The cloud is the de facto transformational platform for leading enterprises. It provides newfound agility, resiliency, and growth opportunities for the hyperconnected fourth industrial revolution. And across all industries, retail is in the top eight for investments and initiatives in the cloud. More than 78% of retailers are either mature cloud users or are advancing cloud investments. In fact, with the current pace of spending, the global retail cloud market will grow to $39.63 billion by 2026.
What is behind this rapid investment? It is a change in consumer behavior. The new consumer leverages social media for product reviews, is comfortable purchasing online and expects better and more personalized experiences across channels. But enterprises find it challenging to address all these expectations with existing, non-scalable legacy system architecture, which isn’t well integrated. As such, many retailers are prioritizing a digital-first retail strategy and adopting a cloud/hybrid ecosystem to leverage cloud-managed services. But identifying and migrating knowledge assets will need to be a central focus in the cloud migration to meet the changing customer and market demands.
Knowledge Management – An Obstacle in Cloud Migration
One critical aspect of cloud adoption is migrating a company’s knowledge assets. The legacy to cloud migration journey requires knowledge sharing across teams. But knowledge assets are typically distributed across many people and sources. This distribution of information with no records or documentation makes migrating the existing asset inventory challenging. And most retail enterprises struggle to share knowledge, find answers to technical/functional queries, etc.
Another hurdle to overcome is the data that drives loyalty program management. This program allows companies to provide a better customer experience but is frequently challenging to manage effectively due to siloed multichannel sales and customer data at the store level. Consequently, contact support teams do not have a 360-degree customer view. AI-based Knowledge Assist can help answer most of the above challenges and equip teams with information, at the right time, from multiple sources and types of data.
How Does AI-based Knowledge Assist Work?
AI-based Knowledge Assist is an effective Natural Language-based assist (query/response) platform. It helps users find various types of knowledge from several sources, like documents and web pages, through a query that uses natural, simple English language. Knowledge Assist prioritizes responses based on the relevance to the user query. The whole process and knowledge search occur quickly, and the user gets the correct information.
Knowledge Assist analyzes a query, searches for relevant documents and returns the summary and links to the user. For asset inventory discovery and rationalization, Knowledge Assist uses the relationship graphs created by the scanning agents to help find the requested assets. These graphs efficiently retrieve asset information and aid in accurate decision-making to rehost/retire.