Legal Knowledge Management and the Rise of Artificial Intelligence
Robotic Refactoring the Workplace
Why Your Next Insurance Claims Processor Could be a Robot
The Forgotten Element in Your Big Data Strategy
"AI -The Future of Automotive Industry"
Nitin Sethi, Global IT Director - Business Transformation & Engagement, Visteon Corporation
WiFi Networks: Shifting from Providing a Service to Improving the...
Daniel J. Strojny, Interim Associate Director of Network and IT Operations, University of St. Thomas
Breaking the Stereotypes in the Development of AI
Yves Jacquier, Executive Director, Production Studio Services, Ubisoft
Operationalize Machine Learning
Zongjie Diao, Director of Product Strategy and Management, Data Center Compute Group, CISCO
Thank you for Subscribing to CIO Applications Weekly Brief
Capitalizing Big Data Prospects in 2019
The digital marketing developments have set a high bar for customer expectations and clients currently expect, deserve, and demand personalized, seamless transactions. By concentrating on data-based AI solutions, companies can ensure the customer journey to be more personalized and profitable in the coming years.
FREMONT, CA: In previous years, businesses have realized the importance of collecting customer data to create highly-targeted, personalized engagement throughout the consumer buying cycle. In recent times, they are overwhelmed with data harnessing the flood of customer information can be one of the biggest challenges CX and digital marketing professionals might face.
The absolute abundance of data available from pixel tracking, geospatial sensors, social postings, CRM reports, and market trends, are moving their focus toward data management and analytics. AI tools with the ability to process and unify an enormous amount of disparate information can quickly process large volumes of data in real-time for businesses to put into use.
Restructuring Companies around Proactive Teams:
Companies need to be prepared to make changes that can allow them to respond with real-time decisions based on a customer-first approach even before Artificial Intelligence (AI) revolution hits them. Old organizational hierarchies having distinct silos of sales and customer service teams can benefit from flattening their structure to let cross-functional teams that focus on customer engagement. Each member of the organization should know how specific actions impact sales, including how rapidly CSR issues can be resolved. By providing teams access to the same information, in real-time can empower businesses to work collectively with the cross-functional groups to encourage collaboration and solutions.
AI tools provide companies with a power to micro-target the entire customer journey in an omni-channel approach that humans cannot. The content needs to be timed and delivered to match the customer’s search queries, shopping history, and app engagement data whilst simultaneously taking into account the location-specific weather and emerging market trends. Furthermore, steering toward keywords and timing, AI tools can show how content should be tweaked to meet the customer needs with video, blogs, social campaigns, and advertisements.
Customized Customer Interactions:
AI-driven chatbots play a significant part in conversational commerce with customer support, and they also carry the additional benefit of not losing their patience while a human interaction. The ability to seize extensive catalog information and inventory levels can help chatbots to engage customers in conversations and make product recommendations depending on their preferences.