NICE inContact CXone Reviews

Delay in report updating - Custom reports are not real time and may take 6 hours to update.

Making a change to a scheduled report require the report to be rescheduled or it will not run properly.

The built-in softphone option is expensive and does not support 911 dialing out which puts call centers in a legal pickle.

The voice platform is not on AWS and is resilient for most the part but not fully fault tolerant. Have seen media server issues affect voice quality sometimes.

The screen recording software Engage is something straight out of the 90s. The interface, crystal reports, the delays. Engage side of the company is bad in products and support. The recording software does not provide 100% recording and they always have an excuse for why Engage does not work but never a solution. I have a missing screens problem open with them for longer than 3 months.

Current data occasionally glitches and is inaccurate.

Building reports need to be more intuitive.

Transfers could be smoother.

Can get slow to respond during busy times.

Freezes fairly often.

Often will not allow calling between departments and will require a reset to function normally again.

At times, it feels the software is running a bit slow. While it can depend on a lot of things, there are ways this can be solved.

AI chatbots are not as good as they should be.

Support for agent profiles or templates that can applied to any new and existing agents.

UI/UX controls doesn't look modern.

The UI for the agent is a bit dated, especially with the Salesforce agent.

They don't seem to have enough UX testing done before releases and have great opportunity to improve and listen to user feedback.

User feedback opportunity is limited. There is nowhere visible really to submit feedback that gets tracked. The process is opaque.

Better communication with TAM

Better weekly conference and update communication

If we can reduce the training time for knowledge engineering, then it will be really useful.

Needs to reduce noise (ie advertisements) from data collected from around the web

Categorization is tedious and takes an extremely long time, especially with high volumes of data

Overall, the system runs slowly. Some days it's better than others.

I have not used Attensity since 2011 so this might be dated. I found it was much less useful the more abstract the subject matter was. I found it VERY effective at finding instances of concrete problems such as problems with a specific product/object/part. I found it much more difficult to analyze and categorize text that had to do with a customer's experience. I don't know that this is a flaw in Attensity's technology. I think this is due to the almost limitless ways a customer can describe an experience. Whereas with products customers tend to use a narrow range of specific terms and model/part #s. With experiences customers/respondents often use different and sometimes 'wrong' terminology. I found it very difficult to build category sets that would capture all/most of the feedback around a specific experience without bringing in too many false positives.

One way around this is to set up respondents (in a survey for example) to focus their comments on something specific, or to provide survey check-boxes for respondents to indicate how they feel their feedback fits into categories. But I found Attensity professional services (this was in 2011 or earlier) to be resistant to using structured data with unstructured. It seemed that they were so in love with their tool that they were reluctant to see how it would be enhanced by using structured data along side it.

I found that Attensity as a company could benefit from having 1 or more methodological approaches that they teach clients step-by-step. They were GREAT at teaching us how to use the functionality of the tool. But I found them lacking in teaching a philosophy or method for approaching the building of a category set and identifying the best standard reports for a clients' audience(s). As a client I wanted more suggestions from them in terms of how to best build a category set and more suggestions on the best reports to build from in for our managers, directors and board.

Normalization of data.

Too difficult to tune the tool.

Natural language can go too far - left can be a direction and the past tense of the verb leave - The tool assumed it was a verb.

Manual categorization is needed to deliver the best analysis. This takes a lot of time.

The Attensity tool is not user friendly. It takes time to learn how to create and manipulate queries.

The Attensity products are expensive.

The analytics are good but the user interface can be challenging to use. If you have a team of expert analysts and need really precise analytics then it can be useful but the learning curve can be high.

The way to create "categories" or "topics" is more cumbersome than with other platforms.

They eliminated some key external data sources when the acquired Biz 360 which made them a less desirable option for our company.

Filtering out bad data.

Response time from customer support.

Lack of account management and concern.

I used Attensity daily to respond to consumers on our brand page. Sometimes there would be a glitch, and the number of posts that were in the queue would not match up with the number of posts that were actually coming in natively. When Attensity is working perfectly the number of posts in the queue is very accurate, but it got to the point where it was hard to trust the tool. Many times we ended up responding natively on Facebook and Twitter to ensure that we saw every post.

Responding through Attensity on social media is sometimes tricky because often times the response window does not show the whole tweet or post. There was a lot of going back and forth between the native post and the post on Attensity. If there was some way that Attensity could better display the number of likes, comments, retweets, favorites, etc. that would make responding much easier.

The way that Attensity is graphically designed is very confusing with many folders for all the different brand pages and teams that own those pages. This would make things confusing while going through the high volume of tweets and posts that the brand page received. The page would frequently receive anywhere from 100-1,000 posts or more in the span of an hour. WIth the high demand for responses and the way the tool is organized, it was easy to miss important posts.