Customer Experience: Trends to Watch for in 2021

Category: Artificial Intelligence, Business, IT staffing and consulting

“It takes 20 years to build a reputation and five minutes to ruin it. If you think about that, you’ll do things differently.” – Warren Buffett

Businesses continue to vie with each other in the competitive market place through emerging trends to delight their customers and increase their profitability. Let’s look at some of these new trends that can create a lasting impact in terms of customer loyalty by optimising customer experience. 

Assess Customer needs

Business leaders need to assess  the customer profiles and redefine them based on the customer needs and expectations. Deployment of design thinking and data driven analytics helps in pre-empting customer demands resulting in innovation of new products. The prototype created by quantitative research and ethnographic studies can be used to identify customer trends and patterns that help in building robust business cases for determining the most treasured customer experience. Digital transformation in business strategy helps in developing a road map for leveraging the capabilities of digital technologies like AI and responding proactively to the dynamic needs and requirements of customers. 

Companies are constantly reinventing themselves for speeding up their plans to deliver superior product offerings and becoming more digitally accomplished by revving up the prioritized experiences. C level leaders need to focus on valuable insights and feedback provided by agents, customer service teams to develop a robust customer experience strategy for customer retention and growth. The think tank needs to review their ROI on a regular basis based on customer insights with a sustained focus on building trust and revenue generation. 

Adopt Omnichannel Startegy

Stepping up omnichannel strategy will result in deepening the customer connection across multiple channels and helps in understanding the choices and customer behaviour. Engaging the customers through web, voice, e-mail channels would help in staying seamlessly connected across the customer journey and having personalised interactions with them at every touch point. This provides a sustainable advantage by streamlining customer services for building long term customer relationships. Resolution of customer queries based on priority would help in eliminating the pain points resulting in better customer satisfaction scores. Reimagining customer experience helps in transforming customer interactions into personalised experience resulting in heightened brand loyalty and advocacy. 

Customer choices and preferences

Businesses need to focus on predictive analytics for maintaining a competitive edge and customer retention. It also helps in understanding the potential threats and flight risks by identifying the key factors leading to churn. Customer choices and preferences can be understood based on product feedback and products can be tailored to suit the customer interest. Predictive analysis also helps in managing the operations better by deploying the right amount of resources for handling customer traffic based on volume teen. The usage of integrated data lakes and customer data platforms helps in identifying customer interventions and provide enhanced end customer experience. 

Training

Employees need to be provided proper training for handling customer interactions effectively and be passionate about serving their clientele.  Empowering the employees and rewarding them for positive outcomes will go a long way in boosting their morale that keeps them motivated for developing customer centric vision and delivering customer excellence. 

Conclusion

We at Newlineinfo Corp have a customer centric team committed to providing top notch services to our customers through digital transformation and innovation. 

Cybersecurity trends to watch for in 2021

Category: Artificial Intelligence, Cyber Security, Deep Learning, Machine Learning

“Cybersecurity is a new area where equality will exist to allow intelligence to succeed”. – Ian R. McAndrew, PhD

The advent of new technologies poses serious security threats due to increasing cybercrimes and attacks by cyber criminals. Inorder to mitigate the threats and vulnerabilities in the cybersecurity landscape businesses can embrace Artificial Intelligence in their modus operandi. Let us look at some of the key implications of AI in Cybersecurity.

AI helps in faster detection of cyber risks and augments the recovery rate in the event of any cyberthreats through analytics and integrating the data sources with threat intelligence. AI sources huge amounts of risk data through research, blogs etc and provides sharp insights about cybersecurity alerts that helps in effective surveillance and staying ahead of any potential threats by raising the standards of Cybersecurity framework. Latest technologies like Machine Learning and Deep Learning techniques help in deciphering cyber risks and provide valuable inputs related to IP addresses of fraudsters and criminals. Security analysts can make informed decisions on the malicious code based on the inputs provided by AI and this saves the time and effort required to pursue large data sets for the cybersecurity professionals.

Due to the skyrocketing costs of recovering the system from  data breaches, businesses need to be prepared to handle any advanced cyber attacks in unforeseen circumstances. Creating a multi layered security system will help in securing the network infrastructure resulting in tightened control and adherence to compliance protocol. AI powered security tools and modern firewalls helps in proactive monitoring of network traffic and identifying the malicious file. Antivirus software can be used to remove the malefic content and viruses in the network infrastructure followed by regular backup procedures for demonstrating effective resilience and disaster recovery. 

AI and Machine Learning can be used for automating threat detection and building threat modelling by leveraging on observational data indicators. Deployment of powerful AI tools like Expert systems and neural networks would help in deploying threat models for identification of cyber threats.  AI and Machine Learning helps in consolidating the knowledge with the help of data analytics for building effective threat models. Business leaders and cybersecurity professionals need to actively engage in building a strategic framework for risk and management for safeguarding any cyber attacks like data poisoning in federated learning and circumvent malicious participants.

Cyber criminals use sophisticated techniques like distributed spam distraction, phishing etc.. for digital attacks with malefic intent. Such digital attacks can take place through emails or email attachments posting false URLs for the purpose of data mining and inflicting malware into the system resulting in financial frauds through business email compromise. The Machine Learning capability in AI helps in blocking the access to malicious links by scanning the images of the fake login pages and using visual indications to establish the genuineness of the login page. AI uses behavioural analytics and secured authentication to identify any fraudulent attempts in the digital landscape. AI upgrades it’s capabilities for detecting any phishing attacks from open source intelligence and it’s identification of phishing efforts breaks all geographical barriers and boundaries.

Development and promotion of ethical guidelines for AI systems would make it more reliable by promoting a culture of transparency, data privacy and adherence to safety standards. Businesses and researchers should be open for sharing ideas related to research carried out in AI for free flow of information and exchange of new ideas. This will help in raising the bar for reaching better heights in the use of the AI in Cybersecurity through collaborative efforts and research work for countering any sophisticated cyber attacks in the future. Businesses need to identify the scope of AI in their business and ensure that adequate testing is carried out before deploying AI. This would help in unearthing any potential risks and flaws that would go unnoticed.

Conclusion

Disposition of AI in cybersecurity provides critical information about potential threats and vulnerabilities. Businesses can now manage the cyberattacks proactively and minimize their threat exposures that help in ensuring business continuity by demonstrating their resilience. AI can help in identifying gaps in the security framework by analysing the effectiveness of infosec controls. Prescriptive controls offered by AI would help in building robust controls and enhancing the quality of cybersecurity governance. At Newlineinfo Corp have a dedicated workforce and driven by our passion to provide world class service delivery to our clients and stakeholders.

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