Tony Coretto Interview on Total Picture Radio


Hi, this is Peter Clayton from TotalPicture Radio.  If you’re like most organizations, chances are that you already have gigabytes or even terabytes of customer data — but that’s not really what you need. The challenge is how best to leverage that data into the most profitable marketing decisions, strategies and results.

That’s what Tony Coretto and the PNT team does.  For more and more marketers who need to do more with less, PNT can provide a full spectrum of customized support services and proven consultative expertise to help you transform customer data into bottom line dollars.  Tony has worked on a variety of key problems in marketing database design, segmentation, householding, and distributed datamarts.  One of his chief goals is to reduce costs, inefficiencies, and frustrations and improve client satisfaction by developing tools and techniques to foster better communications among marketing managers and systems development teams.

Tony, thanks for talking to us today.  First of all, we need to unpack this lingo a bit – householding, datamarts… can you explain this?

Tony:  All of this can be very confusing to the uninitiated.  Let’s bring it down to the business level.  What we’re trying to do here is help folks understand the great drove of information that they’ve got with their customer data and to do that in a way that improves the relationship between the customer and the business.  Part of that is making sure that you understand your customers, and you understand them by understanding how they aggregate their accounts together. 

If you’re a bank for example, you’ll have customers who have a variety of different services with you – a checking account, a savings account.  Often they’re not put together into the same unit or the same household.  We don’t know that the two accounts belong to the same person.  That’s called householding, whether it’s for a bank, or for a telecom company, or a retailer that can be a challenge just to understand who it is that you’re dealing with on the other side of that transaction.  That’s what we call householding.

After householding, what’s critical is understanding the nature of your customers.  Who are they, are they young, are they old, are they transacting a lot or a little, are they making a lot of money for you or costing you money?  That’s the next step of the analysis is to try to understand exactly who they are and what the financial impact of the customer is on your organization.

Peter:  Speaking about financial services, most of the banks I’ve worked with are highly siloed organizations.  You’ve got the investment bank, the private bank, the consumer bank, and the credit card division, and they kind of all playing their own sandboxes, right?

Tony:  Data silos are a huge problem for our customer which is why they hire us.  Although there are a lot of silo busting services out there, there are many, many more buzzwords today than there were five years ago.  For example, there’s MDM (Master Data Management) in which software provider – an MDM provider – will attempt to install software to make sense of data across silos.  Often those efforts are hampered because even though the software might have the capability, the businesses just don’t want to share, or there are not enough data elements that allow the crossing of those silos and the linking up of that information accurately.  There are still challenges, even though the technology is catching up, we still have process issues and personnel issues, and political issues – the three P’s that prevent us from making those connections across silos.

Peter:  Can you tell us about a typical engagement at PNT?  What are you brought in to solve most often?

Tony:  We often come in because folks have a problem with an existing installation.  We do a thing we call our database marketing assessment, in which we’ll quantify and qualify the issues that are plaguing in internal database marketing group.  For example, a group brought us in at a midsize regional bank last year because their internal database marketing support group was having what we call a lot of friction in producing output for the  marketing users in various business groups.  That is, they were spending an awful lot of time spinning their wheels, there were a lot of delays in requests.  What we found out is that the internal team was not being very efficient in using their time.  They spent about 65% of their time putting data together, crossing data silos and reaching out to grab data and reformat it, adding standards - for example, there was no standard definition of a product set.  There was no standard definition of what it meant for an account to be open or closed. 

So we suggested that what they do is create a marketing specific datamart and prepare that for the analytic team on a periodic basis, create these various cross reference tables and product tables and standards and make the internal team more efficient so that they weren’t spending 65% of the time creating the data and only 35% of the time doing analytics but that those numbers were reversed so that they were spending the majority of their time doing analytics.

So that’s the kind of thing that we’ll do is we’ll come in and fix a bad situation, fix a situation in which either the data doesn’t exist, or the data exists across multiple silos, or the internal team is inefficient in their use of that data, or the business is very frustrated because they’re not seeing a return on investment for their technologies spend. 

Often what happens is you see a sort of magic bullet mindset where folks will buy for several hundred thousand to several million dollars, they’ll install a marketing customer information file (MCIF) where they’ll install a datamart or a data warehouse.  At the end of the day, they’ll sit back and say, “Wow that was great!  We just spent $500,000.  Where are the results?”  They don’t realize that all they’ve done is enable results to occur, they’ve put in place the infrastructure, they now have to know how to use it properly and they have to use it in a way that provides results.  That’s what we help with is helping them leverage the tools that they’ve got to use them to perform analytics, to make sure that what they’re doing is bottom line oriented.

Peter:  You bring up an interesting point here, Tony.  Most of these sophisticated databases that existed, they can churn out report after report  after report.  They look really nice too.  But what’s the strategy behind the report that you’re generating and what are you going to do with it once you have it, right?

Tony:  Right.  Often our clients suffer from analysis paralysis.  They wind up of generating too much data and not enough information and direction.  There are several levels here.  There’s raw data which doesn’t mean anything to anybody; it needs to be consolidated and it needs to be scrubbed, it needs to be put in a place where it’s accessible, that’s kind of the basic infrastructure.

Then there’s information that we create information from data but then the information needs to be analyzed and interpreted to provide a strategic direction.  Having information is akin to having all those reports come  spitting out at you.  Now we’ve got the data, we’ve got it corralled and now we’re generating information.  It doesn’t really do me any good to know that sales are up in the eastern region and down in the western region.  What am I going to do with that information?  Does this tell me how to rectify that problem?  Why are sales up in the eastern region and down in the western region?  Is it because we’re adding a lot of new accounts in eastern region?  Or is it because we stemmed our attrition problem in the eastern region?  So were we just doing a bad job of acquiring accounts in the western region or we’re doing a bad job of keeping accounts in the western region?  We don’t know until we begin to peel the onion, but you don’t begin to peel the onion if you don’t know what questions to ask. 

Often people are just presented with this information and then stop dead because they don’t know what the next question to ask is.  So we help them figure out what the next questions are and then the right questions in order to get to a bottom line answer, which is gee, you know what; your sales in the eastern region are increasing because you have completely stopped your attrition problem because we see by analyzing this data correctly that you’ve got a different product set here.  Now let’s go back to the business and ask why is this product set being offered in the eastern region and not in the western region.  What’s so special about the eastern region?  Can we offer that similar product in the western region?  What do we need to do to make it suitable for the western region customers… and so on.  That leads naturally to more strategic thinking in terms of how do we address the customer relationship, what do we do to make that relationship better and stickier and more profitable over time?

Peter:  One of the trends that I’m seen lately with large organizations Tony, is that more of a focus on customer retention and valuing the customers they currently have, where in the past it may have been customer acquisition, all of these programs trying to go out and attract new customers without doing very much to keep the current customers in the fold.

Tony:  Exactly.  We see a lot of that as well.  It’s well known that attracting a new customer is a multiple of the effort and money required to keep an existing customer.  Right there is all of this lead generation, prospecting, wooing, and courting that goes on to establish a relationship with a new customer.  In addition, it takes a while for that new customer often to ramp up and become profitable.  A lot of effort now is being expended in retaining existing customers.

It always has been but frankly, with the recession and the emphasis on the bottom line, folks are realizing that reallocation of marketing dollars towards retention is a more cost effective spend.  That means understanding the relationship more deeply so that you can have an intelligent conversation, an intelligent interaction with that customer.  It doesn’t do any good to contact the customer and say, “Hey we value you.”  The next step is, okay so what?

Peter:  Right.

Tony:  What does that mean exactly?  I understand that, I really appreciate being valued, thank you.  But does that mean I get a better price?  Does that mean you have a different level of service for me?  Does that mean I have different products than everybody else?  What exactly are you talking about?  So that means thinking through a strategy that will yield an actual concrete difference when you’re talking to a customer about a retention program. 

One of the things that we do is help our clients figure out what the appropriate customer incentives are.  We specialize in various customer incentive programs that then incent sticky behaviors and that incent the kinds of behaviors that will result in more and loyal customers.  For example, rather than just offering a customer $50 because they’ve been with you ten years, or offering them a $50 coupon.  You may want to offer that coupon in conjunction with some testable behaviors.  So here’s $50 off; you’re a loyal customer, thank you for being a customer for ten years.  Here’s $50 off your next purchases made and we’re going to do that only for this particular set of skews in these particular stores, because we know that those products are the kinds of products that you are more likely to purchase.  Plus, they happen to be profitable products for us and we need sales in those stores which happen to be in your geography.

We want to tailor the offers that not only benefit the customer, but also benefit the business in terms of the bottom line and building that relationship so that it’s a win-win for both.  You don’t want a one sided offer.  You don’t want to benefit only the business and you don’t want to benefit only the customer.  You must develop the relationship.  Otherwise if you tilt too far towards the customer, then you encourage gaming.  You make an offer without strings attached, then you’ll wind up encouraging gaming behavior.  If you have an offer that is tilted too far towards the business, then few people will take advantage of it because the terms and conditions are too onerous.  You need to have that middle ground and those offers then will result in stronger relationships.  So it’s more customer intelligent offers rather than just 10% off coupon because we like you.

Peter:  Another thing that all of these large organizations today are trying to figure out is the social networking piece - the Twitters, the Facebooks of the world.  Is this something that you’re getting involved in trying to analyze all this data across these social networks?

Tony:  We just started to work on that with a various text mining and data mining tools.  The tweets stream and the stream of communications now is producing.  We talk about gigabytes of data and terabytes of data, well it’s producing pedabytes of data.  It’s producing a thousand terabytes worth of data on a monthly basis.  We’re getting now so much data that we’re trying to extract the various smidges of information from it.

It’s a sort of a difficult exercise, because you’re not sure what you’re hearing in the tweet stream because it’s so context dependent.  If somebody says awful in conjunction with your product name, that may be a good thing or it may be a bad thing depending on the context of the sentence.  It’s awfully good, or it was awfully bad.  It’s a conjunction of words in a text string that leads to determining whether that was a good tweet or a bad tweet.

A lot of cutting edge companies in that space, like Razorfish, are working on brand metrics that speak to the measure of the strength of the brand based on the kinds of tweets that are being made about the brand.  We try to take it into the other direction and not just up towards the brand level but scale it  down towards the customer level.  Our particular groups of customers, do they tend to be more predisposed towards your brand or are they promoters to use the net promoter score?  Are they more likely to be net promoters of your business or net detractors of your business?  That’s a simple metric that describes whether a person is more likely to recommend your business or not to recommend your business.

That’s an interesting space because there’s just so much data there.  So many people are now scrambling to try to make sense of it because more and more people are moving their interactions online.

Peter:  You’re absolutely right.  It’s hard to analyze data, especially on Twitter because so many people use abbreviations.  This is kind of almost like a texting language.

Tony:  Correct.  You must understand what the geeks refer to as elite speak – the elite language that is spoken in those mysterious acronyms.  That can be a challenge as well.

Peter:  One of the biggest complaints I hear from my friends in HR and recruiting of course this is mainly related to employees, but it’s none of their databases play nice together.  Is that something you can help with?

Tony:  Sure.  It’s almost as if there’s been a platform proliferation.  There are so many different vendors out there with so many different platforms.  You’ve got, for example, business could have sales forces as their front end CRM platform.  And then in the backend, they’ll have a point of sale system maybe from IBM that tracks the actual sales interaction.  Then they’ll have an accounting system from Great Plains Software which was purchase by Microsoft.  So they’ll have three different vendors which is not unusual.

Peter:  Right.  Then an ATS system from Kenexa or  Taleo or somebody.

Tony:  Exactly.  Now you’ve got four different systems.  You’ve got different levels of customer data there.  You’ve got data at the invoice level or data at the purchase level from the POS system.  You’ve got data at the individual account levels for the accounting system, on the CRM system or the sales force system, you’ve got stuff that’s at the lead level that may not even be related to a particular customer or relatable.  Then all of the data are stored differently.  They’ve got different use and different purposes.  So how do you make sense of all that? 

While any data can be made to talk to any other data if you know what you’re looking for and how to ask the questions that will lead you to creating this sort of holistic view of the customer out of your business.

As I mentioned earlier, MDM software is one tool that has been brought to bear, but you still have to deal with those three P’s – the people, the process, and the various other pieces that are standing in the way.  Because now, even though the technology is there, you still have to deal with the politics of people who are in different parts of the organization, the accounting guys don’t want to give up their information to the sales guys and the sales guys say, “Hey that’s my book of business.  I don’t want to give that to anybody.”

People process using politics that have to be transcended for the technology to work.  It’s as much about the people side of it and understanding how to play that game as it is about implementing technology.  That’s really something that we help our clients with.

Peter:  I imagine on some days you must feel like a psychoanalyst.  Back to what you were talking about earlier, you walk into a new client, they just spent a couple of million bucks on a database system, a new shiny thing out there that was supposed to solve all their problems.  It didn’t.  They don’t understand it.  Now you’re coming in the door, now they’ve got to spend more money on stuff that they…  Because they don’t even understand what it is they’re spending the money on.  Tony, how can we help potential clients help you be more efficient?

Tony:  I think you’re absolutely right about that data psychology.  It’s a matter of making people feel comfortable enough that they can step off the ledge and not panic about the data situation or about the information situation. 

The first thing to do is to make an assessment, do a diagnostic.  Where are you now?  What has happened?  What’s been installed?  How is it being used?  That provides us with an understanding of where our clients are coming from and it provides them with a comfort level that things aren’t as bad as they thought.  Because often what they’ve installed can be used; it just isn’t being used in the appropriate way.

Step number one is understand, to understand where the data are, what’s happened with the current systems infrastructure, or the people processes and politics (the 3 Ps) that are standing in the way of progress, and then to formulate step 2 to formulate a plan.  So let’s figure out now what the business goals really are.  Let’s tie it back to where we want to be in six months a year, two years or five years.  Let’s look at the higher levels strategic plan and see what we can do to get you there.

Then it’s a matter of adding whatever technology we need to add to that mix to cross the silos on the technology side and then to help folks with processes so they can cross the silos on the people of politics side so that they can cross functional silos in their businesses and talk to each other to enable this more holistic view of the customer.

This last step is to use that view to act.  So we don’t want to just give you a plan, we want to help you act on that plan.  What does that mean?  Does it mean creating new products and services?  Does it mean putting in a cross sell plan?  Does it mean putting in some customer incentives that are intelligent incentives that incent the right kinds of behaviors to create loyal customers?  Does it mean really focusing on the bottom line of your customers because very few businesses realize that they’ve got customers that are losing them money, so do we really want to focus on the various groups that you have – the top tier customers who are making you tons of money and having a different strategy for them as opposed to the middle tier customers who could be making you money if you only understood what it was if they really wanted and how they’re interacting with you.  Then the bottom tier customers who you’ve got to make a decision on whether you want those customers at all, or is there a way that serve them unprofitably by just reducing costs served for those customers, or can some of them be salvaged?  Can some of them migrate to the middle tier and upper tier customers. 

Those are all tactical decisions that can be then supported by the appropriate programs and the appropriate product development, the appropriate training customer facing reps have to talk differently to different groups of customers, and so on and so forth.  All of that can be supported at the act stage.  It’s all about discover, plan, act, and then track.

So now we’re putting these processes in place, let’s track them and see how they did.  We instituted three or four programs, are those the right programs?  Have they done well?  It’s often this last step – this fourth step, the track step, that people leave out because after they’ve acted, they’re saying “Wow, that’s great! We did something.  Now we can rest.”  The appropriate response there is no, you never rest, and then at this point, now you’re in a loop.  You’re in a loop of discover, plan, act, and track, and you’ve got to go back to the beginning.

Once you’ve tracked the results of your programs, now you’ve got to feed that back into your higher level strategy and then that filters back down into what plans should be, how you act, and then track all over again. 

It becomes a new way of thinking about your business.  It becomes a new way of acting rather than just sporadically working with customer information once in a while.  It becomes part of the business MO.  How you operate now becomes driven by what you know about your customers.  And this endless loop of discovering, understanding, acting, and tracking now becomes part of the way you do business as opposed to just a once in a while kind of thing. 

So that’s the biggest shift that we try to help our customers make is it to understand that it has to become an ongoing effort.  It’s a way of doing business.

Peter:  That’s interesting.  You’re absolutely right, because I think most people, it sort of the same analogy to a website of someone puts up a new website and goes, “Okay I’m done.  I’ve got a new website up here.”  Without realizing that unless you continually feed information into that and  upgrade it and revise it, it’s not going to be of any value.  I think people do the same thing when they initiate these database plans, they get the thing up and running, it works and then they forget about it.

Tony:  Right.  It’s as if thinking that getting married is a one shot deal.  You’ve had the ceremony, you’re married, and now that’s kind of it.  Oh boy, I can put that on autopilot, thank God.  Now I don’t have to think about that anymore.”   How many happily married couples you know who don’t work at their marriages. 

Peter:  Right.

Tony:  If somebody were to say that to a married couple, they’d look at you like you had three heads.  Like absolutely not.  You work at it everyday, and that makes a successful marriage.  Because you have adopted a new way of living, you have adopted a new mode of being.  That’s really the sort of philosophical underpinning here is you have to adopt a new mode of doing business that is centered around your customer and knowing your customer, and using that intelligence about your customer, constantly updating it and constantly feeding it back and using it to inform your products of services in the way you interact, the messages you send, the incentives you provide, all have to be formed on the back of that customer intelligence; otherwise you’re flying blind.

Peter:  Tony, thank you so much for taking to speak with us today.  This has been very interesting and informative.  I think it’s really helped to explain a lot of the mysteries around this whole database process.

Tony:  Thanks Peter, it was a pleasure.

We’ve been speaking with Tony Coretto, from PNT Marketing Services.  You can connect with Tony on their website which is 

This is Peter Clayton.  Thanks for listening.