How digital transformation is a chance to upskill workers
Digital transformation is now an increasingly default position for C-suite leadership rather than the sole preserve of an enlightened few as it used to be.
Accelerated by a global pandemic that demanded slick, robust infrastructure to withstand disruption and remote working, all while maintaining a seamless customer experience, the enterprise is turning to predictive analytics and artificial intelligence to inform decisions which in turn are creating new ways of working for those steering and shaping these heightened capabilities.
The once black and white narrative around AI as a technology that simply usurps and replaces human effort, offering only basic automation tools and monosyllabic chatbots, has progressed with rapid advances in machine learning and natural language processing, transforming the experiences consumers have with brands by offering far more personalized experiences.
Meanwhile, machine learning means that natural language processing and speech recognition are always improving, evidenced by the conversational AI solutions that can deduce where problems and challenges lie when dealing with a customer. Gradually, almost every facet and role in the business has become digitized – take the role of the marketer, once solely reliant on leaflets and exhibition attendance, now benefitting from apps that, far from taking over their role, are augmenting creativity, reach and potential, leaving them better placed to identify trends across swathes of customer data.
Crucially, data analytics are no longer used reactively or constrained by the ability to access only the most recent data in the organization, which meant a limited perspective on the environment.
The rise of predictive analytics has been adopted by many enterprises to help them to identify, understand and react to the vast number of insights buried within the data that they have access to. By creating data pools, we can arm AI to predict customer needs based on real-time analytics, allowing businesses to make real-time changes and cater to customer needs. with forward-thinking analysis, this emerges as a core tool to help better understand the customer and in turn, tweak the proposition accordingly to suit their needs.
Predictive analytics allows you to pre-empt what is going to happen based on the datasets that you have in place, therefore, the more and better-quality data you have, the smarter your assumptions will be.
For enterprise, this offers a unique form of risk mitigation, where you can try to predict potential challenges, peaks and troths and identify trends in the market.
For enterprises operating on a B2C model, predictive analytics enables you to engage in a more meaningful way with your customers. Through the knowledge you have gained from data analytics, you’ll be able to identify personal behavior and trends.
An example of this is if one of your customers frequently shops on a quarterly basis to purchase clothing; you can use data such as the customers purchasing cycles, previous purchase history, and overlay this with other customer data of similar demographics to drive products that would be relevant. Real-time analytics reviewing dwell time on pages can offer personalized discounts that can get them over the line, where they may normally pause to convert into a sale.
By simply understanding the end-customer, you will be able to make more informed decisions that create longer-lasting relationships.
