Lilt vs. Verint Speech Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Lilt
Score 8.0 out of 10
N/A
Lilt is an AI-powered language service provider (LSP). Lilt combines adaptive neural machine translation technology, an enterprise translation management system, and professional translators to allow organizations to scale their translation programs and improve the global customer experience. They purport to improve translation speed by 3-5x and reduce costs by 50% or more. Lilt HQ is based in San Francisco and is backed by VCs like Intel Capital, Sequoia, Redpoint, Zetta, and…N/A
Verint Speech Analytics
Score 8.9 out of 10
N/A
Verint Speech Analytics is a tool used to transcribe and analyze millions of calls to discover customer insights and improve contact center performance in the cloud.N/A
Pricing
LiltVerint Speech Analytics
Editions & Modules
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Offerings
Pricing Offerings
LiltVerint Speech Analytics
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
LiltVerint Speech Analytics
Top Pros
Top Cons

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LiltVerint Speech Analytics
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User Ratings
LiltVerint Speech Analytics
Likelihood to Recommend
8.0
(1 ratings)
8.8
(20 ratings)
User Testimonials
LiltVerint Speech Analytics
Likelihood to Recommend
Lilt Inc.
Lilt is a great platform for translating and reviewing content for mainstream languages that are spoken by a large number of people such as Spanish, French, etc. in which case the machine translation tool does a great job of adding the appropriate fluency, grammar, and punctuations. The QA checks also likewise provide apt feedback with rarely any errors. The only shortfall for Lilt is when the content to be translated belongs to any non-mainstream languages (such as regional Indian state ones) and the most noticeable errors are thrown by the QA check tools which have several long-standing unfixed bugs.
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Verint
It's not as appropriate. I'll go with the not first. That's easier if you're looking for call volume for specific volume questions and that's not speech. Speech is not going to provide you, like I said before, that absolute number of this is how many calls came in for this exact topic, why natural inherent limitations of speech, background noise and audio issues and strong accents like myself, so things like that. When we have had some departments come to us and some individuals have requests for insights from speech and we've said, and we discussed it for any request we receive, we have what we call a scope meeting to ensure that that request not only aligns with the goals and the value, it's going to bring value to the business, but to ensure that that is the best source of information for who's out. And sometimes they just didn't realize you can get it somewhere else. So if you're looking for actual call volume, actual numbers of the counts of what, that's not going to be the best source. It is the best source. I'd say when you really want to know what your customers, what your members are thinking, what are they saying? When you really want to know the voice of the customer, that is crucial because that interaction and listening to them is different than what the system can identify the tone and inflection and can identify the terms that they're saying that express joy or disappointment or dissatisfaction or negative emotion, whatever that may be. And yes, the system does an amazing job at identifying all that. For those calls, for example, where there is an accent, where there is background noise, where there are children and dogs in the background, the window's open because calling us from the car front, the freeway, none of those calls are really captured accurately. And so it's an entirely different insight. And sometimes you may have numbers, you may have data, but what impacts data, what brings the story together? I can give you numbers and say, Hey, we've had an influx of calls and the majority of them are talking about, they're expressing negative emotion regarding the Blue Shield website. Let's just say his hypothetical. I'm not saying that's what they're doing. So let's say they call and they have, so the metrics will tell us we're receiving these many calls, they hit the website category that we created, they're expressing negative sentiment, but is it going to tell you exactly what's wrong with the website? Nope. That requires human listening. So yes, the metrics provide great insight and I believe it provides a lot of direction. But when you provide to say to someone in senior leadership, those metrics, and then you also attach, oh by the way, this is verbatim a quote from our member regarding this issue. And that member says some things that are not very pleasant or they're truly expressing their genuine frustration and discontent that has more of an impact because it's not just a number, it's a human, it's the voice of the customer. So I think you need that whole picture to be able to present the scenario to be able to offer a solution. You can't offer the solution if you only have half of the problem or half of the issue. And I love that Verint Speech gives us the ability to do all that because then we partner with the analytics part with the desktop analytics and we can build triggers to know the actual counts and then we can bring that together with the voice of the customer and then present in an entire view so that informed decisions can be made.
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Pros
Lilt Inc.
  • Provide exact and fuzzy match feedback for translations
  • Provide step by step segmented workflow for translating
  • Great QA checks including Batch and Full to help detecting errors
  • Good machine translation feedback to help translators
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Verint
  • One of the things that I find extremely beneficial about Verint Speech Analytics is the transcription. Sometimes you have an hour call, an hour and a half call, and you don't have time to listen to an hour and a half call. The beauty is that we can find the transcription and then we can look in it. It specifies where if you look in the interaction details in the back of the call, you can actually see the transcription. You can see it'll identify where in the call, what line at what timestamp did that call hit your category and with what string, with what term did it hit. And that is extremely beneficial. And we're trying to go through and find those little points of, sometimes they're points of abrasion, sometimes there are things that are going really well. I love that we have a transcription. I love that we can also see the screens that is vital because a lot of times, and again, not that we're trying to find something bad, but the reality is in any industry, there's in any call center environment, should I say, there's call avoidance. There's always going to be some agents, it's just in any call center, in any industry, it happens.
  • Or sometimes our agents are just struggling. And if you see in real life, for example, a very high silence time, when we notice a trend, we'll start going into those calls and actually looking at those screens and seeing, is silence time call avoidance or could it be the agents are having difficulty utilizing the resources? Are the resources not clear? Is that what the delay is? Are they having trouble trying to find the answer? And a lot of times we found that too. We found they're searching and clicking and searching and clicking and it's because they just didn't know where to go. So that is a coaching opportunity. And sometimes it's a coaching opportunity, not so much in a positive way because they're purchasing things from Amazon. But I think, like I said, that's inherent in any call center environment. I do find the screens, the transcription, the trend analysis that's available within speech, there are so many things I could literally sit here and talk to you for quite some time.
  • We love it. And I'm even more excited personally now because I learned so much, as I was saying, about being in the cloud and being in that open-source environment where all of these enhancements that Verint has. And they're so often that they enhance their products and their offering now these little bots and AI to help with all of these different aspects, but that's only available if you're in the cloud and the open source. So there's a lot of benefit in being in prem, in net platform, which is where we are. And we were able to provide a lot of meaningful insight and guidance into a lot of different pain points in the company. But I anticipate, and I have full confidence, that we'd be a much more effective team once we're able to move into the cloud. So I'm very hopeful for that. I'm anticipating what else we could discover.
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Cons
Lilt Inc.
  • Provide greater quality feedback for non-mainstream languages such as Indian regional
  • Improve punctuation and grammar fluency for non-mainstream languages
  • Fix long standing bug issues in QA check reporting mechanism
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Verint
  • I feel like I could have answered that just last week, as good as you make it. So with that said, I'm kind of going to go back to getting with the NT team and fully understanding the way it works to know the best ways to go about it. So on that same flip side, I would say it was the transcription and then we've also had some call recording issues and some, because we've actually got a ticket open now for some duplicated calls and where it flipped the agent and the customer in the recording. So there's little bumps. So if I had to say any of those would probably be problematic, but just specifically for us, I can't speak to everybody, but the Verint team is very supportive and they're doing what they can to keep us in the loop and what they're doing to fix it. So we're doing, I think it's good considering
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Alternatives Considered
Lilt Inc.
No answers on this topic
Verint
Verint Speech Analytics stacks up well against workforce management, we use workforce management mainly for forecasting and scheduling. We selected Speech Analytics because we want to know not only why customers are calling but what is being said in calls. Sometimes customer might get angry or they might ask for a supervisor so when we need to look at escalated calls Speech Analytics helps us pick those out.
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Return on Investment
Lilt Inc.
  • Lilt is helping my organization localize its products to a lot more languages
  • Helps translating large content data like web pages with ease
  • Improves overall quality of work done and hence help gain more clients
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Verint
  • we have the ability to provide actual data to back up leaderships feeling that some agents are performing poorly
  • we have the ability to provide direct feedback to our Sales team regarding good and poor contract handling
  • we have actual recording regarding handling of client fees
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