Saxon Global

  Cloud adoption is a hot trend in the enterprise technology world. Businesses are moving from on-premises systems to cloud systems for flexibility, scalability, efficient process automation, robust   data protection , and seamless remote collaboration. To tell you how big it is going – the global cloud migration market is valued at over   $180 billion in 2023   and is projected to reach $630 billion in the next five years with a CAGR of 28.24%. While this might seem rosy, most   cloud adoption strategies   fail due to poor planning. This is why you need a cloud adoption framework.  Once you decide to invest in the cloud, you will face several questions – how much should be the budget? What should be moved to the cloud? Who is responsible for the migration? What skills and tools are required for the migration?  To help you cut through the complexities and effectively move to the cloud, cloud platforms, such as Azure, AWS, and GCP, offer cloud adoption frameworks.   In this article, let

  Retail is a data-rich industry. Retailers interact with millions of customers every year and produce huge volumes of data. Catering to the needs of these customers while being proactive in the highly competitive market is challenging. However, retailers can use data in their possession to their advantage by leveraging predictive analytics. Let us explore five major applications of predictive analytics in Retail.  In our previous blogs, we have covered how predictive analytics work for  Manufacturing ,  Healthcare ,  Finance , and  Insurance . Applications of predictive analytics in Retail Delivering personalization to customers If you look at reviews for a retailer on Google, you may find negative reviews and 1-star ratings for inconveniences and unpleasant experiences customers might have faced. As a shopper, you often count these reviews and ratings in your purchase decisions, don’t you?   Customer experience is key. It directly impacts brand loyalty and your business success. As f

  If you asked any customer service professional to sum up their experience of the last couple of years, they would likely respond that it was intense! The budgets have been fluctuating, customer expectations are skyrocketing, and service teams are locked in a perpetual quest: How to achieve more with limited resources? Implementing   Artificial Intelligence in customer service  is the right thing to do. With the buzz around   generative AI models   built on pre-trained, large language models that generate human-like, unique content based on prompts, it is no wonder that this technology will be game-changing in customer service.  Meeting the soaring customer expectations   The landscape of customer service has gone through a seismic shift since the onset of the pandemic. Customers’ expectations have soared to unprecedented heights;  72% of customers  choose businesses offering swift customer service. However, customer service agents are constantly swamped with work. Around 78% of custo

  Do you know that the global Intelligent Document Processing (IDP) market is snowballing at a robust CAGR of 37.5%? According to a recent study by  MarketsandMarkets , IDP is projected to account for $5.2 billion by 2027 from $1.1 billion in 2022. The prime reason for this surge in IDP growth can be attributed to the critical need for enterprises to deal with substantial volumes of semi-structured and unstructured documents efficiently. Not just storing and accessing them securely but also facilitating the documents for advanced analytics.   The data insights that lie in all these semi and unstructured documents can fetch a lot of value in the form of analytics and insights. No wonder IDP lies at the core of the operational workflow today for the organizations who have adopted it. Businesses utilizing  Intelligent Document Processing (IDP)  solutions for document processing exemplify how this technology domain is crucial in enabling accelerated operations and innovations and giving a