As we’ve explained in many blogs and 5-minute guides, a cognitive search platform should combine AI technologies such as natural language processing, machine learning, and knowledge graphing to deliver a contextualized search and discovery experience without compromising security. Those technologies can turn ordinary search into something much more powerful and transformative for any organization.
My last post on cognitive computing was a backgrounder, and it stated the importance of search to any cognitive computing initiative. So, how does cognitive computing powered by search lead to digital transformation? In fact, just what is digital transformation?
Looking for a search solution that could power their e-commerce, Intranet, and CRM experiences, National Instruments wanted to optimize the online shopping experience and foster collaboration and engagement across the workforce.
National Instruments is among the innovators that put search at the core of its systems, including digital commerce, the website, intranets, and CRM.
Today’s business users don’t search for documents that may have the information they seek buried within, instead they ask their systems for answers. This shift in attitude is a key driver behind the move to cognitive search.
When IBM Watson burst on the scene a few years ago by famously winning Jeopardy! people swooned. Here was a machine that seemed to live up to the promise of a science fiction future. IBM purported to show us all an artificial intelligence (AI) that could understand human language, sift through massive amounts of data, and provide answers to questions.
When life sciences companies develop new drug therapies or biomedical interventions, what typically attracts the most attention is news about the success or failure of clinical trials. But a lot of work goes on behind the scenes before these efforts ever reach the clinical trial stage. In fact, as life sciences companies decide what promising therapies should receive development resources, it’s often rigorous fact finding and research that determines a go or no-go decision.
When you think about customer support, you tend to think about cost savings for the company. But how often do you think about customer experience?
For too many companies, a focus on customer experience ends when the customer is won. The reality is, it’s only the beginning. If the experience you deliver your customers is poor, they will leave you. And it’s easier than ever for an unhappy customer to move to the next company.
We’ve been posting lately about all the ways cognitive search can help make your business more successful and its employees more productive. The working definition we use for cognitive search is: “Cognitive search allows people to find hidden knowledge.”
Now, “hidden” can mean you don’t know where something is, but it can also mean that it’s not accessible. You know where a certain piece of knowledge is, but you can’t get to it because it’s in a place you can’t connect to. Or you can only connect to it when you’re in the office — not when you’re working from home or on the road.
Customer support is probably one of the most challenging elements of business. Your support team is on the front-line working hard to help customers resolve their issues as quickly as possible.
Customers expect - and often demand – answers, and fast, whether it’s from a support rep or a self-service support solution. If their issues aren’t resolved in the time they think it should take, frustration kicks in and plans to move to the competitive solution start to take hold.
What exactly is cognitive computing? Well, if you ask 10 academics or scientists, you’re likely to get 10 different answers. Look it up on Wikipedia. You’ll see that in the academic and scientific community, there is no agreed upon definition. It’s just marketing jargon. Ouch.
On the commercial side though, we may not have a precise definition for cognitive computing, but we’re very aware of its potential to help our businesses.