Ways AI Can Improve Digital Transformation's Success Rate
The desires, buying power, and loyalty of consumers need to be the catalyst for every digital transformation plan, with AI offering concrete insights that inspire businesses to adapt.
Transforming or changing the interactions of consumers digitally must be the foundation of any investment in emerging technology or business processes. As a strictly technological, abstract construct, it is necessary to get beyond digital transformation and see it as a must-have strategy to maintain clients and attract new ones. The hundreds, if not thousands, of successful customer stories they produce are known as the most successful digital transformation ventures.
Why are customer stories and the data supporting them so relevant for the success of digital transformation strategies? And everyone likes a good customer story that illustrates how digital transformation will make you a more empathic organization that recognizes the greatest challenges of your customers.
In the midst of digital transformation programs, COVID-19 is generating completely new paradoxes for organizations. For instance, it is now necessary to replace designed-in human interaction with customized self-service that can react with perfect precision 24/7. The pandemic is generating completely new client challenges that need to be addressed by digital transformation. Strong data and AI-driven insights need to be focused on solving them. The better the data and observations, the greater the output of the customer. The following are ways that AI can increase the success rate of digital transformation:
AI helps to identify the desires and needs of consumers more clearly, leading from the very beginning to more specific personas that direct digital transformation projects. Based on a more well-defined individual, companies that are the most active in digital transformation efforts will easily see increases in consumer engagement rates and customer satisfaction. People must be the cornerstone of every digital transformation project by using AI to better understand customers. Brand, event and product preferences, location data, viewed content, transaction history, and, most of all, channel and contact preferences are the most advanced uses of AI for personal growth.
AI-based algorithms allow individual propensity models to be developed, and are invaluable for predicting which customers are going to act on a bundling or pricing bid. By design, propensity models rely on predictive analytics to predict the likelihood of a given customer acting on a bundling or pricing bid, e-mail campaign or other call-to - action leading to a purchase, upsell or cross-sell, including machine learning. Growing consumer satisfaction and that turnover, propensity models have proven to be quite effective. The following is a dashboard which demonstrates how models of propensity work.
For a company to reinvent itself today, digital transformation frameworks that are customer-centric and rely on AI are important. There has never been a greater need for more agile, customer-centric approaches to digital transformation. The Autonomous Digital Enterprise (ADE) of BMC, characterized by the three characteristics of AI and Machine Learning (ML) driven agility, customer centricity, and actionable insights, is prescient in how it incorporates every part of a company around the customer while delivering insights driven by AI.
Initiatives for digital transformation also involve digitizing supply chains, allowing on-time output based on AI insights. Supply chains need to be built to excel at time-to - market and time-to-customer success on scale for any digital transformation plan to succeed. 45 percent of companies claim that faster market speed is their primary target in digitizing their supply chain by incorporating intelligence powered by AI and machine learning.
AI is enhancing the success rate of digital transformation in the fields of marketing and sale productivity by being able to monitor purchasing decisions back to channel campaigns and understand why particular people bought when others didn't. Marketing is now analytically oriented, and for the first time, marketers will be able to isolate whether and where their marketing and sale tactics are successful or failing with the rapid advances in AI. Predictive models, like AI, will help predict ideal customer profiles by using AI to qualify more customer and prospect lists using specific data from CRM systems.
AI also affects digital transformation strategies to increase production by reducing the conversion costs of the manufacturer by up to 20 percent, with up to 70 percent of the cost reduction arising from higher productivity of the workforce. BCG found that by using AI to create and produce new goods targeted to individual consumers and to deliver them in a much shorter lead-time, manufacturers would be able to generate additional revenue. Based on BCG's study, the following graphic shows how AI can add increased flexibility and scale to production processes. Source: AI in the Factory of the Future, Boston Consulting Company, April 18, 2018.
Keeping clients, staff, vendors, and partners updated about the progression of digital transformation initiatives is a good way to win and retain their confidence. The more open any company is in these unpredictable times, the better. A good place to begin is by establishing a structure for communication. How some companies have adapted to the COVID-19 pandemic offers a valuable context for the creation of a communications strategy that suits digital transformation initiatives equally well.
The recent paper, What Needs to Be in A CIO 's Contact System For COVID-19, offers lessons learned from speaking with manufacturers and service organizations. The communication plan is based on the idea that convincing individuals that improving how they operate would benefit them is the most challenging field of any digital transformation strategy.