Latest / ContraMinds Podcast - Unlocking Personal Growth and Professional Excellence / Allison Hartsoe on Transforming Businesses by Understanding Customers (#020)

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Allison Hartsoe on Transforming Businesses by Understanding Customers (#020) · ContraMinds Podcast - Unlocking Personal Growth and Professional Excellence

• 0:01
  SPEAKER_00: There's a certain way of thinking strategically that is very rare in younger workers.
• 0:10
  SPEAKER_00: So if I'm 18 and I'm figuring things out, I'm often, and especially as coming out of school, I'm taking an assignment, I'm executing, and I'm used to this pattern of execution, execution, execution.
• 0:22
  SPEAKER_00: And I might not be thinking too much about why, what's the bigger picture?
• 0:26
  SPEAKER_00: Or I might just say, you know, my why is my immediate because the teacher asked me to, or because my boss asked me to.
• 0:34
  SPEAKER_00: I would encourage 18-year-olds to look beyond and see through the data and see through the information to what is the bigger picture.
• 0:47
  SPEAKER_00: That does not usually come from your boss.
• 0:50
  SPEAKER_00: That does not usually come from your everyday work.
• 0:53
  SPEAKER_00: It comes from listening to leaders, listening to sources of information, and developing a sense of triangulation from those sources where you start to get a sense for where the value that of your work is.
• 1:58
  SPEAKER_02: So without further ado, is the conversation with Alison Hot.
• 2:08
  SPEAKER_01: Hi Alison.
• 2:10
  SPEAKER_01: Thank you very much for uh being a special guest in our podcast, and it's really a privilege to have you and uh for you to share our share your thoughts with our audience.
• 2:21
  SPEAKER_00: Thank you, Swami.
• 2:22
  SPEAKER_00: It's a pleasure to be here.
• 2:25
  SPEAKER_01: Great Alison.
• 2:26
  SPEAKER_01: So I wanted to start this conversation with uh something that uh I've read a lot about your passion for customer equity and the fact that data is critical in marketing.
• 2:40
  SPEAKER_01: So, where did this passion for data-driven marketing, customer equity come in in your career?
• 2:49
  SPEAKER_00: You know, what's uh what's so interesting about that is it didn't come from marketing at all, it came from my entrepreneurial background.
• 2:59
  SPEAKER_00: And when I was a young woman in my 20s, I actually sat on the board of a venture-backed startup.
• 3:07
  SPEAKER_00: And in that startup, there was a lot of discussion about what moved the business.
• 3:12
  SPEAKER_00: And then years later, I worked in digital analytics, and there was this big gap where many analysts were saying, we're surfacing insights, they don't seem to go anywhere, we don't have any impact.
• 3:26
  SPEAKER_00: And I thought, wow, I have a unique perspective to share of how data can connect from the boardroom to the tactical war room, and that pipeline is basically the customer through customer equity.
• 3:43
  SPEAKER_01: Fantastic.
• 3:45
  SPEAKER_01: How do you see the difference between brand value and customer value?
• 3:51
  SPEAKER_00: Yeah, I I'm early on, I was not a big fan of brand value, but I do think it is the grease in the wheels now.
• 4:04
  SPEAKER_00: And so let's say, for example, that you have a business and you are very focused on customers and you are working very hard to make sure that good customers buy again from you.
• 4:17
  SPEAKER_00: Is it enough to just drive by the data and continue to pursue those good customers?
• 4:25
  SPEAKER_00: And the answer there is no, no, it is not.
• 4:28
  SPEAKER_00: You need brand value on the other side to help put more grease in the wheels, to make sure that your awareness is top of mind.
• 4:38
  SPEAKER_00: But I but the converse is also true.
• 4:41
  SPEAKER_00: If I only focus on brand value, then I miss the opportunity to make more interesting things, more engagements, more bonded relationships happen with my good customers by not knowing who they are and simply focusing on brand.
• 5:02
  SPEAKER_00: So the two really work hand in hand like brother and sister.
• 5:06
  SPEAKER_00: Sometimes they fight, but mostly they should work together as part of the same family.
• 5:14
  SPEAKER_02: So so, Alison, while preparing for this interview, I was going through your career and your book that you published recently.
• 5:22
  SPEAKER_02: So, congrats on the publication of your book first and foremost.
• 5:25
  SPEAKER_00: Thank you, Vignash.
• 5:26
  SPEAKER_02: Yeah, it's um it's called The Age of Customer Equity: Data Driven Strategies to Build a Sustainable Company.
• 5:33
  SPEAKER_02: But before I uh lead to specific questions about customer equity in the book, there's a very interesting trend I noticed in your career, which is early on in your career you have been uh involved with a lot of startups which have been acquired by larger corporations.
• 5:48
  SPEAKER_02: One of the companies you worked in early in your career was bought by Intubid, then uh Symphonic uh was acquired by Winston Young.
• 5:56
  SPEAKER_02: So I'm very interested to know why uh you consciously chose to go off and seek different adventures when you had the opportunity to work in name brand organizations.
• 6:09
  SPEAKER_00: That's a wonderful question, especially for I think uh for an international audience.
• 6:15
  SPEAKER_00: For me, it was important to work in an environment that allowed me to bring my whole brain, my whole self to work and execute as much as I possibly could.
• 6:32
  SPEAKER_00: I did not enjoy what sometimes happens in a larger brand name organization where you are a cog in the wheel, and that's an important part of a large organization.
• 6:45
  SPEAKER_00: They need everyone to operate lockstep, but that was not comfortable for me.
• 6:51
  SPEAKER_00: And so if you imagine an engine, you know, here you have one cog that's constantly stepping out of the out of the wheel, it doesn't work as smoothly.
• 7:02
  SPEAKER_00: And so I would find myself in these larger companies asking disruptive questions and why do we have to do it that way?
• 7:10
  SPEAKER_00: And why can't I do it like this?
• 7:12
  SPEAKER_00: And it was not well received.
• 7:17
  SPEAKER_00: So when I think about what was right for me uh was the ability to, uh and it was a natural attraction to entrepreneurship because I could work so hard and effectively in all these areas.
• 7:35
  SPEAKER_00: Now, the downside of that is you're working hard in all those areas, and you become a very good generalist, but you also have to have some deep specialist areas.
• 7:49
  SPEAKER_00: Um, early on in my career, and not many people know this, I interviewed at Netscape, and I was very excited, I was very young and really wanted to be part of the whole internet boom in Silicon Valley.
• 8:04
  SPEAKER_00: And I went all in on this interview.
• 8:08
  SPEAKER_00: The interviewer or the recruiter came back to me and said, They don't know what to do with you.
• 8:13
  SPEAKER_00: You know, it seems like you would be a good fit for Netscape, but you're too general here, too general there, you know how to do this, you know how to do that, but you're not like you're not a specific cog in the wheel.
• 8:26
  SPEAKER_00: You're not deep in one area.
• 8:28
  SPEAKER_00: And that is kind of the definition of an entrepreneur, is we're good at a lot of things.
• 8:36
  SPEAKER_00: We're really good problem solvers.
• 8:39
  SPEAKER_00: And we enjoy pro problem solving, but ultimately, if you keep us in one place too long, we get bored.
• 8:47
  SPEAKER_00: And so uh the the reason for me to leave those larger brand name companies was always to go and explore the areas that my curiosity was blooming.
• 9:00
  SPEAKER_00: And in the um a couple years ago, I guess in the 2010s to 2015 time frame, that was analytics and cloud data and all the really cool things that were happening around customer data.
• 9:18
  SPEAKER_01: Fantastic.
• 9:19
  SPEAKER_01: I think uh your definition of why and what drives an entrepreneur was very interesting.
• 9:27
  SPEAKER_01: It was very vivid, I must say, I must say.
• 9:29
  SPEAKER_01: Uh, you're a big believer, uh Alison, on customer lifetime value, and uh that's something that uh has caught the attention of uh you know company valuation, brand valuation, and uh it's uh it's a concept that actually is getting a lot of attention.
• 9:49
  SPEAKER_01: Can you talk to me about what is customer lifetime value and what is the implication it has got on you know the companies' products and the work that they do?
• 10:02
  SPEAKER_00: Yeah, uh so thanks, Swami.
• 10:05
  SPEAKER_00: That's a very big question, but let me start with one of the fundamental ideas.
• 10:11
  SPEAKER_00: Customer lifetime value should always be distinguished from recency frequency modeling.
• 10:17
  SPEAKER_00: Recency frequency modeling is like looking out the rear view window of a car and trying to drive while looking backward.
• 10:24
  SPEAKER_00: It always uses historic data.
• 10:27
  SPEAKER_00: Customer lifetime value projects forward.
• 10:30
  SPEAKER_00: So we're predicting the propensity of customers individually to buy again.
• 10:37
  SPEAKER_00: The other distinguishment uh which you may not have heard in that definition is recency frequency modeling is often averaged.
• 10:46
  SPEAKER_00: So it's big, chunky data.
• 10:49
  SPEAKER_00: Customer lifetime value data is individually calculated and rolled up, which gives you a higher degree of precision.
• 10:57
  SPEAKER_00: So I always know when when a company I'm talking to says, oh, we do customer lifetime value, or they just call it lifetime value, and then they show me a decile chart.
• 11:09
  SPEAKER_00: Um, I always know that they've done it wrong because it it's usually by definition in that display, it almost always comes in as recency frequency modeling.
• 11:23
  SPEAKER_00: That doesn't mean that you can't do customer lifetime value as a decile chart.
• 11:27
  SPEAKER_00: It's just the it's kind of the old-fashioned go-to.
• 11:31
  SPEAKER_00: So, what is the difference then if I were doing customer lifetime value?
• 11:37
  SPEAKER_00: Would I still break it up into deciles?
• 11:39
  SPEAKER_00: Well, if you do that, think about all the actions that you're asking people to take.
• 11:47
  SPEAKER_00: As a human being, I can hold maybe seven different items in my head and then branches of those seven items and branches of those seven items.
• 11:59
  SPEAKER_00: So if I've got a decile chart of 10, and then people are moving in between these different deciles, and I want to apply different strategies and tactics to different ones, now suddenly I've got exponential things to keep in my head, and it makes it very hard to execute.
• 12:15
  SPEAKER_00: So with customer lifetime value, we like to think about it in terms of high value customers, medium value customers, low value customers, and then new customers.
• 12:28
  SPEAKER_00: You can think about it, um, other terminologies that have been used are platinum, silver, platinum, gold, silver, and lead.
• 12:37
  SPEAKER_00: Sometimes lead is pejorative, meaning that it's not a nice way to talk about customers.
• 12:43
  SPEAKER_00: So I prefer high, medium, and low, although low suffers from somewhat the same problem.
• 12:48
  SPEAKER_00: But, anyways, however you decide to break it up, it's important that companies who are using customer lifetime value are not providing um in order to get the human adoption first, you're not providing such granularity that it becomes very difficult to grasp to gain hold of.
• 13:23
  SPEAKER_00: As people start to grasp this concept, what they find is that customers are the core behind any sale.
• 13:34
  SPEAKER_00: So the heart of a business that's usually reported out on any investor call are things like how many stores did you open?
• 13:43
  SPEAKER_00: How many products did you launch?
• 13:45
  SPEAKER_00: What are the margins on those products?
• 13:47
  SPEAKER_00: Well, what are you missing in that?
• 13:49
  SPEAKER_00: Where's the customer?
• 13:51
  SPEAKER_00: The customer is an assumed entity in all of the financial data that's typically reported to Wall Street.
• 13:59
  SPEAKER_00: And Wall Street is part of the problem in that they're they're asking for this data and they're making analysis and values on this data, but I think they are starting to change.
• 14:09
  SPEAKER_00: And the leaders that are out there, um, the Spotify, um, some of the new meal package companies, some of the leaders are starting to report customer cohort metrics.
• 14:24
  SPEAKER_00: And what's interesting about that, in the investment point of view, is maybe Wall Street's asking for it, maybe they're not, but it's a very strong metric of the health of a company.
• 14:35
  SPEAKER_00: So when a company does disclose it, they disclose it because they're comfortable with the number and they feel good about the customer base.
• 14:43
  SPEAKER_00: But secondarily, it also shows that they understand a lot about what's driving their business and the people behind the business, that causes them to be more sensitive to changes in the business, um, changes in the market, changes from competitors.
• 15:02
  SPEAKER_00: And I think that makes them more of a leader.
• 15:05
  SPEAKER_00: We could talk more about that.
• 15:06
  SPEAKER_00: But ultimately, customer equity is the idea that we're using customer lifetime value to drive a sustainable business because it's the customers behind the business that make the difference.
• 15:21
  SPEAKER_00: And knowing whether customers are coming back, knowing whether they're happy with us, knowing whether we are pleasing them, not just that we're selling another burrito, but we're actually selling them to the same people who want to buy again and again, is very meaningful and something that most data sets for everyday companies do not always show.
• 15:47
  SPEAKER_01: Fantastic uh brilliant explanation on CLV and the impact that CLV can make on companies.
• 15:55
  SPEAKER_01: Fantastic uh uh thanks for that uh uh definition and uh you know point of view on CLV.
• 16:02
  SPEAKER_01: Uh one of the questions that I have uh as a follow-up on this, Alison is calculating CLV.
• 16:10
  SPEAKER_01: Many a times, uh, you know, how do you attribute costs?
• 16:14
  SPEAKER_01: Uh, you know, is always a challenge in companies because they don't make investments basis customers, but they make investments basis processes.
• 16:24
  SPEAKER_01: And when I am a customer and you want to really work my lifetime value, uh, how do I define whether a five-year lifetime value is great for a business?
• 16:35
  SPEAKER_01: Uh, whether uh you know seven-year time value is great for business, how do I attribute cost to ensure that I calculate customer lifetime value?
• 16:44
  SPEAKER_01: So, can you give me some examples of how you know you peel the onion in terms of you know CLV?
• 16:54
  SPEAKER_00: Yes, there's there's a lot of different ways to use CLV, and sometimes within the same company, different departments will use it differently for different purposes.
• 17:04
  SPEAKER_00: So, for example, you mentioned five years versus seven years.
• 17:08
  SPEAKER_00: Well, if my purpose is to value a company for investment, then I might use 15 years or 10 years.
• 17:17
  SPEAKER_00: But if my purpose is to use lifetime value for marketing, I might use two years or one year.
• 17:24
  SPEAKER_00: It often depends on the purchase cycle and the purpose.
• 17:29
  SPEAKER_00: So shorter time frames will give you more accuracy, but less dollar volume.
• 17:38
  SPEAKER_00: Longer time frames will give you the maximum dollar volume, which is important if you're trying to sell your company, for example, um, but also be you know somewhat soft and and harder to say, yeah, this will absolutely come through, right?
• 17:54
  SPEAKER_00: You're you're predicting in the future, you know, and assuming that things will stay the same and we don't have COVID or we don't have 9-11 or any of these black swan events that happen.
• 18:06
  SPEAKER_00: So, or competitors entering the market.
• 18:09
  SPEAKER_00: So, back to your question.
• 18:11
  SPEAKER_00: In the formula, when you when you're attributing costs, one cost that you have to attribute is the time value of money.
• 18:20
  SPEAKER_00: So you have to always include a discount rate.
• 18:24
  SPEAKER_00: Um, a lot of people will run a CLB formula, but not discount the dollars in the future.
• 18:29
  SPEAKER_00: And sometimes people will play with that number depending on what they what they think looks good.
• 18:35
  SPEAKER_00: But the best way to do it is to ask your CFO what the discount rate, what an appropriate discount rate might be.
• 18:44
  SPEAKER_00: And now I'll I'll caveat all this by saying I'm not a financial expert, but the way I think about it is if I were having this discussion with a CFO, I would think about the fundamental concept that dollars received today are worth more than tomorrow.
• 19:02
  SPEAKER_00: And what is the cost of borrowing a dollar?
• 19:06
  SPEAKER_00: So the interest rate should go, should be factored in to the idea of the discount rate.
• 19:14
  SPEAKER_00: Now related to other costs, there's a couple different ways to use CLV.
• 19:23
  SPEAKER_00: If you're going to use it to try to figure out how much should I spend in different acquisition channels, then you should include the costs of those acquisition channels in order to get a clean metric between the two.
• 19:37
  SPEAKER_00: But what do you do about your Salesforce?
• 19:40
  SPEAKER_00: Uh, what do you do about your onboarding team?
• 19:44
  SPEAKER_00: So let's say that I'm a SaaS product or I'm a technology and I have an onboarding team and a sales team, and then I have marketing channels.
• 19:54
  SPEAKER_00: Well, it's it's up to you how much you want to include that.
• 19:57
  SPEAKER_00: Companies do include it or they don't include it.
• 20:00
  SPEAKER_00: If you use a fully loaded number and you include maximum costs, then what could be good about that is you're really you're really pushing to profitability.
• 20:14
  SPEAKER_00: But if you are in a growth mode and you're trying to gain as much advantage and you don't care as much about profitability, you care that you're you know within a certain amount of profitability, but you're not gonna push it really hard because you know you've got a lot of money in the bank, you're expecting more venture rounds.
• 20:36
  SPEAKER_00: Well, then you might not care about loading in all those costs.
• 20:39
  SPEAKER_00: You might just load in marketing cost against the channels.
• 20:42
  SPEAKER_00: Does that make sense?
• 20:47
  SPEAKER_00: So that's how I like to think about it.
• 20:49
  SPEAKER_00: Um, but there's a lot of ways to tinker with the formula.
• 20:52
  SPEAKER_00: Ultimately, you need your you need someone internally, such as the CFO or the CEO, to bless the formula so that people agree to take action on the results.
• 21:06
  SPEAKER_02: So, Alison, I have a question uh regarding some of your thoughts on what the future is going to be from a customer equity and data analytics point of view.
• 21:18
  SPEAKER_02: So my question, Alison, is what I what is it that you foresee, or what can you tell us about what are some upcoming customer data mega trends uh if you'd be up for that?
• 21:29
  SPEAKER_00: Certainly.
• 21:30
  SPEAKER_00: Always happy to see around corners.
• 21:34
  SPEAKER_00: I think I think there's a couple trends that are coming up.
• 21:39
  SPEAKER_00: One of the trends that I keep watching is the ESG metrics that are being reported up to the board.
• 21:46
  SPEAKER_00: So board members, uh so let me let me back up a little bit.
• 21:51
  SPEAKER_00: And I talk about this in the book as well, in in one of the ending chapters.
• 21:56
  SPEAKER_00: Um BlackRock put out, I think it was Larry Finger.
• 22:00
  SPEAKER_00: From BlackRock, he put out an investor memo, was it two years ago now?
• 22:05
  SPEAKER_00: Uh, where he was talking about we are not just about shareholder value.
• 22:10
  SPEAKER_00: We are responsible, and we look for companies to invest in that are also responsible for the employee metrics, for the customer metrics, for the social metrics, and the environmental metrics.
• 22:26
  SPEAKER_00: And he made it clear, and then this was echoed by the business roundtable, which is a very powerful group of business leaders, that said, yes, we all agree to this that we are going to drive our companies by something more than just sheer greed and profit.
• 22:44
  SPEAKER_00: What was funny about that was the B Corporation organization responded back, and I think the New York Times, they ran an ad responding to the business roundtable saying, yeah, that's nice.
• 23:00
  SPEAKER_00: But, you know, if you really believed this, you would be a B Corporation, which is what we've done all along.
• 23:06
  SPEAKER_00: You know, put your money where your mouth is.
• 23:08
  SPEAKER_00: And so they had this bit of um debate between the two, and it really isn't resolved.
• 23:15
  SPEAKER_00: But but the question is on the table now, and boards are concerned and they're worried about this because they know that their customers and investors are looking to them to be environmental responsible, socially conscious, sensitive in diversity, um, and part of that is customer-centric and other things.
• 23:38
  SPEAKER_00: But this is a big lift on a company.
• 23:40
  SPEAKER_00: And what doesn't happen, what the company doesn't have is a really good way of understanding what is the impact on the company.
• 23:51
  SPEAKER_00: So companies aren't charities, so at the end of the day, they must exist to make money, they must exist to deliver shareholder value back, otherwise, they don't live to see tomorrow.
• 24:06
  SPEAKER_00: And when they get pressure to report these metrics, I think initially they start out with the trend of let's just report something back.
• 24:20
  SPEAKER_00: And it becomes a little bit of greenwashing, or you know, if it's yay, we did this.
• 24:27
  SPEAKER_00: Are you happy now?
• 24:28
  SPEAKER_00: Let's just check that box.
• 24:30
  SPEAKER_00: But there's a there is a more powerful trend coming in behind that that says, okay, we realize it takes some time to get used to these metrics and to understand what they mean for the business.
• 24:44
  SPEAKER_00: But let's not lose sight of the fact that you need these highly impactful metrics to take root at the board level and start to drive by them.
• 24:56
  SPEAKER_00: I think it's gonna be five years at least before we start seeing more clarity and before companies start to feel comfortable with reporting metrics that are um maybe customer equity based, ESG-based along those lines.
• 25:16
  SPEAKER_00: But this is a very interesting trend and and and a lot too, um, a lot is happening here.
• 25:23
  SPEAKER_00: More tactically, I think we're seeing more trends around lifetime value appearing in every tool as you turn around, right?
• 25:33
  SPEAKER_00: So now my email tool has lifetime value and Google Analytics has lifetime value, and you know, you can hardly turn around without lifetime value appearing.
• 25:44
  SPEAKER_00: I find that this is good, that it's important, but they're but for the reasons we discussed earlier, where the metrics can be calculated differently in a variety of ways, this is not something that you you want to just sit out in a in a different tool and assume that CLV is calculated in the same way across all tools.
• 26:06
  SPEAKER_00: This is a problem, right?
• 26:08
  SPEAKER_00: And and the way they classify and group.
• 26:10
  SPEAKER_00: So, my opinion is always that a company needs to own the CLV operation.
• 26:16
  SPEAKER_00: They need to own that calculation.
• 26:19
  SPEAKER_00: And that's why you know we we put it into Rubino, which is a tool that we have on the side, but designed to basically say customize it, calculate it, inject it into another company's data system, whether that's your email tool, whether it's your core cloud databases, it doesn't matter, but you have to have a system that calculates it the way you believe it should be calculated.
• 26:42
  SPEAKER_00: And if you're going to change it, you have to have access to all the pieces to change it.
• 26:48
  SPEAKER_00: So you cannot black box CLV in order to really drive by it.
• 26:55
  SPEAKER_00: Now that's not to say that you can't get some value out of it.
• 26:58
  SPEAKER_00: It can be good to expose yourself to the ideas.
• 27:02
  SPEAKER_00: You know, you can get some good information about what's moving among your customer base, but I find it very difficult once you start to um unpack the data by CLV, once you start to pivot it by which products and which people and which channels and all the different things that you can do when you attach that to the data stream.
• 27:27
  SPEAKER_00: I find it very difficult to do that if I don't have complete control over the CLV metric.
• 27:33
  SPEAKER_00: So I don't I see the trend, the immediate trend being people are understanding that there's value in CLV, but what that means for them isn't yet clear.
• 27:46
  SPEAKER_00: So the trend will be understanding how to use CLV and using it a little more proactively, especially as data science gets more uh power, more data underneath its wings, it just becomes more powerful as companies mature.
• 28:02
  SPEAKER_01: Fantastic.
• 28:04
  SPEAKER_01: So uh with this mega trend happening, Alison, uh one of the questions uh that I have is how do you really apply this CLV in you know real life corporate uh you know strategy?
• 28:20
  SPEAKER_01: Because you have a number, now I have a channel which is acquiring customers, I have a direct channel of sales teams acquiring customers, there is a digital channel where you are acquiring customers.
• 28:33
  SPEAKER_01: Uh uh, you know, there are multiple ways in which customer can come into an organization.
• 28:38
  SPEAKER_01: So, in your you know, uh consulting assignments, in your advisory services that you provide as a company, uh, how do you really go about looking at implementing this in an organization?
• 28:54
  SPEAKER_01: Because you need an aligned strategy to kind of get it going, right?
• 28:59
  SPEAKER_00: Yeah, yeah.
• 29:00
  SPEAKER_00: I think it depends on where your first stakeholder is.
• 29:05
  SPEAKER_00: And in many cases, it doesn't have to be this way, but in many cases, marketing has the biggest view of the customer, and so marketing can be the first place to apply CLV.
• 29:21
  SPEAKER_00: Again, it doesn't have to be that way.
• 29:23
  SPEAKER_00: So, for example, you could apply it to um to the sales team and start thinking about the type of customers that the sales team is bringing in, but that's a twist on the on the metrics.
• 29:36
  SPEAKER_00: So let's say that your marketing team is your stakeholder, and let's say that you have CLV calculated internally and you're really comfortable with the way that the calculation is being done.
• 29:53
  SPEAKER_00: How then do you start to execute it?
• 29:56
  SPEAKER_00: Well, the first place, and this is what the leaders do, and again, I talk about this in the book, um, particularly in the interview with Zach Anderson at Electronic Arts, where the first place he looked was where the company could, where the company had pain.
• 30:15
  SPEAKER_00: In for for that case study, the company had a lot of pain around the cost of acquisition.
• 30:22
  SPEAKER_00: The cost of acquisition was rising, and frankly, I think this is true for a lot of companies because we can see that paid advertising is getting less and less effective, hence the costs keep going up.
• 30:35
  SPEAKER_00: Um, so that can be a primary place to start acquisition, um, tracing it back through acquisitions.
• 30:44
  SPEAKER_00: Now, my my caveat here is I'm not a big fan of acquisition modeling because I think ultimately when you do the acquisition modeling, what you end up with is basically something that looks like spaghetti.
• 31:00
  SPEAKER_00: Oh, I came in here, I went there, I went around, you know, was I acquired, was I not?
• 31:05
  SPEAKER_00: Did I tell a friend?
• 31:07
  SPEAKER_00: You know, it's just like it's a big mess.
• 31:10
  SPEAKER_00: So and and the second reason I'm not a big fan is when you do that kind of acquisition model, acquisition modeling, it focuses you on the channel, and you keep thinking channel, channel, channel, and what you should be thinking is human, customer, who is this person, of which the channel is a subset.
• 31:33
  SPEAKER_00: So in the first application of CLV, it's it's important to focus on what is the right pain point you're solving for the company.
• 31:45
  SPEAKER_00: Is that a pain point around a cost?
• 31:47
  SPEAKER_00: That's a great place to start.
• 31:49
  SPEAKER_00: How can you quantify how much you're saving the company by adjusting something, a channel mix, for example, uh, that can then be used as a case study for more power for your team and more use of CLV.
• 32:07
  SPEAKER_00: If conversely, you don't pick an area where there's a lot of pain.
• 32:12
  SPEAKER_00: Let's say I pick um let's say I pick survey results and I have a bunch of survey results coming in, and I sort them by customer lifetime value, and I tell my company you should be focused on what high value customers are saying, not on what low value customers are saying.
• 32:35
  SPEAKER_00: How much pain does that solve for the company?
• 32:38
  SPEAKER_00: Well, it's kind of a soft fit, right?
• 32:41
  SPEAKER_00: It's not that there's not any pain there, but it's just not directly attributed to a particular dollar.
• 32:47
  SPEAKER_00: And so it usually requires: okay, are they talking about a specific event?
• 32:51
  SPEAKER_00: Does that mean we shouldn't run the event?
• 32:53
  SPEAKER_00: Is that really going to happen?
• 32:55
  SPEAKER_00: Because then there's a branding effect of if we're not in the market, are we not going to do that?
• 32:59
  SPEAKER_00: So I'd encourage people who are going to use customer lifetime value to take a page from Amazon and think through the second and third order operations.
• 33:08
  SPEAKER_00: It's not just the immediate answer, it's and then what?
• 33:12
  SPEAKER_00: And then what?
• 33:14
  SPEAKER_00: And as you dig, it helps you understand is this the right application for CLV?
• 33:20
  SPEAKER_00: And what will someone do with this?
• 33:22
  SPEAKER_00: And how will that impact their role inside the company?
• 33:26
  SPEAKER_00: If the answer is it will make them look like a superstar, then you've got the right piece.
• 33:34
  SPEAKER_01: So if you so if you get them to be superstars and if you really believe those metrics create superstars, then I think CLV is working, is your uh uh your point, right?
• 33:48
  SPEAKER_01: Yeah.
• 33:50
  SPEAKER_00: The the impact of the analysis done through CLV should be to create a very powerful superstar for whoever you're doing the analysis for.
• 34:03
  SPEAKER_00: So whether that's a stakeholder on the other side of the table, whether that's internally your boss or someone else, uh, I like to think about it that way.
• 34:13
  SPEAKER_00: Is this something that the CMO is going to take to the board?
• 34:16
  SPEAKER_00: Is this something that the director is going to take to the CMO?
• 34:21
  SPEAKER_02: So, Alison, currently you're with ambition data, and uh so you're playing a huge role there.
• 34:27
  SPEAKER_02: And my question to you is how would you describe the vision behind ambition data?
• 34:32
  SPEAKER_00: I have to tie it pretty closely to my own experience because it's my company.
• 34:40
  SPEAKER_00: I think about it as finding ways to connect the customer, finding ways to make the business more powerful.
• 34:54
  SPEAKER_00: I I think back to my own time frame as an entrepreneur sitting in the boardroom, and and as I picture myself in this particular space, I remember wanting the right kind of information, the right kind of metrics, so that I could drive the conversation with the board, as opposed to the board coming to me and saying, XYZ is happening with your competitor over here, why don't you do that too?
• 35:28
  SPEAKER_00: I think there's a very powerful role that CEOs, board members, executives can have when the data is shaped correctly.
• 35:40
  SPEAKER_00: So personally, when I think about my experience and what I want to give back to other companies, it's here's a way to really understand the drivers of your business, not from the everyday top-line metrics, but from the core value, what keeps the doors open tomorrow, the the sustainable strategies that that encourage you to not just create good immediate tactical choices, but also drive the valuation of the business because the same the same metrics that the investors will come back and use later on are very much anchored to the way we think about customer lifetime value.
• 36:30
  SPEAKER_00: So it's easy to get lost in page views and visits and visitors and impressions and all of this jargon that we use in digital analytics and in data analysis, but when we bring it back to the customer and the customer lifetime value, we suddenly get signal in that noise.
• 36:57
  SPEAKER_00: And so that's what ambition data was that was the heart behind it was to kind of say, how can we grow companies along this maturity curve?
• 37:07
  SPEAKER_00: Maybe they're not ready for customer lifetime value, maybe they only need tracking and they can't trust their data.
• 37:14
  SPEAKER_00: That's you solve for that, but then you keep laddering up and you keep you keep moving through the maturity with the right information in the right way.
• 37:24
  SPEAKER_00: And it's just it's like it's like going to a restaurant.
• 37:28
  SPEAKER_00: If you you can order, you know, you can order a great meal in in lots of different restaurants, but sometimes a restaurant really makes just an amazing meal.
• 37:38
  SPEAKER_00: And is it, you know, is it that that restaurant didn't serve fish and the other restaurant did?
• 37:44
  SPEAKER_00: No, they all serve fish.
• 37:45
  SPEAKER_00: But the the fish that you get from this particular restaurant is so well done, it's so perfect, it's just amazing.
• 37:51
  SPEAKER_00: That's like data.
• 37:53
  SPEAKER_00: We want data to feel so amazing, to have that that pop, that wow, this is the impact.
• 38:00
  SPEAKER_00: And it's it's uh it's hard to get there, but it's a very fine difference between good information and great information.
• 38:08
  SPEAKER_00: Sometimes it's what you leave out of the recipe, and sometimes it's what you put in.
• 38:14
  SPEAKER_01: As you as you embark and work on this ambition uh and the mission for uh your company, one of the challenges that I see, Alison, is uh uh customer today, company balance sheets capture all information about company operations.
• 38:32
  SPEAKER_01: It could be cost of funds, it could be uh you know the cost of running a business, but customer value never gets captured.
• 38:41
  SPEAKER_01: Imagine if customers were in inventory and there's so much of uh data that gets captured saying, are you buying at the right price?
• 38:49
  SPEAKER_01: Are you selling at the right price?
• 38:51
  SPEAKER_01: Are you getting better margins?
• 38:53
  SPEAKER_01: But customer value hardly gets captured in a customer balance sheet.
• 38:58
  SPEAKER_01: Uh, is that something that you think is important?
• 39:01
  SPEAKER_01: And how do you really drive this agenda in the board and make it a priority for the CEO?
• 39:09
  SPEAKER_00: It definitely does not appear in the balance sheet, in the PL or in the cash flow statement.
• 39:16
  SPEAKER_00: It doesn't appear in your advertising reports or your sales calls, or I mean, you could just list probably hundreds of data sets.
• 39:27
  SPEAKER_00: Um, your point of sale reports from your um from your stores don't contain that information, they contain products sold and how much do you need to reorder?
• 39:38
  SPEAKER_00: Um there are so many places where customer data doesn't appear.
• 39:44
  SPEAKER_00: I think the only solution there is to start using the customer data and surfacing it in a format that can be thought of like a balance sheet.
• 40:00
  SPEAKER_00: So, for example, one thing that we like to do is to calculate customer lifetime value and say, here's the lifetime value at point of time now, and then what was it 12 months ago?
• 40:16
  SPEAKER_00: And that gives a sense of is the company increasing in value or decreasing in value?
• 40:24
  SPEAKER_00: And it's not exactly on the balance sheet, but it kind of fits in that same grouping.
• 40:30
  SPEAKER_00: Another way to think about that is cohorts, and we are seeing a lot more cohort analyses come through for customers that were acquired in this quarter.
• 40:43
  SPEAKER_00: How does that compare over time?
• 40:45
  SPEAKER_00: What does their spark line look like?
• 40:47
  SPEAKER_00: Are they um growing?
• 40:49
  SPEAKER_00: Are they buying the same products?
• 40:51
  SPEAKER_00: And I do see this becoming much more common.
• 40:54
  SPEAKER_00: So, cohort analysis is starting to be a very easy gateway to get used to customer data and how they're moving and changing in a way that is palatable and meaningful for the board and executives.
• 41:12
  SPEAKER_01: One of the challenges uh that I see, Alison, is a lot of companies collect a lot of customer data.
• 41:19
  SPEAKER_01: And you also talk about it in the book where you say that uh, you know, uh without clearly telling what the customers get in return, uh, you know, there is a lot of customer information overload, is something that you uh you know you passionately talk about.
• 41:36
  SPEAKER_01: So uh that's a real challenge, right?
• 41:38
  SPEAKER_01: Because every time you ask me for more data, but I don't see the visibility of what you're doing with it in my customer experience.
• 41:46
  SPEAKER_01: So there's a big gap between knowing, doing, and visibility of what happens in my uh life in my relationship with the company.
• 41:58
  SPEAKER_01: Is that not a big problem?
• 42:01
  SPEAKER_00: Oh, it absolutely is, and I'm so glad you mentioned that because it reminds me of a trend that I am seeing that I didn't mention earlier.
• 42:11
  SPEAKER_00: The the relationship and and the collection of data for a customer is not just a single point in time, it's a dynamic problem.
• 42:21
  SPEAKER_00: So maybe today I don't want you to collect my information for marketing purposes, but then tomorrow I decide that I do.
• 42:30
  SPEAKER_00: And so my the definition of what data is collected for what purposes is starting to become uh if you look at Europe, you'll see their use of cookies, and they'll have them, you'll you'll get to select which type of information can be used for what purposes.
• 42:51
  SPEAKER_00: I think they're doing a really good job of sorting that out.
• 42:54
  SPEAKER_00: We don't have that in the United States as much, it's basically binary.
• 42:58
  SPEAKER_00: Do you agree to be tracked or not?
• 43:00
  SPEAKER_00: Well, you know, different circumstances, different places, and all that.
• 43:04
  SPEAKER_00: But moreover, once you agree or don't agree, then the use of that data filters through into the company, but the company doesn't necessarily have a very easy way to track whether your what it what is your current state of agreement.
• 43:26
  SPEAKER_00: So let's say that I want you to contact me if my order is late, but I don't want you to contact me for third-party partners.
• 43:36
  SPEAKER_00: And so I allow you to do certain types of matching for my information, but not other types of matching.
• 43:43
  SPEAKER_00: That gradiation, and then you know, factor it out about different choices over time, is really not present in the data sets, but it could be.
• 43:53
  SPEAKER_00: But even if it were, so let's say that I have a data set, and let's say that I put together a really good System that tracks what somebody wants from that how they want me to use their data.
• 44:06
  SPEAKER_00: And let's say I've got different buckets, just like Europe, and I'm monitoring how you can be used in different ways.
• 44:14
  SPEAKER_00: Well, further, even if I have that in place inside my company, the horse is out of the barn.
• 44:21
  SPEAKER_00: My data is all over the place.
• 44:24
  SPEAKER_00: And as a customer, I may not realize that it's not you that has my data.
• 44:29
  SPEAKER_00: It's this other company that has my data.
• 44:32
  SPEAKER_00: And, you know, one of the probably 200, easily 200 databases out there with my data and different fractions of pieces of information.
• 44:43
  SPEAKER_00: I haven't quite figured out how many places I have to go and tell them not to use it.
• 44:48
  SPEAKER_00: So there's a potential for customers to be unhappy that you've used their data when you haven't used their data at all.
• 44:56
  SPEAKER_00: And I think this is a this is a danger that companies are facing and are very uncomfortable with because they're trying their best and they want to do what's right, but the customer doesn't understand the data is everywhere.
• 45:09
  SPEAKER_00: So that brings me back to the trend.
• 45:12
  SPEAKER_00: What is the trend then?
• 45:13
  SPEAKER_00: And what I'm seeing, um, I think um Richard over at GleaNet, uh, they do some interesting work.
• 45:22
  SPEAKER_00: He's a former Googler and he's also a reviewer of the book.
• 45:27
  SPEAKER_00: They are looking at ways that blockchain and data data can be held on, your private data is held on the blockchain, and then you control where it goes.
• 45:39
  SPEAKER_00: And that's the problem today is whether it's one of the 200 databases, or whether it's held by me, or whether it's held in escrow by a third party, we don't have good controls yet.
• 45:54
  SPEAKER_00: But if we imagine a future where either an escrow agent or or by myself, I have some system that allows me to control and parse out what kind of data I allow the usage for under what circumstances, I think that's where we will eventually end up because it is not reasonable to expect companies who are busy operating their everyday company needs, supply chain, customers' operations, all their stuff.
• 46:26
  SPEAKER_00: It's not reasonable to expect them to dig into your data minutiae and manage all of that little, all those little bits and pieces.
• 46:35
  SPEAKER_00: It's very hard lift.
• 46:37
  SPEAKER_00: And so I think we will see a trend with an intermediate or or customer-driven side controlling that.
• 46:44
  SPEAKER_00: But it may be at a it may be at a pretty high price.
• 46:48
  SPEAKER_00: God knows we've already had a Cambridge Analytica.
• 46:50
  SPEAKER_00: How many more of those do we need before that becomes the the obvious go-to choice?
• 46:56
  SPEAKER_00: I don't know.
• 46:57
  SPEAKER_01: That's a great uh way to look at the future.
• 47:00
  SPEAKER_01: And uh uh I think uh we'll move into a uh rapid fire session of a couple of questions that we want to throw at you.
• 47:09
  SPEAKER_01: Uh so the first question that uh I would want to ask you, Alison, is what does the word successful mean to you?
• 47:18
  SPEAKER_00: Really happy, joyful every day.
• 47:22
  SPEAKER_00: That's what success means to me.
• 47:25
  SPEAKER_02: Yeah, Alison, what are what are some of the books that have influenced you the most over the course of your life and career?
• 47:32
  SPEAKER_00: Well, I I've definitely been influenced by Pete Fader's customer centricity book.
• 47:38
  SPEAKER_00: I've definitely been influenced by um, and and they have a subsequent playbook that came out with Sarah Tom's afterward, which and Sarah also wrote the foreword on my book.
• 47:47
  SPEAKER_00: Um, I've also been heavily influenced by Gary Angel's uh Measuring the Digital World.
• 47:53
  SPEAKER_00: Gary is a personal friend I used to work for at Symphonic and just a fantastic thinker.
• 47:59
  SPEAKER_00: Outside of that, um I I tend to enjoy a lot of um a lot of different books.
• 48:09
  SPEAKER_00: Um there's a a book out there about um I think his name is Mike Levine, uh Algorithmic Leadership, uh, which I thought was a really good positioning of using data to lead organizations.
• 48:26
  SPEAKER_00: Um Doug Laney's Infonomics is also a great book, uh, very detail-oriented.
• 48:32
  SPEAKER_00: And let me see.
• 48:34
  SPEAKER_00: Um, oh, and Brian Eisenberg's book, um, Be Like Amazon, even a little even a lemonade stand can do it.
• 48:42
  SPEAKER_00: These are all really um great books for thinking about how to build businesses, how to move forward.
• 48:49
  SPEAKER_00: I tend not to do too much uh casual, uh, you know, casual reading.
• 48:54
  SPEAKER_00: I tend to just be curious all the time and constantly digging into business books.
• 49:02
  SPEAKER_01: Fantastic.
• 49:03
  SPEAKER_01: Uh, what are the you know three or four things that uh you would recommend an 18-year-old studying in the university today?
• 49:13
  SPEAKER_01: What would you want them uh to be ready for in the future?
• 49:18
  SPEAKER_00: I think what's what separates the good from the great around the 18-year-old group, probably two things.
• 49:29
  SPEAKER_00: One is the ability to understand quickly and execute.
• 49:33
  SPEAKER_00: That's often what we're looking for in that age group.
• 49:37
  SPEAKER_00: But the second part is harder to the second part is harder to um describe.
• 49:45
  SPEAKER_00: So let me see if I can if I can frame it.
• 49:50
  SPEAKER_00: There's a there's a certain way of thinking strategically that is very rare in younger workers.
• 49:59
  SPEAKER_00: Um, you know, it's so if I'm 18 and I'm figuring things out, I'm often, and especially as coming out of school, I'm taking an assignment, I'm executing, and I'm used to this pattern of execution, execution, execution.
• 50:12
  SPEAKER_00: And I might not be thinking too much about why, what's the bigger picture?
• 50:16
  SPEAKER_00: Or I might just say, you know, my why is my immediate because the teacher asked me to, or because my boss asked me to.
• 50:37
  SPEAKER_00: That does not usually come from your boss.
• 50:40
  SPEAKER_00: That does not usually come from your everyday work.
• 50:43
  SPEAKER_00: It comes from listening to leaders, listening to sources of information, and developing a sense of triangulation from those sources, where you start to get a sense for where the value that of your work is.
• 51:05
  SPEAKER_00: And the benefit is when you when you get that triangulation, and there's a reason why I'm using that particular word, I'll come back to in a second.
• 51:13
  SPEAKER_00: Um, when you get that sense of of what the value is of your work, you then know what the value is that you want to drive to and what you should command in your salary.
• 51:25
  SPEAKER_00: And that just opens up a whole bunch of great opportunities for any person on the course of their life.
• 51:31
  SPEAKER_00: And and of course, it should align with things that you personally feel happy about.
• 51:35
  SPEAKER_00: So, wow, you know, why why spend a lot of time, you know, grinding in a dead-end job just kind of, you know, nose down to the grindstone?
• 51:44
  SPEAKER_00: That's junk, you know, go with what makes you really happy and where your value is.
• 51:49
  SPEAKER_00: Um, so and and the reason I use the word triangulation is because I got um Avanesh Kalstack said a long time ago, he's a leader in digital analytics, he said, read three books on any subject, and you're basically an expert.
• 52:05
  SPEAKER_00: And and I have found that many times that's true.
• 52:09
  SPEAKER_00: By the time I get to three books or three sources on the same topic and I dig in, I start to hear the same threads again and again and again.
• 52:19
  SPEAKER_00: And that helps you go from tactical worker be to I can hear the signal and the noise.
• 52:28
  SPEAKER_00: And and that's that's hard for a lot of young people because there's so much stuff coming at them, they don't know what's noise and what's signal.
• 52:36
  SPEAKER_00: So I use that rule of triangulation anytime I want to figure out what I should be doing in a particular space.
• 52:45
  SPEAKER_01: Great.
• 52:46
  SPEAKER_01: Uh what's the best piece of advice uh anyone has ever given you, Alison?
• 52:53
  SPEAKER_00: The best piece of advice um anyone has ever given to me has to do with uh the value.
• 53:01
  SPEAKER_00: Well, there's two pieces actually.
• 53:03
  SPEAKER_00: One is whenever you whenever you buy something, always ask, is this the best price you can give me?
• 53:11
  SPEAKER_00: I use that again and again and again.
• 53:14
  SPEAKER_00: I used it last night when I was buying something.
• 53:16
  SPEAKER_00: And the the second thing um that's my my favorite piece of advice is the other side of that, which is the value of what someone is buying.
• 53:26
  SPEAKER_00: Let's say they're buying your company, is what they want to pay for it.
• 53:31
  SPEAKER_00: So it's not like you have to subscribe to any particular multiplier or metric.
• 53:38
  SPEAKER_00: The value is what somebody wants for it.
• 53:40
  SPEAKER_00: Whether you're selling your house or whether you're selling a company, it doesn't matter.
• 53:44
  SPEAKER_00: Always think about it in terms of value, not in terms of what someone tells you the price should be.
• 53:51
  SPEAKER_00: And I have found that is a great way to get fantastic upside on anything that you're selling.
• 53:59
  SPEAKER_01: What is something you believe that nobody else agrees with you on?
• 54:04
  SPEAKER_00: I know my husband doesn't agree with me on how he should dress.
• 54:13
  SPEAKER_00: My kids don't agree with me on a number of things.
• 54:15
  SPEAKER_00: Um, but I think, you know, a uh, you know, probably what we talked about earlier.
• 54:22
  SPEAKER_00: There's a lot of people who are like attribution analysis, media mix modeling.
• 54:26
  SPEAKER_00: I always feel like I have a bit of a contrary point of view when it comes to that.
• 54:30
  SPEAKER_00: I understand the reason why people do it and I understand the need, but I always feel like it's a waste of time.
• 54:35
  SPEAKER_00: You know, it's people we're after, it's not channels.
• 54:39
  SPEAKER_00: Channels don't buy products.
• 54:40
  SPEAKER_02: Um, so my final question to you, Allison, is uh whom would you like to see as a guest on contraminds and why in the future?
• 54:50
  SPEAKER_00: Who would I like to see as a guest and why?
• 54:55
  SPEAKER_00: I don't know why, but this keeps popping into my head.
• 54:58
  SPEAKER_00: I keep thinking about Elon Musk.
• 55:02
  SPEAKER_00: I'd love to see him on contraminds and and see him described because I think he's just such an amazing thinker.
• 55:09
  SPEAKER_00: Um, but you know, moving moving down from Dream World here and in and into more uh reality folks, you know, Gary Angel is of the same caliber think of a thinker, um the same level, I think, as Elon Musk.
• 55:25
  SPEAKER_00: He is incredibly bright, and he runs a company now called Digital Mortar.
• 55:31
  SPEAKER_00: And what's interesting about what he's doing is he's looking at information um as it comes through the camera lenses and as you as you um pick up information about people and where they're going and what they're doing.
• 55:46
  SPEAKER_00: So it's not customer, it's not the same kind of stuff that I do, but it's it's fascinating when you think about what you can learn when you pull in visual data and try to assess the right actions to take at the company level.
• 56:05
  SPEAKER_01: Great.
• 56:06
  SPEAKER_01: Thanks a lot, Alison.
• 56:08
  SPEAKER_01: It was an absolute pleasure listening to you, and there were some great points you made on CLV, the right ways to look at it, the right methods to really apply them in a company.
• 56:22
  SPEAKER_01: Uh, it was absolutely fantastic to listen to some of the concepts there.
• 56:27
  SPEAKER_01: And uh it's as always, uh reading a book is one thing, but listening to the expert is another thing, and that's something that we felt today in this conversation.
• 56:39
  SPEAKER_00: Thank you so much, Swami and Vignash.
• 56:42
  SPEAKER_00: It's been a pleasure to be here, and thank you for um reading the book and enjoying the content.
• 56:48
  SPEAKER_00: That really means a lot to me.
• 56:58
  SPEAKER_01: Thanks for listening to this episode.
• 57:00
  SPEAKER_01: For selected links and detailed show notes, visit www.contramines.com slash blog.
• 57:08
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• 57:14
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• 57:25
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