NICE inContact CXone Reviews

If you want your call center to have flexibility, drive customer satisfaction because of really amazing cool stuff you can make decisions on, or give your agents really good data to work with when answering phone calls, inContact does it. scales well and I recommended for any size business.

Great for contact centers that have plenty of growth and change. Static for companies that have a great reporting system and dynamics.

KE should be more enhanced for each of the industry verticals.

Attensity is best suited for large amounts of data (ie thousands of open ended comments per week). However it is essential to build out the categorization tree perfectly, otherwise you lose out on a lot of value.

I would advice them to marry the unstructured data to structured data wherever possible. If building a survey, I would advice asking multiple questions directed at very specific products or experiences. For example "What could our staff at the <LOCATION NAME> store do to be more helpful?" is a very directed question. "How could we improve our service?" will likely include feedback about the customer service line, the website, other stores and perhaps specific complaints. Ask very specific questions does much of your categorization for you. Also, I find Attensity works better for product feedback than for service feedback.
All clients should make sure to establish their proper nouns ("Entities") with professional services. This can take time.
Example: If you're Carl's Jr. you need to set up Attensity to know that $6 Burger is a proper noun/product name not a dollar amount.

If the core offerings are what is needed. The tools work and are reasonable to implement. However, extending the product's offerings is difficult.

The insight we have found through text analytics is impressive and defines some of the important business decisions that are made. Text analytics should always be used to find the "why behind the what" in any industry. The Attensity product uses the structured data hand in hand with the unstructured data which provides rich and insightful analysis. I have not seen another text analytics tool that does this any better. I did not give it a 10 because of the high cost and the manual labor that is needed in keeping the categorization current.

Make sure to clearly understand how the sentiment works and how it is tuned.
Understand how the discovery process works and how the triples are defined.
Understand how to create categories that are pre-defined rather than being driven by the triples.
Understand the pricing structure and how that compares to other vendors.
Understand how the user interface is evolving and how it meets the needs of the people who will be using it.

Your shop needs a large amount of data for Attensity to work sufficiently. Customer surveys should be tailored to fit the Attensity tool, and not the other way around. The tool also works best within the quality assurance and consumer packaging verticals, which produce high amounts of complaints. Understanding positive feedback through Attensity is also a challenge. It is most useful for filtering through complaints about your business.

I would not really feel comfortable recommending Attensity to a colleague, as it was not very helpful in my case. However, I do see the value in the tool for small brands and startups that have a very low engagement rate. I was working for a major corporation who had an engagement level that would accrue anywhere from 2,000-10,000 posts in a normal day, and I think this made it hard for the tool to keep up, thus making our jobs harder. But for a smaller brand who only accrues 500-1,000 posts in a day, I think that this tool could be a helpful way to organize the posts and how they are engaged.