In our rapidly evolving digital landscape, spam messages have become ubiquitous, infiltrating our inboxes and often disrupting our daily communications. Artificial intelligence (AI) stands at the forefront of combating this issue, particularly in text message spam scoring and filtering. While AI brings many advantages to this arena, it is not without challenges, particularly concerning false positives and their impact on brands. This blog post delves into these challenges while maintaining an optimistic perspective on AI's role in curbing spam, focusing on the importance of model updates and approved change preservation.


1. The Risk of False Positives and Brand Impact

A significant hurdle in AI-driven spam filters is the frequency of false positives. When genuine messages are incorrectly marked as spam, it can have severe repercussions for brands, disrupting customer engagement and tarnishing reputations. This is particularly true for businesses where digital communication is a lifeline.

Spammers are constantly refining their strategies to outsmart spam filters. This necessitates AI systems that are not just responsive but also proactive in learning new patterns and adapting to evolving spam tactics.

For AI to effectively identify spam, it needs access to large volumes of data, which can raise privacy concerns. Users may be wary of how their data is being used and whether their communications are being monitored.


Rethinking Spam Filtering for Verified Brands

One of the most significant challenges in AI-driven spam filtering is the risk of false positives. When legitimate messages from verified brands are incorrectly flagged as spam, it disrupts communication and potentially harms the brand-customer relationship.

A less stringent spam filter could be applied to text messages from brands that have undergone a registration and verification process. This approach presumes that verified entities are less likely to abuse messaging systems. However, this system must be dynamic, adjusting the level of scrutiny based on user feedback and complaints.

3. User Protection and Complaints-Based Adjustment

User protection remains paramount. Suppose a registered brand begins to receive complaints about the nature of its messages. In that case, the AI system should be capable of dynamically increasing that brand's spam filtering level, ensuring users are protected from potential spam.


Benefits of a Verification-Based Approach

By tailoring spam filtering based on verification status and complaint history, AI systems can significantly reduce false positives, ensuring that important and wanted messages reach the user.

2. Encouraging Responsible Messaging by Brands

This approach incentivizes brands to maintain high-quality, relevant messaging to avoid complaints and subsequent stricter spam filtering.

A system that adjusts its filtering based on transparent criteria (like verification status and user feedback) can increase trust among users and brands.


To effectively implement this approach, several key steps must be taken:

1. Ongoing Improvement and Change Preservation

Constantly updating and refining AI algorithms is crucial. Importantly, these updates should preserve previously approved changes to avoid redundant approvals and ensure consistent performance.

The effective operation of AI systems necessitates the integration of dynamic algorithms and continuous learning. These systems should possess the sophistication to dynamically adjust their filtering levels based on real-time feedback and complaint data. Concurrently, they must undergo regular updates and training with new data to maintain their effectiveness. This ongoing process should include preserving previously approved changes to ensure that advancements are not negated. Such a blend of dynamic adaptability and continuous learning is crucial for minimizing false positives and effectively adapting to evolving and sophisticated challenges, like spam strategies.

Users should be able to override default settings, allowing them to personalize their spam filtering preferences.


Conclusion: A Forward-Thinking Approach to Spam Management

In conclusion, while the challenges of using AI in text message spam filtering, such as the risk of false positives and privacy concerns, are significant, they are not insurmountable. Implementing a verification-based approach and ongoing model updates offers a promising solution. This strategy reduces false positives by tailoring spam filtering for verified brands, encourages responsible messaging, and builds trust. The dynamic nature of AI algorithms, coupled with continuous learning and user feedback integration, ensures adaptability to evolving spam tactics while preserving user control and transparency. Ultimately, the right balance of AI innovation and strategic implementation can significantly enhance our digital communication landscape by effectively curbing spam without compromising legitimate messaging.

Navigating the Challenges and Embracing the Potential of AI in Text Message Spam Filtering

In today’s digital environment, efficient and reliable communication methods are essential. Registered Business Messaging is a functional communication strategy that enhances the interaction between businesses and customers by enabling the automated dispatch of personalized messages.

Registered Business Messaging effectively delivers essential information, updates, and promotional content, improving customer engagement and satisfaction. It transforms standard alerts and notifications into more interactive and appreciated messages, enhancing customer relationships and loyalty.

Registered Business Messaging plays a significant role in improving operational productivity by automating various communication processes. It helps businesses focus on broader strategic objectives by reducing manual tasks, improving consistency, and minimizing communication errors.

Registered Business Messaging provides tailored messaging solutions suitable for various industries:

Includes quick transaction alerts and anti-fraud notifications.

Covers appointment reminders and essential health tips.

Involves updates on orders and promotional offers.

Includes booking confirmations and travel updates.

Registered Business Messaging assists in the secure transmission of messages by adhering to stringent security protocols and regulations, safeguarding sensitive business and customer information.

Registered Business Messaging is vital in improving business communication strategies, ensuring enhanced customer experiences and operational efficiency. Adopting Registered Business Messaging is a strategic decision to leverage technology to improve communication effectiveness and results.

The Effectiveness of Registered Business Messaging in Modern Communication

Have you noticed a drop in answered calls from your customers lately? Your business number could very well be flagged as SPAM by network carriers and SPAM filtering third-party services and apps. Numbers that are flagged may even be displayed as “SPAM LIKELY”, “SPAM RISK” or “SCAM LIKELY” to your customers before they answer your call.

Why are my numbers being flagged as SPAM?

Every time your business makes a call to a potential or existing customer, the customer’s phone carrier matches your number against a list of numbers they’ve determined to be SPAM numbers. Numbers are added to this list based on their history, customer complaints and other analytics from scam ID technologies.

Some common reasons that numbers are flagged as SPAM include:

1. A high volume of outbound calls per day by a single number

Carrier’s analytics software can’t always detect whether a number is legitimate or from a robot. The higher the volume of calls from a number, the more suspicious it appears. Generally, more than 100 calls per day from a single number will be viewed as suspicious.

2. Somone reported a number to its carrier as SPAM

Unfortunately, more and more numbers are being reported as SPAM due to increases in spoofing. Spoofing is when a caller disguises their caller ID as coming from a local number or company that the recipient may trust. Robocallers may be masking their identity under the name of your business, lowering the chance of customers accepting your calls.

If your numbers’ outbound caller IDs have not been correctly set, they could likely be flagged automatically as spam by carriers’ SPAM detection algorithms.

Carriers also have various features and apps that are automatically enabled on mobile devices to display incoming call numbers that have been previously reported for SPAM as “Scam Likely”.

In some cases, customers may also opt-in to extra protective features that prevent calls flagged as “Scam Likely” from even reaching their phone.

Unfortunately, these lists of “SPAM” numbers reported are Carrier-specific. There is no central body or service that oversees number designation, which can make getting a number unflagged not such a straightforward process.

How to keep your numbers from being labeled as SPAM

The best way to keep your numbers from being incorrectly marked as SPAM is by being proactive. Businesses can get their number whitelisted among the top U.S carriers (AT&T, T-Mobile and Verizon) by registering their numbers with the 

. By registering, businesses are often able to avoid having their numbers flagged as SPAM for the three reasons mentioned above.

 is also another great way to make sure your numbers aren’t incorrectly labeled as SPAM and boost your answer rate. Verified calling gives your customers the confidence to know it’s really you on the other end by including built-in branding, a verification badge and your reason for calling.

How to get your SPAM labeled numbers unflagged

As mentioned above, each Carrier and third-party SPAM blocking service/app has its own list of numbers marked as SPAM. Use the following links to register your numbers with these carriers and services and appeal to have incorrectly flagged or blocked numbers unflagged or unblocked.

https://hiyahelp.zendesk.com/hc/en-us/requests/new?ticket_form_id=824667


Robokiller is used by millions to block spam callers. Once a number is reported by a single user, it will be automatically be blocked from all other users. Email their support to unflag your number. support@robokiller.com.


Nomorobo is another popular SPAM blocking app and winner of the FTC robocall challenge. To contact them, email reports@nomorobo.com.


Numbers on Icehook’s list are flagged as SPAM if they reach a risk level of 81-100.



Numbers on Truespam’s list are flagged as SPAM if they reach a score of over 60.


Build trust with your customers and boost your answer rate with verified calling. Our experts are ready to assist you with registration or any questions you may have.

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Navigating the Challenges and Embracing the Potential of AI in Text Message Spam Filtering

The Effectiveness of Registered Business Messaging in Modern Communication

Why your number shows up as SPAM (and how to fix it)

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