In order to better service and engage customers we first need to understand them.
Artificial intelligence has the potential to improve the way organizations understand content from customers and know their desires and goals, and transform that information into action, decisions and revenue. This can be accomplished by leveraging AI to transform documents, communications and interactions into meaningful data.
But less than one in five organizations are near where they want to be regarding the core transformation challenge of understanding, anticipating and redefining internal and external customer experiences. To achieve this level of intelligence, content intelligence is the next wave of understanding customers, partners and employees.
Digital Transformation: Hype vs. Reality
More than 81 percent of organizations believe digital transformation is important or very important to their organization, but only 33 percent of large organizations believe they’ll reach 50 percent of their goal. A mere two percent believe they will actually achieve full digital transformation by 2020, according to a 2018 AIIM survey. As a result, many organizations face a rising tide of information chaos and confusion with digital transformation effectiveness leading CIOs to wonder if it’s all just a bunch of hype.
The emergence of robotic process automation (RPA), or software robots, is calming the chaos and enabling digital transformation to become reality. RPA is a subset of AI technology that organizations are realizing can deliver critical benefits to drive decisions. RPA is fast and simple to deploy and puts an emphasis on content to drive decisions. Yet, it also raises awareness of challenges related to content.
Of all the data entering organizations, only 20 percent enters systems of records in structured documents. Structured documents include spreadsheets, CSV files and databases and are considered “visible” date.
Meanwhile, 80 percent of data is in the form of semi-structured, such as invoices, purchase orders, contracts and mortgage applications, and unstructured data, such as emails, instant messaging, voice, images and video – mostly considered “hidden” data since it is not easy to organize and pull context within the content.
To gain insights from data, organizations want to leverage analytics and machine learning as part of their automation strategy. In fact, there is significant spending towards machine learning and cognitive capabilities which is currently overlapping with RPA to digital transforms organizations’ processes.
Advocating for Artificial Intelligence
Ultimately, organizations are trying to understand what AI means to their business – is it an assembly line of robots in a call center? No, not likely.
The most opportune area to derive intelligence is from the plethora of data organizations own and have access to via content intelligence. Content intelligence is AI applied to content and leverages cognitive processing and machine learning to automate the encoding of semantic metadata within text, images, and video, audio and multimedia. It automates the creation of intelligent content by transforming unstructured content into structured content, which can then be easily processed and managed within various processes and adapted for access across different systems, devices and interfaces.
RPA a Catalyst for Content Intelligence
Rapid and accurate access to content is directly tied to RPA. When combined with RPA, content intelligence provides the AI and cognitive machine-learning capabilities required to enable the automation of content centric processes, including the onboarding of new customers, mortgage application loans and new insurance policies.
Looking at the “Content Intelligence Stairway to Value” graphic, you can see when RPA enters into steps 3 and 4, and the AI and machine learning backbone classifies content and transforms content into structured documents so processes can extract insight and data to speed decision making.
Content Drives Customer Understanding & Service
Organizations benefit from content intelligence by gaining real-time understanding of their data and communications. With a deeper understanding of customers’ information, customer facing services, applications and processes can offer faster, more convenient and satisfactory engagements. This will be essential when by 2020 it’s estimated that 85 percent of all customer interactions will be handled without a human agent. This could have catastrophic consequences if the customer interaction is poor.
Validating this point is a recent Zendesk study which found 42 percent of B2C customers purchased more after a good customer service experience, while 52 percent stopped buying after one bad customer service interaction. Resolving customer service issues before they arise, and enacting pre-emptive customer service will significantly lower customer abandonment rates.
Content intelligence is one of the most business critical and value-driven applications for justifying the use of RPA and AI. Once an organization can better understand its customers, additional revenue-generating opportunities will be revealed.
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