#automated data collection services

[itesservices]

Dive into the future of cost efficiency with automated web data collection. Discover how this cutting-edge technology is revolutionizing operations and driving significant savings. Let's explore the benefits together:

- Real-time insights for informed decision-making

- Time-saving automation for repetitive tasks

- Enhanced accuracy and reliability in data collection

Join the conversation and share your thoughts on the impact of data-driven strategies in reducing operational costs

[andrewleousa]

Unlock Efficiency With Automated Data Capture Solutions

Investing in automated data collection services helps streamline the data-gathering process. By partnering with Damco Solutions, you can achieve a significant competitive edge while lowering operational expenses. Entrusting us with automated data capture solutions empowers you to concentrate on strategic business activities and foster the growth of your company.

[andmineworlddigitalmarketing]

The Undeniable Benefits of AI Chatbots for Lead Generation in 2025

Forget being limited by business hours! AI chatbots offer 24/7 availability, acting as tireless representatives for your brand around the clock. Imagine a potential customer exploring your website late at night. Instead of encountering silence, they can engage in an immediate conversation with your chatbot, receiving instant answers and feeling valued. This constant presence ensures you never miss a crucial lead, regardless of time zone or schedule.

The Power of Instant Engagement

Imagine a potential customer landing on your website at any hour of the day. Instead of being greeted by a static page, they're met with a friendly, interactive chatbot ready to answer their questions instantly. This immediate engagement is a game-changer. Chatbots can:

Provide instant answers: Addressing visitor queries immediately reduces bounce rates and keeps potential leads engaged.

Qualify leads proactively: By asking targeted questions, chatbots can filter out unqualified visitors and identify those with genuine interest.

Offer personalized experiences: Based on user interactions, chatbots can tailor conversations and offer relevant information, increasing the chances of conversion.

Streamlining the Lead Generation Process

Traditional lead generation methods often involve manual data entry and delayed follow-ups. Chatbots automate and streamline this entire process, offering significant advantages:

24/7 Availability: Unlike human agents, chatbots work around the clock, capturing leads even when your team is offline.

Automated Data Collection: Chatbots seamlessly collect valuable contact information and insights into customer needs and preferences.

Seamless Integration: Modern chatbots can integrate with your CRM and marketing automation platforms, ensuring smooth data transfer and efficient follow-up.

Reduced Response Times: Quick responses demonstrate excellent customer service and prevent potential leads from losing interest.

Boosting Conversion Rates and Sales

By nurturing potential customers through interactive conversations, chatbots play a vital role in moving them down the sales funnel:

Guiding Customers: Chatbots can guide visitors through your website, highlighting key information and directing them towards relevant products or services.

Addressing Objections: By proactively answering common questions and concerns, chatbots can overcome potential roadblocks in the customer journey.

Scheduling Appointments: Chatbots can automate the process of scheduling demos or consultations, making it convenient for both your team and the potential lead.

Improving Lead Quality: By qualifying leads effectively, chatbots ensure your sales team focuses on prospects with a higher likelihood of conversion.

Data-Driven Insights for Continuous Improvement

The interactions chatbots have with website visitors generate a wealth of valuable data. Analyzing these conversations can provide crucial insights into:

Customer Pain Points: Identifying frequently asked questions and concerns helps you understand your audience better.

Content Gaps: Analyzing chatbot interactions can reveal areas where your website content may be lacking.

Marketing Effectiveness: Tracking which chatbot interactions lead to conversions helps you optimize your marketing campaigns.

Looking Ahead: Chatbots in the 2025 Landscape

In 2025, we can expect chatbots to become even more sophisticated, leveraging advancements in Natural Language Processing (NLP) and Artificial Intelligence (AI). This will lead to:

More Human-like Interactions: Chatbots will become even better at understanding and responding to complex queries.

Omnichannel Integration: Seamless chatbot experiences across websites, social media, and messaging apps will become the norm.

Hyper-Personalization: Chatbots will leverage data to deliver even more tailored and relevant interactions.

Conclusion

In the competitive digital landscape of 2025, businesses that embrace the power of chatbots for lead generation will gain a significant advantage. From instant engagement and streamlined processes to improved conversion rates and valuable data insights, the benefits are undeniable. It's time to move beyond traditional methods and unlock the full potential of conversational AI to fuel your business growth.

[adobeenterprice]

Abode Enterprise

Abode Enterprise is a reliable provider of data solutions and business services, with over 15 years of experience, serving clients in the USA, UK, and Australia. We offer a variety of services, including data collection, web scraping, data processing, mining, and management. We also provide data enrichment, annotation, business process automation, and eCommerce product catalog management. Additionally, we specialize in image editing and real estate photo editing services.

With more than 15 years of experience, our goal is to help businesses grow and become more efficient through customized solutions. At Abode Enterprise, we focus on quality and innovation, helping organizations make the most of their data and improve their operations. Whether you need useful data insights, smoother business processes, or better visuals, we’re here to deliver great results.

[jcmarchi]

CallMiner’s 2024 CX Landscape Report: AI Key to Customer Experience, But Costs Exceed Expectations

New Post has been published on https://thedigitalinsider.com/callminers-2024-cx-landscape-report-ai-key-to-customer-experience-but-costs-exceed-expectations/

CallMiner’s 2024 CX Landscape Report: AI Key to Customer Experience, But Costs Exceed Expectations

A new report reveals that while businesses view generative AI (GenAI) as a game changer for customer experience (CX), many struggle with the cost of implementation. The findings come from CallMiner’s 2024 CX Landscape Report, developed in collaboration with research firm Vanson Bourne, which surveyed 700 global CX leaders across industries including financial services, healthcare, retail, and technology.

According to the report, 87% of CX leaders see generative AI as essential for improving customer service. An even higher percentage, 91%, believe AI will optimize their CX strategies. However, despite this enthusiasm, 63% of respondents admitted that the financial investment required to implement AI technology has been higher than initially expected.

The Increasing Role of AI in Customer Experience

Over the past two years, AI has revolutionized how organizations approach CX, particularly in contact centers. AI is becoming central to how businesses streamline operations, enhance agent productivity, and personalize customer interactions.

The report highlights that 62% of organizations have already implemented some form of AI in their operations, while 24% are in the early stages of adoption. However, these early adopters are cautious, focusing on foundational AI applications that demonstrate quick returns on investment (ROI) before exploring more complex implementations.

In particular, organizations are adopting AI-driven automation to boost efficiency, with 44% of respondents using AI to streamline tasks and 43% deploying chatbots or recommendation systems to improve CX. By automating routine tasks, AI allows employees to focus on more strategic and creative problem-solving, a trend that 43% of respondents have embraced.

The Financial Challenges of AI Implementation

Although AI is seen as a critical driver of business success, the costs associated with its deployment have been a significant obstacle. In fact, 63% of CX leaders noted that AI implementation has been more expensive than anticipated. This includes not just the cost of acquiring and maintaining the technology, but also the resources required to train teams and integrate AI solutions effectively. Specifically, 42% of respondents cited the cost of maintaining an AI-supporting team, while 40% mentioned the time needed to train staff on the new technologies.

One of the major ongoing challenges is the difficulty of measuring ROI from AI investments. According to the report, 27% of CX leaders stated that they still don’t know how to gauge the success of their AI systems. Moreover, 37% of respondents struggled with determining which AI technology best suits their organization’s needs, though this figure shows a modest improvement from last year’s 44%.

Growing Confidence in AI, Fewer Fears

Interestingly, the survey indicates a growing confidence in managing AI, with the complexity of AI technology being less of a concern compared to previous years. Only 21% of respondents now consider AI too complicated, a notable drop from 31% in 2023. Additionally, worries about AI-related security and compliance risks are waning, with only 38% of leaders expressing concerns, down from 45% last year.

This reduction in AI-related fears is largely attributed to better education and increased awareness of AI’s potential. As organizations become more knowledgeable, they are increasingly confident about using AI to enhance CX without jeopardizing security or compliance.

AI as a Tool for Employee Empowerment

While some still fear that AI could replace jobs, the report paints a different picture. Instead of replacing human workers, 90% of organizations see AI as a means of empowering employees to reach their full potential. The majority of companies are using AI to handle repetitive, low-value tasks, freeing up employees to focus on more complex challenges.

This trend is further evidenced by the fact that 37% of organizations are adopting AI to increase their workforce’s capacity for high-level tasks. In many cases, AI is also being used to provide real-time guidance during customer interactions, with 46% of respondents reporting the use of AI-powered live support.

Additionally, 39% of organizations are turning to AI-driven scoring systems to evaluate both customer interactions and employee performance. This shift toward data-driven, objective evaluation methods is helping companies offer more unbiased assessments of their CX strategies and employee effectiveness.

Evolving Data Collection and Customer Feedback

As customer interactions spread across more channels, organizations are collecting vast amounts of data. However, the report notes that solicited customer feedback—gathered through surveys and reviews—has proven limited in scope. In contrast, unsolicited feedback from customer interactions, especially those in contact centers and social media, provides a more nuanced view of customer experience.

A growing number of organizations recognize the value of unsolicited feedback. The report shows that 64% of respondents are still primarily relying on solicited feedback, down from 71% in 2023 and 79% in 2022. In addition, 25% of organizations now collect an equal mix of solicited and unsolicited feedback, up from 20% the previous year.

This expanding data collection is driving the need for automated analysis. According to the report, 60% of organizations are using automation to process their customer data, a 5% increase from last year. By analyzing this data more efficiently, companies can uncover valuable insights that inform their CX strategies and drive improvements across the business.

Looking Ahead: Balancing AI’s Promise and Challenges

As the CX landscape continues to evolve, the CallMiner 2024 CX Landscape Report reveals a growing awareness of both the potential and challenges of AI. While the technology offers significant benefits, such as improved efficiency, greater personalization, and enhanced employee productivity, organizations must navigate the complexities of implementation and the financial costs that accompany it.

The key to success, according to CallMiner’s founder and CEO, Jeff Gallino, lies in balancing the promise of AI with practical and secure execution. Companies that can strike this balance will be well-positioned to capitalize on AI’s transformative potential in the contact center and beyond.

With 87% of organizations recognizing the importance of generative AI in CX, it is clear that this technology is set to play a pivotal role in shaping the future of customer experience. But as the report makes clear, businesses must be strategic in their approach, ensuring that they invest not only in the right technology but also in the people and processes that will drive long-term success.

For more detailed insights, readers can access the full CallMiner 2024 CX Landscape Report.

[tagxdata]

Data preparation for AI-fueled Geospatial Analysis

Its been ages since businesses, governments, researchers, and journalists are using satellite data that helps understand the physical world and take action. As the geospatial industry evolves, so are the ways in which geospatial professionals use data to solve problems. Satellite imagery contains information that is useful for data-related projects. That’s why we’re seeing the rise of AI and ML in this industry.

Geospatial intelligence provides geographical information and distribution of elements in a geographic space and is now an essential tool for everything, from national security to land use and planning to agriculture and a host of commercial and government functions.

AI and Computer Vision for Geospatial Analysis

Artificial intelligence (AI) is revolutionizing the field of geospatial analysis by providing advanced tools and techniques to process and analyze vast amounts of geospatial data. Geospatial data includes information about the Earth's surface, such as satellite imagery, aerial photographs, and geographic information systems (GIS) data.AI algorithms and computer vision techniques are used to extract meaningful insights from geospatial data. These technologies enable automated data processing, pattern recognition, and scalable analysis, significantly improving the efficiency and accuracy of geospatial analysis tasks.

One of the key advantages of using AI in geospatial analysis is the ability to process large volumes of data quickly. Traditional manual methods of analyzing geospatial data can be time-consuming and labor-intensive. AI-powered algorithms can analyze massive datasets in a fraction of the time, enabling faster decision-making and response.AI also enhances the accuracy of geospatial analysis by reducing human error and subjectivity. Computer vision algorithms can detect and classify objects in satellite imagery, such as buildings, roads, and vegetation, with high precision. This helps in various applications like urban planning, disaster response, and environmental monitoring. Below are a few applications of Geospatial AI which cater to many industries and use cases:

Object detection

One of the primary applications of AI and Computer Vision in geospatial and satellite imagery is object detection and recognition. Through deep learning algorithms, AI models can accurately identify and classify objects such as buildings, roads, vegetation, and water bodies in satellite images. This capability is crucial for urban planning, environmental monitoring, disaster response, and infrastructure development.

Classification

Another significant use case is land cover classification, which involves categorizing different land types based on satellite imagery. AI algorithms can analyze multispectral and hyperspectral data to identify land cover classes like forests, agricultural fields, urban areas, and water bodies. This information is vital for land management, ecological studies, and monitoring of changes in land use over time.

Anomaly detection

AI and Computer Vision also play a crucial role in change detection and anomaly detection in geospatial imagery. By comparing satellite images taken at different times, AI models can identify changes in the landscape, such as deforestation, urban expansion, or natural disasters. This helps in monitoring environmental changes, detecting illegal activities, and supporting disaster management efforts.

Furthermore, AI-powered image segmentation techniques enable the extraction of detailed information from geospatial imagery. For instance, semantic segmentation can accurately delineate different land cover classes within an image, while instance segmentation can identify and track individual objects or features of interest. These capabilities find applications in precision agriculture, infrastructure monitoring, and resource management.

Map better with Data preparation for Geospatial AI

Accurate training data is essential for geospatial AI applications to provide precise and reliable results to users. Geospatial AI involves analyzing and interpreting data related to geographic locations, such as maps, satellite imagery, and spatial databases. Training data acts as the foundation for training machine learning algorithms and models in geospatial AI systems. Here are the typical steps involved in data preparation for geospatial AI:

Data Collection

Data collection involves gathering relevant geospatial data from various sources. This can include satellite imagery, aerial photography, GIS databases, GPS data, sensor data, and user-generated content. The data collection process should align with the specific requirements of the geospatial AI application. For example, if the application involves mapping and navigation, data collection may focus on obtaining accurate and up-to-date map data, including road networks, points of interest, and traffic information. If the application is related to land use analysis, data collection may involve acquiring satellite imagery with land cover information. The goal is to collect a diverse and representative dataset that encompasses the geographical area of interest.

Data Curation

Data curation involves the process of cleaning, organizing, and preparing the collected geospatial data for training AI models. This step is crucial for ensuring the accuracy, consistency, and quality of the data. Data cleaning entails removing duplicate records, addressing missing or erroneous values, and handling outliers or noise present in the dataset. It may also involve standardizing the data formats, ensuring consistent coordinate systems, and resolving any inconsistencies or conflicts within the data. Additionally, data curation may involve preprocessing steps like rescaling or normalizing numerical attributes to facilitate effective model training. The goal of data curation is to create a refined and reliable dataset that is ready for subsequent analysis and model training.

Data Annotation

Data annotation is the process of labeling or tagging specific features or regions of interest within the geospatial data. It involves assigning semantic or spatial labels to the data to provide the necessary ground truth for training supervised AI models. In geospatial AI, annotation can encompass various tasks such as object detection, segmentation, classification, or tracking. For example, in satellite imagery, data annotation may involve marking buildings, roads, vegetation, or water bodies. In aerial imagery, it could involve labeling objects like vehicles, pedestrians, or buildings. The annotation process can be performed manually by human annotators with domain expertise or using automated tools in some cases. Data preparation services encompass various annotation techniques tailored to geospatial applications.

Point Annotation: Point annotation involves marking specific points or coordinates within geospatial data. It is commonly used for tasks that require pinpointing precise locations or points of interest. For example, annotating specific addresses, landmarks, or geographic coordinates enables accurate geocoding, location-based searches, or geofencing.

Image Classification : Image classification in geospatial AI enables tasks such as environmental monitoring, land use planning, infrastructure assessment, or change detection. It provides valuable insights and information by automatically categorizing and analyzing large volumes of geospatial data. Data annotation experts classify objects in images based on custom taxonomies, such as land, road, vehicles, residential properties, and more.

Conclusion

Data preparation plays a pivotal role in the success of geospatial AI applications, enabling accurate and reliable results in various geographic contexts. Geospatial AI relies on diverse and precise data, collected from various sources, to train models effectively. By emphasizing TagX's expertise in each step of the data preparation cycle, we demonstrate our ability to deliver high-quality geospatial AI solutions. Our proficiency in data collection, curation, and annotation ensures that the training data we provide is accurate, reliable, and tailored to meet the unique requirements of our clients. With our comprehensive data preparation process, we empower users to leverage geospatial AI effectively and achieve their goals with super-sharp results.

[rjzimmerman]

Excerpt from this story from the Inter Press Service:

A groundbreaking initiative to revolutionize global ocean observation is being launched this week at the UN Ocean Conference side event, aiming to enlist 10,000 commercial ships to collect and transmit vital ocean and weather data by 2035.

Known as “10,000 Ships for the Ocean,” the ambitious program seeks to vastly expand the Global Ocean Observing System (GOOS) by collaborating with the maritime industry to install state-of-the-art automated sensors aboard vessels that crisscross the globe’s waters.

“Ships have been observing the ocean for centuries, but today, we are scaling up with purpose and urgency,” said Joanna Post, Director of the Global Ocean Observing System at UNESCO’s Intergovernmental Oceanographic Commission (IOC), at a press conference. “What we want to do now is to create a win-win model for the shipping industry and the planet—providing useful data for forecasting and resilience, while helping optimize shipping routes and reduce risks.”

The initiative, backed by the World Meteorological Organization (WMO), France, and major shipping players, comes at a pivotal time as climate-driven disasters increasingly wreak havoc on vulnerable coastal communities. Observations from the ocean surface—ranging from temperature to salinity to atmospheric conditions—are critical for weather forecasts, early warning systems, climate models, and maritime safety.

“Ocean observations are not just a scientific endeavor. They are critical infrastructure for society,” said Post. “We need this data to understand climate change, predict extreme weather events, and respond to disasters. Yet the ocean remains vastly under-observed.”

Currently, only around 1,000 ships regularly collect and share data with scientific networks. The initiative aims to increase this number tenfold, mobilizing 10,000 vessels to provide near real-time ocean data that can be used to power the UN’s Early Warnings for All initiative, support the Global Greenhouse Gas Watch, and advance the goals of the UN Ocean Decade.

[mariacallous]

On February 10, employees at the Department of Housing and Urban Development (HUD) received an email asking them to list every contract at the bureau and note whether or not it was “critical” to the agency, as well as whether it contained any DEI components. This email was signed by Scott Langmack, who identified himself as a senior adviser to the so-called Department of Government Efficiency (DOGE). Langmack, according to his LinkedIn, already has another job: He’s the chief operating officer of Kukun, a property technology company that is, according to its website, “on a long-term mission to aggregate the hardest to find data.”

As is the case with other DOGE operatives—Tom Krause, for example, is performing the duties of the fiscal assistant secretary at the Treasury while holding down a day job as a software CEO at a company with millions in contracts with the Treasury—this could potentially create a conflict of interest, especially given a specific aspect of his role: According to sources and government documents reviewed by WIRED, Langmack has application-level access to some of the most critical and sensitive systems inside HUD, one of which contains records mapping billions of dollars in expenditures.

Another DOGE operative WIRED has identified is Michael Mirski, who works for TCC Management, a Michigan-based company that owns and operates mobile home parks across the US, and graduated from the Wharton School in 2014. (In a story he wrote for the school’s website, he asserted that the most important thing he learned there was to “Develop the infrastructure to collect data.”) According to the documents, he has write privileges on—meaning he can input overall changes to—a system that controls who has access to HUD systems.

Between them, records reviewed by WIRED show, the DOGE operatives have access to five different HUD systems. According to a HUD source with direct knowledge, this gives the DOGE operatives access to vast troves of data. These range from the individual identities of every single federal public housing voucher holder in the US, along with their financial information, to information on the hospitals, nursing homes, multifamily housing, and senior living facilities that HUD helps finance, as well as data on everything from homelessness rates to environmental and health hazards to federally insured mortgages.

Put together, experts and HUD sources say, all of this could give someone with access unique insight into the US real estate market.

Kukun did not respond to requests for comment about whether Langmack is drawing a salary while working at HUD or how long he will be with the department. A woman who answered the phone at TCC Management headquarters in Michigan but did not identify herself said Mirksi was "on leave until July." In response to a request for comment about Langmack’s access to systems, HUD spokesperson Kasey Lovett said, “DOGE and HUD are working as a team; to insinuate anything else is false. To further illustrate this unified mission, the secretary established a HUD DOGE taskforce.” In response to specific questions about Mirski’s access to systems and background and qualifications, she said, “We have not—and will not—comment on individual personnel. We are focused on serving the American people and working as one team.”

The property technology, or proptech, market covers a wide range of companies offering products and services meant to, for example, automate tenant-landlord interactions, or expedite the home purchasing process. Kukun focuses on helping homeowners and real estate investors assess the return on investment they’d get from renovating their properties and on predictive analytics that model where property values will rise in the future.

Doing this kind of estimation requires the use of what’s called an automated valuation model (AVM), a machine-learning model that predicts the prices or rents of certain properties. In April 2024, Kukun was one of eight companies selected to receive support from REACH, an accelerator run by the venture capital arm of the National Association of Realtors (NAR). Last year NAR agreed to a settlement with Missouri homebuyers, who alleged that realtor fees and certain listing requirements were anticompetitive.

“If you can better predict than others how a certain neighborhood will develop, you can invest in that market,” says Fabian Braesemann, a researcher at the Oxford Internet Institute. Doing so requires data, access to which can make any machine-learning model more accurate and more monetizable. This is the crux of the potential conflict of interest: While it is unclear how Langmack and Mirski are using or interpreting it in their roles at HUD, what is clear is that they have access to a wide range of sensitive data.

According to employees at HUD who spoke to WIRED on the condition of anonymity, there is currently a six-person DOGE team operating within the department. Four members are HUD employees whose tenures predate the current administration and have been assigned to the group; the others are Mirski and Langmack. The records reviewed by WIRED show that Mirski has been given read and write access to three different HUD systems, as well as read-only access to two more, while Langmack has been given read and write access to two of HUD’s core systems.

A positive, from one source’s perspective, is the fact that the DOGE operatives have been given application-level access to the systems, rather than direct access to the databases themselves. In theory, this means that they can only interact with the data through user interfaces, rather than having direct access to the server, which could allow them to execute queries directly on the database or make unrestricted or irreparable changes. However, this source still sees dangers inherent in granting this level of access.

“There are probably a dozen-plus ways that [application-level] read/write access to WASS or LOCCS could be translated into the entire databases being exfiltrated,” they said. There is no specific reason to think that DOGE operatives have inappropriately moved data—but even the possibility cuts against standard security protocols that HUD sources say are typically in place.

LOCCS, or Line of Credit Control System, is the first system to which both DOGE operatives within HUD, according to the records reviewed by WIRED, have both read and write access. Essentially HUD’s banking system, LOCCS “handles disbursement and cash management for the majority of HUD grant programs,” according to a user guide. Billions of dollars flow through the system every year, funding everything from public housing to disaster relief—such as rebuilding from the recent LA wildfires—to food security programs and rent payments.

The current balance in the LOCCS system, according to a record reviewed by WIRED, is over $100 billion—money Congress has approved for HUD projects but which has yet to be drawn down. Much of this money has been earmarked to cover disaster assistance and community development work, a source at the agency says.

Normally, those who have access to LOCCS require additional processing and approvals to access the system, and most only have “read” access, department employees say.

“Read/write is used for executing contracts and grants on the LOCCS side,” says one person. “It normally has strict banking procedures around doing anything with funds. For instance, you usually need at least two people to approve any decisions—same as you would with bank tellers in a physical bank.”

The second system to which documents indicate both DOGE operatives at HUD have both read and write access is the HUD Central Accounting and Program System (HUDCAPS), an “integrated management system for Section 8 programs under the jurisdiction of the Office of Public and Indian Housing,” according to HUD. (Section 8 is a federal program administered through local housing agencies that provides rental assistance, in the form of vouchers, to millions of lower-income families.) This system was a precursor to LOCCS and is currently being phased out, but it is still being used to process the payment of housing vouchers and contains huge amounts of personal information.

There are currently 2.3 million families in receipt of housing vouchers in the US, according to HUD’s own data, but the HUDCAPS database contains information on significantly more individuals because historical data is retained, says a source familiar with the system. People applying for HUD programs like housing vouchers have to submit sensitive personal information, including medical records and personal narratives.

“People entrust these stories to HUD,” the source says. “It’s not data in these systems, it’s operational trust.”

WASS, or the Web Access Security Subsystem, is the third system to which DOGE has both read and write access, though only Mirski has access to this system according to documents reviewed by WIRED. It’s used to grant permissions to other HUD systems. “Most of the functionality in WASS consists of looking up information stored in various tables to tell the security subsystem who you are, where you can go, and what you can do when you get there,” a user manual says.

“WASS is an application for provisioning rights to most if not all other HUD systems,” says a HUD source familiar with the systems who is shocked by Mirski’s level of access, because normally HUD employees don’t have read access, let alone write access. “WASS is the system for setting permissions for all of the other systems.”

In addition to these three systems, documents show that Mirski has read-only access to two others. One, the Integrated Disbursement and Information System (IDIS), is a nationwide database that tracks all HUD programs underway across the country. (“IDIS has confidential data about hidden locations of domestic violence shelters,” a HUD source says, “so even read access in there is horrible.”) The other is the Financial Assessment of Public Housing (FASS-PH), a database designed to “measure the financial condition of public housing agencies and assess their ability to provide safe and decent housing,” according to HUD’s website.

All of this is significant because, in addition to the potential for privacy violations, knowing what is in the records, or even having access to them, presents a serious potential conflict of interest.

“There are often bids to contract any development projects,” says Erin McElroy, an assistant professor at the University of Washington. “I can imagine having insider information definitely benefiting the private market, or those who will move back into the private market,” she alleges.

HUD has an oversight role in the mobile home space, the area on which TCC Management, which appears to have recently wiped its website, focuses. "It’s been a growing area of HUD’s work and focus over the past few decades," says one source there; this includes setting building standards, inspecting factories, and taking in complaints. This presents another potential conflict of interest.

Braesemann says it’s not just the insider access to information and data that could be a potential problem, but that people coming from the private sector may not understand the point of HUD programs. Something like Section 8 housing, he notes, could be perceived as not working in alignment with market forces—“Because there might be higher real estate value, these people should be displaced and go somewhere else”—even though its purpose is specifically to buffer against the market.

Like other government agencies, HUD is facing mass purges of its workforce. NPR has reported that 84 percent of the staff of the Office of Community Planning and Development, which supports homeless people, faces termination, while the president of a union representing HUD workers has estimated that up to half the workforce could be cut The chapter on housing policy in Project 2025—the right-wing playbook to remake the federal government that the Trump administration appears to be following—outlines plans to massively scale back HUD programs like public housing, housing assistance vouchers, and first-time home buyer assistance.

[wolfliving]

It starts with him

What was once a promise of technology to allow us to automate and analyze the environments in our physical spaces is now a heap of broken ideas and broken products. Technology products have been deployed en masse, our personal data collected and sold without our consent, and then abandoned as soon as companies strip mined all the profit they thought they could wring out. And why not? They already have our money.

The Philips Hue, poster child of the smart home, used to work entirely on your local network. After all, do you really need to connect to the Internet to control the lights in your own house?  Well you do now!Philips has announced it will require cloud accounts for all users—including users who had already purchased the hardware thinking they wouldn’t need an account (and the inevitable security breaches that come with it) to use their lights.

Will you really trust any promises from a company that unilaterally forces a change like this on you? Does the user actually benefit from any of this?

Matter in its current version … doesn’t really help resolve the key issue of the smart home, namely that most companies view smart homes as a way to sell more individual devices and generate recurring revenue.

It keeps happening. Stuff you bought isn’t yours because the company you bought it from can take away features and force you to do things you don’t want or need to do—ultimately because they want to make more money off of you. It’s frustrating, it’s exhausting, and it’s discouraging.

And it has stopped IoT for the rest of us in its tracks. Industrial IoT is doing great—data collection is the point for the customer. But the consumer electronics business model does not mesh with the expected lifespan of home products, and so enshittification began as soon as those first warranties ran out.

How can we reset the expectations we have of connected devices, so that they are again worthy of our trust and money? Before we can bring the promise back, we must deweaponize the technology.

Guidelines for the hardware producer

What we can do as engineers and business owners is make sure the stuff we’re building can’t be wielded as a lever against our own customers, and to show consumers how things could be. These are things we want consumers to expect and demand of manufacturers.

Control

Think local

Decouple

Open interfaces

Be a good citizen

1) Control over firmware updates.

You scream, “What about security updates!” But a company taking away a feature you use or requiring personal data for no reason is arguably a security flaw. 

We were once outraged when intangible software products went from something that remained unchanging on your computer, to a cloud service, with all the ephemerality that term promises. Now they’re coming for our tangible possessions.

No one should be able to do this with hardware that you own. Breaking functionality is entirely what security updates are supposed to prevent! A better checklist for firmware updates:

Allow users to control when and what updates they want to apply. 

Be thorough and clear as to what the update does and provide the ability to downgrade if needed. 

Separate security updates from feature additions or changes. 

Never force an update unless you are sure you want to accept (financial) responsibility for whatever you inadvertently break. 

Consider that you are sending software updates to other people’s hardware. Ask them for permission (which includes respecting “no”) before touching their stuff!

2) Do less on the Internet.

A large part of the security issues with IoT products stem from the Internet connectivity itself. Any server in the cloud has an attack surface, and now that means your physical devices do.

The solution here is “do less”. All functionality should be local-only unless it has a really good reason to use the Internet. Remotely controlling your lights while in your own house does not require the cloud and certainly does not require an account with your personal information attached to it. Limit the use of the cloud to only the functions that cannot work without it.

As a bonus, less networked functionality means fewer maintenance costs for you.

3) Decouple products and services.

It’s fine to need a cloud service. But making a product that requires a specific cloud service is a guarantee that it can be enshittified at any point later on, with no alternative for the user owner. 

Design products to be able to interact with other servers. You have sold someone hardware and now they own it, not you. They have a right to keep using it even if you shut down or break your servers. Allow them the ability to point their devices to another service. If you want them to use your service, make it worthwhile enough for them to choose you.

Finally, if your product has a heavy reliance on the cloud to work, consider enabling your users to self-host their own cloud tooling if they so desire. A lot of people are perfectly capable of doing this on their own and can help others do the same.

4) Use open and standard protocols and interfaces.

Most networked devices have no reason to use proprietary protocols, interfaces, and data formats. There are open standards with communities and software available for almost anything you could want to do. Re-inventing the wheel just wastes resources and makes it harder for users to keep using their stuff after you’re long gone. We did this with Twine, creating an encrypted protocol that minimized chatter, because we needed to squeeze battery life out of WiFi back when there weren’t good options.

If you do have a need for a proprietary protocol (and there are valid reasons to do so):

Document it. 

If possible, have a fallback option that uses an open standard. 

Provide tooling and software to interact with your custom protocols, at the very least enough for open source developers to be able to work with it. This goes for physical interfaces as much as it does for cloud protocols.

If the interface requires a custom-made, expensive, and/or hard-to-find tool to use, then consider using something else that is commonly available and off the shelf instead.

5) Be a good citizen.

Breaking paid-for functionality on other people’s stuff is inherently unethical. Consider not doing this! Enshittification is not a technical problem, it is a behavioral one. Offer better products that are designed to resist enshittification, and resist it yourself in everything you do.

Nothing forced Philips to do what they are doing: a human made a decision to do it. They could have just as easily chosen not to. With Twine’s server lock-in, at least we chose to keep it running, for 12 years now. Consider that you can still make a decent living by being honest and ethical towards the people who are, by purchasing your products, paying for your lifestyle. 

We didn’t get here by accident. Humans made choices that brought us to this point, and we can’t blame anyone for being turned off by it. But we can choose to do better. We can design better stuff. And we can choose not to mess things up after the fact.

We’re putting this into practice with Pickup. (We also think that part of an IoT reset is giving users the creative freedom of a general-purpose device.) If you’re looking for something better and our product can fill a need you have, consider backing us. We cannot claim to be perfect or have all of the answers, but we are absolutely going to try. The status quo sucks. Let’s do something about it.

Published October 15, 2023 By Jeremy Billheimer

[itesservices]

Automated data collection is transforming financial services by improving efficiency, reducing costs, and ensuring accurate data analysis. This approach enhances decision-making, minimizes errors, and drives profitability. Organizations leveraging automation gain a competitive edge, ensuring better returns on investment. Discover how embracing this innovative solution can elevate your financial operations while optimizing resources effectively. 

[andrewleousa]

Enhance Speed and Accuracy with Automated Data Capture Solutions

Enhance efficiency, accuracy, and speed with automated data capture solutions. Accelerate your decision-making and save a big deal on costs. Collaborate with Damco to experience the advantages of automated data collection solutions and streamlined data management excellence.

[spacetimewithstuartgary]

NASA payload aims to probe moon's depths to study heat flow

Earth's nearest neighboring body in the solar system is its moon, yet to date, humans have physically explored just 5% of its surface. It wasn't until 2023—building on Apollo-era data and more detailed studies made in 2011–2012 by NASA's automated GRAIL (Gravity Recovery and Interior Laboratory) mission—that researchers conclusively determined that the moon has a liquid outer core surrounding a solid inner core.

As NASA and its industry partners plan for continued exploration of the moon under Artemis in preparation for future long-duration missions to Mars, improving our understanding of Earth's 4.5-billion-year-old moon will help teams of researchers and astronauts find the safest ways to study and live and work on the lunar surface.

That improved understanding is the primary goal of a state-of-the-art science instrument called LISTER (Lunar Instrumentation for Subsurface Thermal Exploration with Rapidity), 1 of 10 NASA payloads flying aboard the next delivery for the agency's CLPS (Commercial Lunar Payload Services) initiative and set to be carried to the surface by Firefly Aerospace's Blue Ghost 1 lunar lander.

Developed jointly by Texas Tech University in Lubbock and Honeybee Robotics of Altadena, California, LISTER will measure the flow of heat from the moon's interior. Its sophisticated pneumatic drill will penetrate to a depth of 3 meters into the dusty lunar regolith.

Every half-meter it descends, the drilling system will pause and extend a custom-built thermal probe into the lunar regolith. LISTER will measure two different aspects of heat flow: thermal gradient, or the changes in temperature at various depths, and thermal conductivity, or the subsurface material's ability to let heat pass through it.

"By making similar measurements at multiple locations on the lunar surface, we can reconstruct the thermal evolution of the moon," said Dr. Seiichi Nagihara, principal investigator for the mission and a geophysics professor at Texas Tech. "That will permit scientists to retrace the geological processes that shaped the moon from its start as a ball of molten rock, which gradually cooled off by releasing its internal heat into space."

Demonstrating the drill's effectiveness could lead to more innovative drilling capabilities, enabling future exploration of the moon, Mars, and other celestial bodies. The science collected by LISTER aims to contribute to our knowledge of lunar geology, improving our ability to establish a long-term presence on the moon under the Artemis campaign.

Under the CLPS model, NASA is investing in commercial delivery services to the moon to enable industry growth and support long-term lunar exploration. As a primary customer for CLPS deliveries, NASA aims to be one of many customers on future flights. NASA's Marshall Space Flight Center in Huntsville, Alabama, manages the development of 7 of the 10 CLPS payloads carried on Firefly's Blue Ghost lunar lander.

IMAGE: LISTER (Lunar Instrumentation for Subsurface Thermal Exploration with Rapidity) is 1 of 10 payloads flying aboard the next delivery for NASA’s CLPS (Commercial Lunar Payload Services) initiative. The instrument is equipped with a drilling system and thermal probe designed to dig into the lunar surface. Credit: Firefly Aerospace

[jcmarchi]

Surojit Chatterjee, Founder and CEO at Ema – Interview Series

New Post has been published on https://thedigitalinsider.com/surojit-chatterjee-founder-and-ceo-at-ema-interview-series/

Surojit Chatterjee, Founder and CEO at Ema – Interview Series

Surojit Chatterjee is the founder and CEO of Ema. Previously, he guided Coinbase through a successful 2021 IPO as its Chief Product Officer and scaled Google Mobile Ads and Google Shopping into multi billion dollar businesses as the VP and Head of Product. Surojit holds 40 US patents and has an MBA from MIT, MS in Computer Science from SUNY at Buffalo, and B. Tech from IIT Kharagpur.

Ema is a universal AI employee, seamlessly integrated into your organization’s existing IT infrastructure. She’s designed to enhance productivity, streamline processes, and empower your teams.

Can you elaborate on the vision behind Ema and what inspired you to create a universal AI employee?

The goal for Ema is clear and bold: “transform enterprises by building a universal AI employee.” This vision stems from our belief that AI can augment human capabilities rather than replace workers entirely. Our Universal AI Employee is designed to automate mundane, repetitive tasks, freeing up human employees to focus on more strategic and valuable work. We do this through Ema’s innovative agentic AI system, which can perform a wide range of complex tasks with a collection of AI agents (called Ema’s Personas), improving efficiency, and boosting productivity across countless organizations.

Both you and your co-founder have impressive backgrounds at leading tech companies. How has your past experience influenced the development and strategy of Ema?

Over the last two decades, I’ve worked at iconic companies like Google, Coinbase, Oracle and Flipkart. And at every place, I wondered “Why do we hire the smartest people and give them jobs that are so mundane?.” That’s why we are building Ema.

Prior to co-founding Ema, I was the chief product officer of Coinbase and Flipkart and the global head of product for mobile ads at Google. These experiences deepened my technical knowledge across engineering, machine learning, and adtech. These roles allowed me to identify inefficiencies in the ways we work and how to solve complex business problems.

Ema’s co-founder and head of engineering, Souvik Sen, was previously the VP of engineering at Okta where he oversaw data, machine learning, and devices. Before that, he was at Google, where he was engineering lead for data and machine learning where he built one of the world’s largest ML systems, focused on privacy and safety – Google’s Trust Graph. His expertise, particularly, is a driving force to why Ema’s Agentic AI system is highly accurate and built to be enterprise ready in terms of security and privacy.

My cofounder Souvik and I thought what if you had a Michelin Star Chef in-house who could cook anything you asked for. You might be in the mood for French today, Italian tomorrow and Indian the day after. But irrespective of your mood or the cuisine you desire, that chef can recreate the dish of your dreams.  That’s what Ema can do. It can take on the role of whatever you need in the enterprise with just a simple conversation.

Ema uses over 100 large language models and its own smaller models. How do you ensure seamless integration and optimal performance from these varied sources?

LLM’s, while powerful, fall short in enterprise settings due to their lack of specialized knowledge and context-specific training. These models are built on general data, leaving them ill-equipped to handle the nuanced, proprietary information that drives business operations. This limitation can lead to inaccurate outputs, potential data security risks, and an inability to provide domain-specific insights crucial for informed decision-making. Agentic AI systems like Ema address these shortcomings by offering a more tailored and dynamic approach. Unlike static LLMs, our agentic AI systems can:

Adapt to enterprise-specific data and workflows

Leverage multiple LLMs based on accuracy, cost, and performance requirements

Maintain data privacy and security by operating within company infrastructure

Provide explainable and verifiable outputs, crucial for business accountability

Continuously update and learn from real-time enterprise data

Execute complex, multi-step tasks autonomously

We ensure seamless integration from these varied sources by using Ema’s proprietary 2T+ parameter mixture of experts model: EmaFusionTM. EmaFusionTM combines 100+ public LLMs and many domain specific custom models to maximize accuracy at the lowest possible cost for wide variety of tasks in the enterprise, maximizing the return on investment. Plus, with this novel approach, Ema is future-proof; we are constantly adding new models to prevent overreliance on one technology stack, taking this risk away from our enterprise customers.

Can you explain how the Generative Workflow Engine works and what advantages it offers over traditional workflow automation tools?

We’ve developed tens of template Personas (or AI employees for specific roles). The personas can be configured and deployed quickly by business users – no coding knowledge required. At its core, Ema’s Personas are collections of proprietary AI agents that collaborate to perform complex workflows.

Our patent-pending Generative Workflow Engine™, a small transformer model, generates workflows and orchestration code, selecting the appropriate agents and design patterns. Ema leverages well-known agentic design patterns, such as reflection, planning, tool use, multi-agent collaboration, language agent tree search (LATS), structured output and multi-agent collaboration, and introduces many innovative patterns of its own. With over 200 pre-built connectors, Ema seamlessly integrates with internal data sources and can take actions across tools to perform effectively in various enterprise roles.

Ema is used in various domains from customer service to legal to insurance. Which industries do you see the highest potential for growth with Ema, and why?

We see potential across industries and functions as most enterprises have less than 30% automation in processes and use more than 200 software applications leading to data and action silos. McKinsey & Co. estimates that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually in productivity gains (source).

These issues are exacerbated in regulated industries like healthcare, financial services, insurance where most of the last decades technical automations have not happened since the technology was not advanced enough for their processes. This is where we see the biggest opportunity for transformation and are seeing a lot of demand from customers in these industries to leverage Generative AI and technology like never before.

How does Ema address data protection and security concerns, especially when integrating multiple models and handling sensitive enterprise data?

A pressing concern for any company using agentic AI is the potential for AI agents to go rogue or leak private data. Ema is built with trust at its core, compliant with leading international standards such as SOC 2, ISO 27001, HIPAA, GDPR, NIST AI RMF, NIST CSF, NIST 800-171 To ensure enterprise data remains private, secure, and compliant, Ema has implemented the following security measures:

Automatic redaction and safe de-identification of sensitive data, audit logs

Real-time monitoring

Encryption of all data at rest and in transit

Explainability across all output results

To go the extra mile, Ema also checks for any copyright violations for document generation use cases, reducing customers’ chance of IP liabilities. Ema also never trains models on one customer’s data to benefit other customers.

Ema also offers flexible deployment options including on-premises deployment capabilities for multiple cloud systems, enabling enterprises to keep their data within their own trusted environments.

How easy is it for a new company to get started with Ema, and what does the typical onboarding process look like?

Ema is incredibly intuitive, so getting teams started on the platform is quite easy. Business users can set up Ema’s Persona(s) using pre-built templates in just minutes. They can fine tune Persona behavior with conversational instructions, use pre-built connectors to integrate with their apps and data sources, and optionally plug in any private custom models trained on their own data. Once set up, experts from the enterprise can train their Ema persona with just a few hours of feedback. Ema has been hired for multiple roles by enterprises such as Envoy Global, TrueLayer, Moneyview, and in each of these roles Ema is already performing at or above human performance.

Ema has attracted significant investment from high-profile backers. What do you believe has been the key to gaining such strong investor confidence?

We believe investors can see how Ema’s platform enables enterprises to use Agentic AI effectively, streamlining operations for substantial cost reductions and unlocking new potential revenue streams. Additionally, Ema’s management team are experts in AI and have the required technical knowledge and skill sets. We also have a strong track record of enterprise-grade delivery, reliability, and compliance. Lastly, Ema’s products are differentiated from anything else on the market, it is pioneering the latest technical advancements in Agentic AI, making us the go-to choice for any enterprise wanting to add next-generation AI to their operations.

How do you see the role of AI in the workplace evolving over the next decade, and what role will Ema play in that transformation?

Ema’s mission is to transform enterprises and help every employee work faster with the help of simple-to-activate and accurate agents. Our universal AI employee has the potential to help enterprises execute tasks across customer support, employee support, sales enablement, compliance, revenue operations, and more. We’d like to transform the workplace by allowing teams to focus on the most strategic and highest-value projects instead of mundane, administrative tasks. As a pioneer of agentic AI, Ema is leading a new era of collaboration between human and AI employees, where innovation flourishes, and productivity skyrockets.

Thank you for the great interview, readers who wish to learn more should visit Ema.

[stuarttechnologybob]

How Do Healthcare BPOs Handle Sensitive Medical Information?

Healthcare BPO Services

Handling sensitive and personal medical and health data is a top priority in the healthcare industry as it can be misused. With growing digital records and patient interactions, maintaining privacy and compliance is more important than ever and considered to be a tough role. This is where Healthcare BPO (Business Process Outsourcing) companies play a critical role.

As these providers can manage a wide range of healthcare services like medical billing, coding and data collection, claims processing and settlements, and patient on-going support, all while assuring the strict control over sensitive health information is maintained and carried out on the go.

Here's how they do it:

Strict Data Security Protocols -

Healthcare companies implement robust security frameworks to protect patient information and personal details that can be misused. This includes encryption, firewalls, and secure access controls. Only the concerned and authorized personnel can get the access towards the medical records and data, as all our available on the go all data transfers are monitored to avoid breaches or misuse.

HIPAA Compliance -

One of the primary and key responsibilities of a Healthcare BPO is to follow HIPAA (Health regulations policies and acts with standard set regulations). HIPAA sets the standards for privacy and data protection. BPO firms regularly audit their processes to remain compliant, ensuring that they manage patient records safely and legally.

Trained Professionals -

Employees working and the professionals in Healthcare services are trained and consulted in handling and maintaining the confidential data. They understand how to follow the strict guidelines when processing claims, speaking with patients, or accessing records. As this training reduces and lowers down the risk and potential of human error and assures professionalism is maintained at every step.

Use of Secure Technology -

Modern Healthcare BPO operations rely on secure platforms and cloud-based systems that offer real-time protection. Data is stored and collected in encrypted formats and segments, and advanced monitoring tools and resources are used to detect the unusual activity that prevent cyber threats or unauthorized access.

Regular Audits and Monitoring -

Healthcare firms conduct regular security checks and compliance audits to maintain high standards. These assist to identify and address the potential risks at the early stage and ensure all the systems are updated to handle new threats or regulations.

Trusted Providers in Healthcare BPO:

The reputed and expert providers like Suma Soft, IBM, Cyntexa, and Cignex are known for delivering secure, HIPAA-compliant Healthcare BPO services. Their expertise in data privacy, automation, and healthcare workflows ensures that sensitive medical information is always protected and efficiently managed.

[a-friend-of-mara]

If I had magic powers I would first [remove] [orange man] and [fascist x man]

After that i would make a line of blajah plushies that trans your gender while you cuddle them, it's completely non permanent and safe, takes like a week to have full effect, and will decay after a month, very safe, easy for trans kids to convince parents not to freak out, maybe some cis people will just become a different gender because they can try it for a summer or smthn idk

Then I'd make noise canclers that remove all sound waves so I can have portable quiet

I'd install a system that isn't capitalism because a system that values money above the people in the system is beyond stupid and put a system that values the people in the system first and foremost

I'd topple all the monopolies and elevate competition in the markets making companies actually deliver good products

Make subscription services heavily regulated so you never have to hear about a subscription for heated seats or a baby monitor *ever* agian

Make "we the people" mean "every living human"

Make glowing strawberries that give you the ability to double jump

Make internet access free

Make a system where everyone's basic necessities for life are free and you never have to work a day in your life if you don't want to which will provide people the motivation they need to create and discover the kinds of things we only see once in a decade

Legalize owning foxes as pets

Make land sharks (that are friendly unless you is transphobic)

Make teleporters because everyone has at least one friend that lives far away that they miss

Make "government mandated" nap/stargazing/quiet time for mental health reasons

Educate the masses about all the hateful stuff they've been told and probably internalized

Provide plushies to everybody so they have someone to hold when they feel low

Allow people to communicate with their pets

Obtain Philipee (a pet fox)

Hug Philipee

Make HRT that changes your height

Remove society's stigmas about a lotta things like mental health

Let humans fly but only one Thursdays and Saturdays, note because of this anyone who uses it will have an inexplicable urge to sing at the top of their lungs until they land

Make smartphones and personal computers able to capture an image of the thing you're thinking of (only with user permission) so you can come back to that idea later or so you don't loose it while you draw or write it down

Make diversity in government

Unify the planet

Make a railgun to shoot probes into space

Make death by any means other than old age reversible (and your brain won't start to deteriorate)

Automate only the jobs that are dangerous or that nobody wants to do

Make data privacy laws very very very in the consumers favor (to the point where collecting any data requires an opt in that is intentionally harder than an opt out)

Personally i think if there's no reason to steal and no reason to be desperate then crime will go down dramatically

[agolaaa]

2025 Digital Marketing Trends: What You Should Really Pay Attention To

If you’ve been paying even a little attention to digital marketing lately, you’ll know things are moving faster than ever. Platforms change, algorithms shift, and customer behavior keeps evolving. What worked last year might not work today—and what’s working today might be gone by next quarter.

It can feel a bit overwhelming, sure. But here’s the good news: if you stay curious and pay attention to the right trends, there’s huge opportunity to stand out. Whether you're already in the field or just starting your journey through the best digital marketing training institute in Calicut, understanding the pulse of 2025 gives you a major edge.

1. Welcome to the Age of Real-Time Experiences

Marketing is no longer just about putting content out there and hoping people see it. In 2025, it’s about responding while it’s happening—right in the moment.

Think live streams, interactive polls, flash deals during events, or even AI-powered chat assistants that talk to customers at midnight. Real-time engagement is now a core part of strategy, especially in e-commerce and service-based industries.

2. Storytelling > Hard Selling

Let’s be honest: people don’t like being sold to. At least, not directly. What they do love is a good story.

Brands that can wrap their message into a narrative—about a mission, a journey, a personal experience—are finding it much easier to connect with audiences. It’s not about pushing a product. It’s about pulling people in with emotion, relevance, and relatability.

3. AI Is Helping, But Human Creativity Still Wins

Everyone’s talking about artificial intelligence, and yes, it’s a big deal. It helps with automating repetitive tasks, generating ideas, and even scheduling campaigns. But here’s the kicker—it doesn’t replace creative thinking.

In fact, the best marketers right now are the ones who use AI as a tool, not a crutch. They let it handle the backend, while they focus on crafting bold ideas, unique angles, and messages that sound like they came from a real person.

4. The Death of the Third-Party Cookie is Real

Browser cookies—those tiny data files that track your every move online—are fading out. Privacy laws and consumer pushback have forced platforms to rethink how data is collected.

As a result, marketers are shifting focus to first-party data—info gathered directly from your audience via sign-ups, feedback forms, or gated content. This makes email marketing and CRM systems more important than ever.

5. Search Isn’t Just Google Anymore

Search engine optimization (SEO) isn’t just about ranking on Google. People are now “searching” on Instagram, YouTube, TikTok, Pinterest, and even LinkedIn.

Each platform has its own rules and algorithms. That means your content has to be optimized for where your audience hangs out, not just for traditional search engines. Understanding platform-specific search behaviors is a critical new skill.

6. Digital Marketing Is Becoming More Localized

While the internet connects the world, customers still care about what’s happening in their area. Hyperlocal marketing is on the rise, using geotargeting, local SEO, and community-focused campaigns.

If you're promoting a business or service, tailoring your strategy to a specific city, language, or even neighborhood can drastically improve engagement.

And yes, that includes people looking for the best digital marketing training institute in Calicut—they’re searching locally too.

7. Email Is Making a Comeback—With a Twist

It might surprise some, but email marketing is still one of the highest ROI channels around. The difference now is how emails are being written.

Gone are the boring newsletters. In their place? Story-style formats, curated content digests, and personalized emails that talk like a friend, not a corporation. A strong email list is a goldmine—if used right.

8. Your Personal Brand Matters More Than Ever

People trust people more than companies. Whether you’re a freelancer, job-seeker, or business owner, your personal brand is a major asset.

Being active on LinkedIn, sharing behind-the-scenes on Instagram, or even starting a blog can build credibility and open doors. Clients and employers now Google you before they hire or buy. Make sure they find something worth their time.

9. Short Learning Cycles Are Replacing Traditional Degrees

Here’s something that’s become crystal clear in 2025: you don’t need a 3-year degree to start working in digital marketing. What you need is skills, hands-on practice, and the ability to adapt quickly.

That’s why so many learners are choosing the best digital marketing training institute in Calicut instead of traditional routes. Institutes that focus on live projects, real tools, and actual industry challenges are the ones producing job-ready professionals.

10. Platforms Come and Go—But Strategy Stays

It’s easy to get caught up in whatever platform is trending this month. Threads today, TikTok tomorrow, something new next week. But if you know how to build a good campaign—identify an audience, craft a message, and choose the right timing—you can adapt to any platform.

The fundamentals are what set you apart. And that’s what solid training focuses on—not just learning tools, but understanding strategy.

Final Thoughts

Digital marketing in 2025 isn’t just about being online—it’s about being intentional, creative, and quick to adapt. The landscape will keep changing, but those who stay curious, keep practicing, and learn from the right sources will always stay ahead.

If you're someone thinking about breaking into this space, consider your options wisely. The best digital marketing training institute in Calicut won’t just give you certificates—they’ll give you confidence, clarity, and real-world skills that matter.

You don’t need to be a genius. You just need to start. And there’s never been a better time than now.