Technology Explained
Still Receiving Emails After Unsubscribing? Here’s What to Do
Still Receiving Emails After Unsubscribing?
Unsubscribing from emails should get you taken off the mailing list. But if you’re still getting some slip through, here’s what to do.
Have you ever unsubscribed from a company’s email list, only to receive another email from them the next day? If a sender has already annoyed you enough to hit the unsubscribe button, the last thing you want is to see their name pop up in your inbox almost instantly.
Why Am I Still Receiving Emails After Unsubscribing?
Unsubscribing should be the hassle-free way to stop receiving unwanted emails, but it doesn’t always do the trick. There are several reasons you might continue to receive emails from a company, even after unsubscribing:
- You’re signed up to multiple email lists: Many companies will try to sign you up for multiple email lists (marketing, news, customer service, etc.), which means you have to unsubscribe from all of them to stop receiving any emails from them.
- It takes time to update email lists: Hitting the unsubscribe button doesn’t instantly remove you from an email list. Companies have to update their lists, and this can take time, depending on the system they use and their inclination to act quickly.
- Technical issues can happen: While the chances are relatively slim, technical problems do happen. For example, the company could break something during an update or their email system might experience downtime, failing to unsubscribe anyone during such periods.
- The company needs to send certain emails: If you’re still buying from the company or using their products, they’ll need to send certain types of email–no matter how much you unsubscribe: transactional emails, T&Cs updates, pricing changes, etc.
- Some companies ignore unsubscribe requests: No, it’s not fair, but some companies simply don’t play by the rules.
While none of these reasons makes it any less annoying that you’re still receiving emails, they can help you take actionable steps to protect your inbox. Before we go any further, though, make sure you only unsubscribe from emails you recognize–never unsubscribe from suspected spam emails.
How to Stop Unsubscribed Companies Sending You More Emails
Now you know the main reasons you can still receive emails from a company after unsubscribing, you can take steps to address them.
1. Check Your Email Subscription Settings
The first thing to do if you’re still receiving emails after unsubscribing is to check whether you’re signed up to multiple email lists. If you have an account with the company, sign in to your account and check your email settings or preferences in the back end of the system.
For example, if you’re receiving a bunch of emails from Instagram, log into your account and click Settings and privacy > Email notifications to change your email preferences.

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If you don’t have an account with the company in question, go back to one of the emails they’ve sent you and cycle through their unsubscribing process again. Make sure you click the unsubscribe link in their email, not the one in your email client.
As you repeat the unsubscribe cycle, look out for anything that shows you’re signed up for multiple lists: checkboxes, toggles, etc. Read every step of the unsubscribe process carefully for anything that suggests you’re signed up for other lists or will continue to receive certain types of email.
For example, if you’re still using a company’s software product, you’ll continue to receive emails for updates on pricing, purchase confirmations, etc.
Also, keep an eye out for links to the company’s privacy policy or anything related to email practices that could explain why you’re still receiving emails. You might even see some small print explaining why you’ll still receive occasional emails or that it takes up to 24 to 48 hours for your email address to be removed from their lists.
Hopefully, repeating the unsubscribe process will provide the answers you need. If it doesn’t, head to the company’s website and take a look at their privacy policy on email communication.
2. Wait a Day or Two for Settings to Change
Most companies use email marketing systems to automate communications. These software tools automatically send emails to recipients and handle a range of other tasks, including unsubscribes. Some of these systems will update email lists as soon as you hit the unsubscribe button, but many don’t.
It could take anywhere between 24 and 48 hours for an email system to update its contact lists. This means you’ll continue to receive emails from the sender until their system has run the next update cycle.
In an ideal world, companies will inform you of this during the unsubscribe process, but many don’t. In fairness, a lot of companies may not realize there’s a delay or even pay much attention to subscription requests. Either way, it’s always worth waiting 24 to 48 hours after unsubscribing before you take any further action.
3. Report As Spam If You’re Still Receiving Email
If you’ve waited 24 to 48 hours after unsubscribing, and you’ve done everything possible to make sure you’re not signed up to other email lists, it’s time to take stronger action. By this point, any company that’s still sending you unwanted emails is spamming you, so you should start marking any further emails as spam.
If you’re using Gmail, you can do this by selecting the checkbox next to any spam emails, and then click the Report spam button.
This won’t stop further emails coming through, but every spam report is another black mark on their email sender reputation with ISPs. This means more of their emails will head straight to people’s spam folders and their email marketing efforts will suffer. So, even though it’s annoying to keep dealing with these emails, every spam report you submit is making a difference.

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4. Block the Sender to Stop Receiving Email
If you reach a point where you simply want to stop receiving further emails from a particular sender, you can block them completely. The easiest way to do this in Gmail is to click the three-dot icon at the top of an email and select Block [sender name] from the dropdown menu.

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Keep in mind that this only blocks the exact email address used to send the email in question. So, if the company uses a bunch of email addresses for different types of emails, you won’t block them all.
A more robust method is to create a custom email filter. You can do this in Gmail by clicking the gear icon (Settings) > See all settings > Filters and blocked addresses.

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Next, click on the Create a new filter link and this will bring up the following box:
This time, you want to type in the domain name of the email sender into the From field, which is normally the text following the @ symbol. For example, emailprefix@domain.com. This will block all emails from the domain, so it’ll block anything sent from other people or departments at the same company.
Unfortunately, this still won’t protect you from companies that keep switching domain names to get past spam filters. However, you can type the company name into the Includes the words field and this will help filter out any emails that include the company’s name (which should be all of them).

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Again, this isn’t foolproof, but it should deal with the vast majority of emails from legitimate companies.
5. Raise a Complaint With the Company
Hopefully, the steps we’ve covered will help you deal with any unwanted emails that you’ve tried to unsubscribe from. That being said, you might want to contact the company in question to make them aware of the issue.
Broadly speaking, companies are legally obliged to respect any subscription requests you make, and it might help to remind or make them aware of this. Point them in the direction of the CAN-SPAM Act to make them aware you also know they’re legally obliged to respect your wishes.
As mentioned earlier, it’s possible to continue receiving emails due to a system error or legitimate mistake. Raising the issue with a company could help them identify an unknown problem and resolve it.
They might even inform you that a temporary (and fixed) issue kept you on an email marketing list. In this case, manually removing you from an email list on their end of the system could resolve the problem for you.
Sometimes, Unsubscribing Isn’t Enough
As annoying as it is, unsubscribing from an email list isn’t always enough to stop receiving emails from a sender. Sometimes, they intentionally make it harder than it should be to remove your email address from all of their marketing lists. In other cases, they might not understand the rights and wrongs of email marketing–or even care about them.
Either way, it always helps to know the tools Gmail and other email clients give you to take control over your inbox and the emails reaching it.
Key Points Summary Table:
| Reasons for Still Receiving Emails | Steps to Take |
|---|---|
| Signed up to multiple email lists | Check email subscription settings |
| Time required to update email lists | Wait for settings to change |
| Technical issues | Report emails as spam |
| Necessary emails | Block the sender |
| Non-compliance by companies | Raise a complaint with the company |
Technology
Privacy in the Digital Economy: The Rise of zk Crypto
The digital asset industry presents a critical reality for investors, developers, and institutions alike: information is powerful yet fragile.
It can strengthen systems or dismantle them, depending on how it is stored, processed, and shared. Over the last decade, blockchain technology has gained traction, largely because it addresses trust issues. However, this solution has created new challenges.

The Double-Edged Sword of Transparency
Blockchain’s hallmark transparency quickly turned into a double-edged sword. Initially seen as a pillar of decentralization, this transparency inadvertently exposed critical financial operations, identity behaviors, and organizational workflows.
The same quality that inspired confidence began to limit practicality. As a result, there arose a pressing need for privacy in digital interactions.
Emerging privacy-first ecosystems, driven by Zero Knowledge technology, provide a response to this tension. These systems allow for the verification of information, identities, transactions, and artificial intelligence computations without revealing underlying data.
This shift represents one of the most significant architectural innovations since the inception of smart contracts. Industries requiring high confidentiality, while still needing decentralized integrity, can benefit from a privacy-focused, computation-ready blockchain network.
The Intersection of Utility, Value, and Privacy
In this evolving digital landscape, the growing volume of digital assets is reshaping the interplay among utility, value, and privacy. These assets are not merely transactional; they support encrypted computations, reward participation, and foster ecosystems centered on end-to-end confidentiality.
zk Crypto: A New Type of Digital Asset
The rise of zk Crypto signifies a momentous reevaluation of digital finance. Traditional cryptocurrencies often emphasize transparency and accessible transaction histories. While these features are beneficial in certain applications, they pose challenges for sectors such as healthcare, finance, defense, artificial intelligence, and identity systems. These sectors urgently need verifiable data communication that maintains confidentiality.
This is where zk Crypto diverges. It connects directly to networks that permit encrypted computation through advanced Zero Knowledge architectures. By default, privacy governs this ecosystem. Every transaction, calculation, or identity exchange remains secure and provable. The decentralized encrypted environments at its core empower selected users to engage in complex artificial intelligence tasks, authenticate sensitive data, and execute private digital workflows.
The Role of Proof Pods
Users invited into these Proof Pods receive compensation through a native token, reflecting the computational value they bring to the network. This reward system intertwines with zk Crypto’s identity and becomes the economic engine that sustains privacy-first operations. Future presales will open participation to a broader audience, enabling both early supporters and institutions to engage in the ecosystem.
As the demand for encrypted workflows grows, the role of zk Crypto expands. The token embodies a distinct kind of utility, closely associated with the future of confidential digital finance.
The Economic Rationale of Zero Knowledge Digital Assets
To grasp zk Crypto’s long-term value, one must consider the broader economic trends shaping the data-intensive industry. Increasingly complex regulations weigh on institutions, while the costs associated with data breaches continue to soar. Artificial Intelligence systems require vast quantities of data, but they also amplify privacy concerns and potential misuse.
Today, awareness around the collection and sale of personal data has reached unprecedented levels. Trust in digital platforms has waned, and privacy has emerged as a vital asset category.
Zero Knowledge ecosystems present a viable alternative in this pressure-laden environment. They foster trust by employing encrypted validation rather than exposing data, steering clear of centralized computation that might compromise sensitive information. Instead, they distribute computational tasks across a network of privacy-conscious nodes, embedding privacy into their very foundation rather than treating it as a premium feature.
Within this framework, zk Crypto serves as the internal mechanism supporting encrypted workloads. Those who operate Proof Pods earn zk Crypto by facilitating private AI operations and verifying confidential information. This transformation shifts digital asset utility from a passive role to an active manifestation of computational effort. It meets a growing global need for privacy and security in digital interactions.
Meeting Regulatory Demands
As regulatory regimes tighten globally, the necessity for privacy-first infrastructure increases dramatically. This demand reinforces zk Crypto’s financial foundation, anchoring its trajectory in measurable participation within encrypted computing ecosystems.
Conclusion
The emergence of zk Crypto marks a pivotal transformation within the digital financial landscape. It highlights the evolution of blockchain technology amid heightened concerns for data sensitivity and the rapid growth of AI. Rather than succumbing to hype cycles, zk Crypto thrives on genuine computational needs.
This innovative ecosystem leverages Proof Pods to enable confidential AI execution, secure data validation, and personal identity management. Trust emerges from mathematical certainty in Zero Knowledge architecture, not from exposure.
As we advance, the next phase of blockchain innovation will see assets aligned with encrypted computation. The digital economy is evolving towards privacy, scalability, and verifiability. zk Crypto embodies the convergence of technological requirements and economic innovation.
This progression signifies a future where privacy and performance coexist harmoniously. Sensitive information can be managed responsibly, allowing digital systems to empower users rather than expose them. The trend toward privacy-first ecosystems is gaining momentum, signaling zk Crypto’s role in promoting secure, confidential, and computation-ready digital finance.
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NVIDIA GeForce GTX 1060 Mobile: Portable Gaming
Technology Explained
AI Testing Tools: Transforming Modern Software Testing
Introduction
Software Testing has evolved over the years from its traditional methods of Manual Testing and Automated Testing based on rules to AI-assisted testing tools. As applications increase in complexity and release cycles are shorter, many teams have turned to AI-based testing tools for increased quality, speed, and efficiency of their software.
Many testing tools use Machine Learning (ML), Data Analytics, and Intelligent Algorithms to automate test creation, optimize the execution of tests, and detect defects automatically and accurately so that engineers can deliver high-quality software with less manual effort.
What Are AI Testing Tools?
AI testing tools are software-based solutions that apply artificial intelligence and machine learning to various points in the software testing process. Artificial intelligence testing tools learn from experience by analysing the way a program operates, how it interacts with the user, the way it stores and retrieves data, and many more factors.
An AI testing tools will continue to learn and improve its testing decision-making capability over time based on the testing results it has recorded from previous applications. AI testing tools can be used in conjunction with traditional automation tools, as they offer a number of advantages over traditional testing tools when testing more complex applications, such as: Web Applications; Mobile Apps; Application Program Interfaces (APIs); and Microservices”.
AI testing tools are software solutions that use artificial intelligence, machine learning, and data analytics to improve the testing process. Unlike traditional testing methods, which rely heavily on human intervention, AI testing tools can learn from past test results and predict areas that may require attention. These tools can:
- Automatically Generate Test Cases: AI algorithms analyze application behavior and create test scenarios.
- Detect Bugs Early: AI identifies patterns and anomalies that humans might miss.
- Optimize Test Coverage: AI ensures that all critical areas of the application are tested efficiently.
- Reduce Manual Effort: Testers can focus on strategic tasks while AI handles repetitive work.
By integrating AI testing tools, companies can accelerate software release cycles without compromising quality.
Rise of AI Testing Tools: Transforming Modern Software Testing
AI testing tools have grown rapidly in recent years as software development becomes more complex. Traditional testing methods are often slow and require a lot of manual work. AI testing tools use artificial intelligence to analyze code, find bugs, and suggest improvements automatically. This rise in AI tools is changing the way companies test software, making the process faster and more accurate. More businesses are adopting AI testing because it saves time, reduces errors, and helps release software more confidently
Popular AI Testing Tools in the Market
1. Testim
Testim uses AI to automate functional and regression testing. It provides self-healing capabilities, meaning the tool can adjust to minor changes in the UI without breaking test scripts.
2. Applitools
Applitools focuses on visual AI testing, ensuring that the software’s UI looks correct across all devices and screen sizes. It uses machine learning to detect visual differences and layout errors.
3. Mabl
Mabl is a cloud-based AI testing platform that combines automated testing with machine learning. It offers features like auto-healing scripts, predictive analytics, and detailed test reports.
4. Functionize
Functionize uses natural language processing to allow testers to create test cases using plain English. Its AI engine helps detect functional defects and adapt tests automatically.
5. Selenium with AI Integration
While Selenium is a traditional testing tool, AI integrations can enhance it by improving test maintenance, generating intelligent test scripts, and predicting failure points.
How AI Is Used in Software Testing
AI enhances software testing in multiple ways:
1. Intelligent Test Case Generation
AI models analyze application workflows and automatically generate relevant test cases. This reduces human effort and ensures better test coverage, even for edge cases that testers may miss.
2. Self-Healing Test Automation
When UI elements or APIs change, AI-driven tools can automatically update test scripts without manual intervention. This significantly reduces test maintenance costs.
3. Predictive Defect Detection
By studying historical test failures and source code changes, AI tools can predict high-risk areas in an application, allowing teams to focus on critical test scenarios.
4. Smart Test Execution
AI tools optimize test execution by prioritizing important test cases based on impact, risk, and previous failures, helping reduce overall testing time.
Types of AI Testing Tools
AI testing tools can be broadly categorized into the following types:
1. AI-Powered Test Automation Tools
These tools enhance traditional automation by adding intelligence for test creation, maintenance, and execution.
2. AI-Based API Testing Tools
Focused on validating APIs, these tools automatically generate tests from API traffic, detect anomalies, and validate responses accurately.
3. Visual UI Testing Tools
AI compares visual elements across different browsers and devices to identify layout issues that conventional automation often overlooks.
4. Performance and Quality Intelligence Tools
These tools analyze system performance data and detect patterns that indicate potential failures or performance bottlenecks.
Benefits of Using AI Testing Tools
AI testing tools bring many advantages to software development. They can detect errors and issues faster than humans, which reduces the chances of releasing faulty software. These tools also help save time and cost because fewer people are needed for repetitive testing tasks. AI tools can run tests continuously and cover more scenarios, improving overall software quality. Additionally, they can learn from past tests, making future testing smarter and more efficient. Overall, AI testing tools make software development smoother, faster, and more reliable.
Using AI testing tools offers several advantages:
- Faster test execution and feedback cycles
- Reduced manual testing effort
- Improved test accuracy and coverage
- Lower maintenance for test scripts
- Early detection of defects
- Better software quality and reliability
These benefits make AI testing tools highly suitable for Agile and DevOps environments.
Role of AI Testing Tools
The main role of AI testing tools is to support software teams in finding and fixing problems quickly. They can automatically test different parts of an application, predict where errors might occur, and suggest fixes. These tools also help improve test coverage by checking parts of software that might be missed in manual testing. By reducing human effort on repetitive tasks, AI testing tools allow developers and testers to focus on more complex and creative work, improving the overall development process.
Challenges of AI Testing Tools
Despite their benefits, AI testing tools face some challenges. They can be expensive to implement for smaller companies. Some tools also require technical knowledge to set up and use properly. AI may not always understand complex software logic or unexpected user behavior, which can lead to missed errors. Another challenge is the need for high-quality data for the AI to learn effectively. Companies must carefully manage these challenges to make the most of AI testing tools.
Despite their advantages, AI testing tools also come with challenges:
- Initial setup and learning curve
- Dependency on quality data for accurate learning
- Limited transparency in decision-making
- Not a complete replacement for human judgment
AI testing should be used to assist testers, not replace them entirely.
Best Practices for Adopting AI Testing Tools
- Start with small pilot projects
- Combine AI testing with existing automation frameworks
- Continuously train models using real test data
- Maintain human oversight for critical testing decisions
- Evaluate tools based on project requirements
Tips for Implementing AI Testing Tools
- Identify Testing Goals: Understand which testing areas can benefit the most from AI, such as regression or UI testing.
- Choose the Right Tool: Evaluate tools based on features, ease of use, and integration with your existing workflows.
- Train Your Team: Provide proper training so your QA team can leverage AI effectively.
- Monitor AI Performance: Regularly review AI test results to ensure the tool is working accurately.
- Combine AI with Human Testing: While AI is powerful, human judgment is still crucial for usability and exploratory testing.
Future of AI in Software Testing
The future of AI in software testing is highly promising and continues to evolve rapidly as software systems become more complex and delivery timelines become shorter. With advancements in machine learning and data-driven models, AI testing tools are expected to become more autonomous, adaptive, and predictive. These tools will move beyond simple automation and start making intelligent decisions based on application behavior, historical test data, and user interactions.
In the coming years, AI-driven testing solutions will focus on predictive defect detection, allowing teams to identify high-risk areas in code before bugs reach production. Continuous testing will become more efficient as AI optimizes test execution, prioritizes critical test cases, and reduces redundant testing. Self-healing test scripts will further minimize maintenance efforts by adapting automatically to UI or API changes.
AI will also play a vital role in enhancing testing accuracy and coverage across modern architectures such as cloud-native applications, microservices, and APIs. By integrating seamlessly with Agile and DevOps pipelines, AI testing tools will help organizations deliver faster releases without compromising quality. Overall, AI will become a core component of next-generation software testing strategies.
Conclusion
AI testing tools are redefining how teams approach software quality. By automating complex tasks, predicting failures, and optimizing test execution, these tools enable faster and more reliable software releases. While challenges remain, the adoption of AI-driven testing is becoming essential for organizations building modern, scalable applications.
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