The New Data Unification Imperative

Summary

Vikas Bhambri, Vasili Triant, and Beth Ziff discuss the importance of data unification in customer service in this webinar. The participants discuss how real-time data helps solve customer problems during help conversations, rather than analyzing the data after the fact. They also discuss the need for data unification across different customer service channels, the impact of data unification on customer service metrics, and the future of customer service metrics. Finally, the participants share their thoughts on the role of different stakeholders in an organization, including marketing and IT, in ensuring effective data unification.

Key Takeaways

1. Real-Time Data Analysis: The use of real-time data in customer service can help solve problems during conversations, leading to immediate resolution and improved customer satisfaction.
2. Data Unification: Unifying data across different customer service channels can provide a more accurate understanding of customer behavior and the effectiveness of various channels.
3. Impact on Customer Service Metrics: Data unification can significantly impact customer service metrics, providing a clearer picture of whether issues were resolved or if customers simply switched channels.
4. Future of Customer Service Metrics: The future of customer service metrics may involve a combination of customer effort score and the impact of the customer’s interaction with the customer service team.
5. Role of Different Stakeholders: Various stakeholders within an organization, including marketing and IT, play crucial roles in ensuring effective data unification. Their collaboration can lead to more effective customer service strategies.

Transcript

Hi, everyone. And welcome to the new data unification imperative. That is a very lofty title for a conversation between the three of us, but we’re gonna get into that and what really that all means.

My name is Beth Ziff. I’m part of a premier response. We provide omnichannel contact center support to companies who want to differentiate themselves in the service space. And I am very, very excited to be joined by Vasili and Vicas, who will introduce themselves and tell you where they’re from, and then we’re going to get into that debt lofty title.

So, Vasili, let’s start with you. Thanks, Beth. Glad to be here today. I’m Vasili trying.

I’m chief operating officer at UJET or a cloud contact center application and happy to be here.

I guess that’s me. So, Vicus Bambry, responsible for sales and CX at customer, which is a CRM for customer service platform. And looking forward to the conversation Beth.

Well, thank you, and thanks for joining. And obviously, you can tell that we all kind of have this relationship in need. We use each other’s services, which is kind of cool and exciting. So I think we are the right people to be discussing this topic.

So, because let’s start with you, and let’s just talk about this. What does this mean data unification? You know, we collect data from all different places. I know that we have bone system, and then we have CRM tools, and maybe we have some reporting tools, and we have other technology that we may use, and so what?

So we get it. We put it all together. We create some reports. What does this all mean?

What is this unifying data across multiple sites thing about? I think you hit the nail on the head there with the last statement around, we do it in reports. And I think historically, when we’ve looked at data about our customers, it generally sits in a data warehouse or it’s available to our marketeers, right? Because that’s where we’ve been most focused on leveraging that data.

The data unification story when it comes to customer experience or the contact center is something newer, right? And it’s something that we’re now looking to operationalize all the data that we have about the customer so that not only can we deliver a seamless experience through the agents, but also through automation as well. So, historically, you know, data set in a black box and you got to use it, you know, once in a while, you’d run a report for a contact center leader and you’d let them know, look, This is how many calls you’re getting in, these are the types of customer issues you’re having, etcetera.

Now it’s in real time, and it’s actually something that can not only be actioned by your contact center leaders, but actually by the folks on the floor as well.

Actioned in real time, that’s kind of very interesting. What do you think about that facility? How does that work?

Well, I think that it’s a perfect topic. It’s something that we can all actually personalized as well, because in our own lives whether it’s dealing with products or services or for some reason, I always come back to an analogy of of automobiles. Right? It’s if you’re looking at real time data that’s going on within your car, then people could actually know that you’re having a problem and solve that problem as it’s happening versus what we’re used to through decades is your car has a problem, you take it in they plug it in to a computer, it pulls down the data that says, here’s the problem and then you go through the fix and probably more damage has happened at that point.

And you only know what happened after the fact and then you get to fix. So you can take that analogy and apply it across every other experience. So when you get to customer experience, it’s around you are looking for answers, you are looking for information, trying to find something that you wanna buy, or you’re trying to fix a problem, or you’re speaking with an agent live.

Knowing that you can solve that problem in that moment has become part of our ethos now and part of every action that we want to have because we’re like a real time society. Right? Everything has to happen now. But what ends up what’s been going on for a long time is like, you know, Vika said, it goes into a black box. We analyze it after the fact. So now you have the real time information, you can determine intent, what the user was looking at online, looking through knowledge bases trying to find that answer, and if you know it real time, you can actually solve the problem in that conversation.

Versus you look at it after the fact and you analyze, okay, that person called in, they were looking at these things, and you have great meetings internally within a business. And analyze, oh, could have made our knowledge base better. We should have answered the question a little bit differently. And that’s how we’ve been operating. The reality is, taking that real time data, implying intelligence to it, and and actually making that happen right now while we’re talking versus post the conversation.

So that’s interesting, and that’s great because that can help build loyalty. That can generate revenue. That could do a lot of things. I can think about a lot of ways we could leverage all of that and putting it all together. So that’s very interesting.

So what I’m curious about though is what we talked about data unification What does that mean? I’m getting all those pieces of data. Aren’t they connected? Aren’t they unified? What is this data unification? So facility, I’ll start with you, and I’m going to ask you the same question, Fikas.

Well, so data unification like the true ideal around it is having a common data lake, right? So we’re going to call it a data lake, but essentially your data is in one place. And that way you have a single source of truth.

One place where you can put intelligence and action on top of, and people can look at it, whether that’s agents, supervisors, you know, other managers within the business in order to determine you know, what is it that we need to be doing. Or if you’re gonna apply artificial intelligence on top of it that is looking at one place to grab or transcribe or action that. What happens today is data unification because of limitations in really technology platforms out there has become let’s integrate all these platforms together. So every application actually has its own database.

It has its own data lake. So to unify everybody starts doing API push and pulls to try to make it all happen. Now there’s things that get lost in translation, when that happens, and there’s time lags in those things, right? So the most common thing is everybody wants to integrate a contact center platform with a CRM such as customer, but it’s like a thirty minute push and pull.

So if I’m trying to action something now, in the conversation you and I are having.

But that data is not gonna get to customer for thirty minutes.

What conversation am I actually analyzing? So now I’m going to analyze it in the contact center platform would be the solution, but then the agents looking at customer interface.

So if that data unification isn’t happening complete and creating a true single source truth, real time, then all the artificial intelligence that actually apply on top of it is happening at the wrong place. And that’s something that has to change in the space. That’s something obviously that we’re leading at is real time data streaming, not trying to link two databases together, but truly create one single source of truth. So in this relationship here, customer becomes the single source of truth. We put all the information in one place. Like let’s not be religious and egocentric about like I have to own the data, you have to own the data, like the agent is looking at that data in the CRM, let’s put it all in one place and let’s send it there real time. Then let’s apply intelligence and action on top of it, ultimately leading to all of us having a better experience, right?

So Because before you go, before you respond to that, how what am I is the rep though? So if my team What are they looking at? Is that do they have to still have multiple things open? Is it just one place?

How are they inputting this stuff so that we’re getting it out in one source? That’s kinda interesting. That’s a great question. Bebo.

Oh, go go ahead, Vasila. Oh, sorry. I was I was sorry. So it’s actually customer with UJET embed in it.

So UJET is the is kind of the routing mechanism, but customer is the source of truth, is the system of record. So they’re just looking at one interface combined. Sorry, Vigas. I’ll I’ll let you know.

No no problem. Think Beth, you bring up a good point, right? If you walk on most contact center floors today, you will see somebody sitting there, and obviously, if they’re not sitting at home today, but maybe even if they’re sitting at home, most agents are still operating from multiple monitors.

Right? That is what I call the data unification strategy of the nineties, which was, hey, we’ll just give them multiple screens. Right? And on those multiple screens, they’re gonna have multiple applications.

They’re gonna have a ticketing system over here, an order entry system over here, maybe a social application over there. So now when you, as a consumer, call in to that contact center, I love it when an agent tells me, and we’ve all had this experience. I’m sorry, our systems are running a bit slow today. And because all of us are in the business, we all chuckle because what we know They’re buying time because they’re literally trying to navigate multiple applications on multiple screens.

Right?

So What data unification really means in the contact center is a single agent interface. Which they can work from that gives them all that conversation data, whether it’s telephone calls that are coming in, whether it’s chat messages that are coming in social interactions, emails, it gives me an understanding of who that customer is, So I wanna know who Beth is. What’s her value to the company? Is she a first time customer, a long time customer?

I want to know what order she’s placed. And as Vasili mentioned before, maybe I want to know that you recently were trying to serve self serve on the website but we’re unable to. So now I’ve got that complete view of you so I can have an intelligent interaction with you to try to resolve your problem without asking all those mundane questions that frankly consumers hate and agents hate, which is Who are you? Why are you here?

And how can I help you? Right? It’s getting right to the heart of it. Right.

So many things so so interesting. I think one thing that stands out for me is, yes, everybody wants that, and they don’t wanna have to answer those mundane questions and things. But I wonder about as because we’re so security conscious and we have to worry about all of these new rules. Don’t reach out to me, don’t call me, don’t market to me, all the don’ts, lose my data.

Where do you store my data? So what do we do about this? I guess I I throw this to both of you. What do we do about security?

How do we maintain that? How do we know we have all of this at our fingertips, but elegantly use it in the conversation and and and make that experience work without scaring anyone, and ensuring that we have data integrity.

Well, you know, my my position on that is, you know, leave that to our friends in marketing. Right? Reality is When we’re looking at this from a customer service perspective, the customer has purchased from you. They have signed up for a service they’ve given you, and they’re aware, right, through your terms and conditions, and through their entry forms, etcetera, that they’ve given you certain data components, right?

Whether it’s their name, address, phone number, etcetera? And of course, the orders that they’ve purchased. Now, if you’re using that data to deliver a better experience for them when they have an issue with said product or said service then that whole, you know, data question is less of a question. And, you know, yes, you still have to comply with GDPR, CPA, HIPAA, all those regulations, absolutely.

But remember, we’re looking at this of a customer service experience for somebody who is purchased from us, not blindly kind of marketing, not that marketeers do that to somebody who’s never purchased or experienced or maybe even signed up for any interest in our offering?

Yeah, okay, that’s so interesting.

So Beth, I’m gonna I wanna add on that a little bit. Sure. So I think that, you know, Vegas is absolutely right around, you know, you have the information you have kind of consent on using the information to make that experience better. One of the challenges though that exists in in the space where I was talking about everybody creates these databases and they try to link them for, you know, companies that are looking to kind of unify their data.

You have all these applications out there and each one has a system of record and you’re trying to link them all, you actually now have to worry about security and privacy around every one of those data stores. And that, you know, you know, as Vika says, you still have to do GDPR and PCI and HIPAA. Mhmm. Reality reality is Two things, not everybody does all those.

So you may have applications that differ in both, you know, what their certifications are and what they call in scope But also you’re having to make sure that you have four or five or six different data repositories that are secure. And so in our world, the message when we’re talking with customers, true daddy unification is you look at one system of record, one place where the data is put into. So what we do between UJED and customer is take two typical data sources. Across the entire industry in the entire world, you take a CRM and a contact center, there’s always two data sources.

We unify it, we create the only single data source between a CRM and a contact center platform. And then what it is is you’re only focused in one place. You only have one area where you’re trying to make sure that I’m protecting that PII information. So one is how I use that PII information.

The second is protecting it from obviously right now like cyberattacks are on the rise. Right? Data breaches are on the rise. It’s kind of the the new, you know, currency of, I mean, call it like a cyber warfare, right?

And that’s important. And it’s going to rise in importance and being able to keep one focus is gonna help companies as they scale and they grow geographically as well as domestically.

Absolutely. You know, It’s interesting. So we have this one source then, and we talked in the beginning a little bit about reporting. How what are we getting out of this?

Let’s talk about output of that and we we mentioned that I think or maybe I read this or you said this about real time. I can get it now. I don’t have to wait till tomorrow to get that information. I can action something immediately.

Let’s talk about that. I I’m curious to hear both of you from from both of you on your thoughts about reporting what should we be even looking at in measuring now that we have this one source? I I I’m interested in that. I think the traditional metrics go away.

We don’t care how fast something is happening. What difference does it make? If I can do it in ten minutes or twenty minutes, if it’s a meaningful interaction, and it’s a meaningful experience. And again, for me, I’m building brand loyalty or I’m getting you to buy more or just sort of advocate on behalf of the company.

I’m turning into a you into a brand ambassador. So those are the kinds of things that, to me, are the measurable more important things So talk to me about reporting and what’s the advantage of that one source and real time. Sure. I think you know, when I think about the data unification strategy around the customer, I think reporting is frankly a secondary benefit, right?

Because, frankly, you can get data unification through reports, right? I mean, even though age myself a bit. Right? Even if I go back into the days of crystal reports, I could connect the crystal report to multiple data sources and get quote, unquote, single view of the customer.

The problem is, I couldn’t do anything with it. It literally sat in that report where, you know, whether it’s a data analytics person or a marketing person or somebody would have to go and do something with.

Now, you know, as as Vaceli said before, by creating a a single system of record.

Really cool thing is how you can operationalize this. So let’s take a couple of examples.

One, your consumer comes to your web Right? And a lot of consumers nowadays wanna self serve, you know, they would love to solve their problem themselves without having to engage an agent, right? So now, once that person has identified themselves, maybe by going through your app, or your secure portal, or maybe even volunteering, here’s my name, and my email address, etcetera. Once you identify them, if you have that single repository, you can identify what type of customer they are and perhaps even offer up to them proactively solutions like Oh, we saw you just purchased something recently.

Are you hearing about this pair of jeans that you just bought two weeks ago and show them their order Right? And maybe they say, yes, and then you could say, well, what would you like to do? Would you like to refund? Would you like an exchange?

And so allow them to self-service Now, if you don’t have that single view of the customer, you don’t know who they are and the fact that they have that order, then you can’t have that conversation. So that’s one example.

The second is how do we take the data that we have about the customer and then use that to either prioritize their issue or route them to the right team. So imagine this, somebody calls into your contact center, and we identify that they are a high value customer who just purchased their first item. We wanna prioritize them over somebody who, you know, is a low value customer, right? However, you define that in your business. So you can do those things once again, if you understand who they are. And, you know, the agent view, we talked about earlier, that single pane of glass allows them to also have intelligent conversations around the customer and their issue in potential solutions, because I now know who you are. I know what I know that you have a flight that’s leaving tomorrow so you understand the urgency of your situation.

And I understand that you’ve booked with us previously. So I understand all of that so I can have intelligent conversation. Right? And last but not least, this whole concept now that we’re seeing more and more of is this whole concept of proactive service, How do I use my data once again? That I know that you’re a customer who has purchased this product from us, and maybe the manufacturer of that product has, you know, issued a recall. So how do I send out a notification to all those customers to say, look, Before you’re even aware of a problem with the service you purchased from us, we’re getting ahead of it, and we’d like to replace that for you. So these are some kind of real world use cases of how once you embark on a data unification strategy, you can do some really cool things and fundamentally alter the customer experience that you deliver to your customers.

I absolutely agree on all the points Vic has said. I think the other part as you’re kind of alluding to Beth is the traditional contact center metric I mean, they’re legacy. They’re a thing in the past that focused on contact center as a cost center right? So average speed of answer, average hold time, talk time, all those things. It was all around like how do I reduce the costs of my contact center because labor’s expensive and hence why we’ve moved into kind of all these channels.

Reality is if we all pull ourselves out of our professional lives and put ourselves in our personal and when we’re dealing with brands and services, we really can simplify the question we’re all trying to ask ourselves. Right? What matters the most? And the thing would be for me is number one, first contact resolution.

And then I mean, I guess you could call it sentiment, net promoter score, you know, repeatability, right, which you could also pull from you know, how many other times do they buy products or services. But the question and when you end that conversation, whether it be contextual like, you know, SMS, chat social or voices. One, did I solve their problem on the first go? Two, were they happy with that?

And you could either get that through sentiment or you could I mean everybody wants to do surveys, but I mean I’m so busy in my life every time United or anybody asks me for a survey, I never do it, right? So the only people that answer surveys are either the ones that are ticked or I don’t know, they wanna sit there and maybe they think they’re getting a five dollars Starbucks gift card or something if they answer the survey. But reality is, you know, are you solving that problem? Two, when you’re solving those problems and you look at what the reason for whether the disposition or the actual interim action was, is there a correlation across that?

And does it stem to something bigger that you can’t control in the contact center? Something from a production line or something from a marketing message or something environmental out there that’s that’s causing your service a problem, you could then correlate that and like Vika said, you could get proactive to future customers about about those problems.

The other thing is, and this is a little bit lost right now because there’s so many amazing marketing messages around all these platforms that you can bolt together and create automation.

Is, you know, there’s a huge thing about deflection right now. And deflection stemmed out of what Vicka said is people want like us as customers want to self serve. So the technologies are coming and saying, I can deflect live interactions and save you money. But the question is, are you actually really deflecting? And this is kind of the next evolution that we’re seeing with data is did you actually deflect me or I just came in through a different channel? If you can unify that data and unify the platforms, you will be able to correlate Did I actually automate FCR?

Or did the the user just come in through a different channel? Right? The way the metrics are done today is did they move from that automated interaction to a live channel?

And I can tell you from my personal experience. I typically abandon at that point and I just do something else. Right? I call in or something something else.

I had an issue the other night with watching one of these goofy fights, you know. My kids all wanna watch the Logan Paul versus Floyd Mayweather, right? And showtime. No resolution fight.

Yeah. Yes. Yes. The no resolution.

No resolution even on the show time problems that were happening. Sorry, show time if you’re listening, but obviously major blunder And you know, I went in to like try to figure out like what’s going on because my son has like twenty friends over to watch the fight, And I’m stuck in a, you know, a chatbot to deflect and guess what? They deflected me because it kept going in a circle. And I never got to anybody that can answer my problem.

It never even got to a live person. And that didn’t solve my problem. Definitely didn’t make me want to subscribe to Showtime or watch a pay per view event on Showtime ever again. Mhmm.

And that is an example a real life example of things that we see heated over and over again in the space. And the goal here is that I make you happy and do you want to contact me Again, because then I’m gonna buy more products and services. Right? And lifetime value has overtaken cost of a contact center.

Some brands have gotten it a lot. The majority still haven’t. Right? The majority still haven’t gotten that lifetime value is that key metric rig.

The cost to acquire a customer is less than the cost of losing that customer. Right?

Well, I think one of the things you mentioned is anytime that you have any metric that, you know, has been around an industry for so long, the practitioners figure out how to game the system. And I think, you know, FCR is a great example, right? It’s been around so long that I think practitioners know how to set it up so that when they’re presenting to their CEO or executive team, they’re like, look, our FCR is fantastic. But the reality is what does the customer actually have to experience? And I think that’s why you’re seeing more and more people transition, for example, to customer effort, because look, if you’ve resolved my problem the first time I reach out to you, but I had to get transferred to three agents, and I had to, you know, you know, got you know, went through an exhaustive list of, you know, password resets and, you know, rebooting my device and all of that.

You know, that’s not going to want to make me purchase more from you either. So I think, I agree with what Vasili is saying. I think the future state is going to be a combination of customer efforts score? How easy is it for the customer to get that resolution?

As well as what is the impact that the interaction they had with the, you know, with the contact center team, with the customer experience team, happen post, are they purchasing more? Does Vasili go and purchase the next fight, right? Because you resolved their his problems so seamlessly.

And I think those are the two things that people are going to start being held accountable if they’re not already in that state today.

That is so very, very true, and I totally agree that is where we’re going. And and the other thing that I think is so interesting is we’re talking about this and I’m always thinking about we should mention marketing, we talk about operations, obviously the IT to make all of it work, there are other stakeholders in in organization that have to buy into this notion that we’re talking about. Whether it’s legal, whether it is data privacy and security, which we touched on a little bit, maybe it’s R and D or quality. Those are key stakeholders that are interested in what’s going on in some of these outputs and the data capture and things.

So I’d also just love to hear your thoughts about that. And how do we sort of sell this to those stakeholders? Because sometimes the service organization is the one that’s using the tools and experiencing it, but they report up through those other pieces of the organization and they have to get that buy in and they have to show that value. Whether it’s the dashboard reporting or, again, just sort of even resolving for these issues that we were just talking about.

So we have lots around that. I think you’re absolutely right. And I think that’s what, you know, Vasili was alluding to earlier is you have to have a secure scalable, cloud infrastructure, you know, that complies, right, at the very basics with a lot of the PII you know, regulatory requirements, but on the flip side is how does this data not become like a black box, right? And I think that’s one of the challenges with a lot of, you know, what we call the SaaS one point o vendors that are out there, is the data really becomes something where and, you know, because of the the business models of those businesses is they wanted everything to sit in their data repository, and they wanted to hold you to it.

And I think, you know, the approach we’ve taken is the data belongs to that particular company or brand. And we want to make it, as easy as we want to make it to get data into our platform form so that you can do all the amazing things we just talked about. We wanna make it super efficient and effective to get the data out of the system so that you can then do your analysis whether it’s on an operational level for reporting, whether it’s a data warehousing, archiving strategy, whether it’s for legal and compliance. Right?

Because it’s amazing. Like, the SaaS one point o vendors would tell you we’re only gonna hold your data for two years, and you’re like, wait a minute. The financial authority expects me to hold on to data for seven years.

Oh, well, you need to get data out of our system, and you’re like, that’s virtually impossible. Right? I need to run all these scripts and reports and batches. And so from our standpoint, we absolutely want to enable our customers to comply with those expectations. So we allow you to stream out in real time, and real time is another, you know, kind of thing we talked about earlier. Out of our platform, every single conversation that takes place with a customer, any change to their profile information, any change to an order, all of that in real time so that you can then comply with whatever standards you’re held to.

So we just have oh, go ahead, Vasiliy. We go No. No. You go. I was I was basically gonna agree with Vicus across the board there.

So I I don’t have too much more to add on that one. We’re all in agreement with that. Well, I think we’ve covered an awful lot. We’ve given everyone many, many things to think about.

And I I will throw it back to you, and Vasili will start with for some just some closing remarks because this has been really enlightening for me, and I’m sure for our audience as well about things to think about, what where we are going as an industry and how and the tools to get there. They’re here. We could be using them. So, Vasili, I give it to you and and go from there.

Beth, you said it. There are tools that are here and that we could be using them. So the the limitations that existed as, you know, Vick has called it one point o. We’ve kinda seen two shifts in cloud technologies now, so we kinda like cloud two point o and and sorry, cloud one point o and cloud two point o, but there’s been a dramatic shift.

And if you architect the product appropriately for the different use cases of the customer, one is solving or care problem, but also like you mentioned, there’s engineering, there’s security, there’s IT, like there are a lot of things that can be done differently. And the ideas people have, you do not have to sacrifice and create limitations because you just decided to choose a couple vendors that that’s how they architected their product. There is a new wave of technologies that solve these problems that truly unify the data that put real time intelligence against this, to solve those problems, doing it securely and frankly scalably.

And there is messages about data unification in our space, specifically in the UJET space of cloud contact center, there is no one doing it. They’re creating their own systems of record. There’s a war between do you put it in the CRM or do you put it in the contact center vendors want it with them?

CRM vendors want it with them? Reality is we realize that customers want it in a unified system of record, predominantly the CRM, and we’ve said we’re going to architect our platform to solve that case. It’s here, it’s available today and you don’t have to encompass those limitations of multiple data stores anymore.

So in Vickus?

Yeah, I think if you’re sitting there as a practitioner and you’re sitting there and say, okay, today I am kinda where Vickus was talking about earlier. I met this multiple desktop, multiple monitors, multiple applications, and what what we’re talking about sounds great, but it sounds like a holy grail.

The question is, how do I get from a to b? And it really is a crawl walk run approach, but not in a crawl walk run like, oh my goodness, this is going to be a three year change management exercise. Right? I think what Vasili was talking about is the way we’ve architected our platforms to come together a as one between customer, but then the ability to seamlessly bring data in from these other systems, your e commerce system, your reservation system, if you’re an airline, etcetera, all into one is not something that is going to take a tremendous amount of time and effort.

So, I think a lot of times, particularly in the contact center space, we get to the position of yes, we know we need to do something but it sounds like a lot to swallow. And the reality is people are doing it. And effectively, if you’re not doing it, your competitors are going to out steer you, because we’re seeing further and further competition on the acquisition side so customer experience becomes extremely vital to the long term success of a business.

Thank you. This has been a great dialogue, a great conversation.

I hope that those of you who are watching continue the dialogue and and reach out, and I’m sure you wanna have many, many questions but everything is here. It’s you have to get started somewhere. I think you have to start with one. I love that.

It’s simple. Just start with one. I love it. The tools are here. So Hopefully, we’ve identified the new data unification imperative.

I know we have.

See you again. Thank you so much, Beth. Thank you very much Vasili. You’re welcome. Thank you, Vikas.