Using machine learning in customer support equates to taking your most experienced rep – someone with years of experience responding to customer questions – and making her/him exponentially faster. Taken a step further, machine learning allows you to replicate their expertise and newfound proficiency amongst all of your reps.
In this day and age, there are very few questions without answers. They may not always be right answers but even the most well thought out Google query can lead you down a rabbit hole of theories, thoughts, and best guesses that help you craft answers to even the hardest questions like, “What is the meaning of life?”. The power of modern search engines has made the spread of information more equitable and trained us that any question can be answered via search.
But in reality, not all information is created equal, especially in the business world where proprietary knowledge and the free-flow of team- and company-specific information is essential. You can’t just Google, “How many of our orders shipped late last quarter?”
Did you know employees in 44% of life sciences companies typically need to draw from 7 or more structured data sources to find answers? And when you add unstructured data to the mix, another 38% also have 7 or more unstructured data repositories where they could find possible answers? That's a lot of data silos to look through, and as much as 36% of an employee's day can be spend looking for information.
Unifying Unstructured & Structured Data through Intelligent Search
But AI-powered, cognitiive search can help - by unifying unstructured and structured data, and adding AI-capabilities like machine learning, natural language processing, and text analytics, employees can find the answer they need to virtually any question, right away.
Many roles in today’s enterprises are metrics-driven and metrics-motivated. The search architects and search platform administrators we work with are no different; they’re hungry for feedback and insights about how users are searching (user analytics) and what content is performing best. With Attivio’s new Search Analytics capabilities (available today), we give search architects the information they desire, in real-time and right at their fingertips.
Search Analytics enables you to better understand the performance of your search platform by delivering insights into:
In case you missed it, here’s a recap of last week’s webinar, New Modules in the Attivio Platform, presented by Attivio’s Director of Solution Architecture, Brian Flynn.
During the session, Brian reviewed two new modules that are included in the Attivio platform: Query Frames and the Search UI Toolkit, or “SUIT” for short.
As you may know, the Attivio platform includes a patented capability called Query-time JOIN. This combines indexed structured & unstructured data dynamically to answer questions like “What are the customers in my region saying about the new products they bought in the past 90 days?”
The ability to search for information and find what you need is a critical knowledge management capability for any enterprise search platform. But too often, search is limited to a quick keyword search and a set of links that leave you trying to figure out what you need.
What if you could take search to the next level? What if you could get search results that show you how things are connected (or aren’t), enabling you to get the insights you need to make good decisions quickly?
A Knowledge Graph transforms basic search into a set of relationships, connecting what may at first glance seem completely unrelated, or what would take you days or weeks to connect manually.
Introduced in 2002, Google Search Appliance (GSA) was the answer to many companies’ need for a search solution for their website, Intranet and internal content. It provided a way for you to index internal content to make it findable quickly. And it was good - for a while.
The demand for better search solutions that offer more than simple keyword and text indexing has forced a major evolution in the search space. And that makes solutions like Google Search Appliance obsolete. Maybe Google knew that because in February of 2016 it announced that it was ending its licensing and support for GSA.