Semantics: More friends, better questions, and answers
The value of unstructured information to an organization’s business intelligence process goes well beyond sentiment analysis. Unstructured information, if properly utilized, can fill in the gaps between the polarity of “Like” or “Dislike” and provide the why (why you choose them), how (how you feel) and where (where you stand) that every company should want to know.
Today, I’d like to share some real-world examples of customers who are using semantic technology and robust tools for natural language understanding to derive real business intelligence (and not just sentiment) from unstructured information.
Knowing your ‘friends’. Every company with a Facebook page and thousands of ‘friends’ to match has a wealth of market research at its fingertips—whether they actually convert to customers or not, knowing more about your ‘friends’ can only help your business and product strategy.
Information shared on social networks—preferences, tastes, desires—can be translated into valuable business intelligence when integrated into your existing data—demographics, sales data and other statistics—adding great depth and insight to your customer model. As one of our customers is currently experiencing, implementing a good semantic product can help you not only understand your customers, but also how the values you are trying to communicate through your brand are perceived, and what customers think of you vs. the competition. The advantages are significant: up-to-the-minute insight that is significantly less expensive compared to traditional BI or market research.
From questions to answers. When companies implement self help solutions, their main focus is on the savings achieved by deflecting calls from their customer service center. We calculated a $2 million/month savings for one customer—a major manufacturer of handhelds—simply by implementing a self help application on its devices. What the numbers don’t tell us—and semantic technology does—is that the ROI goes much deeper.
Using semantic technology to analyze the inquiries customers made through the self help application gave us valuable insight that allowed our customer to:
- Improve the knowledge base to make sure it contained all the information customers were requesting.
- Link or cluster the information with that available on the CRM system to produce a demographic representation of customers and create customer profiles or types.
- Understand which customers were asking questions most often, which were interested in information outside their normal scope of products and services, and who responded positively to campaigns, etc.
This information—all from existing data—adds more dimension to customer information, and provides not just savings, but intelligence that can impact every area, from sales and marketing to product development and more.
Author, Luca Scagliarini.