Subhasish 0:01 So if you are billing dispute with one of these public safety companies, that can be handled. Right? What they can't compromise is the availability of the network. Right? We pay off it. And we'd know, like, hands down, there is one network in this country that, like, trumps all of them when it comes to reliability of it. And that's where we kind of and with what does network slicing truly offers is with just a product revolution on top of it, I think, is the key. Objectivity, to some extent, we're all human. We're, like, subjective, uh, to our thoughts and biases. But being objective, trusting the data a bit more. However, when I joined around eight years ago, we used to have a we have to go to our central offices just to see how the cable is laid out, how the machines are. So you are not looking at a product out in a spreadsheet or somewhere. You know actually how the product will work.

Stephanie 0:58 Hello, fellow insight seekers. Welcome to the Curiosity Current, a podcast that's all about navigating the exciting world of market research. I'm Stephanie Vance.

Subhasish 1:08 And I'm Matt Mahan.

Matt 1:09 Join us as we explore the ever shifting landscape of consumer behavior and what it means for brands like yours.

Stephanie 1:15 Each episode will get swept up in the trends and challenges facing researchers today, riding the current of curiosity towards new discoveries and deeper understanding.

Matt 1:26 Along the way, we'll tap into the brains of industry leaders, decode real world data, and explore the tech that's shaping the future of research.

Stephanie 1:33 So whether you're a seasoned pro or just getting your feet wet, we're excited to have you on board.

Matt 1:39 So with that, let's jump right in.

Stephanie 1:42 Welcome to the Curiosity Current. Today, we're thrilled to be joined by Subha Nanda, director of customer insights and analytics at Verizon. With the wealth of experience in leveraging big data, marketing analytics, and machine learning, Subha has led groundbreaking customer retention strategies at one of the largest telecom companies in the world. Subha's career spans various leadership roles in strategy, business transformation, and marketing science, where he's been at the forefront of Verizon's evolution in delivering exceptional customer experiences. In today's conversation, we'll dive into how technology and insights come together to drive customer retention and loyalty, and how brands can stay ahead in this ever evolving landscape. Subha, welcome to the Curiosity Current.

Subhasish 2:27 Oh, thank you, Stephanie. Thank you for having me.

Stephanie 2:29 Yeah. We're excited to chat with you. So just jumping right in, if I can, in your role leading customer insights and analytics at Verizon, how has the intersection of data science and customer insights evolved over the years? 0:02:27] Subhasish: Oh, thank you, Stephanie. Thank you for having me. Yeah. We're excited to chat with you. So just jumping right in, if I can, in your role leading customer insights and analytics at Verizon, how has the intersection of data science and customer insights evolved over the years?

Subhasish 2:44 Well, I've been in this space for it's close to seven years now, and we could see oftentimes in past. When I say in past, not even, like, five years ago. Data science and analytics used to be a team in marketing. It's just as a team. Right now, they are the driver of marketing operations. So we can focus on retention, but there is both side of it too. But in both both the cases where marketing was mostly driving the operation, we have the traditional marketing managers, strategist. They usually believe on, like, certain kind of programs and then come back to and tell the data guys to tell what they're looking for. Whereas it has completely pivoted to a point where we start with analytics, understand the market space, and understand our customers, what they're looking for. And then most of the time, even the strategies are driven by this. So we probably over the next, uh, few quest interactions, we'll go over certain definite cases. But the head of our marketing operation at this point is the person who actually drives the analytics main site. So it's data being most of the strategy, most of the operation even is being driven by the insights rather than insights being playing as a, you know, just a hitting block.

Stephanie 4:05 Got it. So almost bringing that bottom up approach to what the strategy should be rather than taking that top down a priori, like, we have an idea. Right?

Subhasish 4:15 Yep. We move from more anecdotally thinking. Anytime we have a question, like, I feel like no customers are looking for this. We move from there to let the data speak what our customers are truly feeling. Right? Both from predictive side and analytics. Right? So more both on analysis going back three years, four years, and trying to understand how our customer behaving to what we think this particular scenario or this particular customer would be.

Stephanie 4:44 Got it. Can you talk a little bit about you've talked about how AI and machine learning are sort of, you know, part of the world that you work in. How do you use these technologies in your day to day work or these approaches?

Subhasish 4:58 I don't want to really mix data analytics or data science with AI. AI, more you are looking at taking certain actions. But the big part that existed, and even without the generative AI, was the data analytics space, and that evolved first. Right? And that's your

Stephanie 5:18 Sure, Sean.

Subhasish 4:58 I don't want to really mix data analytics or data science with AI. AI, more you are looking at taking certain actions. But the big part that existed, and even without the generative AI, was the data analytics space, and that evolved first. Right? And that's your

Stephanie 5:18 Sure, Sean.

Subhasish 5:19 I usually work on is very focused on the data analytics or data science side. And, again, we have evolved in terms of how advanced algorithms have become, how advanced our processing has become. Right? So if you are running data models in a old, like, a data ma suite, you hire limited capabilities versus if you're running it on GCP or AWS depending on what you pop up. You get more access to newer newer technologies, newer platforms, newer more complex algorithms, actually coming up with the your predictive models. Same thing on analysis side. Right? So, traditionally, we have gone with, say, Tableau or PowerScale or PowerPoint. Different visualization analytics tools that historically has been used. But go moving from that to something like Looker, something like AI powered analytics where you have the data more of uh, horizontal datasets that we have built out, very denormalized sets, and we can ask independent questions rather than having built a Tableau view and looking at that static set. You can actually create your why do we have Tableau reports? Right? On on the analytics side, we have a Tableau report so that we can look for anomalies, we can look for trends, and things like that. Whereas we have now tools available to us where they will do the anomaly detection for us because we get limited by what we can see or how we synthesize the report. Right? We are often our ceiling is to the point we can analyze the particular report that we're looking at. Whereas the AI models who can scan through the data, scan through the report, and give us the insight that who the questions that we might not might not have been asking. I think that's the key distinction between just the p, p, or, you know, as I said, like, two stages. One was just processing the volume of data and the complex ways of processing the data. Then on the analytics side, the new tools that we have, more on interpreting those data to more, what do you call, systemic way rather than, you know, depending on a particular leader's interpretation of the data.

Stephanie 7:29 Definitely. So I'm curious, especially with the like you said, with generative AI being used more to, like, interpret or to spot those trends and see those trends maybe before you. What does that free you up to do then with your time? Like, how have you what does that level you up to do?

Subhasish 7:45 Oh, pastor Paul. It's not just freeing up the time. It's actually doing a much better job than you.

Stephanie 7:51 Yeah. Great point. Yeah.

Subhasish 7:53 No matter how objective we want to become by the just human nature, we have certain beliefs or that certain what I'm missing the word for it. But, uh, preconcept preconceived notions.

Stephanie 8:05 Like ISC. Yeah. Yeah. I'm looking han you. Yeah. Great point. Yeah.

Subhasish 7:53 No matter how objective we want to become by the just human nature, we have certain beliefs or that certain what I'm missing the word for it. But, uh, preconcept preconceived notions.

Stephanie 8:05 Like ISC. Yeah. Yeah. I'm looking

Subhasish 8:07 at a report. I'm trying to find something that I know is there even though it might not be there. Right? But whereas the AI platforms are doing a better job doing that synthesis with true objectivity. Right? That's a better job that they're doing in the first place. Second, I can then focus on what does it mean. Yeah. The part of it is, okay, we have a trend in certain customer segment who either know higher churn or higher growth. What particular data points that's the trend the AI engine tells me. And now I can focus on a couple of things. How do I communicate that upstairs, right, to put it in the hand of the real decision makers? And second, contextualize them, right, and hand it over to my marketing partners who can come up with ideas on how to address them. But now take advantage of it depending on what you're talking about. So that's, like, the true value addition on top of it.

Stephanie 9:00 Yeah. That makes a ton of sense. To switch gears a little bit, Verizon has made significant strides with its customer first strategy. I think it's pretty well known, especially, like, with the introduction of the groundbreaking initiatives like three year price lock and free phone guarantee. How do customer insights drive the creation of these types of offerings, offerings, and what impact have they had on loyalty and long term retention for Verizon? I think it's pretty well known, especially, like, with the introduction of the groundbreaking initiatives like three year price lock and free phone guarantee. How do customer insights drive the creation of these types of offerings, offerings, and what impact have they had on loyalty and long term retention for Verizon?

Subhasish 9:25 Those couple of programs that you mentioned, they were driven by certain insights and looking at going from two years to three years. What does it mean? But it also has some strategic ideas behind it. Right? So you look for not just, you know, why you are and let me give you an example for two years versus three years. Right? Uh, there was a time when Apple, every new version of Apple, has this huge drive from people. People used to, like, stand in queue for two days, three days to get a new iPhone. Right? And Samsung or other other Android devices were, like, far behind in terms of the technology. And they were even when they evolved, devices used to last for, like, a year, two year before they become obsolete. That's no longer is the trend. Right. Right? People hold on to their devices longer for a couple of reasons. It's almost I won't say that plateau in terms of the like, we have maximized to the point like, right now, all our phone delivers us Ultra HD streaming, right? All the stain qualities and all that. Even if they increase that by a bit much tomorrow, eyes and mind able to interpret the difference? Probably not. Like, we have reached the diminishing return of investment in terms of the investment into the devices themselves. So for one reason that they're actually much better, like, durable. If you look at the screen, the construct the physical construct of the phones are much better today than they were, say, five, six years ago. And software and technology wise, they have kind of reached that point of low marginal return on investment. Right? When you are seeing those two trends, and we identified that a few years ago, the people are holding on to their devices. Why two year price warranty was or two year device log was there before? Because every two years, people used to update their devices.

Stephanie 11:13 Yeah.

Subhasish 11:14 So instead of two years, if you give it three years now, you know, you get it it works out well for everybody because, again, you do not looking to upgrade your device in two years. You can hold on to a device. You get a better price for it. Right? And it's actually financially works better for us too because, again, devices are expensive for carriers. So that's, like, one of our bigger cost base. Right? So if we can extend the device for the customer, we get them for three years, and then customers pay much less for it. Right? And we can build on or we'll probably will get to it, like, how phone line itself has become kind of commoditized. So you look for services on top of it. So longer do you listen you are with the customer, you understand them a bit better, and you can tell them what this customer is truly looking for. Phone a mean to their need, and their need could be much more than just talking a telephone line. lf has become kind of commoditized. So you look for services on top of it. So longer do you listen you are with the customer, you understand them a bit better, and you can tell them what this customer is truly looking for. Phone a mean to their need, and their need could be much more than just talking a telephone line.

Stephanie 12:08 Yeah. Absolutely. It's so interesting to hear you talk through that. I worked in telecom. I actually worked for a mobile manufacturer. It's been about ten years. And at that time, you're you're it's it's so different than what you're talking about now. You're right that, like, every year, just the the iterations that were happening were large and big and would take your phone so much further. And so even waiting those two years could be kind of brutal, but it doesn't feel like that anymore at all. So it totally makes sense.

Subhasish 12:37 The well, the simplest way I think about is, like, I often try to put myself, like, what I used to do. Like, I live to twenty tens, twenty twelves, twenty four tens. I was upgrading my device almost every year.

Stephanie 12:48 Yes. Yeah.

Subhasish 12:50 That's just how much I use my phone versus, you know the same thing we'll talk about maybe network technologies. Right? The change the way it applies to certain fields varies. Right? So where is, like, I don't want to go from, like, four g LTE to five g, five g c band to ultra wide band. Just for a pure consumer's use of the phone does not change as much. Again, I we work in B2B space. There are like thousands of use cases for it, for five gs, ultra wide web event in business, B2B, large corporate, right, public sector. But for consumer, LTE is many times is more than enough for their mobile browser.

Stephanie 13:34 Yeah. That makes sense. So customer expectations, this is one thing we wanted to chat with you about, are you know, and and it's relevant to the conversation we're having now. Maybe not for phones, but expectations are constantly shifting, especially in industries like telecom. How does Verizon ensure that its retention strategies remain ahead of evolving demands? And do you use predictive analytics, I heard you talk about them a little bit earlier, to kind of anticipate what these future behaviors are going to look like? tations are constantly shifting, especially in industries like telecom. How does Verizon ensure that its retention strategies remain ahead of evolving demands? And do you use predictive analytics, I heard you talk about them a little bit earlier, to kind of anticipate what these future behaviors are going to look like?

Subhasish 14:06 To some extent. I wish we do a better job of this. Oftentimes, with any large corporation with P and L goals, quarter to quarter, month to month, you get bogged down on how can I meet my target for the month? How can I meet my target for the quarter? One of my personal push has been to our marketing and sales leader, especially in small business, is to look at least six to nine months ahead so that we don't get into this busier cycle almost every two weeks. Uh-huh. But yes, there are parts of our team who are focused on looking for trends more on the longer term. So can I look at a customer nine months ahead and tell what this customer could potentially do when their next contract renewal is coming up or when that device plan the loan payoff ends or when the company or the customer is going to go through that? Um, some middle sized company or and definitely all the big companies, they do to this periodic rebalancing of their accounts. So when they go through those cycles, what are they gonna make those decisions? So we use a lot of past data, some market indicators. Some fields we are better in predicting. Some places are not. Right? At least in public sector, this year has been top. Right? Federal government with lot of thing and all that. So Yeah. Those unpredictable indicators, we can't use them.

Stephanie 15:34 Makes sense.

Subhasish 15:34 There are some macroeconomic factors we can't take them. And maybe we'll go to a point where I don't know how to frame this, uh, but we try to. We try to put customers in segment and try to behave, like, predict what they can do. That's the challenge with business b two b business. Right? So I often say consumer our Verizon consumer business, they're, like, five times bigger than us in terms of the revenue. Uh, seventy, eighty times bigger than us in terms of customer base, customer number. But we are probably a 100 times more complex than that.

Stephanie 16:06 100%. Yes.

Subhasish 16:08 That's the building a true predictive model for a complex business. And I'm not talking about mom and pop stores because many of them do behave very similarly. So that small business segment where we can use some predictive behaviors, we do. And they kind of behave behave close to consumers, and we do use their past performance as similar like, similarity analysis. We do those to predict what they could do when the mile those milestones come. Right? I said contract expiration date is a milestone. Loan payoff date is a milestone. Mhmm. We'll go through those low you believe it or not, like, tax return is kind

Stephanie 16:46 of Interesting. Yeah. Yeah. Yeah. arity analysis. We do those to predict what they could do when the mile those milestones come. Right? I said contract expiration date is a milestone. Loan payoff date is a milestone. Mhmm. We'll go through those low you believe it or not, like, tax return is kind of Interesting. Yeah. Yeah. Yeah.

Subhasish 16:48 We look at those milestones and try to predict for these accounts, these customers should behave. But when it comes to anybody I'm talking, like, 50 plus clients customers Yeah. We we're very account best focused at that point because they're kind of looking for. They're kind of unique in their own way. So we can't really start putting them into buckets. There are certain drivers that will impact. Right? We start looking at competitors. What's our blue guys and purple guys are doing. Right? So we have to look at what they're doing, and some of their indicators will drive them. But most of inside, looking at our own existing customer base, it has to be a little more hands on for all the larger guys.

Stephanie 17:29 That totally that makes sense. And I I have to say, I have that same experience too with, you know, um, work on the supplier side with larger clients in a b to b environment. So I know exactly what you mean. They're they're all different in their own in their own ways. I'm curious. What do you think, you know, being so close to, like, customer analytics and and, you know, especially b to b customers and the way you think about them, what are the biggest myths that people have, whether either in your industry or just kind of across the board, about customer behavior that you feel like companies hold on to that you might challenge? Does anything come to mind for you? I like that. ou know, especially b to b customers and the way you think about them, what are the biggest myths that people have, whether either in your industry or just kind of across the board, about customer behavior that you feel like companies hold on to that you might challenge? Does anything come to mind for you? I like that.

Subhasish 18:09 We need it right now. Like, there is this idea that all customers are price sensitive, and all they're looking for is price. All they're looking for, give them a discount, they'll stick around. Or no. They are moving to our competitors because they're offering better price. Most of the time, it's not. Some of the they are, but most of the time, stem not. Customers do look for value, and value is an object much larger than just the price tag. Right? So Verizon's people stick with Verizon for value, like, their perceived value. And I say perception is reality many times. I can give you a small example. We see certain segments, certain customers start disconnecting. Right? And they're disconnecting. They're disconnecting. They're joining, and they're porting out the lines to our competitors who are giving this device buy buy, loan payoff programs. You owe Verizon $800 on your devices. Yeah. We pay $800 for you, join port your lines to us. Right? So your knee jerk reaction to that would be, oh, if we can pay off the loan, give us give them an early upgrade, they will probably stick with us, right? Wrong. Because they're not putting out because, you know, they got 800 free dollars or they want to upgrade their device. As you just talked in the beginning, they're not nobody is in a hurry to upgrade their devices. They they love their devices. They want to hang on to it. Right? So they're not in a hurry to upgrade their device. They're not in a hurry to move to a different carrier. What their hurry of is getting out of Verizon. Why? And many times, we found because of certain customer experiences there. Many experiences is even go back to when they first joined or passed added these lines. Many times, that first impression is everlasting. We had we had issue in customer onboarding. We had issue in, like, bill gaps in understanding the bill. The first bill, you see the discount, don't see the discount, and all that. Sometimes the promos that got applied like, lot of miscommunication in the customer experience when they join, when they go through some of the milestones in the in the customer life cycle with us Yeah. And hold on to those. When they get piled on, they hold on to those, and all they're looking for is somebody to free them off their contract. Right? And they would have put it out after the loan payoff happened. Then somebody came and said, I'm gonna pay off your loan. So, okay, assign assign me up. That, like, that that customer experience piece is the key driver for many, many of the customers. So that concept on that, okay. If I give them promo, if I give them discount, they will stay. I think our customers are smarter than that. Right? They most of the times, if you make their life simple, we're talking about small business owners. We're talking about people who are making thousands of decision every day. . So that concept on that, okay. If I give them promo, if I give them discount, they will stay. I think our customers are smarter than that. Right? They most of the times, if you make their life simple, we're talking about small business owners. We're talking about people who are making thousands of decision every day.

Stephanie 20:56 Right.

Subhasish 20:56 They if we can make them make one less decision, like porting out a carrier is not an easy thing. It's a hassle.

Stephanie 21:03 Right.

Subhasish 21:04 Like, credit along with everything they are going with.

Stephanie 21:06 Yeah.

Subhasish 21:06 So we can make their life easy by I I often talk, like, there are three ways of looking at it. First, we'll study the customers who left us and go back, look like since the day of their inception, study their journey and what could have triggered. Right? And then you look for those triggers. Could we have addressed them? Then what we have started doing is we have identified those infraction points and have programs with our digital engagement, with our customer service organization, start engaging with the customers and solving their problem in, uh, in in time. Then the latter is the more strategy is looking at, fundamentally, what is the problem? With with our tech stack is the problem, if the business process is a problem, or product pricing is the problem. Whatever it is, right, look at strategic changes to make those. So those are, like, three stages. You have to look at these problems and not just look. My team manages all the loyalty offers and all the discounts and all that. And we see there. It's doesn't make a marginal defect if, uh, effect if we give 20%, 30% discounts to the customers. Those who are gonna leave, they're gonna leave.

Stephanie 22:17 That's such an important learning. I I mean because it sounds like when you do the root cause analysis that, like you said, it's not about the price at all. It's about some unhappiness in their experience that needs to be addressed directly rather than through a discount. Right? And then you're leaving money on the table on top of it.

Subhasish 22:36 More importantly, that's always has been Verizon's brand. Right? We don't do Yeah. We are a premium service provider for a reason, for the quality of service we provide, for the kind of network we have. Yeah. So you don't as our brand are protecting our brand, we don't want to get into that care.

Stephanie 22:53 No. Yeah.

Subhasish 22:55 With our customer kind of competitors. t do Yeah. We are a premium service provider for a reason, for the quality of service we provide, for the kind of network we have. Yeah. So you don't as our brand are protecting our brand, we don't want to get into that care.

Stephanie 22:53 No. Yeah.

Subhasish 22:55 With our customer kind of competitors.

Stephanie 22:57 Totally makes sense. Well, you mentioned some segments a little bit before talking about, you know, the uniquenesses that come with with, like, larger enterprises. I'm curious about another audience that you serve. And I'm thinking about the introduction of Verizon's frontline network slides for first responder. It seems like it really exemplifies how Verizon has advanced its tech offerings with customer centricity in mind. How do you approach customer retention in these highly specialized markets, like public safety where service needs and expectations are really different from, like, general consumer behavior?

Subhasish 23:34 If we do the market sizing today, like, market share, Verizon is, like, hands down, uh, leads when it comes to public safety, both in federal and right? And public sector in general. But it's as I said, it's a lot of white glove approach. But even going down to if you're talking about public safety, their customer service is paramount always, but their trust in the technology and trust in the network is even more important.

Stephanie 24:04 Sure.

Subhasish 24:05 You see, we do I'm not saying I'm not belittling. You know, if we have bill disputes or if we have credit disputes with with a police service, you know, and New York City. I'm giving just example. Right? Hypotheticals here. So if you have billing dispute with one of these, you know, public safety companies, that can be handled. Right? What they can't compromise is the availability of the network. Right?

Stephanie 24:29 Sure.

Subhasish 24:30 We'll pay off it. And we know, like, hands down, there is one network in this country that, like, trumps all of them when it comes to reliability of it. And that's where we kind of and with what does network slicing truly offers is with just a product revolution on top of it. Right? So you have pretty good network to start with. Now you are prioritizing, you know, certain bandwidth, certain segments for explicit use. Yes. And, again, all our competitors have started doing that too, but I think we are far ahead in terms of implementing the network slicing for public safety, and come our customers know that.

Stephanie 25:09 Yeah. Yeah. Makes sense. I am curious about something. As we're entering this area where traditional concept of, like, loyalty programs and retention strategies, you know, that's the current world we live in, but we're approaching this world where AI and automation are really gonna be at the forefront. Do you feel like in this sort of future state that we are rapidly heading towards that, like, loyalty programs and retention strategies are gonna be far more personalized, like, hyper personalized and individualized.

Subhasish 25:44 Yes. Absolutely. Can get a little creepy. I think I've onna be at the forefront. Do you feel like in this sort of future state that we are rapidly heading towards that, like, loyalty programs and retention strategies are gonna be far more personalized, like, hyper personalized and individualized. Yes. Absolutely. Can get a little creepy. I think I've

Stephanie 25:48 been Yes. Talk about that.

Subhasish 25:51 Just thinking of ideas. Right? We're talking about customer flows, and they're clicking on this button, and we kind of anticipate that, okay, probably the customer is heading towards this way. Right? And then start offering them certain, you know, experiences that we predict. Like, the capabilities exist, but it's a fine balance between we do that today in a more you go and just to begin, if I can say this, but it's I think it's common. Right? So if you if you are a subscriber on anything, I'm not not I'm not talking Verizon phones. Right? Sure. And you want to unsubscribe that particular service, what is the first thing you do? You go to the payment side and you are sign off autopay. Right? If you have one autopay, you want to turn off your autopay and then go cancel the service. Right? They might have charged you for last month or next month, but they won't charge you anymore because you canceled the service. And also, just to be safe, you took us took yourself out of the autopay. So we look for people whose, you know, you're browsing the autopay button or you are doing the autopay sign up as, okay. That's a trigger. Like, you know, we have AI kind of observing that and then say, okay. If this customer sign up on autopay, go and study what his account looks like and what can we offer them. This might be a signal for them, you know, moving on. Yeah. There are is right? You turn off a feature. Right? If you're a price sensitive guy or your your business is going through downturn and you bought tons load over and up. Say you're a consumer. You're buying, like, Disney bundle, Netflix bundle, and all that. You go to Verizon account and start signing off those disconnecting those bundles. If you're disconnecting those bundles, that should trigger that, oh, this customer might become price sensitive for some reason. Yes. Would offer them some other price plans that might be better for them. And it will pop up, like, as they're browsing. Yeah. The to some extent, that's good. At some point, people are gonna be like, are you gonna are you then watching my every step on what I'm doing?

Stephanie 27:41 Right. Right. Right. It's a fine line. Right? Yeah. It's relevance without creepiness. Right?

Subhasish 27:49 So we do talk about like, whenever such an idea come, it we do have a, like, a thought go to kind of filter it down and say, okay. What is the customer would look like? Right? What's the customer experience is going to be so that it does not come to a point where customer feels uncomfortable interacting with us. sish: So we do talk about like, whenever such an idea come, it we do have a, like, a thought go to kind of filter it down and say, okay. What is the customer would look like? Right? What's the customer experience is going to be so that it does not come to a point where customer feels uncomfortable interacting with us.

Stephanie 28:06 Makes sense. Yeah. Well, Subha, to kinda wrap us up, there's a question that we always like to ask our guests. We have a lot of, you know, folks who are getting, you know, master's degrees in market research or just starting their careers in analytics. And so we always like to ask our guests who are typically have been in the field for a while. Looking back on your career, is there a piece of advice that you would offer to somebody who's just starting out in the field of, you know, either customer insights, customer analytics, something like that?

Subhasish 28:37 I don't know if I'm the ideal candidate for it because I accidentally landed in this role.

Stephanie 28:41 I think, like, that's true of 80% of us. So, no, irrelevant still.

Subhasish 28:46 So but at the same time, I think who's that? Einstein or somebody said, like, you know, curious mind, analytic? You just need to be have that curiosity, I think, is the key. Objectivity, to some extent, we're all human. We're, like, subjective, uh, to our, um, thoughts and biases. But being objective, uh, trusting the data a bit more. But more importantly, I think no matter and that's probably helped me because I came from I for a while, I was in technology, so I understand how platforms and tech stacks work. And I I I was actually in CX, so, like, CRM solutions development and all that. Then I worked quite a bit in business transformation. And that business transformation, but it was very aligned towards product, network. Like, understanding what we're selling, understanding who our customers are, does not require analytics. Right? And if you're just I have met a bunch of people, like, really exceptionally talented, very smart, comes with, like, PhDs. They can teach data science in MIT for all that matter. But it's a big bird is understanding your customer, how to be it, understanding your business model, what you are selling. Right? So the first thing I say, like, if if I'm working in this, especially in the business operation side, I need to know the product I'm selling. I need to know the peep move my product to. No matter what operation I am in finance, I am in business transport, I am in product, does not match what my role, and try to do that with my team, is understand the products that we're selling, understand who you are selling to. Then comes the functional role. Right? You can't, irrespective of you want to be a data analyst, you want to be business analyst, you want to be an architect, you want to be a data scientist, the those are just tools. Those are mechanism mechanics that are gonna help you with the job. Fast thing comes is understand your product, understand your customers, and then see how your skill sets gonna fit in there. alyst, you want to be business analyst, you want to be an architect, you want to be a data scientist, the those are just tools. Those are mechanism mechanics that are gonna help you with the job. Fast thing comes is understand your product, understand your customers, and then see how your skill sets gonna fit in there.

Stephanie 30:43 No. That is excellent advice. And it also just reminds me I'm I'm sure you think about this a lot too, but just that you have to cultivate an orientation towards outcomes over, like, approaches. Right?

Subhasish 30:56 So when I approached my SVP of this organization that I'm part of right now, I approached him, like, six years ago on, like, where do we move next? I was part of this central business transformation organization, which was a lot of ideas on understanding the product and coming up with concept and such. He said, Suba, you need to spend some time in the operations because operations results are the key. Like, you have a number, you have to hit that number. How am I going to hit that number? You are not coming up with three year project plans. Right? They see like, I I just like, sometime I mentioned it. We are in a two weeks to one week cycle right now. We have weekly KPIs that we need to hit. Wow. The number look like. So sometimes it gets too granular. Right? That I have to dedicate

Stephanie 31:44 pretty heavy.

Subhasish 31:45 For at least six to nine months, not three years, but six to nine months.

Stephanie 31:49 Yeah.

Subhasish 31:49 But operations, I think it goes back to, as I said, knowing a product, knowing a customers, you have to work in operations so that, you know, you get the hand, you know, pulse to understand how it's truly moving. How do we even sell things? Right?

Stephanie 32:03 Right.

Subhasish 32:04 We have this getting out to market operation. So we like, I will visit a retail store here somewhere. I will see how they're using, what's the customer interaction will look like. Like, visiting field is kind of a mandatory write up process for people in Verizon. You are in any kind of leadership role, you need to know the market.

Stephanie 32:23 Yeah. We used to have

Subhasish 32:23 a when I joined around eight years ago, we used to have a you have to go to our central offices just to see how the cable is laid out, how the machines are. So you are not looking at a product in a spreadsheet or somewhere. You know actually how the product works.

Stephanie 32:39 Theoretical. Yeah. Like, you know. I love that.

Subhasish 32:43 Right? You know, when you talk somebody about network slicing, you at least know what is network slicing. Doesn't have

Stephanie 32:49 Yeah.

Subhasish 32:49 Expert. Right? So, yeah, I think that's very much important. And I look at my SPP who is, like, twenty five, twenty eight years in Verizon. He knows inside out

Stephanie 33:00 Yeah.

Subhasish 33:01 Company. Well so that's what, like, I think any young leader should be aspiring for. Expert. Right? So, yeah, I think that's very much important. And I look at my SPP who is, like, twenty five, twenty eight years in Verizon. He knows inside out

Stephanie 33:00 Yeah.

Subhasish 33:01 Company. Well so that's what, like, I think any young leader should be aspiring for.

Stephanie 33:06 Makes a ton of sense. Well, Sue, what I have to say, we appreciate your time so much today. It's been great to learn about what you're up to at Verizon. Clearly, a lot of good work happening there these days. Been really fun conversations. So thank you so much for joining us.

Subhasish 33:22 Oh, thank you very much, Stephanie, for having me, and I really enjoyed the time.

Stephanie 33:28 The curiosity current is brought to you by AYTM.

Matt 33:32 To find out how AYTM helps brands connect with consumers and bring insights to life, visit aytm.com.

Stephanie 33:38 And to make sure you never miss an episode, subscribe to the Curiosity Current in Apple, Spotify, or wherever you get your podcasts.

Matt 33:47 Thanks for joining us, and we'll see you next time.