What’s Brewin’ | E4 | Financial Services Spotlight: Turning Your Data into a Competitive Asset

Learn how Financial Services organizations can use BI tools to understand their data and turn it into actionable insights.


George Shalhoub: Hey everybody. Thank you for joining us on today’s episode of What’s Brewin’. I’m your host, George Shalhoub RVP of the Financial Services Practice here at Plative. Today we’re going to be covering a topic very near and dear to my heart. Since we’re doing a financial services spotlight, we’re diving deeper into how to turn your data into a competitive asset. Before I pass it over to my co-host, Michael Konon for today’s episode, a big part of the, What’s Brewin’ series here is to talk about the coffee that we have also just brewed to be prepared for today’s what podcast episode. And so with that, I’m in what I would consider North American coffee capital in Seattle, Washington. I’m drinking Seattle Coffee Works, South American Bean. I believe it was from Guatemala. Been drinking it all week. Absolutely fantastic. Really crisp and clean cup of coffee. And then Mr. Konon, I’ll pass it over to you before we get into our scheduled content.

Michael Konon: Perfect. Thanks so much, George, and, and very excited to be here and thanks listeners for listening to this podcast. I’m Michael Konon. I’ve got about 14 years in the financial services industry. I’ve worked in a number of different roles on the industry side. I’ve been a business analyst, I’ve been a stockbroker. I was a quasi-fund manager. I’ve worked in global capital markets and that was where I was introduced to Salesforce as an accidental admin. Loved it so much that I became a consultant and now I’m here at Plative which is fantastic. What am I drinking? So George, I’m on the opposite end of the spectrum here. We have a three month old baby. It’s our first baby, so time is of the essence, so I have switched over to instant coffee. I’m actually drinking a Nescafe gold medium roast. Which is pretty good, the coffee is fresh, it tastes okay. Not nearly as good as your amazing coffee that you’re having there. But I will say that my coffee consumption has gone down. I used to drink a lot of French press but now I’m drinking maybe two cups a day versus two liters a day.

George Shalhoub: That’s an improvement my friend, well done. All right, now we can get into our scheduled content for today. So, as we were talking through these different podcast topics and what we wanted to cover, we hear this come up all the time, and I say we as myself from the onboarding side, we’re bringing clients into the business is they always ask questions about how to use their data and what they could do with it.

And Michael’s one of our lead consultants that then helps clients realize, the dreams and ideas and what they actually want to do on the platform. So, you’ve got me that talks a big game, and then you got Michael that can actually deliver on those promises that I’m making. And so with that, we’re going to dive deep into how to turn that data into competitive asset.

The first question that I want to ask just to kind of set the stage of everything. Once again, in financial services, everybody talks about data. There’s so many different sources and different types of data. So, with that, Michael, what are some of those most common sources or data types that you’ve seen within the industry? And then maybe if there’s, of course, the different sub-verticals in some industries of financial services.

Michael Konon: You know, George, that is a great question. So, the biggest piece of the two biggest pieces of data or modules of data or types of data are related to marketing and transactions. So marketing we’re talking about lead generation, we’re talking about data that is coming in from people attending web to lead conferences. We’re talking about data that’s coming in from events. We’re talking about people who are listening to podcasts. We’re talking about data from people who are asking for information. All that good stuff.

And then the other biggest piece that we see in financial services is transaction data. This is specifically within wealth management, alternative asset management, regular asset management, even retail banking. What are people buying? What are people selling? What are people holding? What is like, what is it that clients are doing? Those are really two huge, siloed pieces of data that we work with all financial services clients regardless of their vertical.

George Shalhoub: Yeah, that makes total sense. And those are the main pieces that we see. Or I should say, even for us what we talk more about with the onboarding side is really more of that transaction data. Thinking about internal analytics on the products that you’re actually selling and what your clients are actually buying from you but didn’t even really think about the marketing data and keeping track of like almost putting together like fire personas and understanding where did they actually convert over and get edited into the funnel, and then where could we actually attribute that back to the transaction.

And of course, this is a marketing focused podcast that we’re running as well, so there’s even pieces that I could see how this works for us as well. But how might we actually be able to take some of that data from a marketing standpoint to then understand and tie that back to a transaction.

Michael Konon: Well, that a great question, George. So really your marketing data is really the beginning of your customer 360 view of clients. So, think about your marketing data as the beginning of your lead funnel. So, there’s an expression of interest, somebody is interested in something that you’re selling, whether it’s a product or service. Maybe they’ve entered the funnel, like I said previously, whether they’ve asked for information on a website, which is web to lead. Perhaps they’ve attended one of your in-person or online events. Maybe they’ve been working around for a while and talked to somebody in person.

Well, once they’ve expressed interest, you want to capture that information. Now, once you’ve got that lead, you want to work through them, you want to qualify that lead. And once that lead has been qualified, meaning that not only are they interested, but they can purchase your funds. But you see a lot of people who are interested in funds, but perhaps they’re not accredited investors.

And, and this is a very specific wealth management scenario. However, regardless of industry, everyone has to be qualified. So once they’re qualified, you convert that lead into an opportunity and then you can start working the opportunity. Once you’ve worked that opportunity and gotten to the point where the client is getting onboarded, whether they’re going to be signing up for a new bank account, whether they’re going to be purchasing a new mutual fund, maybe they’re very interested in some ESG that’s when you convert that opportunity into an account and then all of a sudden, you have a client.

So, as you can see everything starts at the very beginning with marketing. And what’s really cool about Customer 360 is that if you’re capturing all that data and if you have everything connected, you can see the actual journey of what they were interested in, and what is it that we did to make sure that that person became a client. And then once they’re a client, how do we make sure that we’re going to keep them as clients, and service them as they should be serviced so that they don’t go to competitors or buy any other products or services from anyone else.

George Shalhoub: Right. And that’s that end piece right there just hit on. We talked about the analytics and kind of tracking the buyer persona, but then different analytics that you could see that might attribute to losing a client. If you notice that there’s a lot of withdrawals coming from an account or if they’re selling out of different positions that you might have put them into, so, so many different ways we talked about onboarding and then just retaining and keeping the clients themselves.

Now my mind is just racing with all of the memes about how salespeople think that marketers don’t do anything. And then vice versa, where marketers don’t think that salespeople do anything. And now we’re seeing that there’s a crossover where both people are holding up their end of the bargain.

Michael Konon: Oh, absolutely. I’m glad that you mentioned activity data there because all of this data is great when you’re seeing it in a silo, but really analytics becomes very, very powerful when you kind of start to break down those silos and you can start to cross reference that information to actually create a picture of what might be happening. Because really, the point of analytics is not just to know what happened yesterday or the day before or last week, but really you want to get to a place where you are able to create leading indicators and understand what’s about to happen and get in front of that. So that you can, again, service your clients in a way that, that they want to be serviced. Making sure that you’re retaining clients and really parsing that information on let’s say an account record within Salesforce allows you to do that. So I’m really glad that you also mentioned you know, redemptions.

Well, you know one scenario that, that you see all the time within wealth management and even wholesaling is you’ll have a client who’s very good. They’ve been coming to all their regularly scheduled client review meetings, but then all of a sudden, they stop coming.

Maybe they’re making some kind of excuse. Maybe something’s happening in their personal lives, and they can’t attend, and that’s fine. But then also that client might be redeeming your funds, they might be getting out of any sorts of investment vehicles.

So, I’ve just described just two modules of data. By themselves, they kind of paint a little bit of a picture, but they don’t really tell you what’s going on. But let’s say you combine those two things, so all of a sudden if I’m an account manager and I can see that my client has maybe skipped the last three or four monthly check-ins with me, and they’re starting to redeem funds, well all of a sudden that’s painting a picture that something’s wrong.

And that provides me an opportunity as that account manager to get in front of that, contact them and see what’s going on. Because you, you never know, maybe they need those funds for something else. But maybe they’re transferring those funds and buying one of your competitor’s products. But maybe you already have a product that they’d like to purchase and they’re just not aware of it.

George Shalhoub: Right. Basically, surfacing the opportunities to save that client. Maybe they’re on the way out, but they’re just not aware of a different product that you have or a different fund that you could offer them.

Michael Konon: That’s right. That’s a pretty vanilla use case. We see that in our industry all the time.

George Shalhoub: All the time. Yeah, absolutely. So clients wanting to get set up with the BI tool, figuring out how to visualize their competitive advantage, which is of course data. What’s one of the biggest challenges that you see when clients are actually looking to set up one of these BI tools? What are you mainly advising them on, aside from the tool? What are some of the bigger challenges that they deal with just in setting it up in general?

Michael Konon: I would say number one, hands down, and this is across the board with every client, data quality. BI really only works when your data is clean. And what that means is that number one, the data exists. So if we’re talking about activity data, well, you’re going to need to have your salespeople using, let’s call it Salesforce to capture those activities. So you’re actually creating data points. Number two, you want to make sure that the correct data is being captured in the correct way.

So we have seen a lot of examples where clients just kind of, they create fields and they create a sales experience such that it’s easy for a salesperson to maybe use the CRM, but it’s not really capturing the data that they need. So they can’t actually do those analytics. But that’s really a data quality issue. You’re just not capturing the right data or the data that you are capturing is just a poor quality or the data’s missing.

George Shalhoub: Yeah. We say that all the time. Even with clients, when they think about migrations or integrations into Salesforce, whatever, from wherever to wherever. In theory, we talk about record completeness.

Who’s actually going to be accessing this record? What information do they need? Of course, we could set up different views and we could visualize different information from marketing. Account management or for sales, or even for a C-level executive, they can all see different information. But how much information do you need to know about this individual person so that every single person could run the reports that they need to do their job better?

And record completeness is a big part of that. That’s why data migrations sometimes can be very costly because we really want to think about where all these sources that we could pull everything together. And then that way from one screen you can see everything about that individual and then run all those reports like you’re talking about, for those four distinctly different use cases internally.

Michael Konon: Yes, absolutely. Data by itself is really just one dimension of what it is that people want to ingest. Really, data isn’t too useful until you start to figure out what your use cases are and then you work backwards from there. As a high level perhaps, easy example here is if I want to figure out leading indicators for clients redeeming funds, well I need to make sure that I’ve connected my trade system into Salesforce and I’ve got that pipeline of information coming in and being surfaced on the account level, and I’ve also got a BI tool so that I can digest and, and really create these reports and dashboards. And maybe even some AI in there to ensure that I can surface these leading indicators and get in front of that. But, what I’ve just described requires some work and some infrastructure to be built in so that at the end of the day, you want your salesperson to have an experience where they click into an account record, and they can visualize what’s going on. And perhaps, there’s, let’s call it Einstein, you’re going to have Einstein predict predictive analytics showing that this person might be a flight risk, and you should really get on that ASAP.

George Shalhoub: Yeah. And that’s even, I mean, product aside, but just to dive into Einstein as a tool, since you just brought it up. That’s why it’s one of those tools that’s so simple to use for the end user. They don’t realize all of the backend data and the setup and the integrations and everything that goes along with it.

When they log in, they see John Doe as a client, and he’s got a grade of an A. And they’re like, cool, this is a client, they’re an A, they’re not at risk of leaving and that’s wonderful to see. But then they could log in and they could see someone that’s a C and this is what their risks are, and these are the things that you want to make sure that you talk about.

And then it could surface, these are the pieces of marketing material that you want to send out to this client to make sure that you could turn them from a C back to a B. And they just simplify the analytics experience where it’s not something where it’s only something that’s visible for the IT team and the tech team, it’s something that makes it easier for the salesperson to make actionable insights on how to actually service that client, and that’s why we love Einstein. I know that we wanted to try to keep this agnostic of an individual tool, but just because you brought that up, that’s really one of the main powerful use cases that we’ve seen with Einstein.

Michael Konon: Yeah, absolutely. And if we take that a step further, you can create a report that surfaces all of the clients that are created C and if you’re a salesperson trying to figure out what you’re going to do for your day, you’re probably going to want to review that list and start to contact those folks and make sure that you can mitigate them as flight risks.

So, it also helps you become more efficient, while also providing you more insights. Which is really the end goal here.

George Shalhoub: Yeah, for sure. And what we’re talking about here is really visualizing the data. So, we talked about common data sources, the big challenge of making sure that you have clean data.

And now of course when it comes to BI it’s visualizing it, you know, just seeing it. Now that you’ve got 15 different data sources compiled into giving you that one complete record, what have you seen some of the leaders in the industry actually do to visualize this data and create some of those actionable insights for the edge users?

Michael Konon: In my experience the leaders really understand their metrics first and foremost. So, they understand their KPIs and they understand their metrics, and that’s really what forms the backbone of all of this type of BI analysis. If one of my metrics is to reduce current client churn by 10%, well, I need to make sure that I can create a report so that my salespeople can kind of get in front of that and reduce client churn. Other clients really kind of understand the personas of their clients. So for example, a CEO, he needs top level information that’s really easy to access and view and digest. Typically, executives, they’re not going to be in Salesforce for too long. They just really want to understand what’s happening, click into any chart reports or dashboards that have been built for them so they can drill in as they need. They’re more interested in understanding what’s not quite working and then delegating the responsibility of finding that out to one of their sales VPs or the president of sales. And if you’re thinking about it, think about it as a hierarchy. At the very highest level, you’ve got your executives that see everything, and then if you go down one level, you’ve got your direct, then your VPs that can maybe see less information, but that’s very pertinent to them. And then you go down one level further and then you have management. Managers can see what’s happening on their teams. And if you go down one level below that, then you’ve got the end users who really need to be digesting that information.

So, they’re all seeing the same information they’re just digesting it in different ways for different purposes. But really all of that’s driving everybody to ensure that you’re hitting your company metrics and you’re hitting your KPIs.

George Shalhoub: Yeah, and exactly what you just said is really tying it all together, like I had mentioned with that complete record where you’ve got all these different departments viewing the same record, but you viewing it for different reasons. And that’s where record completeness comes into play. That’s where members of our team like you are so important is because you have to work with the client and say, I understand that you want BI, it’s an easy word to say, but it’s a harder to actually set up. So we need to make sure that we’re pulling in all the information that you need so that from a C level down to an individual sales associate, everybody could access the same page in Salesforce or the same page in any system and see exactly the type of information that they need about that individual.

Now, are there any other challenges that you’ve seen with BI? Things that clients should be thinking about, even if they’re not clients of ours, perspective people that are looking to set up anything BI related, whether it’s tools, whether it’s journeys that they should take themselves on just to learn a little bit more about the industry. Any other insights that you might have that you, you might think are important for people to hear about?

Michael Konon: Great question, George. One other big thing is making sure that you’ve got the internal skillsets for folks to be able to create the data and the dashboards and the outputs that are required for everybody.

You know, BI is its own beast. There’s a reason why a data scientist role exists. There’s a reason why people go to school and not just get degrees, but get advanced degrees in this type of thing, because it’s not necessarily too easy. Now, I don’t want people to think that it’s super difficult, but you really have to make sure that you’re providing your teams with the opportunity to be successful.

BI is not something that you do off the side of your desk. Typically, our clients, our larger clients especially, they have dedicated teams of data scientists whose sole responsibility is to make sure that the data’s cleaned, the data’s connected. They’re thinking up new and different ways to surface that data, especially on the analytics side. That’s all they do, all day, every day. Just dedicated towards really creating actionable insights that they can pass on to sales teams so that we can hit our KPIs and our metrics, whatever might be within the company.

George Shalhoub: Yeah, of course structuring the data so that then it could be read by one of these BI tools to then give you the output of what you want. We’re going to have to end here. Konon and I could go on for hours talking about this, as you could tell. But listeners, thank you guys so much for joining us here today. Konon always a pleasure talking to you, my man. This was a really useful.

Michael Konon: Absolutely.

George Shalhoub: I learned a couple things. I learned a couple lines that I’m going to take with me on high travels as well. But everybody, thank you so much for joining us on today’s episode of What’s Brewin’. I’m your host, George Shalhoub. Everybody have a wonderful day. Thank you so much.

Michael Konon: Thanks everybody. Great to talk to you, George, and looking forward to the next one.

George Shalhoub: Yes sir.

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