While service portfolios in the banking and insurance sectors are analogous, the evergrowing mountain of data resulting from digitization offers a huge opportunity to improve customer service. Automated incoming mail classification allows companies to handle incoming customer inquiries in the areas of finance, insurance and administration far more efficiently, and provides a uniquely compelling way for companies to set themselves apart from the competition. Mindbreeze, a specialist in data analysis and intra-corporate search engines, summarizes the trends in the area of incoming mail classification for 2016.
Self-learning, Intelligent Systems
This year, self-learning and intelligent systems will experience a true upsurge. On a certain level, these solutions can comprehend the contents of a document. This capability offers a wide range of advantages. For instance, the system can learn from its own experience (“machine learning”) and understand information. These self-learning systems provide support across the board in all areas of IT.
Automating the Incoming Mail
The sheer amount of mail that companies receive every day through many different input channels (e.g. the mailbox, the e-mail system, social media channels) is growing steadily. This makes it compelling for companies to look for better solutions in this area, within the bigger context of increasing digitalization. Enterprise search solutions provide automated incoming mail classification that supports the mail sorting. Unstructured sources of mail are becoming more common, and it is simply no longer enough just to be able to analyze and classify data from forms. Instead, the classification needs to be possible regardless of the file format and the structure of the document (from a form or from free text). Only content-based and form-free analysis can truly automate incoming mail classification from all input channels. This frees staff from having to read all mail and manually forward it to the right department. Enterprise search makes quick work of that, so that employees can devote their energies to more significant tasks.
Proactive Customer Service
Another trend in 2016 will be the optimization of community portals and forums. Many companies use these online platforms to provide their customers with a point of contact for concerns and questions as an alternative to call centers. These forums are usually crowded, confusing and messy, and more often than not you will find the same question answered in several different ways on one forum. In order to gain and maintain a real overview, functions, systems and mechanisms are needed which proactively provide the customer with similar resolved cases, solutions and explanations even before he posts his question. This new approach to community portal management lightens the staff workload and increases efficiency by decreasing the number of posts. This kind of online customer service optimization will be a major issue in 2016.
Predictive Analytics – A Game Changer
Business processes are in constant flux. Predictive analytics are being implemented on a broader scale, with highly specialized orientations, and in well-known fields of activity. One application is incoming mail classification (i.e. the distribution of mail within a company) – often done manually, but trending toward automation. This may signal the beginning of the ultimate triumph of predictive analytics.
Digitizing Paper Archives Without Digital Waste
In the future, paper archives will be increasingly digitized in order to save space. Rather than resulting in usable information, this process just tends to create digital waste. That’s why it’s becoming more and more important to use intelligent systems from the get-go, to extract valuable data from the documents and to generate value from this information. After all, if you digitize your data, you should also be able to take full advantage of it.
Automated classification in document management systems
Employees dealing with document management must register metadata before information is handled and processed, in order to know which topic, project or area of responsibility is applicable for that document. That is why it is becoming increasingly important in document management systems to use enterprise search solutions that automatically extract the metadata from the documents and classify them appropriately.
Gerald Martinetz, author of this article, is responsible for sales in the area of data extraction and classification at Mindbreeze. Mindbreeze GmbH, based in Linz, Austria, is a leading European provider of software products for enterprise search, big data and knowledge management. The products “understand” information and provide a consolidated view of the company’s knowledge – regardless of where (data sources) and how (structured unstructured) this data is saved. www.mindbreeze.com
