or systems. This messaging technology makes your smartphone, refrigerator, wearables, thermostats, remote sensors, and other intelligent gadgets exchange data with each other.
Data flow in MQTT works via a simple publisher / subscriber system with the help of a server / broker. A publisher transmits data on a Topic through the server; the server then transmits data to clients subscribed to that Topic.
Analytics technology is very important for modern business. Companies spent over $240 billion on big data analytics last year. That figure is expected to grow as more businesses discover its benefits.
Analytics Can Be Essential for Helping Companies with their Pricing Strategies
We all know how difficult it can be to get the pricing right in B2B contexts. In today’s business world, pricing has become one of the most important parts of a company’s strategy. Prices must account for the company’s key value metric, cost structure, buyer personas, and other factors like competition.
Analytics technology can help companies optimize their prices more effectively. Last year, Tullika Tiwary addressed some of the reasons in her post in CustomerThink. Here are some ways companies can benefit from an analytics-driven pricing strategy:
Analytics helps companies segment their customers, so they can get a better understanding of their behavior. This helps them determine how different customer segments will behave in various situations, which helps them set their prices appropriately.Analytics can use existing data to model scenarios where customers will respond to different prices.Analytics technology helps companies make more nuanced insights about different products and the prices they should charge for them.
This article will walk you through 5 top B2B pricing models that you should consider when determining your own strategy. We will also talk about ways to incorporate data analytics into these models. We will also introduce methods to help you choose which model is right for your organization, as well as the implications of selecting a particular model.
Why Is It Important To Use Get B2B Pricing Right?
When you get the pricing right for your B2B business, you demonstrate your knowledge about buyer personas and their needs. You are proving that you understand your value-based metric and the dynamic factors in the marketplace, such as changes in the economy.
You are making buyers aware of how their competitors price their products and services to make informed decisions about what to pay for yours. That is why getting B2B pricing right is essential if you’re going to make a business value for your consumers and profit from it.
Since pricing strategies are so important, it is essential to use all technology at your fingertips to make the best pricing decisions. Analytics technology can help you significantly in this regard.
5 Top B2B Pricing Models and Ways to Use Analytics with Them
The best way to get the pricing right in B2B contexts is to consider how customer personas value your product or service, how price affects the buyer (their buying process), and your company’s cost structure.
We’ll look at each of these factors in detail and discuss their implications for successful B2B pricing decisions and how to use analytics with them.
Cost-Plus Pricing
The cost-plus pricing model is often used by small businesses that don’t have a lot of experience in B2B pricing. In this model, you create a cost structure for your product, then add a required profit margin. You can use analytics tools to track costs of your inputs and set prices correctly.
Value-Based Pricing
In a value-based pricing model, your price is determined by the value you provide to your buyer. The seller usually determines the price based on their ideal solution for a particular task as well as their budget. The value-based model is appropriate for companies focused on adding high-value products and services to their product offerings or just starting.
Analytics technology can be very useful in this regard, especially when costs are not static. You can use analytics models to forecast future costs of your inputs and apply the right markups on your products.
Needs-Based Pricing
Needs-based pricing is the opposite of value-based pricing. You may read here about the main differences. It considers a solution’s costs and benefits rather than its value to buyers. These are usually strictly business decisions where there is no selling involved. This method will help when you’re making decisions about services that add value to your overall product offering – for example, a consulting arm of your business or extra features on your SaaS solution.
Again, analytics technology can be very helpful, although the benefits will be applied in reverse. You will use data mining tools to understand the values customers get from various products and services and analytics technology will help you assess them. This will help you make more nuanced decisions.
Competition-Based Pricing
Competition-based pricing is a relatively straightforward approach that you can use for either new or existing B2B businesses. In this model, you look at your competitors’ prices and adjust yours appropriately to make sure your product or service is still profitable. You are interested in how the market reacts to your price and how consumers perceive it.
Analytics technology will help you better understand your competitors. You can use data mining tools to research pricing and sales volume of your competitors. This will help you understand your competitors and price your own products accordingly.
Dynamic Pricing
Dynamic pricing takes into account external factors that affect the buyer’s decision-making process. It can apply to any of the models we’ve discussed so far and is extremely useful when buyers are particularly sensitive about costs or when their cost structures change quickly over time.
This is one of the biggest reasons analytics is important. External variables that affect prices change quickly in many industries. You can use real-time data to stay up on these trends and take advantage of analytics to make the right decisions.
Choosing the Best Analytics-Driven Pricing Strategy
Once you’ve determined which analytics-based pricing model is right for you in your B2B situation, you need to pick the one that will work best in that context. You can do this by considering your value metric and then deciding based on it.
Know Your Value Metric
Your value metric is the yardstick to which you’re measuring your benefits to customers. It usually accounts for what your product or service gives customers (its value), as well as how long it lasts and how much of an impact it has on their lives.
Utilize Buyer Personas
Before choosing a pricing strategy for your B2B business, you need to know who your buyer persona is. Buyer personas are archetypes of real potential buyers that you create after analyzing the data about the type of person who would buy your solution. You should have complete knowledge about their age, profession, income level, and other information that will help you tailor your product or service to their needs.
Decide On A Pricing Model
With this information, you will be able to make more informed decisions regarding your pricing model and be able to make more money in the process. This works in both B2B and B2C contexts – whether you’re running a consulting business or launching a new SaaS solution that solves certain problems for companies in the industry they belong to, this guide will help you understand how to price your product or service properly.
Consider Buyer Expectations
There are many things that potential buyers expect from a product or service and what they need from it. For example, some buyers just want an easy way to access a service in their preferred way, while others may also want to make money on it as well – for example, by selling it to other businesses or customers. Understanding this will help you determine whether your product or service is suitable for those buyers and ensure that your B2B business is successful in the long run.
Take Into Account All Other Factors
Before deciding what type of pricing model will work best for your particular business, consider all other factors that affect how you price your product or service. Your company’s cost structure, its ability to work with clients, and market demand are just some examples.
Analytics is Vital in Pricing Strategies
Pricing strategies are different for B2B and B2C contexts, but the core principles of effective pricing strategies apply to both. The key to getting B2B pricing right is knowing how to read the data and information in your marketplace, your company’s cost structure, your value metric, and what buyers expect from a product or service. You will need the right analytics tools and the right pricing strategy to make the best decisions.
If you want to make more money with your business or just get the most out of it, use this guide today to get solid insights on how you can do it. It will help you determine the right pricing model for your needs and choose it so you can start using it immediately.
The market for cloud technology is booming. Companies spent over $405 billion on cloud services last year. The sudden growth is not surprising, because the benefits of the cloud are incredible.
Enterprise cloud technology applications are the future industry standard for corporations. Cloud computing has found its way into many business scenarios and is a relatively new concept for businesses.
Here’s how enterprises use cloud technologies to achieve a competitive advantage in their essential business applications.
Data streaming
Information is moving at a faster pace today than ever before. Companies must take advantage of the information about their customers to stay updated and respond in real-time for quick decision-making.
Cloud computing (https://www.striim.com/product/striim-cloud/) can be used to support real-time data streams for better business decision-making. With cloud computing, companies can use their servers and hardware as much as they want with little overhead from extra hardware and software.
Cloud technology results in lower costs, quicker service delivery, and faster network data streaming. It also allows companies to offload large amounts of data from their networks by hosting it on remote servers anywhere on the globe.
Multi-cloud computing
Cloud computing allows companies’ multiple servers to store and manage their data in a distributed fashion. The model enables easy transfer of cloud services between different geographic regions, either onshore or offshore.
Companies have the flexibility to choose the location where they have the best infrastructure to deploy their businesses. Cloud computing has provided additional advantages like interoperability with traditional enterprise systems via APIs.
Testing new programs
With cloud computing, companies can test new programs and software applications from the public cloud. Parameters can be changed, updated, or performance enhanced without the time-consuming installation of new hardware and software.
Cloud technology allows companies to test many programs and decide which ones to launch for consumers quickly. The testing helps reduce the overall cost, time, and risk associated with building new hardware so companies can focus more on their core business functions.
Centralized data storage
Cloud technologies provide users with centralized storage for all information. For example, e-mail messages and documents are stored in the cloud, giving users access to their data from any location.
Information is encrypted and stored on firewalls or protected by redundancy and many other security methods to ensure data safety. The data storage from one company can be accessed by another company through multiple clouds, decreasing or even eliminating the need for traditional onsite storage systems for companies.
Disaster recovery and data backup
Cloud technology helps companies recover business processes in a natural disaster. Cloud technology allows for information to be shared and stored in remote data centers, making it possible to continue operations even when premises get damaged. Companies can also implement redundant systems and virtualized equipment to ensure the continuity of services.
Data backup is one of the most important benefits of cloud computing. The data backup solution makes it possible to recover your business operations when a system fails. The system eliminates the requirement to purchase expensive backup systems and other equipment.
Big data analytics
The amount of data in today’s world is growing exponentially, and cloud computing provides excellent tools that analyze large volumes of information and carry out marketing segmentation. Using data mining and advanced analytics, companies can better analyze customer behavior patterns to predict their needs and provide more customized products and services.
An organization can process vast amounts of unstructured data from social media networks and websites by running computationally intense workflows on these applications in a distributed network environment.
Provision of infrastructure as a service (IaaS) and platform as a service (PaaS)
Cloud technologies allow companies to rent servers and storage to provide IaaS. The IaaS model works well for new startups that don’t want the capital expense of building an IT infrastructure.
Companies that handle hardware, software, and security measures in a data center provide managed cloud hosting services. Companies can share resources and pay according to their usage with automatic billing, lowering costs while still enjoying the security of scalable IT offerings.
Companies use PaaS to rent access to a development environment with applications and storage. Users can develop new software or update existing programs without installing additional software. Cloud computing enables companies to quickly deploy new applications for employees without wasting time on installation in their IT networks.
Before you go
Cloud technology has proven to be an excellent model for large companies. Cloud computing allows companies to increase productivity with reduced costs and improve their business structures by improving real-time information. Cloud technology also provides customers and employees new ways of connecting, sharing data, and creating customized services.
