Customer Equity Accelerator Podcast

Ep. 43 | The Customer Revolution is Here


"It’s not 1980, it’s the 21st century; and connecting well with the right customers matters more to than ever before." - Allison Hartsoe


This week in the Accelerator host Allison Hartsoe summarizes a selection of key insights from the Custora conference in New York City. This conference was all about CLV, personalization and the best uses of customer analytics. Allison includes kick off commentary and key industry sticking points from Custora CEO Cory Pierson, McKinsey’s personalization framework and finally, a series of maturity personas from Forrester. Get the key insights from this power-packed episode and see how you stack up against the industry.     

Please help spread the word about building your business’ customer equity through effective customer analytics. Rate and review my podcast on Apple Podcast, Stitcher, Google Play, Alexa’s TuneIn, iHeartRadio or Spotify. And do tell us what you think by writing Allison at or Thanks for listening! Tell a friend! See the full transcriptView all episodes.


If you want clearer insights from your data, check out how we can help:

Ambition Data Services

CLV Model Example

Marketing Reporting Example

Ep. 44 | Generating Quality Customers Ep. 42 | Junction of Customer Experience & CLV


Show Transcript

Allison Hartsoe - 00:32 - This is the Customer Equity Accelerator. If you are a marketing executive who wants to deliver bottom-line impact by identifying and connecting with revenue generating customers, then this is the show for you. I'm your host, Allison Hartsoe, CEO of Ambition Data. Each week I bring you the leaders behind the customer-centric revolution who share their expert advice. Are you ready to accelerate? Then let's go!

Welcome, everyone. Today's show is a summary of a recent customer centric conference put on by Custora in New York City. Now, if you know me, you might know that I also subscribe to the conference signal to noise ratio, which is simply this. If you want to figure out the signal to noise ratio of any event, then take the number of conference attendees times the number of vendors, speakers, and divide that by the number of conference attendees again, and that will give you the signal to noise score.

Allison Hartsoe - 01:38 - For example, Adobe's conference gets 10,000 attendees and at least a hundred vendors speakers, so 10,000 times 100 divided by 10,000. Again, it gives you a signal to noise score of 100 pretty low signals, pretty high noise, and if you've ever attended that event, you know what it's like where you go from session to session hoping to get a nugget, not knowing if you'll get it, but it's largely um, high entertainment event. There's a lot of fun activities, great networking events, so there can be other virtues, but if your goal is to pick up really good knowledge that is not the conference for you. Conversely, the Chief Analytics Officer conferences, which we will cross link in the, in the notes for this podcast, get about 200 attendees, about ten vendors, speakers and annoy score of about 10, which is really good. Signal to noise ratio, I use this because basically I have no tolerance for bias and if I'm going to be away from my friends and family, it needs to be worth it.

Allison Hartsoe - 02:50 - All of that comes back to Custora's conference, which again, I attended a week or two ago and Custora rings in at a pretty high signal to noise level with a score of 15 for a company that's a vendor putting on an event. That's pretty impressive. Now I had to smile when I noticed the theme for Custora's event matched our conference theme from two years ago. Uh, but I have to say they did it really, really well. The theme and the most important message I want to get across, the main thing you should take away from this episode is the customer revolution is here. And if you are not on this train, you are falling behind. So before we dive into this topic, remember you can download the free customer centric CMO guide by texting ambitiondata to 31996 super easy. It contains all the best nuggets summarized into one document. So text, ambition data, one word to 31996. Now let's dig into the historic conference.

Allison Hartsoe - 04:22 - What you just heard was the song of a customer revolution. Based on Les Mes. The lyrics go something like this. Do you hear the insight? Singing, singing, the song of retention. It's the music of the data that will not be changed. Again, here's a lifetime value chart showing how loyalty is one fantastic concept and that was Corey Pearson singing who is the CEO of Custora. He also kicked off the day with concepts that we stress all the time on this podcast. So go, Corey. I want to thank Corey for not starting the day with that. A beautiful song because for us West coasters, it was awfully early, uh, that he did kick off the day with some really great data about the industry and about what's happening. So, Corey, you've cited a McKinsey report which was about 700 companies that were surveyed showing that customer analytics do indeed drive growth.

Allison Hartsoe - 05:21 - Well, yes, we're all familiar with that, but what makes a winner? This particular competency, the customer analytics competency made the companies twice as likely to beat the rest of their industry when they had a competency in the customer, so I thought that was an interesting stat and then he cited examples like Nike, which of course acquired Zodiac earlier this year, Tiffany's and Zara, which has taken that concept to the extreme by pushing it into supply chain and Crocs, which we've talked about on this show before, so it's clear that customer analytics is driving a big change within an industry, but the challenge is also taking those predictive insights to scale across every touch-point, every part of the organization, not just creating a model that sits on the shelf and many people did talk about that, how they were fantastic models that have been created, but the organization was incapable of using them.

Allison Hartsoe - 06:22 - So the application really matters. Email seems to be the first place where that comes in, so better email, better store experiences, better products for the more sophisticated companies, and that includes interaction from the CFO and the product teams. Again, things that we've all talked about on this show previously, so kudos to Corey for making that very obvious for the attendees in the room, but he also did a really good job of outlining why making the shift is hard, and it's hard for some reasons. He gave about six reasons. The first and the keystone to the entire process is that customer data needs to be unified. If you haven't brought it together, you can't get out of the gate. You can't understand what's going on. If your customer data is sitting in five different tools across your, your systems or more. And with the proliferation of Martech, I continue to believe that a lot of Martech tools don't do us any favors.

Allison Hartsoe - 07:25 - The data has to come together. Second, he cited the AI models need to be built and stay alive. And this is probably true of all models, but really true of AI. That is not just a one time disconnected. Hey, that's nice. Uh, you know, let's apply it and then be done with it. No, these are continuously updated models that live, and that's because your customers live to you should be doing this in a dynamic cycle. Third, he talked about teens and the ability to deliver those insights across the company, and we did hear this from other speakers during the course of the day who talked about how the insights were delivered across their companies. It starts with the business objectives and then everyone has to have access to the customer insight and think about how is it that this applies to my job? It's not just some theoretical concept, and again that reminds me of the John Doerr Measure What Matters book and how everybody snaps to alignment.

Allison Hartsoe - 08:29 - When you get the sense of what the company is trying to deal, it's the same thing here. What is the team trying to do around customers and how can we all ladder in to make everyone else's job easier? How can we all work together? If you don't have that customer insight as for the tip of the spear, then you won't be able to think about that across the board. You'll be thinking about the product. You'll be thinking about operations, or something that is naturally siloed now for generating creative, especially dynamic creative is another challenge. Campaigns are created, but they might need multiple versions, and if it takes four months to get five versions of we to miss your email out, then it is definitely going to be a challenge to get creative that helps personalize and support the customers that state of mind at any particular part of their journey.

Allison Hartsoe - 09:25 - So getting support to do that was a, was a key concept. The fifth point was integrating insights into every touch-point is definitely hard, and I have to agree with that because not only do you have to tackle the data problem, that was number one and the modeling problem of number two, but you've got to have number three, the teams in place and number four. So the fifth problem is really building across all the other problems. So in order to get action, it's not just surfacing a dashboard, it's really integrating across the company in a variety of ways. So the execution across touch-points can happen. This theme of insights across the touch-points is a very pervasive theme. We see it a lot when companies talk about dashboarding and trying to pull insights across the customer base from those dashboards. It is a difficult thing to do because all of those pieces have to come in place beforehand.

Allison Hartsoe - 10:28 - So what can you do? Well, you can focus on larger chunks sometimes, uh, you can focus on perhaps customers that are a risk and just segment to make specific pushes to a specific touch point or you might want to try different ways to upload a list of one-off behavioral changes versus long-term segment identity. An example of that might be the birthday email or the time that someone hasn't been buying from you. So there's a one-off timing where someone is due to come back, but they didn't come back. Uh, you could try uploading a onetime list to see if you get a lift from that group and then use that to start pushing more data integration, pushing more modeling, more insights across the team and dynamic, creative. So there is definitely an, and I oftentimes hear this theme at the, uh, customer analytics conferences. There's definitely the need to start with small winds and create a dynamic cycle before you are suddenly integrating insights across every touch points because as we just said, the integration across touch-points for the insights is very hard and it's very hard to do at scale and speed.

Allison Hartsoe - 11:49 - Finally, the last point Corey made was you are what you measure, and we don't obsess over lifetime value enough, and that is true. I often talk about this as the tip of the spear because people say, Oh, I use customer data, or I talked to one company on the east coast and they were using CLV, but they were putting it inside of other models as a feeder into the model instead of making it the tip, the the most important piece and everything else being a dimension of it. That is a key problem, and so when Corey says, we don't obsess over LTV Enough, he is right. The focus is often a, I want to hit my revenue for this quarter, and that's not wrong. Wall Street still pushes companies to hit those numbers, so we have to balance the short-term revenue. Hitting thinking with the long-term, a competitive advantage of LTV and LTV is really the ultimate metric of customer value as they talk about in the, in the Custora world, they oftentimes focus on the top five percent drawing at least 30 to 40 percent of the value of the company.

Allison Hartsoe - 13:04 - Now, that varies by industry and in retail, that's definitely the case. Uh, so it's a massive issue for retailers if one to two percent of the folks leaves or don't come back, that's a big problem. So LTV is the master, and then you can break it down by average order value, repeat purchase acquisition goals, goals by segment, other things. These are all great points that Corey made, and we are definitely aligned when we think about that. Yes, LTV is the tip of the spear. We have a number of challenges across the industry, but that doesn't change the fact that the customer revolution is here and it isn't easy. Now, previously on this podcast, we've had a number of examples from retailers like Crocs and Bonobos. I'll cross-link to those podcasts, and we have a couple more coming up. So in this episode, I really want to spend some time covering the industry movers and drivers, the main forces that are happening that affect what the retailers can and cannot do.

Allison Hartsoe - 14:11 - So along those lines, I just talked about Corey Pearson's kickoff session. I also want to cover what McKinsey said and what Forrester said in the show, which I think is incredibly powerful for where we are in the industry right now. So let's talk about Sean Flavin, who is with the Marketing and Sales Practice at McKinsey. He was also up in the morning at the Custora conference, and he talked a lot about personalization. And one of the statistics he cited was that 83 percent of customers want personalization. And Ninety-five percent of companies see it as a priority. Yay, good alignment. But 23 percent of consumers think retailers are doing a good job. And 15 percent of marketers say this, and you know, he raised the question, how can I close this gap? Now I can feel this on a personal front because I can tell you every time I go into a particular bank nearby, they have done some lifetime value calculations, and the person behind the screen says to me, Oh, have you considered x, Y, Z, other product, and I just makes me want to scream because it is the exact wrong way to look at personalization because there's no connection to the person at all.

Allison Hartsoe - 15:36 - There's just product pushing, and if there's one message we have to get across in this customer revolution, it is that we're talking people to people. We're not talking about product pushing anymore. Companies no longer have that kind of power. It's not 1980. It's the 21st century and people matter, and they really matter more to your business. The lifetime value, your ability to be of service to them, to engage them is critical to that. So anyways, going back to what Sean was saying, he said, how can you get that kind of effective personalization across channels using customer and prospect triggers to optimize the timing? Content offer and design of experience are what personalization is about. And he talked about it as tailored in real time, depending on the attributes or the context of the behavior. I like to think about this as a, as a cocktail party, right?

Allison Hartsoe - 16:37 - Like you're coming in, and people are having a conversation, and everything is very contextual. And if you are missing a beat as a marketer, then you're basically offering a person in order of, or a drink when they already are holding that in their hand, and we've all had that experience where, you know, you've, you've just booked a hotel room, and then they proceed to re-market to you all across the Internet to please book this Hotel Room drives me bananas. Right? And I think that's the disconnect that, that Shawn was citing earlier in the percentage difference. So how do we get to that kind of contextual behavior? Uh, would he cited is the need to seamlessly connect is really driven by a central engine, and that has to be executed through new operating models that transform a company's way of working. So it's not just the central engine, it's the, uh, it's the ways that we work as a company, which we all call customer-centric, but I know that term has been battered around so much, it hardly has enough definition, but customer centric is really more than putting the customer at the heart of your business.

Allison Hartsoe - 17:49 - It's really about making the trade-off for the value that you received from the customer as important as the way that you relate to the customer and seek to be of service to the customer. So for Sean, he talked about the journey for a brand is something like this, again, like Corey. He cited the data foundation of the database, that's number one, and then he said the decision is really number two, which is the engine connected to the channels or the brain. And then number three is the design or the operating model that you use to make it work. And he didn't specifically say that, that that operating model included the organizational chart. But I have a feeling that it does. And then number four is the distribution or the ability to get those findings across the organization. I would throw a measurement in there as well.

Allison Hartsoe - 18:47 - Uh, so in order to optimize, we really have to be talking about measurement. So McKinsey's model is really about trying to put that higher testing through, put in, making faster changes, uh, so if you do all those things, what does it look like? And I think he's a sighting of a really important process of getting a taste, a cross-functional taste into the organization and of what does it look like, what does it feel like getting that quick win and then moving it through because for them and for everyone, really personalization is about listening to those customer signals. And he talked about um, mass-targeted trigger rates varying between five to 15 percent. So in order of mass marketing has open rates between five and 15 percent. Targeted marketing has between 15 and 25 percent, and high degrees of personalization have between 25 and 40 percent. Now I also want to emphasize that as those percentages go up, the volume goes down, right?

Allison Hartsoe - 19:59 - Because you're not mass marketing anymore. You're looking for the propensity of people who are likely to look at that product. So he talked about weather triggers and life-cycle triggers. Now smart getting is still very common, and it does have a place, but it is a huge problem when you're trying to connect to the product set and, and you're trying to say what's the right intent, what's the right context for this email going out in order to personalize? So Sean went on to say, uh, it takes a lot of time to get those. He underscored the same problem with the campaign functions. It can take weeks to get those campaign functions going and you might personalize first based on the geographic presence, or you might personalize based on the product of course. So he talked about here are our best sellers in Cleveland and that you could get a collaborative model of all the people from that are responsible for the creative and the product and the execution of the email.

Allison Hartsoe - 21:03 - Um, all those groups together in a room and take your whole process down to one to two weeks to get tests out the door. And what that really meant was speed to revenue. A really great concept, speed to revenue. Two hundred dollars to 400 percent increases in a pull through and conversion when you do this. So fantastic session on a, on why to do that kind of testing and if you haven't heard the session with Brooks Belle and her testing philosophy across, link that in the podcast notes too. She talks a lot about how to get to the right test and what to think about. Finally, Sean covered something that I've heard before at the chief analytics officer conferences, and that is that there is this key role of translator people who connect the dots between marketing and technology. They're not exactly Unicorns, but there are people who have enough data science, enough analysts, enough technical architects to understand what's happening across these different divisions.

Allison Hartsoe - 22:08 - And then he said this, you actually go half as fast without a translator. And I thought that was a great concept. Uh, I had not heard that before. And since we play in that space of being translators, I absolutely loved that. So clearly don't wait for perfection. Look for how you can step into that role. What can you do today? Don't waste time putting out an RFP for new tools when the old ones will work. That's a direct quote from Sean, and I loved it because we see that all the time as well and think about that journey from broadcast to macro to micro to one to one to dynamic personalization. How are you going to get there at scale? It's not just reading a test. It's running the dynamic learning process that companies are doing today. The customer revolution is learning from your customers.

Allison Hartsoe - 23:01 - Now toward the end of the day was Brandon Purcell from Forrester, and he's part of their customer insights team there. We've had Joe Stanhope on the show from Forrester as well earlier. Joe Works more on the technical side, and again I'll. I'll include that in the show notes, but Brandon was talking about how we all have lots of data. We want to turn it into insights to help the customer. It's clearly the age of the customer, so you have to do customer analytics to win, serve and retain customers, and then he underscored a theme that we've been hearing all day, which was he had personally built a lot of good models that just sat on the floor because the operational processes were typically missing. Analytics that's been created for insights and remains unused is a big problem. But what I really liked about Brandon session is the four personas of maturity, and I'm going to summarize these episode based on these four personas because I think this is a really nice framework to think about where you are.

Allison Hartsoe - 24:08 - So he had this, um, the slide that he put up and he talked about personas from rookie to guru rookies are not investing in customer analytics. They do a lot of ad hoc activity, and their data is not managed efficiently. Now that might be you. The data not being managed efficiently is really getting around the idea that you've got pockets over here, pockets over there, but the organization is really not rowing in the same direction. Everyone's got their own little area, and they're all working on how can I be the best in my little area, so he didn't go into the organizational side of it, but I think that's very much a part of it. Data in a sense is a signature of your organization, a data and the flow of it indicates how customer-centric your organization is and how healthy it is. How much is it able to compete in the 21st century?

Allison Hartsoe - 25:08 - If your data is locked up in silos, it's just like an unhealthy person that doesn't get enough exercise. Corporations are still entities, and just like a healthy person, you need all those parts and pieces to work together. So Brandon talked about the next persona was the dabbler persona, so first was rookies, then dabblers and dabblers or still decentralized, but they're segmented for acquisition and retention goals. This is a great place to start. In fact, we've had Bryan Eisenberg on the podcast who talked a lot about the flywheel, how companies can be like Amazon. That's a retention goal. That's an. Again, I'll cross link that in the notes, but dabblers are starting to get some movement of the data across the system. That's compared to pros where customer analytics is a strategic priority.

Allison Hartsoe - 26:07 - They're using it predictively, they're using digital data, but in the pros group you still have a pretty good chunk that isn't very good with the digital data, and he actually said 40 percent we're not touching the digital data, which is huge, so using some digital data isn't enough.

Allison Hartsoe - 26:28 - There is so much intent locked up in that digital data. You've really got to use it to be a pro, and of course, that leads to the fourth stage which is gurus. Gurus are using customer analytics, and again this isn't just any customer analytics, this is really lifetime value to inform every decision across the organization. Actually, I'm gonna restate that because what Brandon said and what's different in the model that we use is he said it was across the CX, the customer experience, and I think there's a level beyond the gear real that I have seen from companies that are really leading the space and that it is not just across marketing, they take it to the supply chain, they take it to the product development, they take it beyond into the entire organization. So it might start in marketing, it might start with, um, other areas that touch the customer experience, but in the most sophisticated companies.

Allison Hartsoe - 27:33 - And now I'm not talking about what Brandon said, I'm talking about beyond gurus. They would be driving it into operations. They would be driving it into her, uh, and this is what the most sophisticated companies do. So it is a complete changeover for the organization when they start getting into or really adopting customer analytics. So that was a that was Brandon summary. And then he also talked about how to start a, like others start with the business objectives. You have to align with what the business cares about. If you're going to get any traction at all, engage your stakeholders or early inventory the data he and he stressed as others, so stressed you don't need a 360-degree view first just to get some quick wins and then to select the appropriate analytics plan for action, measure success, communicate results. And this is all this structure I think is pretty commonly known so I won't dwell on it, but it does remain the right way to go about getting action.

Allison Hartsoe - 28:40 - Get those people in early, get your stakeholders, I, you know, I would almost call it and and in the examples that I've seen where people have gotten massive success but they've actually done is they've gotten air cover, so they get a senior executive to protect their strategies as they roll them out because people are not always aligned with a new strategy and the organization hasn't changed yet. So for your fledgling efforts to take off, you must have air cover from that executive that is different than engaging stakeholders early, which I think is more of a lateral move. So I'll just add my little twist on top of that. Now, if you want to hear more about companies that are a part of the Custora conference, I'll be doing some more interviews with those folks. Uh, in the sessions coming up. You can also hear Jordan session that I'll link to in the show notes where he talks about specific examples of companies that are leading by customer lifetime value, and they're using customer analytics correctly.

Allison Hartsoe - 29:44 - And of course if you want to talk more about the subject or perhaps find a way to improve your own strategy, you can also reach out to me, allison@ambitiondata or @ahartsoe on twitter or Allison Hartsoe on LinkedIn and you can get that free strategy download of everything that we've figured out. Everything we know put into this customer-centric CMO guide by texting ambitiondata to 31996. So ambition data, all one word, lowercase to 31996. I want to thank everyone for joining us today. This really was a good episode with a lot of great insights. I hope you got a lot from it. As always, links to everything we discussed, including all of those cross-linked podcast that I mentioned are going to be on Thank you for joining me today. Remember, when you use your data effectively, you can build customer equity. It is not magic. It's just a very specific journey that you can follow to get results.

Allison Hartsoe - 30:49 - Thank you for joining today's show. This is your host, Allison Hartsoe and I have two gifts for you. First, I've written a guide for the customer-centric CMO, which contains some of the best ideas from this podcast, and you can receive it right now. Simply text, ambition data, one word to 31996 and after you get that white paper, you'll have the option for the second gift, which is to receive The Signal. Once a month. I put together a list of three to five things I've seen that represent customer equity signal, not noise, and believe me; there's a lot of noise out there. Things I include could be smart tools. I've run across articles, I've shared cool statistics, or people and companies I think are making amazing progress as they build customer equity. I hope you enjoy the CMO guide and The Signal. See you next week on the Customer Equity Accelerator.


Key Concepts:  Customer Lifetime Value, Marketing, Digital Data, Customer Centricity, Long-Term Customer Value, Marketing Leaders, Analytics, Creativity, Product Development, Audience Research


Who Should Listen:  CAOs, CCOs, CSOs, CDOs, Digital Marketers, Business Analysts, C-suite professionals, Entrepreneurs, eCommerce, Data Scientists, Analysts, CMOs, Customer Insights Leaders, CX Analysts, Data Services Leaders, Data Insights Leaders, SVPs or VPs of Marketing or Digital Marketing, SVPs or VPs of Customer Success, Customer Advocates, Product Managers, Product Developers

Podcast Updates

Sign up to be notified when each week's episode is released.




Recommended Episodes


Ep. 42: Intersection of CX and CLV with Ehow Chen



Ep. 54: 2019 Predictions Show Financial Impact from Marketing with Dan McCarthy



Ep. 62: Cultivating Customers with Prof. Elea Feit at Drexel



Ep. 71: Four stages of Loyalty with Pete Fader


Listen to the Customer Equity Accelerator Podcast




Available on itunes  



Listen on Google Play Music