#Behavioral Analytics

[felixer-of-life]

The science of behavioral analytics is the framework that both dog training, and behavioral therapies work on. It's not just little kids either. You can train just about anyone if you know their preferred activities and treats. But like, don't do that without consent. Modifying someone's behavior without their consent is deeply unethical.

I want to apologize to my friends and family who have children for low key treating their kids like dogs but the standard methods for training dogs are even more effective of them because they actually understand language and are better at reasoning.

Positive reinforcement is amazingly effective, like I saw my nephew poking their cat so I sternly told him no, he stopped and I immediately changed my demeanor and cheerfully told him thank you and how happy I was that he listened to me instead of staying angry at him and he got this strange “Oh…It actually does make a difference wether I’m naughty or not” and later my sister in law asked why he’s so polite around me.

That’s literally what works best on dogs. Let them know when you don’t like what they’re doing but also let them know when you’re happy with them even if that means changing your demeanor on a dime (and even if you’re still a bit mad at them for doing it in the first place).

Oh and little treats. I skipped the aunt phase and is already turning into a grandma who has candy in her pockets for the kiddos for good behavior.

[leonbasinwriter]

AI-Driven Cybersecurity: Protecting Education from Breaches

By Leon Basin | Alumnus, Santa Clara University Leavey School of Business | Bridging Academic Rigor & Real-World Cybersecurity Executive Summary 2025 Education Cyberattack Snapshot In 2025, 56% of U.S. school districts suffered cyber breaches—many stemming from compromised privileged accounts (K12 SIX). With K-12 breach costs averaging $4.45M per incident (IBM), institutions must act…

[philomathresearch]

Customer Research Unplugged: Innovative Engagement Tips

Discover innovative strategies to deeply understand your audience, engage effectively, and drive customer experiences with customer research. For more detail visit here: https://www.philomathresearch.com/blog/2025/02/17/customer-research-unplugged-innovative-strategies-to-understand-and-engage-your-audience/

[felixer-of-life]

In the professional behavioral world they're called token economies! And they are Incredibly Good. Positive reinforcement builds behavioral pathways like using a laser cutter.

i literally love when people realize positive reinforcement works like yes its so silly isnt it. but it literally works humans love juice reward too

[huffmanirrellco]

Huffman Irrell Co. How to Improve Your Debt Collection Success Rate with Data Analytics

In today's fast-paced digital world, debt collection is becoming increasingly complex. However, by leveraging data analytics, companies can dramatically enhance their success rates. Huffman Irrell Co. recognizes the importance of data-driven decision-making in transforming the debt collection process. By employing data analytics, collection agencies can not only streamline their operations but also increase the likelihood of recovering debts promptly. This blog explores the key ways data analytics can revolutionize debt collection practices, offering insights that can benefit companies of all sizes.

Leveraging Predictive Analytics to Identify High-Risk Debtors

One of the key benefits of data analytics in debt collection is the ability to predict which accounts are at higher risk of defaulting. Huffman Irrell Co. uses predictive analytics to analyze historical payment behavior, credit scores, and other relevant data points. This allows them to prioritize efforts on high-risk accounts, ensuring resources are allocated efficiently. By identifying patterns that suggest a higher likelihood of delinquency, companies can act proactively to mitigate risk and improve collection outcomes.

Optimizing Collection Strategies Through Data Segmentation

Data analytics enables debt collection agencies to segment their accounts based on various factors such as payment history, debt size, and customer demographics. Huffman Irrell Co. uses this segmentation to tailor collection strategies for different groups. For instance, younger debtors with smaller debts may respond better to digital communication methods, while older debtors with larger debts may require a more personalized, traditional approach. This level of customization increases the chances of successful recovery while maintaining positive customer relationships.

Improving Customer Engagement with Behavioral Analytics

Behavioral analytics plays a significant role in refining debt collection practices. By analyzing data on how customers interact with different communication channels—whether it's emails, text messages, or phone calls—Huffman Irrell Co. can determine the most effective engagement strategies. This helps optimize the timing and frequency of contact, ensuring that customers are approached in ways that increase responsiveness. With behavioral insights, collection agencies can create more effective outreach campaigns, leading to improved collection rates.

Reducing Compliance Risks with Automated Data Analysis

Debt collection is a highly regulated industry, and non-compliance can result in hefty fines and legal complications. Data analytics can help agencies like Huffman Irrell Co. automate the monitoring of compliance with industry regulations. Automated data analysis ensures that all communication and collection efforts adhere to federal and state laws, reducing the risk of violations. By using data to track compliance metrics in real time, collection agencies can maintain high standards while avoiding costly mistakes.

Utilizing Performance Analytics to Enhance Collection Team Efficiency

Performance analytics can provide valuable insights into the effectiveness of a debt collection team's efforts. Huffman Irrell Co. tracks metrics such as call success rates, recovery amounts, and average time to close a case. This data helps managers identify areas where collectors excel and areas that need improvement. By leveraging these insights, teams can adjust their techniques, optimize workflows, and ultimately boost overall productivity and success rates in debt recovery.

[internet-marketing-stats-blog]

 Predicting Consumer Behavior with Data Analytics

Predicting the ever-evolving consumer behaviour is one of the biggest challenges faced by marketers around the world. Well, it has always been a challenging task, but today, it is even harder as consumers are constantly being exposed to new technologies, products and even new wants! With a plethora buying options to their disposal, today’s consumer behaviour flickers way too often. Now, thanks to the advent of e-commerce and mobile commerce, buying a product or service is not a simple task it used to be. As they say, ‘Choices make life more complex,’ buying a product or a service in the present era is accompanied by a lot of comparisons and checking out for deals. Businesses face the brunt of this as many a time, after spending a good deal of money to promote their products, customers often leave the product in the shopping cart – never to return!

While all this is heart-wrenching for the businesses who keep losing the sale to competitors, all hope is not lost. Smart marketers put their money on data analytics to best understand their consumer behaviour.

Marketing cannot happen in isolation – a mere positioning of product to a potential buyer is not going to make the sale. Converting an interested buyer into a customer, in the era of digital overexposure, requires a deeper scrutiny of users’ digital movements. This involves tracing the digital footprints of your prospective buyers with the help of smart and intuitive data analytics tools.

For More Information : https://www.dotcominfoway.com/blog/infographic-predicting-consumer-behavior-with-data-analytics/

[technorail-blog]

How can behavioral analytics increase conversion rates

In today’s highly competitive digital landscape, businesses are constantly seeking innovative strategies to boost their conversion rates and optimize user experiences. One such potent method is harnessing the power of behavioral analytics, coupled with comprehensive product insights. This dynamic duo not only provides a profound understanding of user behavior but also empowers companies to make informed decisions that can significantly enhance their conversion rates.

Behavioral analytics, often referred to as behavioral data analysis, is the process of studying user actions and interactions with a website, application, or digital product. By analyzing user behavior, businesses can identify patterns, preferences, and pain points that influence their decision-making processes. This invaluable information helps in tailoring strategies that resonate with users on a personal level, making it more likely for them to convert from casual browsers into loyal customers.

The integration of product analytics and behavioral analytics is where the real magic happens. A cutting-edge product analytics tool or product analytics software plays a pivotal role in collecting and organizing vast amounts of data generated by user interactions. This software, offered by analytic software companies, empowers businesses to delve into granular details of how users engage with their products.

By analyzing user behavior through the lens of product analytics, companies can uncover hidden insights that shape their offerings. These insights serve as a compass for refining user journeys, optimizing interfaces, and addressing pain points that might hinder conversions. A well-executed behavioral analytics strategy can reveal which product features resonate most with users, the pathways that lead to the highest conversion rates, and the precise moments where users might be dropping off from the conversion funnel.

Furthermore, behavioral analytics and product insights also play a crucial role in A/B testing and iterative improvements. By identifying which changes lead to improved user engagement and conversion rates, businesses can refine their strategies in real-time. This iterative approach ensures that decisions are based on concrete data rather than assumptions, making the optimization process more efficient and effective.

In summary, leveraging behavioural analytics and product insights can significantly increase conversion rates for businesses. By analyzing user behavior, product analytics tools enable analytic software companies to provide invaluable insights into user preferences and pain points. This collaborative approach empowers businesses to refine their strategies, optimize user experiences, and make data-driven decisions that directly impact their bottom line. In today’s digital landscape, the marriage of behavioral analytics and product insights is no longer a luxury; it’s a necessity for businesses aiming to thrive and succeed.

[felixer-of-life]

In behavioral analytics they've done So Much research about this. Punitives destroy stuff. Positive reaction reinforces very strongly. Punitive reinforces fear, increases maladaptive behaviors and prevents learning. Don't fuckin do it.

"Punishment works!!!" We're drowning in three to four generations of people so pants-shittingly terrified of ever being wrong that half of everyone has constructed a worldview wherein they never even consider the possibility that they could be wrong and the other half behaves like one wrong move will make anything or anyone explode violently into a million irreperable pieces. I don't think it works guys

[brigitoshaughnessy]

Share for larger sample to find out if we’re all weird. Mine is 149 right now.

[shimmerandfists]

Modern Au ViJinx thoughts:

Jinx exists in this universe as opposed to Powder but she's really a truer mix of the two than a direct 1:1 with Arcane's Jinx. She's closer to how Jinx was with Isha I think, still mentally ill but for the most part present and healthy, she has the tools to manage her symptoms for the most part.

She's been on the path of independence for a couple years now and at 19 she's antsy to move out of Vanders place. She's been relying less and less on Vi, Vander and Silco (everyone is alive at this point) as she gets older to the point she's making enough of her own money to save and buy things.

She doesn't have any real job of any kind but she's found under-the-table fix-it jobs for whoever needs it and pays the most. Unfortunately that usually ends up being shadier individuals, and has gotten her in trouble a couple times. She still hangs out with Ekko when they can. She helps him out with his college projects, even if it's his not-so-subtle way of trying to get her interested in going to college with him.

Vi is 23-24 (both the ages they are in the show) and has long since moved out. She's worked her way through an apprenticeship at a mechanics shop and has pretty steady work and income because of it. She tries her hardest to keep up her relationship with Jinx and drops just about everything to make time and space for her. Jinx hasn't asked for any of that in at least a year or two now. She keeps offering up her spare room to Jinx when she moves out but she hasn't gotten a solid answer from her yet.

Nobody has any clue what she does except for Vi, who bailed her out of jail the first and only time she got arrested. It may have been from a DUI she got for a party one of her clients invited her to when she first started working. She's the only one she would ever call if she needed anything at this point in her life even if she doesn't know how to talk with Vi like she used to.

She has her recently realized feelings for her older sister as well, she never really noticed them at all until Vi had moved out. Powder at the time was 15 and Vi was 20. Jinx didn't fully notice WHAT they were until she turned 17 and by then the space and time had changed their relationship. No matter how hard they both tried to keep it up, the fact was they both matured into different people they didn't fully recognize anymore. Neither think it's a bad thing, only that it's different and they don't know each other as well as they feel they used to.

With Vi living on her own and working a full time job, and with Jinx growing up and out into the world, it seemed inevitable. With more steady job leads popping up in the area where Vi had moved to, Jinx is starting to consider her sisters offer a little more seriously about the apartment room. Ultimately, she'd decide to get her own place but not too far away. Luck would have it that there was an apartment opening up in the same complex Vi was living at, a couple units down.

Vi is ecstatic about this and Jinx can't contain her enthusiasm either. The thought of spending time with each other was what both of them needed, they had really missed the other and there isn't anything like spending time in person to regrow lost connections. Vi was a little hurt at first Jinx declined her offer again but with how things worked out she doesn't hold on to that, and Jinx gets her own space while still being within bothering distance of Vi. They spend a stupid amount of their free time with each other, slotting back into each other's lives as if no time had passed at all.

That's about as far as I'm getting tonight but I'd love to explore this a little bit more later. With the flavor and depth and less of the foundation building. Like a detailed scene of Jinx' jail fiasco or some moments between the two when Jinx still lives at Vanders and Vi is in her own apartment. Future moments of them living in the apartment complex together, figuring out that in the process of getting to know each other again after that much time apart, they don't just love each other anymore. To both of their frustration, they're falling IN love with each other, and definitely in lust with each other.

Inspired by this edit: Flashing, Volume Warning

[queeraskae]

Sometimes, I still think back on how two years ago my therapist explained the functionality of the Four Basic Emotions to me, and what the required action was for each of them. It was MINDBLOWING. My life has been so much simpler since that day🥺❤️

[ego-sum-arbor]

Really not a fan of my dad’s tendency to go on about how autistic people statistically struggle with theory of mind and are therefore so callous and incapable of considering other people’s perspectives.

[sumechiayuu]

Society if Danganronpa fans realized that Toko isn't in love with Byakuya more so that she's in love with the idea of him, proven in how she straight up imagines things Byakuya would not say in any circumstance and Ultra Despair Girls where she fantasizes just that. A fantasy of how she wants Byakuya to be: the ideal man of her dreams:

[philomathresearch]

Customer Research Unplugged: Innovative Engagement Tips

Are you truly in tune with your audience? Do you know what keeps them up at night, what drives their decisions, and why they choose your brand over others? Customer research isn’t just a “nice-to-have” anymore—it’s the lifeblood of any business striving to stay ahead. And in the fast-paced, ever-changing world of today’s market, understanding your customer isn’t just about surveying them once a year. It’s about ongoing, real-time engagement and truly listening to their voices.

Imagine having the ability to read your customer’s mind. What if you could tap into their preferences, behaviors, and needs without guessing or assuming? Well, that’s what customer research can offer, and in this blog, we’ll dive deep into the latest, most innovative strategies to make sure you’re not just hearing your customers but understanding them in ways that drive real impact.

So, let’s start with a few questions to get the gears turning:

When was the last time you truly engaged with your customer on a personal level?

Have you ever analyzed customer behavior using data, or do you rely on intuition?

Do you know what motivates your customers to purchase or engage with your brand?

If these questions got you thinking, then it’s time to take a closer look at customer research—and how you can leverage innovative strategies to truly understand and engage your audience.

What is Customer Research and Why Does It Matter?

Customer research, at its core, involves gathering data and insights to understand customer behaviors, needs, and preferences. It’s about answering key questions like:

What do customers want?

What drives their buying decisions?

How can we improve their experience with our brand?

Businesses use customer research to develop better products, improve services, enhance customer satisfaction, and ultimately, boost sales. And here’s the kicker: companies that use customer insights effectively grow faster and build stronger customer loyalty. According to a report by McKinsey, businesses that integrate customer feedback into their strategy are 60% more likely to outperform competitors in terms of profitability and customer satisfaction.

But let’s face it: traditional methods of customer research—like surveys and focus groups—are evolving. The world is moving towards faster, more digital solutions, and businesses need to adapt.

Innovative Customer Research Strategies

So, what innovative strategies can you adopt to dive deeper into customer behavior and ensure you’re engaging your audience effectively? Let’s break it down.

1. Real-Time Feedback with Online Communities

Gone are the days when market research was conducted in isolation. Today, online communities have become a powerful tool for continuous, real-time customer engagement. These communities are groups of engaged customers who actively participate in sharing feedback, answering surveys, and discussing their experiences with your brand.

For instance, brands like Coca-Cola have turned to brand communities to shape their marketing strategies. Coca-Cola created a “Coca-Cola Creations” community where users can submit ideas, vote on new flavors, and provide real-time feedback on products. The result? A more loyal customer base, richer insights, and a greater sense of community.

Real-time feedback through online communities gives you the ability to capture immediate reactions, which allows you to make adjustments in real-time, whether it’s for a product, an ad campaign, or a service offering.

2. Social Listening and Sentiment Analysis

Another innovative approach to understanding your audience is through social listening. Social listening involves monitoring online conversations about your brand, products, or industry to understand customer sentiments and trends. Tools like Hootsuite or Brandwatch help businesses track customer feedback in real-time across platforms like Twitter, Facebook, and Instagram.

Here’s an example: Nike uses social listening to track conversations around athletic wear, sneakers, and even cultural trends. By tapping into customer sentiments, they can align their marketing efforts, respond to potential issues, and even identify emerging trends before their competitors.

With social listening, companies can make their marketing more personalized, reactive, and agile. It’s a strategy that enables brands to truly meet their customers where they are and provide immediate responses.

3. Behavioral Analytics: The Power of Data

What if you could track your customers’ every click, scroll, and purchase decision? Well, with behavioral analytics, you can. Unlike traditional surveys that ask customers about their opinions, behavioral analytics monitors real-time actions, giving you the full picture of how customers interact with your brand.

Amazon is a prime example. The company uses behavioral analytics to recommend products based on past purchases, browsing history, and even the time of day. These tailored recommendations are the result of continuous customer data analysis, which allows Amazon to predict future behavior with remarkable accuracy.

With tools like Google Analytics, Hotjar, and Mixpanel, businesses can track user journeys across websites and apps, identifying pain points, drop-off zones, and areas where customers are most engaged. This level of insight helps businesses refine their user experiences, boost conversions, and drive more targeted marketing campaigns.

4. Predictive Analytics and AI for Trend Spotting

Predictive analytics is one of the most futuristic customer research methods currently available. By using historical data and machine learning algorithms, businesses can predict future behavior with impressive accuracy. AI-powered tools can identify patterns and trends, which can help you stay ahead of the curve.

For example, Spotify uses predictive analytics to recommend playlists and songs based on user listening habits, even before the user knows they’ll like the track. Similarly, Netflix applies predictive algorithms to forecast what shows you’re most likely to watch, keeping you engaged and loyal to the platform.

Predictive analytics isn’t just about forecasting the future—it’s about making data-driven decisions today to improve the customer experience, optimize marketing strategies, and even develop new products that customers didn’t know they needed.

5. Customer Journey Mapping

Understanding your customer’s journey is key to improving their experience. Customer journey mapping involves visualizing the entire customer experience from the first point of contact with your brand all the way to post-purchase interactions. It helps businesses understand pain points, moments of delight, and areas for improvement.

For example, Zappos, the online shoe retailer, has mastered customer journey mapping. They track every step of the customer’s experience, from browsing shoes online to their delivery experience and even returns. This meticulous mapping has helped Zappos create an outstanding customer experience that leads to high levels of satisfaction and loyalty.

Mapping your customer’s journey isn’t just a one-time exercise. It’s an ongoing process that should evolve with customer expectations and market trends.

6. Interactive Surveys and Gamification

Traditional surveys can often feel like a chore, but what if they were fun, engaging, and interactive? That’s where gamification comes in. By turning surveys into a game-like experience, you can capture your customers’ attention and get more detailed responses.

A great example of this comes from Starbucks. The coffee giant regularly uses gamified loyalty programs to engage with customers and encourage repeat purchases. Customers earn rewards and can even unlock achievements by participating in surveys or taking actions that align with Starbucks’ business goals.

Gamifying surveys makes them feel less like a task and more like a reward, leading to better participation rates and more meaningful data.

7. Personalized Email and Mobile Surveys

Not all customers are the same, and today’s businesses must treat each customer as an individual. Personalized email and mobile surveys leverage customer data to tailor surveys to individual preferences and behaviors, making the survey feel more relevant and timely.

For instance, Airbnb sends personalized surveys to customers based on their recent bookings and experiences. These surveys ask questions related to the specific listing or service they used, which increases the likelihood of detailed and actionable feedback.

By sending personalized surveys, businesses not only gather more useful data, but they also show customers that their opinions truly matter.

8. Ethnographic Research: The Deep Dive

Ethnographic research is about immersing yourself in your customers’ world. It’s a qualitative approach where researchers spend time observing and interacting with customers in their natural environment to gain deeper insights into behaviors, attitudes, and motivations.

Conclusion: The Future of Customer Research

In a world where customer preferences are constantly shifting, relying on traditional customer research methods is no longer enough. Brands that leverage innovative strategies—whether it’s real-time feedback, predictive analytics, or gamified surveys—will have a competitive edge in understanding and engaging their audiences.

The key takeaway here is that customer research is a continuous, evolving process. You must adapt to changing technologies, customer expectations, and market conditions. By embracing these innovative strategies, you’ll not only gain a deeper understanding of your audience but also create more personalized, impactful experiences that drive business success.

As you embark on your next customer research project, think of it not as an isolated task but as a strategic, ongoing initiative that empowers you to understand, engage, and ultimately delight your customers in new and exciting ways.

Ready to unlock the full potential of your customer research? Let’s dive deeper together with Philomath Research—we’re here to help you make data-driven decisions that transform your business.

FAQs

What is customer research, and why is it important?

Customer research involves gathering data to understand customer behaviors, needs, and preferences. It’s crucial because it allows businesses to make informed decisions, improve customer satisfaction, develop better products, and drive growth. Effective customer research helps businesses stay competitive by aligning their offerings with what customers truly want.

2. How can online communities help in customer research?

Online communities provide a space for customers to share feedback, ideas, and experiences in real time. This continuous engagement offers valuable insights that allow businesses to adjust their strategies, improve products, and increase customer loyalty. Coca-Cola’s “Coca-Cola Creations” community is a great example of how businesses can tap into real-time feedback for better brand engagement.

3. What is social listening, and how can it benefit my business?

Social listening involves monitoring social media conversations about your brand or industry to understand customer sentiments and trends. By analyzing online conversations, businesses can gain insights into customer opinions, identify potential issues, and spot emerging trends. Brands like Nike use social listening to stay ahead of the curve and refine their marketing strategies based on customer feedback.

4. How does behavioral analytics help in customer research?

Behavioral analytics tracks customer actions, such as clicks, scrolls, and purchases, to understand how customers interact with your website, apps, or services. Unlike traditional surveys, this data gives you a clearer picture of customer behavior in real-time. Amazon uses behavioral analytics to personalize product recommendations based on user history, which enhances customer experience and increases sales.

5. What is predictive analytics, and how can it improve customer research?

Predictive analytics uses historical data and machine learning to forecast future customer behavior. It helps businesses anticipate trends, optimize marketing strategies, and develop products that meet future demand. Companies like Netflix and Spotify use predictive analytics to offer personalized recommendations, keeping customers engaged and loyal.

6. What is customer journey mapping, and why is it important?

Customer journey mapping visualizes the entire experience a customer has with your brand, from initial contact to post-purchase. By mapping each touchpoint, businesses can identify pain points, opportunities for improvement, and areas where they can enhance the customer experience. Zappos, for example, uses journey mapping to ensure a seamless experience from browsing to delivery.

7. How can gamification improve survey participation and data quality?

Gamification turns surveys into engaging, game-like experiences, making them more fun and interactive for customers. This approach encourages higher participation rates and generates more detailed responses. Starbucks uses gamified loyalty programs to boost customer engagement, rewarding them for completing surveys and participating in brand activities.

8. What is the benefit of personalized surveys?

Personalized surveys tailor the questions and experience based on customer data, making them more relevant and timely. By targeting specific customer preferences and behaviors, businesses can gather more actionable insights. For example, Airbnb sends personalized surveys based on customers’ recent bookings to gather more detailed feedback on their experiences.

9. What is ethnographic research, and how can it improve my understanding of customers?

Ethnographic research involves observing and interacting with customers in their natural environment to gain deeper insights into their behaviors, attitudes, and motivations. This qualitative approach helps businesses design products or services that closely match customers’ real-world needs. IKEA is known for conducting ethnographic studies to better understand how people use their furniture in their homes.

10. How can Philomath Research help my business with customer research?

Philomath Research specializes in innovative customer research strategies that help businesses understand and engage their audiences. We use advanced tools like behavioral analytics, social listening, and real-time feedback mechanisms to provide actionable insights that drive business success. Contact us to learn how we can help your business gather meaningful data and make data-driven decisions.

[technorail-blog]

What is the difference between behavioral analytics and customer analytics

Behavioral analytics and customer analytics are two essential branches of data analysis that provide valuable insights into user interactions and preferences, enabling businesses to make informed decisions. Despite some overlap in their methodologies, these two approaches focus on distinct aspects of consumer behavior and play vital roles in enhancing product development and customer engagement strategies.

Behavioral Analytics: Behavioral analytics primarily analyze user behavior within digital platforms, applications, or websites. It centers on understanding how users interact with a product, including their actions, clicks, navigation paths, and engagement levels. This analysis uncovers patterns and trends in user behavior, providing businesses with actionable insights to optimize their products and user experiences.

One of the key tools in this realm is product analytics software, which empowers companies to gather and process vast amounts of behavioral data. This software tracks user actions, such as clicks, scrolls, and feature usage, to build a comprehensive picture of how users engage with a product. By utilizing behavioral analytics, businesses can identify pain points, track feature adoption, and make data-driven decisions to enhance the overall user experience.

Customer Analytics: On the other hand, customer analytics takes a broader approach by examining data related to customer characteristics, preferences, and interactions. It delves into demographic information, purchase history, feedback, and communication history to develop a comprehensive understanding of individual customers and segments. By leveraging these product insights, companies can tailor marketing strategies, personalize communication, and create products that resonate with specific customer groups.

Both behavioral analytics and customer analytics contribute to the overarching concept of product insights. However, product analytics primarily focuses on understanding how users engage with specific product features, aiming to enhance the product’s functionality and user experience. In contrast, customer analytics takes into account the holistic customer journey and aims to deepen customer relationships and loyalty.

In the realm of e-commerce, for instance, behavioral analytics might reveal that users tend to abandon their shopping carts at a certain point in the checkout process. This insight can prompt improvements to the checkout flow. Meanwhile, customer analytics might identify that a particular customer segment prefers eco-friendly products, leading to the creation of targeted marketing campaigns and new product offerings.

In conclusion, both behavioural analytics and Product analytics provide invaluable insights to businesses. Utilizing specialized tools like a product analytics tool helps companies make sense of behavioral data analysis and drive product enhancements while incorporating customer analytics ensures tailored marketing and improved customer relationships. By understanding the nuances and distinctions between these approaches, companies can develop more effective strategies for growth and customer satisfaction. Leading analytic software companies provide sophisticated solutions that aid in understanding user behavior intricacies.

[jcmarchi]

Beyond Security: How AI-Based Video Analytics Are Enhancing Modern Business Operations

New Post has been published on https://thedigitalinsider.com/beyond-security-how-ai-based-video-analytics-are-enhancing-modern-business-operations/

Beyond Security: How AI-Based Video Analytics Are Enhancing Modern Business Operations

AI-based solutions are becoming increasingly common, but those in the security industry have been leveraging AI for years—they’ve just been using the word “analytics.”  As businesses seek new ways to use AI to create a competitive advantage, many are beginning to recognize that video devices represent an increasingly valuable data source—one that can generate actionable business intelligence insights. As processing power improves and chipsets become more advanced, modern IP cameras and other security devices can support AI-powered analytics capabilities that can do far more than identify trespassers and shoplifters.

Many businesses are already leveraging AI-based analytics to improve efficiency and productivity, reduce liability, and better understand their customers. Video analytics can help enterprises identify ways to improve employee productivity and staffing efficiency, streamline the layout of stores, factories, and warehouses, identify in-demand products and services, detect malfunctioning or poorly maintained equipment before it breaks, and more. These new analytics capabilities are being designed with business intelligence and operational efficiency in mind—and they are increasingly accessible to organizations of all sizes.

The Growing Accessibility of AI in Video Surveillance

Analytics has always had clear applications in the security industry, and the evolution from basic intelligence and video motion detection to more advanced object analytics and deep learning has made it possible for modern analytics to identify suspicious or criminal behavior or to detect suspicious sounds like breaking glass, gunshots, or cries for help. Today’s analytics can detect these events in real time, alerting security teams immediately and dramatically reducing response times. The emergence of AI has allowed security teams to be significantly more proactive, allowing them to make quick decisions based on accurate, real-time information. Not long ago, only the most advanced surveillance devices were powerful enough to run the AI-based analytics needed to enable those capabilities—but today, the landscape has changed.

The advent of deep learning processing units (DLPUs) has significantly enhanced the processing power of surveillance devices, allowing them to run advanced analytics at the network edge. Just a few years ago, the bandwidth and storage required to record, upload, and analyze thousands of hours of video could be prohibitively expensive. Today, that’s no longer the case: modern devices no longer need to send full video recordings to the cloud—only the metadata necessary for classification and analysis. As a result, the bandwidth, storage, and hardware footprint required to take advantage of AI-based analytics capabilities have all dramatically decreased—significantly reducing operational costs and making the technology accessible to businesses of all sizes, whether they employ a network of three cameras or three thousand.

As a result, the range of potential customers has expanded significantly—and those customers aren’t just looking for security applications, but business ones as well. Since DLPUs are effectively standard on modern surveillance devices, customers are increasingly looking to leverage those capabilities to gain a competitive advantage in addition to protecting their locations. The democratization of AI in the security industry has led to a significant expansion of use cases as developers look to satisfy businesses turning to video analytics to address a wider range of security and non-security challenges.

How Organizations Are Using AI to Enhance Their Operations

It’s important to emphasize that part of what makes the emergence of more business-focused use cases for AI-based video analytics notable is the fact that most businesses are already familiar with the basic technology. For example, retailers already using video analytics to protect their stores from shoplifters will be delighted to learn that they can use similar capabilities to monitor customers entering and leaving the store, identify high- and low-traffic periods, and use that data to adjust their staffing needs accordingly. They can use video analytics to alert employees when a lengthy queue is forming, when an empty shelf needs to be restocked, or if the layout of the store is causing unnecessary congestion. By embracing business-focused analytics alongside security-focused ones, retailers can improve staffing efficiency, create more effective store layouts, and enhance the customer experience.

Of course, retailers are just the tip of the iceberg. Businesses in nearly every industry can benefit from modern video analytics use cases. Manufacturers, for example, can monitor factory floors to identify inefficiencies and choke points. They can use thermal cameras to detect overheating machinery, allowing maintenance personnel to address problems before they can cause significant damage. In many cases, they can even monitor assembly lines for defective or poorly made products, providing an additional layer of quality assurance protection. Some devices may even be able to monitor for chemical leaks, overheating equipment, smoke, and other signs of danger, saving organizations from potentially dangerous (and costly) incidents. This has clear applications in industries ranging from manufacturing and healthcare to housing and critical infrastructure.

The ability to generate insights and improve operations extends beyond traditional businesses and into areas like healthcare. Hospitals and healthcare providers are now leveraging analytics to engage in virtual patient monitoring, allowing them to have eyes on their patients on a 24-hour basis. Using a combination of video and audio analytics, they can automatically detect signs of distress such as coughing, labored breathing, and cries of pain. They can also generate an alert if a high-risk patient attempts to leave their bed or exit the room, allowing caregivers or security teams to respond immediately. Not only does this improve patient outcomes, but it can also significantly reduce liability on slip/trip/fall cases. Similar technology can also be used to improve compliance outcomes, ensuring emergency exits remain clear and avoiding other potentially finable offenses in healthcare and other industries. The opportunities to reduce costs and improve outcomes are expanding every day.

Maximizing AI in the Present and Future

The shift toward leveraging surveillance devices for business intelligence and operations purposes has happened quickly, driven by the fact that most organizations are already familiar with the equipment they need to take advantage. And with businesses of all sizes—and in nearly every industry—increasingly turning to video analytics to enhance both their security capabilities and their business operations, the development of new, AI-based analytics is unlikely to slow anytime soon.

Best of all, the market is still growing. Even today, roughly 80% of security budgets are spent on human labor, including monitoring, guarding, and maintenance capabilities. As AI-based video analytics become increasingly widespread, that will change quickly—and businesses will be able to streamline their business intelligence and operations capabilities in a similar manner. As AI development continues and new, business-focused use cases emerge, organizations should ensure they are positioned to get the most out of analytics—both now and into the future.