From Crawl to Run: Using Data and Analytics to Drive Omni-Channel Marketing

 

Do you crave the benefits of omni-channel to better reach and serve your customers, but lack the analytics and integrated tools to make it work effectively?

Watch Neustar and a panel of industry experts in this must-see webinar to discuss how you can navigate these challenges, and adopt the right technologies to incorporate data across your marketing value chain to:

  • Pair internal data assets with external market intelligence
  • Drive decisions to create a complete, real-time portrait of their prospects and customers
  • Enable a personalized dialogue across all marketing touch-points
  • Measure results in real-time across channels
 

Video Transcript

Elizabeth Robillard:

Welcome to our second omni-channel theme Net Finance webinar. We are happy to be joined by Neustar who will be helping us frame this discussion surrounding how financial services companies can use data and analytics to drive omni-channel marketing. We are also joined by a panel of industry experts who’ll be helping us understand how their institutions are currently using data and how the industry in general is using data. But quickly before I introduce our panelist, I’m excited to announce our next live event, Net Finance Interactive which will be taking place December 2nd and 4th in San Diego. That event will have a completely new format with 50% high impact heads out presentation and 50% interactive session, round tables, and workshop. And we already have over 50 speakers confirmed. So if you are interested in learning more about that, please let me know and e-mail me at elizabeth.robillard which is R-O-B-I-L-L-A-R-D at wbresearch.com. And now on to our panelists, on the line we have Christianne Moretti from TD Bank, Alex Jimenez from Rockland Trust, Bob Meara from Celent and Andrei Utkin from Neustar. Alex could you please take a moment to introduce yourself to the group?

Alex Jimenez:

Sure. I am the director of digital channel management of Rockland Trust. I’m in charge of all of our remote channels and also our debit cards and I’ve been at this position for two years, prior to that I headed our deposit operations area and prior to that I headed our project management office and I used to work at Bank of America prior to that.

Elizabeth Robillard:

Perfect, thanks, Alex. And Christianne could you please introduce yourself?

Christianne Moretti:

Well thank you. My name is Christianne Moretti. I’m a senior product manager with the mobile product team at TD Bank. I’m responsible for both Canada and the US, focused around understanding our mobile data, how to leverage it, how to be looking at the market, how to engage our customers better and how we can be leveraging the various data points actually be reaching our customers and selling and marketing to them as well.

Elizabeth Robillard:

Perfect, thank you. And Bob, could you introduce your self to the group?

Bob Meara:

Okay, sure thing. My name is Bob Meara. I’m a senior analyst in Celent’s Banking Practice and among other areas my coverage includes customer analytics.

Elizabeth Robillard:

Perfect, thanks. And Andrei if you could finish up with a quick background of yourself and Neustar?

Andrei Utkin:

Yes, hello. My name is Andrei Utkin. I’m director of professional services here at Neustar. I’ve been with the company for about a year. Neustar is an information services and analyst company that is focused on a variety of marketing services solutions and other types of solutions for our customers. My role is to work with clients to implement some of the marketing key things and segmentation targeting basing solution and to some of the consultants to large clients. I’ve spent 10 years prior to Neustar at Capital One as director of digital marketing. So I bring both the client side and the professional service side experience with professionals.

Elizabeth Robillard:

Great. Thank you so much. So now we’re going to head into some panel questions to discuss data and analytics with omni-channel. So we’re going to have our first question here and I’m actually going to start off with Bob who’s going to give us the sort of industry wide lens on this question which is what are some of the challenges that banks are facing when it comes to omni-channel marketing? So Bob, if you wouldn’t mind kicking us off.

Bob Meara:

Sure thing. What a great starter question. I mean I can’t help but to think a little bit of a level set might be needed here. So from Celent’s perspective we see omni-channel marketing and financial services really is as aspirational. In fact we’re not aware of a single financial institution that is you know fairly contempt with its current capabilities rather everyone seems to be in progress somewhere with rather significant differences in omni-channel capabilities from bank to bank, and part of the challenge though is that the number of use cases continues to explode and in that sense omni-channel marketing doesn’t really have a price definition right? So even if we all agree on the basic definition of what omni-channel even means and by the way I think there’s quite a bit of confusion on that topic right? Even then there’s still a lot of wicker room in terms of what banks might pursue.

For example, on the marketing campaign side some banks are tailoring by customer and by channel driven by, channel and customer preferences and customer and ________ [00:04:56] right but typically not real time. Other banks are segmenting based on customer profitability for example and typically with some views to likelihood of attrition and likelihood to purchase products and services but again typically not real time but both of these right are great examples of omni-channel marketing. And then another example might be one we see significantly fewer banks doing that is presenting next best offers to all channels in real time. Those that have done this and they start in the branch and call center channels because that’s where this all has been done historically with the next horizon perhaps been doing this that is next best offer in our contextually relevant way in additional channels. And doing this requires real time analytics.

Elizabeth Robillard:

Perfect. Thanks, Bob. A great insight there. I’m going to turn the question over to Alex from Rockland Trust. Do you have any thoughts on some of the challenges you face when it comes to omni-channel marketing?

Alex Jimenez:

I think aspirational is absolutely the word here. It’s really a journey for us. We are still very much into the traditional marketing and a few years ago digital meaning non-traditional channels was something that we did off our side of our desk. We’re trying to combine things together but we still lead with what we traditionally have done, but if you track our expense and how we approach your customers, we start seeing we’re certainly not doing any other things we used to do many years ago with like newspaper ads and all that kind of stuff that it’s long gone. But where those funds have gone, with our efforts have gone haven’t exactly gone directly to say the web or other channels and even what Bob mentioned, the whole idea of targeting by channel, by preference, by segment, a lot of those things are not available yet with our systems. So it, we’re still just recreating some of the things that we do in the physical channels and remote channels. So you know the same ads that we have in some piece of collateral literature are being presented online and while we are doing something that are only for online and for the digital channels, it’s usually goes more from physical to the digital side.

Elizabeth Robillard:

Great, thanks, Alex. And I also like to get Christianne’s perspective from the sort of more mobile side of this omni-channel marketing next. Christianne any thoughts on this question?

Christianne Moretti:

Yeah, actually it’s been interesting as we’ve been looking at how to leverage mobile within the context of broader reach across omni-channels for marketing and one of the things we’re really learning and I’m sure if anybody that’s in the mobile space this is no surprise is that when you’re looking at leveraging, the mobile channel to market, you do have to rethink quite a bit how you position the data that they’re advertising. How you link it and then how do you actually look at it? How do target it? How do you get to the customer what they need? Because in mobile because it’s so much more of a personal setting and an immediate setting, you don’t want to surface things that isn’t relevant to them because it’s right there in front of their phone and they go well, you got all my data. Why aren’t you surfacing stuff that’s important to me? So it has been a journey and we’ve been trying to figure out, how to do that, how do we leverage the data and get it out there? But then it’s also how do you change the advertising content, the messaging so that it really is easier to consume and faster to consumer. And then the final piece is then if the customer clicks on that ad, what kind of experience are you sending them to because you can’t just send them to an online experience. You actually have to create a full stream of okay then like if you click through it, you’re going to a mobile optimized experience and then if you actually want to fulfill on the backend, the fulfillment needs to be done in a mobile experience as well, so you’re almost reworking your full supply chain like almost I’ll call it a marketing supply chain from how do you surface it? How do you get it there and then how do you fulfill on the back end? Well that’s a lot of what we’re exploring and trying to figure out as I’m looking at specifically from a mobile context.

Elizabeth Robillard:

Okay. Andrei if you wanted to chime in real quick with any thoughts about that?

Andrei Utkin:

Absolutely. So I think you know we heard all this big perspectives on omni-channel marketing being a process. At the basic level you know one of the channels I wanted to be in and how do I make each of the individual channels work, how do I export some of my experience from offline channel to online. Those are all great questions and probably we feel all of our clients facing. I want to talk about two additional questions which I think are really important and post challenges to most financial services market. The first is how to make the different channels work together in terms of consistent experience? And the second one is how do you measure across channels?

What I mean by the first question is ideally you want to make sure that customers see the same messages, same experience across the different touch points. And that’s much easier said than done especially if you do targeting. If you have multiple different experiences, for example in the online space, you use some data overlay to differentiate other experience between super prime or subprime customers. You want the idea to make sure that the message the person is locked into when they go from one display experience to another one, they go from display to mobile and ideally even you know even offline channel which obviously is a big challenge.

The cross channel measurement question I think is even more important. If you want to understand how one channel influences the other, a lot of advertisers have kind of locally solved for optimizing each individual channel, so they are have nice ROI positive results in most of the online channels if they are direct response marketers, but it’s really hard to say how for example TV advertising influences display response. And many people are just basically you know don’t even attempt to solve for this problem but it’s there and we have seen time and time again that channels doing in a very big way both online channels within the online ecosystem as well as online to offline. So to me one of the big questions is how do you create a measurement framework for channels in directing together and how does that influence your investment decision, your understanding ________ [00:12:20] each of the channels and ultimately your ________ [00:12:22].

Elizabeth Robillard:

Okay, thanks, Andrei that was a good wrap up there. So let’s move on to our next question here which is when it comes to omni-channel analytics, which problem is more acute? Getting the right data or getting the right insights from the data? So I wanted to open it up to Bob again for the industry lens, if you have any insight on this question here.

Bob Meara:

You sure you want me to go first again?

Elizabeth Robillard:

I mean if you are up to it.

Bob Meara:

So, yeah, for sure I’ll give it a try and it’s easier to be first anyway right. So they both are difficult right. And omni-channel ambitions complicate things because much of the necessary data resides in siloed system ________ [00:13:07] right? So some form of you know marketing customer information ________ [00:13:12] and then I do believe that data discovery, the analytics discovery can begin. That said given the right data in the right place at the right time is necessary but not sufficient right for making database decisions. A recent Celent survey just you know hot off the press actually in financial institutions suggest that the biggest challenges lie with having the fragmented data environment or poor data quality meaning dirty data or having data where not where it needs to be for example in some cases you know residing in spreadsheets and so this speaks to the pragmatic need for some kind of data governing disciplining, in fact we find that most do this informally and not necessarily at the enterprise level which gives rise to some of this problem.

Either way we think analytics just as Alex was mentioning is very much a test and learn kind of a journey. So banks can start small with you know using exquisitely internal data for example and then grow from there. And so we’re not seeing anyone doing this as some sort of an enterprise wide you know big bang but rather one challenge to this adventure is knowing upfront where data is needed. And which data is need rather but that can be a moving target as it progresses. So it’s really you know kind of ________ [00:14:34] journey in our opinion.

Elizabeth Robillard:

Perfect. Thanks, Bob. And Christianne do you have any thoughts on this question about getting the right data or getting the right insight from the data from your perspective?

Christianne Moretti:

Yeah. I tend to agree with Mr. Meara actually, because I don’t think you can see it’s either or. It’s getting the right data so you have to make sure that your data sources are going to give you the right information about your customers. But then it’s being able to manipulate and work with that data to give you meaningful insights because if you just have a data–you know spreadsheet of data and you look at it and its like what the heck does it tell me. Once I can actually work that data and give me insights to say okay, my mobile customers are doing that or Bob is my specific customer is doing this and this and this and has these types of relationships with me and it’s like through this life moment etc., etc. Then you can get your marketing to be context specific, life event specific, etc. But you have to make sure you’re getting the right data and then I need to move on to doing kind of a step one, step two. You know step one is get the right data and then step two is being able to manipulate it into a meaningful and usable format.

Elizabeth Robillard:

Perfect, great thoughts there Christianne. Anything from you Alex on this point here?

Alex Jimenez:

Just from our experience with what Bob mentioned the data not being in the right place for a few years. We try to do some of this with a data warehouse supplemented by some spreadsheets and Access databases that really hasn’t worked and for the past year or so we’ve started working on a bigger project of looking at analytics across the whole organization and we know this is necessary for us to do to actually get any data out of, any insight because what we were getting we’re probably anecdotal at best even though we were working with data. So until banks can get their act together with the data, it’s difficult to drive any significant insights. But now that we have been able to put probably 80% of the data together, we’re starting to gather some insights and some of the things have totally surprised us.

For example, we have learned that our mobile banking customers which being towards being younger are heavy users of branch something we never expected before. So that certainly impacts how we talk to them and what we tell them. We were thinking that the vast majority of them were not users of branches and that doesn’t seem to be true.

Elizabeth Robillard:

And any thoughts on what’s just been said Andrei from your perspective at Neustar?

Andrei Utkin:

Yes. I agree with everything that was said and especially what I heard in terms of you know one not working without the other. It’s definitely true. You cannot get good insight without good data but then if you collect good data but cannot get inside of it then the data is useless. I think most financial services companies these days don’t struggle with not having access to data. If you have an ad agency, if you operate in the online world especially you will get probably more data than you know what to do with that key issue that data has to be again desperate sometimes not kind of rum it on the insides, you’re trying to get to.

For example, if you’re running you know large number of different online channels, you will probably get a lot of cookies level information about the different channel performance or what kind of conversion they drive, etc. The problem with the data is that it is hard to connect the dots between different cookies and it’s hard to get down, it’s hard to make the connection from cookies to individual customers or household. This is where Neustar usually plays a big role and we have a lot of interesting partnerships with advertisers in all kind of industries being able to connect online data to offline insights and summarizing the insights at the household level, the you know anonymous cookie level and being able to connect, close the loop between multiple channels which seemed not disconnected with each other but in fact where the is a lot of overlap.

So both in terms of measurement of how these channels work together and then the insight that come out of the measurement that we tend to try to bring up to the customer or household level are usually challenges we help the customers with. In that sense I think getting the right insights from the data is where we see a lot of value that’s happening.

Elizabeth Robillard:

Okay, thank you Andrei. So let’s move on to this next question here. It should be coming up on your screens. What is your wish-list when it comes to the data you want and ideally what you want to use it for? What functionalities or decisions could be optimized by using this data? And actually I wanted to start off with Christianne. I wanted to see if you had any insights into this question from your perspective.

Christianne Moretti:

Me first. I can’t wrestle up with somebody. Wish-list when it comes to the data you want and what would I use it for? I would love to get down to the individual customer level when it comes to the data that I want and having that ability to be able to understand their relationship with me as their provider. And what I would use that data for is to be able to surface not only just product sales and not but actually help the customer and guide the customer based on their individual needs and what they’ve gone historically to be able to service them better. So and you can service customers and cross help them at the same time. So what you’re doing is you’re delivering value to the customer and at the same time extending that relationship and that that’s a product for the customers. So that’s what I would look at if I have you know nirvana of being able to use the data.

And functionalities or decisions that could be optimized by using the data, well if I look at that and this is not a marketing specific question. If I have customer behavioral data as I look at developing the capabilities within my mobile experience, so what do I offer my customers to be able to do in mobile? The more I understand my customer behavior and what that customers are doing and acting and experiencing with my brand, the better I can fill the functionality and capability that’s actually going to deliver the highest value. But rather than doing a shot in the dark on what customer wants, I’m actually giving them what they want without having to ask them. So then you become proactive with your customers as opposed to reactive.

Elizabeth Robillard:

Yeah, that definitely makes sense. Alex, do you have any thoughts on what either Christianne has said or any thoughts on the question in general from your perspective?

Alex Jimenez:

I think she did an excellent job of answering. I don’t think I have any answer.

Elizabeth Robillard:

Perfect, perfect. Bob, did you have any thoughts on just industry wide on what Christianne has said. Is that something you’re seeing similarly from other financial institutions?

Bob Meara:

Yeah. Absolutely, yeah. I think it kind of starts with what decisions you’re seeking to make from the data right. And you kind of start there right? What’s the big decision objective or the problem or pain points to be addressed right? But kind of generally we’re seeing banks who look for to seek an aggregate data from kind of four buckets. One obviously for current customers there is product information all the resulting revenue stuff, right, so you can build up customer and account P&Ls and transactional data from the courses including the channel data. So how customers transact what the bank is actually huge because that can heavily influence customer profitability and customer preferences and not the best served up in your proactive communication with the customer right.

And then demographic data typically garnered from account opening and maybe sourcing third parties data sources for you know cycle graphics and things of that sort because some banks will point out that demographics loan are kind of the poor predictor of things. And then lastly you know customer opinion data. So whether that be social media and other external sources or internal sources for all customers offer opinions. So for example how they respond to product offers with the in source opinion and no, I’m not interested in home equity loan, so don’t pester them next week with the same question right.

But kind of one random example here is Comerica which uses the tool they call Account Planner which prompts retail banking prospects online to answer the small ample questions about their interest and preferences like banking services, their networth, preferred transaction channels and that sort of thing and then an algorithm delivers product recommendation back to the customer realtime and customers are offered the ability to setup an appointment via e-mail or the phone or in person. And so for Comerica they are able to capture terrific sales lead information. Low cost and for customers they’re given resources right there that presumably are timely and relevant to explore their needs that would be much more at least potentially useful than simply going to the internet and searching because they’ve provided in this case Comerica’s algorithm engines with a handful of very useful tidbits of what’s important to them and then the banks responded with hopefully a much more useful customer experience.

Elizabeth Robillard:

Okay, thanks, Bob. And Andrei did you have any final insight into this question or whatever was said so far?

Andrei Utkin:

I think the panelists did a fantastic job summarizing some of the most acute places where metadata or good data is required. The thing that we see a lot of our customers ask for is moving from anonymous data to more specific personalized information I think that resonates a lot with what Christianne was talking about. Wouldn’t it be great if every time someone came to your website instead of seeing a cookie that hit your website, you are able to see what specific type of prospect you’re dealing with, is it a high value prospect for you, is it a low value prospect, what kind of demographics they might represent, what products they could be interested in and what experience would be best to provide to them. And same goes to you know anonymous or new phone calls from new lines coming in to your call center being able to customize the experience immediately based on readily available insight about who the person might be enriching the experience a great deal and I would be talking a bit more what we need to help with these things in the little presentation I will give towards the end of this webinar but I think back to Christianne’s point, I think it is, it’s mostly about moving from anonymous cookies or what have you to customer specifically.

Elizabeth Robillard:

Perfect. Thanks, Andrei. So on to this new question here and I’m going to start with Alex actually this time. The question is how do you coordinate data and analytics gained from online and offline channels? How do you use one to impact the other? Or even if you are doing this as of right now. So Alex any insights on this?

Alex Jimenez:

I think I got the best, the easiest question because my answer is we don’t.

Elizabeth Robillard:

Okay.

Alex Jimenez:

And this is one of those aspirational things that we’re trying to get our arms around this but even some basic information from our online customers is really difficult to translate to our offline you know basic things like you know online and our online channel we sign sort of a set of credentials that don’t necessarily match with the way we think about relationships or households for our offline channels. So sometimes we get into a whole discussion of you know is it really an online customer when one person out of a household of three is online and is that really an online customer versus an offline customer. But even just being able to tie the data together it’s tricky, we’re trying to do it but we are far away from it.

Elizabeth Robillard:

Okay, thanks, Alex. And Christianne, any thoughts on this or want to build off of anything that Alex had just mentioned?

Christianne Moretti:

Yeah, I would agree with Alex actually that definitely the desire and the aspiration is there. We’re starting to get there, we are moving in the right direction but we’re not there yet.

Elizabeth Robillard:

Okay, perfect. And Andrei any follow-up thoughts on what Christianne and Alex had to say about the question?

Andrei Utkin:

Yes. I think this is one of the most exciting and dynamic areas of analytics that is happening in the omni-channel market space right now. I think there are two types of problems here. One is what Alex is referring to in terms of just being able to identify customers who might have registered with you or bought a product from you online when they call you in the call center or even just authenticate them across multiple channels. It’s hard to translate an online identity to phone identity or a personal identity. But there are other question which is something I spend the most time solving for our clients is understanding how online marketing impacts offline response and potentially the other way around as well. So again if you run a multimillion dollar display social, mobile or search campaigns, quite often people will see that but they might want to respond to a different channel. They might come to your branch and say hey, I saw your advertising. Can I subscribe to the product that I saw on the display? Or they might call your call center. Right now very few advisers are able to connect those dots and therefore they won’t give proper credits to the investment they’ve made in online channel because they cannot necessarily check it back to the response they’ve got in the offline world. We do have a set of proprietary tools that allows to connect online and offline identities and actually do this type of close loop measurement which I think is a great opportunity for us and a fantastic value.

Elizabeth Robillard:

Thanks, Andrei. Really closely while we’re going through this, if anyone has any questions at all, anyone in the audience, if you wanted to just you can type and there is a function on GoToWebinar where you should be able to type in any questions that you have and we’ll be answering them towards the end of the session. I just wanted to remind everyone that that is definitely a possibility, if you have anything that you wanted to ask the panelists. So moving right along to our next question, I’m once again going to start with Alex. I’m not sure if you’re maybe going to have the same answer as the last question but this question here is how do you or are you coordinating data and analytics gained from both inbound and outbound marketing efforts?

Alex Jimenez:

I guess it’s sort of part of the same answer. We’re trying to put it all together into a database if you will.

Elizabeth Robillard:

Okay.

Alex Jimenez:

Not exactly a database and we’re having some early successes with some very specific data you know for example we looked at certain regions and certain customers on how they use their debit cards and we use that as a proof of concept to get more funding to you know go after more data. And that’s been fairly successful but yeah, we’re not doing a great job yet.

Elizabeth Robillard:

Got you. Christianne any thoughts on that? Is it something similar to what Alex has experienced?

Christianne Moretti:

Yes. I would say I think Alex summarized it really well. We’re in a very similar situation.

Elizabeth Robillard:

Okay, perfect. And Andrei any follow-up comments to those two?

Andrei Utkin:

Yeah. I’m also not surprised that this is that trend in the social room today. It’s hard to do to make these connections. It’s similar to how it is hard to make connections between the online and offline world. I think if you just think about the online ecosystem. There are some marketers out there who are doing this more aggressively than others. Most companies that utilize online outbound channels such as social display do some sort of targeting and segmentation when they try to reach out to the customers and going back to the point I made earlier, I think what we talked about the first question, ideally I want to ensure that if you subjected your customers to certain type of ad then they see the same experience coming in. But equally importantly if you are able to segment on the outbound side and say hey, I will have different message of the different products being shown to the different customers. You should be able to do this in the inbound space as well. And this is where I don’t see as the much activity as I think the opportunity would call for.

There’s a lot of leverage in identifying who you are dealing with when someone comes to your website, to specifically engage and customize the experience to that specific person’s need and do it in a way where you maximize your own objective function, whether that is closing a product sale online, whether that’s getting the customer sign up for newsletter or do anything else that is basically an action or converging event for you. And there are lots of opportunities these days to again move beyond the cookie and identify its not the specific person you’re dealing with then of course lot of privacy issues that you have to work around but you can always bucket the customer to potential target segment and customize the experience. Again both to improve the customer’s you know specific satisfaction with that transaction but more importantly to also ensure that your website is maximized in how it is converting customers to products and generating ROI. So I think both in silo inbound and outbound efforts are equally important to segment and customize. But there’s a lot of coordination between those efforts as well that can be done marketer’s today.

Elizabeth Robillard:

Great. Thanks, Andrei. So sort of a related question I’m actually going to start off with Bob this time. Our next question is do you keep your marketing channels or are financial institution keeping the marketing channels siloed when it comes to data and performance analysis or do you have a central database analytical platform for all of the channels? Bob, you have sort of an industry wide perspective on this at all?

Bob Meara:

Yeah. Typically the former but it gets worse and here’s what I mean by that. And so my caveat since we don’t have a precise you know quantitative view of this but observed that many banks are approaching analytics. So if you think with the term of analytics first and then marketing analytics next, their analytics efforts are departmentally driven so for example finance might have a platform to form strategy or to look at customer channel profitability, marketing might be using analytics platforms for campaign targeting analysis and then risk and compliance might separately employ the initiative right. And moreover some banks have separate efforts on the lending side right? One for deposit, another one for lending focused on risk based pricing for example.

So and I think this view is shared by the primary vendors in the analytic platforms who quickly conceive you know I wish I had you know 100% market share in any given client but most large organizations are employing multiple analytics vendors right. So it’s very much a siloed environment I think.

Elizabeth Robillard:

Great, thanks Bob. And Alex, is that something you are experiencing at Rockland Trust?

Alex Jimenez:

Yeah. And to Bob’s point as I mentioned before we had various databases in places where we had data and you know we’re putting in time to centralize it and trying to put it all together in one place where our different departments can report out from the same data or plan from the same data or take some action from the same data. And I probably will take quite a bit of time. I start specific within marketing you know we have the data that we have always used in our CMIF for the traditional marketing pieces but even trying to get some of our e-mail data for example has been tricky because there are platforms not necessarily one where we could have that information in there. So there’s some structural thing that we have had to upgrade to even just being able to do the day to day marketing stuff.

Elizabeth Robillard:

And Christianne, any thoughts on your perspective from TD Bank?

Christianne Moretti:

Yeah. So there’s been a huge amount of effort to get a centralized database in the analytical platform across channels and across marketing. We’ve done a lot of work on that actually and one of the things that we’ve also been looking at is as customers engage in marketing across the different channels how do we then go back and so say, I’d buy it, I get on my ATM, I go to my ATM and you offer me a credit card and I’ll go wow that thing I want that. And then you buy it. Well then it shouldn’t, that ad should not surface again in my phone or in any other digital experience. That’s it. Like you bought you, the only other image that might come up on my phone for example is thanks for buying that credit card. It’s in the mail. You should get it in a week. So it’s kind of thinking about you know taking that data and centralizing it which we are trying to do and then being able to leverage it so that you’re not double hitting or triple hitting or completely hitting the customers when you’re looking at it.

So and I think if we have a similar challenge in that you know different groups over time have bought different analytical engine, so we do struggle with that. We’re getting better and there is an objective to get that centralized but we’re not there yet.

Elizabeth Robillard:

Perfect Christianne. And Andrei, do you have any quick insights as to what was just said?

Andrei Utkin:

Yeah. I can relate a lot to what Christianne was saying. You know I think this question can be discussed at two levels. The first level is simply do I even have all the marketing data that I need? If I’m working with multiple vendors which is quite often the case, do I have the right data warehouse where I can store you know all the past marketing information, investments, impressions, response, actions, etc. And can I access all the data from one database across all the channels that I’m using. That’s usually I mean generally data warehousing problem but there is a high level question as well which is even if I have all the data, do I have the right kind of horizontal data management platform to understand how the data works together. So again if you are working with multiple online vendors for example, you would might have the impression volumes and the response from each of those vendors how it needs to be in your database separately. But you also want to know what percentage of all the impressions where you know overlapping, well how many individual customers did I reach through all those channels? Did I end up hitting the same cookies over and over again across all the different channels and therefore am I potentially wasting money because I’m buying access to roughly the same audience through multiple vendors where the cost could be multiple X. So this is I think the high level cross channel data management question that clearly has a lot of solutions for.

Neustar offers the aggregate knowledge data management platform that answers some of these questions and many others and try to take that horizontal view on all channels where a cookie can be placed. They even have a question across online and offline channels going back to the things we discussed earlier moving away from you know individual cookies and impressions to household level information that’s I think the data management platform of the future that Neustar is actively thinking through right now. And this is the question we don’t think there are solutions for in the marketplace yet that sold all of the needs that marketers have.

Elizabeth Robillard:

Okay, thanks, Andrei. So actually this next one is going to be our last question. And I’m going to start with Alex and then we’re going to move to Christianne and then we’ll move over to Andrei for his presentation from Neustar. But this last question here is when you have data showing multiple marketing touch points, a conversation can be attributed to, what attribution methodology do you use? So Alex, any opinions on that from what you guys are doing over at Rockland Trust?

Alex Jimenez:

This is my favorite question so far. You know we wrestle it, we wrestle and then somebody wins. Okay. In reality it’s something that we kind of take down the path we haven’t really done a great job. Generally we attribute it all to the branch which is not perfect certainly only because the, you know with all the data challenges we have, it’s difficult to say that you know that this is attributed to this. So unless we have specific campaigns where we are capturing something like a discount coupon kind of thing which we don’t do too many of, it’s really difficult for us to attribute it to something that we’ve done to maybe from direct mail maybe.

Well one of the things that we’re starting to see with the data that we are now putting together is we’re starting to see that everything bleeds through and a few years ago when we were looking to increase our digital marketing spend for example, we had to keep it all within the digital channel. So if we’re spending a dollar on SEO or SCM, we assumption that that was going directly to online sales but we are seeing is that something like 70% of our customers in physical channels search for us online, did something where there is with just looking at our locations or they actually went to our website or looked at rankings in different websites, bank rate or something like that. So we’re starting to understand that just because you’re a customer who walks into a branch, you may have seen us in a digital channel, similarly we are seeing people who open an account who did not search for us directly. So maybe a billboard somewhere and then just went right to their website and typed rocklandtrust.com and went to our website and opened an account. So long winded answer is no, we’re not doing it and we hope to do more of it in the future but it’s not possible yet.

Elizabeth Robillard:

Okay, thanks, Alex. And any quick thoughts on this Christianne before I move to Andrei?

Christianne Moretti:

Yeah. I think the one place where we’ve been able to do attribution so there’s always that question of you know we can get some credit, right? So I think in some cases it’s very clear so if a person starts in mobile, they click through, they fill in a credit card application and they just sell. Then you can attribute it to the mobile channel. But if it’s more of a lead gen type of piece, what we focus on is okay, let’s see the amount of click through and the amount of phone calls that it generated. So did it generate lead? But in the end if they went to the branch or they go to the phone channel, will you attribute it to the branch or the phone channel. And it’s not as Alex was mentioning before it’s very difficult to understand the multiple touch points that are involved to the customer making the final decision. So I think there’s a magic in the sauce where somebody could actually sit there and go okay, a customer, they bought this and they did these five different things before they made that decision. Then that would be magical then we know how to position different pieces along that journey for the customer.

Elizabeth Robillard:

Okay, great. Thank you so much Christianne. So we are going to move over to Andrei who’s going to be able to sort of synthesize some of the things we’ve been talking about and some of the solutions that they are offering over at Neustar. So Andrei if you wouldn’t mind taking over here for a little bit.

Andrei Utkin:

Absolutely. Can you guys see my screen?

Elizabeth Robillard:

I could see it.

Andrei Utkin:

Perfect. Yeah, so thanks first of all to all the panelists, we had a great discussion. I think the issues you are dealing with and the solutions you are looking for resonates really well with what we’re hearing from many of our other clients and again it’s not limited to financial services although we definitely have strong relationships in this space as well. So I have about ten minutes to go through a fairly long text. I’ll try to just hit on the key points which summarizes the discussion and talk about some things you start out here.

So you know at the center of the types of problems that we deal with on the day to day basis and our clients ask for solutions for. You know one of them have to do with identity. Advisers want to know who their customers are, where they are located, what kind of products they prefer, what media would be best to reach them and use all of that information to do marketing analytics. The problem is that you know you might see the individual cookies or the individual phone number of your customers of your prospect or you might be even you know, know a lot about the actual customers who you have underwritten or converted for your products in terms of the name and address, if you have a CRM database we have all those things. The problem is that this is a very dynamic space. A lot of people change their addresses, their phone numbers, cookies are not stable and we talked about and bringing all this together is really, really hard. So most of our clients actually do not have a very accurate view of their customers and many are open to admit that.

Why is it important? Well without a good strong view of who your customers are you cannot identify what are the meaningful segments to use to target them and to offer your products. Two, you may not have the best idea of which marketing channels to use. A lot of times we see our partners just make intuitive bets as opposed to making you know letting actual data speak for the channel choice and then personalization and targeting becomes a big challenge if you again don’t have a strong identity to look at. And then finally bringing all this together and looking at cross channel impacts things that we talked about today is really hard if again you don’t have this type of information.

And in the online world as we discussed today cookies are the primary currency so to speak to identify interactions across channels or to kind of build back analysis of how many times you reach certain prospects and whether they have converted or not. But you know and then cookie based solutions are definitely much better than not doing any sort of online analytics at all. But increasingly advertisers are looking beyond the cookie because of the fact that a lot of the customers you know have interactions with multiple channels. Something that Alex and Christianne talked about a lot today and because it’s really hard to go beyond the _________ [00:51:40]. You know you really need to understand, use other sources, other type of research to understand really what is the interaction between channels and how online influences offline. 58% of our surveys on customers said that they just don’t have the tools or technology to connect the dot between different channels and those that would do usually use cookie based solutions.

So moving beyond cookie and actually doing a lot of this at the household level is something that Neustar differentiates itself on and we pride ourselves of being well one of the most authoritative consumer data sources available. We are able to identify customers and tie an identity to a specific household based on just one out of five or six different identifiers. We can work with a phone number, we can work with an address, a name and you know a cookie or even an IP address and we have the technology that is powered by over 200 authoritative data providers to connect those identities to physical household therefore uncovering the specific customers left behind both your prospect database as well as your customer database. And this information is being updated on a very frequent basis, we use multiple sources to collaborate and we have basically information on large share of any given prospect database that you might be dealing with as an advertiser.

Once we connect people to specific households, we have a database of on all of 120 million households in the United States and we offer a lot of different insights both demographic and psychographic behavior and others that is relevant to funding and analysis of who these people. So like I said identities at the core of our solutions, we offer fundamentally two types of intelligence on top of identity, customer intelligence is one of these things. So you know examples of this would be verification. If someone is your existing customer and you know their home phone number but they’re calling your call center from a mobile phone, we offer solutions which allow to instantly identify this person as being an existing customer and either rush them through those authentication process or immediately send them to the appropriate agent or experience. The same can be also done online through our cookie verification process. We also allow segmentation and targeting based on this. So again once you are able to tie specific prospects to demographic groups, you are able to show them dedicated experience both as outbound those kinds of things and when they come to your website or call into your call center.

And then the other type of service that we’re offering is immediate intelligence. I talked a little bit about the aggregate knowledge. Data management platform we are able to offer a cross channel view of how you spend your marketing dollars, how the different channels work together and how different channels influence each other both in the online world as well as in the online to offline world.

The use cases are numerous but as in a day our clients use these sets of insights either to more efficiently spend their marketing dollars and therefore grow their reach or their sales and we both, if I have a few minutes I will talk about a couple of use cases here. So I have three minutes left. Let me just talk about two really quick case studies here. One is with Lenovo. So this is not in financial services but its very relevant example to what we talked about today. Lenovo has a major customer facing website and historically they’ll be showing the same hero banner to every person who hits it and therefore there was no segmentation on targeting. Their goal was to unmask who their visitors are and to try to show them most relevant product for every single customer. Not everyone wants a premium laptop which was the default experience. Some people want a tablet, the others want the cheap laptop, others want the desktop where other you know other products. We were able to analyze what kind of clients come to their website and how they–what kind of products they tend to consume, created several audience segments and now when someone comes to the Lenovo website they will be showing the experience that is expected to maximize their chance of actually purchasing a product in that very session. The result 30% CTR lift for the banners. So more people are clicking on this hero banner and go into the next step. And on those people 40% lift in actual order conversion. So a huge result to the client, hugely ROI positive and we have multiple similar examples this product is digitized and we utilize it across many industries.

The other quick example is the closed loop measurement study. Christianne this might be relevant to your world. We had a client who wanted to figure out how much mobile campaign influence actual in store sales. This specific client was in the consumer electronic space. So they didn’t have direct sales data but to partner with the panel that data provider that allowed us to tie to the specific household who were exposed to the mobile impression in this advertising campaign to purchases made in stores like Walmart, Best Buy, etc. We looked at where the people who were exposed to the campaigns were more likely to come in and push the specific brand versus those who were not exposed to the mobile advertising and connecting this online to offline data allowed us to uncover the specific ROI of this campaign which was over 400%. So for every dollar they invest it in mobile marketing they ended up getting $4 or more in incremental sales directly attributable to this campaign. A huge insight and a huge win for the customer.

So sorry I kind of rush through this. If you have any questions about you know how Neustar works in the online and offline spaces and how we connect cookies, phone numbers, names, addresses to identities and how we use those identities to uncover marketing insights mostly to inbound or outbound space, please feel free to contact us and we’ll be happy to have a first line discussion with you.

Elizabeth Robillard:

Thanks, Andrei. I also wanted to say if you had–if anyone had any questions for any of our panelists as well feel free to e-mail those to me and we’ve just about run out of time and unfortunately we’re going to be able to take any questions. But please e-mail me at elizabeth.robillard which is R-O-B-I-L-L-A-R-D at wbresearch.com and I’d be able to pass those on to any of our panelists. And I wanted to thank everyone that was on the call today. So much great insight from all of our panelists and I also wanted to thank Neustar for their support of Net Finance and thank all of you for attending.