Verint Open Platform

My main use case for Verint Open Platform  is mostly within the workforce management open platform. For workforce management, I specifically use it to look at agent real-time metrics. I use it mainly for scheduling, forecasting, and also performance tracking metrics, business metrics, and agent efficiency tracking.

The scheduling, looking at the agent workforce, assigning with the skill groups, and real-time metrics are very useful within the WFM.

The best features Verint Open Platform  offers are that it is easy to use and integrates well with other CRM  tools and within contact center applications. We have been very grateful for this, especially during our migration from other WFM, which was quite seamless. The newer platform allows for robust, easy-to-use scheduling and forecasting.

Verint Open Platform has positively impacted my organization by increasing the use by the supervisors for their agent workforce, allowing business stakeholders to easily access performance metrics and efficiency. Assigning skill groups and forecasting has been easy based on the business demands within the real-time queues, as well as looking at the incoming, inbound, and outbound contact centers, which has been very easy to use.

One improvement needed for Verint Open Platform is that the upgrades need to be scheduled, and there is a need for application improvement in terms of latency, as real-time takes time to refresh the screen. That is one of the improvements we would like to have. At this time, there are no other improvements needed with Verint Open Platform that we have not discussed.

I have been using Verint Open Platform for almost three years.

Verint Open Platform is stable.

Verint Open Platform's scalability is satisfactory, as we have not seen much in the way of performance issues. Initially, we had some issues, but after working with the Verint technical teams, those issues were resolved, and it is meeting our needs at this time.

The customer support from Verint is good and offers great customer support.

My customers previously used Aspect  WFM before switching to the newer cloud solutions, as we migrated from on-premise to the Verint cloud solution.

Since using Verint Open Platform, I have seen a reduction in manual work, with almost a 70 to 80% uplift from the manual effort and other WFM tools when we transitioned to Verint, which represents a very significant uplift and reduction in manual work. We definitely need fewer employees and have saved money, which can be good metrics, as well as saved time. I do not know the exact money saved, but there is definitely time-saving with the WFM.

I am not sure if other options were evaluated before choosing Verint Open Platform; I was not part of the decision, but I believe the organization has looked into other tools in the market.

My advice for others looking into using Verint Open Platform is that scheduling and forecasting are very important. We need to feed in all the data into the WFM so that we can see all the agent workforce and metrics in detail. The data we provide to Verint is very important to achieve the best outcomes from the platform.

Regarding Verint Open Platform's AI capabilities, we still need to explore how the data is shared across different platforms, and we need to have strict governance rules around the platform regarding how it will be used and what level of security it is built on, ensuring biasing and trust. Those are the main things we are looking to validate in the future for our customers.

The accuracy and reliability of Verint Open Platform's AI capabilities depend on the prompt engineering; how I ask about the details matters, so I need to structure my inquiries appropriately to get the best output. I still have not explored its full capabilities, as we are still learning about it.

I would rate this review an eight out of ten.

The main use case I have for Verint Open Platform  is the use of AI, both to handle the coaching part and real-time validation of what happens on the call with alerts to the supervisor when something is going wrong, as well as in the Speech Analytics  with AI part, where I can have data close to what is happening in near real-time. I can also ask open questions to the AI based on everything that has been transcribed, and thus have more certainty about what is happening in my contact center.

One of the use cases, for example, is activation in the healthcare area when the customer is dissatisfied and is going to open some kind of proceeding, for instance against the company, or a NIP proceeding from the Ministry of Health. The tool automatically generates an alert for the supervisor, notifying that there is a call that tends toward a proceeding, allowing the company to act in a more proactive way.

This greatly reduced the number of cases and proceedings opened with the National Health Agency, significantly optimizing the time of those who did this analysis before, very manually. Today they already receive this proactively and can act in a much more assertive way with these customers and agents.

There are a few features that I consider the best, one of them being this sentiment analysis, not only on the customer side but also an analysis of how the service is on the agent's side, giving a customer experience view and a pro experience view. You can have an overall picture to catch cases of burnout, for example, to intervene so that agents take a break or have a conversation to ensure they provide quality service.

I actually sell Verint Open Platform , and the customers who had this type of solution saw gains. For example, with the solution, especially Speech Analytics  with AI, they had a reduction in the number of proceedings the company received. The companies that implemented the Quality Bot saw operational gains, an increase in NPS , an improvement in quality, and more assertiveness in identifying which agents were not performing at their best.

Broadly speaking, I can share that these customers had a reduction in the number of people doing manual evaluation. The NPS  figure saw an increase of about twenty percent for the Quality Bot part, and the number of proceedings decreased using Speech Analytics with AI.

Points for improvement in Verint Open Platform are in terms of giving more autonomy to the end customer in terms of some features, which is already on the roadmap. Broadly speaking, the tool is very good as it is today.

Support leaves a bit to be desired, and I think it is an area for improvement that Verint has in the support part.

It is a stable platform.

It is flexible.

These were the first solutions we used with AI for these customers.

Everything was acquired through Avaya, Verint's partner.

We are their partners and resellers with an OEM solution to resell within Avaya together with Avaya solutions.

I would advise them to do a return-on-investment study together with Verint, as many of these tools make it easy to demonstrate this to the customer. Verint has some packages, like a try and buy, where you can use the tool for three months to show and see the results.

I do not have those numbers with me right now, but the experience, as I am the vendor and not the end customer, indicates that many times we have to be aggressive on discounts because of competition. For platforms where you can demonstrate a higher return on investment, it is easier to sell at a higher added value.

For these customers, we were competing with Genesys  and NICE.

Our customers use Verint Open Platform both in the public cloud and on-premises. The customers who are on-premises now, we are migrating all of them to the public cloud, so the trend is that everything goes to the public cloud, while we have both environments.

I believe Verint Open Platform is an excellent tool, but like every tool, there is always something to improve and something to progress. In terms of perfection, I believe that to reach a ten, you need a one hundred percent platform, and I think nine is excellent. I would rate this review a nine overall.