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How Virtual Reality Can Enhance Customer Experience Centers in a Post-COVID World



How Virtual Reality Can Enhance Customer Experience Centers in a Post-COVID World

Due to the challenging times the world is facing right now, we are seeing more and more companies look to alternative means to showcase and demonstrate products. 

One of the things that have been on the rise of late has been the Customer Experience Center or CEC for short. Brands are looking for creative ways to connect with their customers, and utilizing modern technology to showcase a company’s vision has tremendous benefits.

CEC’s have proven in recent years to be one of the most effective ways for brands to showcase their latest products and identify with customers in unique ways like never before.

Benefits of the CEC

One of the more effective ways of showcasing complex enterprise offerings or products is through a live and interactive demonstration. This is the core value of the CEC; being able to provide prospective customers with the “try it before you buy it” approach. This is especially true for cutting edge technology, many times in which executives and enterprise decision-makers haven’t even tried as of yet.

With virtual reality specifically, a vast majority of C-level executives haven’t used the medium in an enterprise training setting. A small sampling has tried it for gaming but just haven’t had the opportunity to gauge the effectiveness of VR for improved learning efficacy.

Enter the CEC VR demo, a chance to see first hand the power of using VR as a medium for knowledge enhancement. It is one thing to have an online demo or case study, but it an entirely different ball of wax to put on a VR headset and try a simulation first hand.

Not only does the CEC provide a chance for brands to show off their latest technology, but they also showcase the brand’s leadership towards innovation and product excellence. This also gives a chance for brands to consolidate sales offerings in one convenient location without having multiple channels for difficult to showcase products. Many times due to cost it just isn’t feasible and this leads to longer sales cycles which slow profits — being able to consolidate is a huge win and should bolster overall win ratios.

Drawbacks of the CEC

While the CEC can be a unique way to showcase and demonstrate product offerings, it does not come without some disadvantages. Specifically, during the current global pandemic, there may be issues having groups of people close together for product demos. Due to COVID-19, there is a lot more pressure on companies to reduce social interactions, and this may directly relate to the CEC mantra. In fact, due to the Coronavirus pandemic, a lot of CEC’s were forced to shut down as they typically had large groups visit them at a time.

Another thing to be aware of is the initial cost to put a CEC together. They take up considerable real estate, and the cost is generally high as many times they feature cutting edge technology and require specific hardware and support staff to maintain and utilize effectively.

How Current Drawbacks Are Being Addressed

In order to optimize the effectiveness of CEC’s many groups are starting to include them in their HQ’s where dedicated employee resources can be tasked without the need for extended travel costs and upskilling. This way the center is managed effectively and workers have the flexibility and freedom to continue their day to day activities outside of the CEC.

In the wake of COVID-19, many centers have had to reduce the number of people they can allow inside at one time. Space has been created between showcases and demonstrations and careful considerations are being taken to sanitize high traffic areas. By doing this and following social distancing protocols CEC’s can still function in a safe and effective way.

Immersive Technology & Hands-On Demos

With the advent of immersive technology, we have seen a number of CEC’s start to adopt using both VR and AR use cases inside their centers in order to have interactive demos of product offerings in order to bolster sales. Many times products can be complex and having a first-person demo of the product or simulation where the user can “try” the product even in a virtual environment can be extremely helpful for a buyer.

Virtual Reality specifically can place the user in an exact replica environment and allow the customer or prospective buyer to simulate the function of any product or even service. Augmented Reality, on the other hand, can be used with real-world props to highlight features and showcase overlays to enhance product knowledge to provide a more informed consumer which leads to bolstered sales. In the example above a box of Samsung headphones can be scanned with a smartphone to produce an augmented view on a mobile device and allow the user to see product reviews, technical specifications, and sharing options for getting a 3rd party opinion if needed.

All of these are tools that will enhance enterprise sales of which is the main role of the CEC anyway. With CEC’s using modern technology businesses that are adopting will see an uptick in sales as a more informed consumer is one that buys more. Overall the CEC revolution will continue to grow and we will see more and more brands look to enhance their sales and product offerings using immersive technology.

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How Deep Learning Has Proved to Be Useful for Cyber Security



How Deep Learning Has Proved to Be Useful for Cyber Security

The threat of cyber attacks has recently increased dramatically and traditional measures now appear to be insufficiently competent.

Because of this, deep learning in cyber security is rapidly gaining ground and may hold the key to solving all your cybersecurity issues.

With the advent of technology, there is also an increase in threats to data security and the need to protect an organization’s operations using cybersecurity tools. However, companies are struggling due to most cybersecurity tools being dependent. They rely on signatures or evidence of compromise for the threat detection capabilities of the technologies they use to safeguard their business. Because they are only useful for identifying risks they are already aware of, these technologies are useless against unknown attacks. Here is where deep learning in cyber security can alter the course of events. Deep learning, a branch of machine learning, is excellent at using data analysis to address issues. By subjecting the deep neural network to a vast quantity of data, which no other machine learning in the world can handle, digest, and crunch, we are mimicking the brain and how we operate.


The cyber security industry is facing numerous challenges and deep learning technology might just be its salvation.

Behavior Analysis

An essential deep learning-based security strategy for any firm is tracking and examining user activities and habits. Since it goes beyond security mechanisms and sometimes doesn’t trigger any signals or alerts, it is substantially harder to spot than conventional malevolent behavior against networks. For instance, insider attacks happen when employees utilize their legitimate access for nefarious purposes rather than breaking into the system from the outside, making many cyber protection systems ineffective in the face of such attacks.


One effective defense against these attacks is User and Entity Behavior Analytics (UEBA). After a period of adjustment, it can learn the typical patterns of employee behavior and identify suspicious activity that may be an insider attack, such as accessing the system at odd hours, and then raise alarms.

Detection of Intrusion

Intrusion Detection and Prevention Systems (IDS/IPS) are capable of identifying suspicious network activity, blocking hackers from gaining access, and notifying the user about the same. They are generally characterized by well-known signatures and common attack formats. This is helpful in defending against risks like data leaks.
Previously, ML algorithms handled this operation. However, the system generated several false positives as a result of these algorithms, which made the work of security teams laborious and added to their already excessive exhaustion. By more accurately analyzing the traffic, lowering the number of erroneous alerts, and assisting security teams in differentiating between malicious and lawful network activity, deep learning, convolutional neural networks and recurrent neural networks (RNNs) can be used to develop smarter ID/IP systems.

Dealing with Malware

A signature-based detection technique is used by conventional malware solutions like typical firewalls to find malware. The business maintains a database of known risks, which is regularly updated to include brand-new dangers that have recently emerged. Although this method is effective against basic threats, it fails to counter more sophisticated threats. Deep learning algorithms can identify more complicated threats since they are not dependent on the memory of well-known signatures and typical attack techniques. Instead, they become familiar with the system and can see odd behavior that can be a sign of malware or malicious activity.

Email Monitoring

To stop any form of cybercrime, it is essential to monitor the employees’ official email accounts. For instance, phishing attacks are frequently carried out by sending emails to employees and requesting sensitive information from them. Deep learning and cybersecurity software can be used to prevent these kinds of attacks. Using natural language processing, emails may be checked for any questionable activity. Automation is essential for defending against the enormous amount of risks that businesses must deal with, but ordinary machine learning is too constrained and still needs a lot of tweaking and human involvement to produce the desired outcomes. Deep learning in cyber security goes above and beyond to keep improving and learning over time so that it can foresee hazards and stop them before they materialize.

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