Customer Equity Accelerator Podcast

Ep. 64 | Classifying CDPs with Jimi Li


"There is not a one-size-fits-all CDP solution. Start with your use case to narrow the pack." - Jimi Li


This week Jimi Li, who built L’Oreal’s global ecommerce platform as well as NewsCorp’s data lake, now a partner at Valence MI, joins Allison Hartsoe in the Accelerator to sort out the messy world of Customer Data Platforms (CDPs). Jimi outlines how various tools migrated to the CDP space and why one tool might be a solid technical fit for a smaller company but not the right fit for an enterprise with a more customized tool stack. Listen in to hear how he frames which CDPs could be right for your company.   

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Ep. 65 | Beyond CDPs: Customer Intelligence Ep. 63 | Hari Mari’s Valuable Customer Community
Show Transcript

Allison Hartsoe: [00:01] 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 about customer data platforms, often called CDPS and which CDP is right for you. For your company. To help me discuss this topic today is Jimi Li. Jimi is a partner at valence MI, which is a marketing integration company, and I don't often invite, as you know, if you listen to this show, I don't often invite services companies or vendors to my show unless I think they have something really interesting to say and Jimi definitely meets that criteria, so Jimi, welcome to the show.


Jimi Li: [01:11] Hi Allison. Thanks for having me. Glad to be here.


Allison Hartsoe: [01:14] Can you tell us a little bit about your background, and you know, how you got into this topic of CDPs?


Jimi Li: [01:22] Sure. My background is primarily, I would say marketing technology. I pretty much spend my entire career working on marketing content engagement systems, B to C commerce technology. I really, you know how to utilize data system to better understand consumers, uh, generate insights and turn that insight into better customer experience. And they started off building a global online marketing system for GE capital as our marketing automation lead generation. So it was kind of sayings. And after that, I moved to the beauty cosmetic industry, uh, working for a company called L'Oreal, uh, build. They're a multi-brand global e-commerce platform that really helped drive the customer engagement then increase the revenue quite significantly for them. And that experience really helped me to realize how important data is and is crucial to have a data-driven mindset. So then I also launched an e-commerce commerce platform for Coach, which is not the pastor group that owns Kate spade and sewer waste. Man. I did a lot of work for news corp doing, seems like customer data, Lake CDP and some other data products. And now I'm a partner, a co-founder of marketing technology comes down and see a car. The valence marketing infrastructure.


Allison Hartsoe: [02:48] Yeah. I think it's so interesting that you've been hitting this martech evolution, you even coming right alongside it. So from the very beginning of global online marketing systems at Ge and then moving along with the e-commerce platform and then the data lake at Newscorp, you've basically seen a lot of evolution of technology. Would that be fair?


Jimi Li: [03:12] Exactly. That's kind of my career.


Allison Hartsoe: [03:14] Yeah. It's not exactly something we study in college, but it certainly becomes useful as we, as we, uh, get into our careers and we see the whole industry evolve around us. Right? Yeah, exactly. Yeah. Yeah. Okay. So, um, let's talk about CDPs why CDP and not CRM? So customer data platform versus customer relationship management tool. You know, a lot of customer data is already in my CRM. Maybe. What's the difference? Why should I think about any other tool if I already have a CRM?


Jimi Li: [03:52] That's a great question. Um, I actually get a lot of those questions from our clients. Um, I think there are a few key differences. Um, number one, I think fundamentally they store very different types of data. So a traditional CRM system, they store, um, customer demographic information, shopping history, sales order info, some of the preferences may be. But what is CDP stores I think is much more rich than that. So the idea is to collect every single related to that customer to form a 360, a single customer view across all the touch points. Uh, things like browsing history, social activities, location information, behavior data, and their engagement across online or in store where even, you know, the interaction they have with customer service. So among the richness of data is, it's just not comparable. So in addition to first all those first-party data, some CDP can also ingest, I would say second party data from your partners or sister business were some even can do serp party, and non immerse data integration.


Jimi Li: [05:15] So it's really powerful compared to CRM, and also CRM system I think is originally we're built as a B to B tool or technology and just to accommodate B to C use cases. But, um, it's more of a for reporting purposes, and it has tools to automate the customer interactions. But for CDP they're viewed more for companies to have a, um, I would say a holistic view of the customers and provide real-time actions. So from a technology standpoint, they use very different components. So for example, some CVP provide real-time personalization capabilities, and that required data streaming technology which collects and process the data in real time. So we're talking about a much faster response speed, a much larger data set as well.


Allison Hartsoe: [06:11] And when you say a larger data set, could you give someone a relatable example of how large the data is in that are CDP might handle versus what a CRM is built to handle? What's the magnitude of difference?


Jimi Li: [06:27] I will say in terms of the storage requirement and processing power is probably somewhere between the range of 1 to 10 to 1 to 50. So I used to work for L'Oreal and Newscorp. For those two companies the CRM data is much less than the CDP or consumer data leg information. So the ratio is I would say one to 20 on average.


Allison Hartsoe: [06:53] Wow, that's a lot. That's a lot of volume. I saw an example at one point, and this was years ago, we were talking about big data, how big is big data? And the example said if you think about a set of books on a shelf, 30 feet long, and all of the text that's in those books, that that is basically what you would put on a CD. If you think about an office building filled floor to ceiling with filing cabinets with the same kind of taxed volume, that would be the equivalent of what a CRM could handle. But then the third layer was if you think about a city block filled with office buildings, filled with the same kind of four-drawer filing cabinets filled with text. That step up was more of what we're thinking about with big data. And so when you think about big data, the volume is so different than what you might have with a traditional CRM. Do you agree with that context? Does that kinda in the same one to 20 ballpark?


Jimi Li: [08:03] Definitely. I'm a technology guy, so sometimes I use numbers a lot. But your example is much better than that one.


Allison Hartsoe: [08:11] Well, I wish I could claim credit for it. Somebody else had the creativity to put that together. But along those lines, it makes me wonder if the traditional CRM vendors are positioning themselves as CDPs.


Jimi Li: [08:25] It's an interesting point, right? While the example I think I can give is Oracle. So Oracle recently launched a CDP product called CX unity. I think it stands for customer experience unity platform. So it's not a CDP in the traditional sense. So it's a platform that they position as a customer profile and customer intelligence platform. So they pretty much just use it as a brain to interact with the other, uh, customer touchpoint or other engagement system that the customer already have, and is not a direct replacement for CRM, DNP or any of their existing data solutions. Uh, it's just something in addition, and I think it does represent the way of how large companies or large vendors is ready to tap into the space. Hmm.


Allison Hartsoe: [09:24] Hmm. That makes a lot of sense. So let's switch back to, you know, not so much the traditional CRMs, but back to the CDPS. There must be, I don't know, somewhere between 20 and a hundred and literally I think every day I hear another CDP vendor coming out, you know, how do we define what a CDP is, and maybe the different flavors of CDPs.


Jimi Li: [09:51] Sure. And you're absolutely right that the CDP state spaces rather chaotic right now, and everybody has their own definition is really difficult to provide a universal definition. But um, at least for my personally experience as seeing a CDP is really a data solution that integrated consumer data from multiple silo data sources, and groups them into one centralized efficient platform, and also creating a single view of a consumer, which then can be leveraged across multiple analytical system, reporting system, or transactional system, or for data activation purposes. But the foundation is really the data repository and the unification and identification of data to form that single customer view. And that we'll say every single else is just a different flavor, different add-on on top of that. So in terms of uh, flavors, I think they come from different, I would say history or background, right? So I think there are five major categories.


Jimi Li: [10:59] Number one is act managers, so they focus on identification and unification. So one of the examples is helion, so they came from, they are a traditional tuck managing system and also insighten, so naturally, they're very good at identify the customer, unify the customer profile, uh, which is really important. But what they lack is probably the personalization worth integrated marketing campaign management capabilities. Right? So the second piece or a second type is data integrators. So they are really good at ingesting the data and process the data. And usually they work with large enterprises to process their data, and their focus is data quality, the reliability, and those so focused on compliance, security requirements. So vendors such as, I would say Informatica, Treasure data, there were a few examples of this category. the third one I think is personalization, make product, content recommendations, and for the right moment to the consumer.


Jimi Li: [12:09] So a few examples will be, let's say Evergage, reach and relevance, Ng Data, even M particle. Those are the vendors that were really doing well in this space. And the fourth one, is marketing automation, so Linux, Custora, HubSpot, I think there is a peel for certain companies to integrate those marketing automation or campaign management capabilities as part of the single view, right? So when you see data in the reporting system, you can't act on it right away. So that's what was so powerful. And the fifth one I think is, of course, we talk about the traditional CRM vendors, a vendor such as Oracle, I believe that I say p will come into this space, even Microsoft on some other very well known big players who enter the space in the near future.


Allison Hartsoe: [13:04] Because of their ability to understand the customer across a large data set. Do you think as part of the traditional, and they're not CRM vendors, but do you think there's an interesting angle for a Facebook, an Amazon, a Google to enter this space?


Jimi Li: [13:22] So a CDP really, I would say for Facebook, for example, right? Facebook basically have their own war Garland, right? So the way that Facebook share their information, they don't give you the Pi customer data. A lot of the customer demographic data is anonymous, right? So they allow you to personalize the experience on the Facebook platform. So the way to use their data is very different compared to using your own first-party data, or second party data, on your own system or on your own web properties, right? So I think in a way they are already in the space, but they're not really competing directly with existing CDP vendors.


Allison Hartsoe: [14:08] Yeah, that makes sense. Let's think for a minute about the tech underneath these vendors or these five different flavors. I'm wondering, in order to run personalization, it seems like the texts back underneath is dramatically different than what it might be the simply unify data. And does that then mean that certain categories of CDPs will have a difficult time extending into other categories?


Jimi Li: [14:39] I think personalization is a category that all the CDP company are trying to get into, where at least they're trying to provide a certain level of personalization capabilities. So if you think about it, the reason why we need to understand and have a single customer view about the consumer information is we want to act on the data, act on the insights, right? And personalization is probably one of the biggest use case for this purpose. So that's why I do see that these capabilities will remain the top two capabilities for a CDP platform, and number one, of course, is you need to provide a data repository and unification, ensure the data quality, and the second step is how do you use that data? How do you make it actionable? For a lot of retailers, a lot of company, personalization is the answer.


Allison Hartsoe: [15:33] I always think the personalization as a bit of a range. You know there's personalization as in I can customize an email and put your name on it and maybe suggest some products and then there's customization that is almost fluid trigger based, very contextual for the right time, almost AI driven where it's trying to process so much information, so much context very quickly in order to send the information back out. I think there's a big range in personalization. If you agree, then would that mean that certain vendors have to be really well positioned in the horsepower underneath or the hardware underneath if you're going to stay with them for a long time?


Jimi Li: [16:17] I definitely think so. I was seeing there are two perspectives. Number one is really how advanced we're how mature the vendor is within a certain industry. Uh, in terms of algorithms, in terms of data size abilities, right? So how do they process and understand and turn that data into action is a very important capability? The other one I would say is the ability to integrate, right? So when you personalize, you're not only just come up with this insights or suggestions, you actually have to integrate with all those engagement systems, and tell those systems whether it's a website, mobile, or in-store system, what to do, what content to show, what actions, what kind of offers that you can give to the user. Those require a level of maturity or technical competence at the infrastructure, at the core technology level. So when you select a CDP vendor, I look at their personalization capability, their taxa is also a very important factor to consider.


Allison Hartsoe: [17:22] Well let's talk a little bit about some of the companies with regard to what might be right for me. So let's say I'm a small company with limited resources. Maybe I'm a fast moving retailer, and you know my number one concern is getting the product out the door and getting a lift on my sales and I'm growing like gangbusters, but I don't have a team of a thousand people, and I certainly don't have a deep tech team. What kind of CDP would be right for me in that scenario?


Jimi Li: [17:54] Sure! I think this question actually align very well with the customer maturity model that you previously mentioned on the podcast. Thank you. I think let's take the approach. Probably this can help structure the discussion a little bit better. So let's say the customer is in the lessons stage of the maturity curve. So most of the company in this stage, their focus should be building that data repository and ensuring that they have a single customer view. And a lot of company have limited resources, maybe four in the case of a smaller retailer that you mentioned, they don't have a ton of data. But they may have something to store the customer data. All they need to do is they need another layer on top of their existing infrastructure, and that could be uh, absorbed eight dabbyass, or it could be Tara Data


Jimi Li: [19:01] or any kind of data system that they have. So another layer to basically provide that unification and processing to form that single customer view, and of course by using a CBP vendor there are some trade-offs. So a CDP vendor, they have their proprietary cloud were their entire system is in the cloud, right? So there are privacy concerns, security concerns and in fact if you look at the industry, a lot of CDP vendors, their customer are smaller to mid-size companies, and a lot of large corporations actually have concerns about compliance, security and the transparency of how the process and technology works. So I would say for smaller business was limited resource, but really fast growing they can definitely go with the CDPs a solution that can greatly accelerate that process. So if you think about it, a CDP solution cannot only bring you the data repository, the unification of data, but it also combines personalization, some level of automation capabilities.


Jimi Li: [19:58] And the reason why it's good for smaller retailers were a smaller companies is smaller company tend to use some off the shelf solution. They don't customize it that much, and then make it very easy for the other box integration with some of the major CDP solution. So that means quicker time to market and less cost to implement for a large corporation. I will say if they haven't already moved from a product-centric mindset to customer-centric mindset, and that means from a data structure perspective, they're not transitioned yet. They definitely need to start doing that because it takes time for large corporations as a journey to get there. What they can do is they can focus on very specific use cases. So let's say, if they want personalization for their content management system for their website, e-commerce, we can choose a vendor that is very strong in that area. Or if they want to connect to an advertising system, and really increased their conversion where the effectiveness of their advertisement, they can choose a CDP vendor that focused on that area as well. It really depends on what kind of use case that you have, and what kind of the system that you already have in place. So once you decide that, I think that could be a good starting point for large corporations, especially those the lessons stage.


Allison Hartsoe: [21:29] So it sounds to me like you have some examples around advertising or e-commerce personalization, especially based on your background. Are there any stories you can share about how you went through that process of, you know, setting it up and launching that kind of system?


Jimi Li: [21:47] Absolutely. So I used to work for a company, Cobb News America Marketing, which is one of the business units for News Corp. So the challenge that they have was they already have a data system, but the way to utilize data in from a maturity perspective, they were still in the lesson stage. So they're not really data-driven. All of their data structure we're product-focused, they're not consumer we're a customer focus.


Allison Hartsoe: [22:15] Jimmy, can you elaborate for people? What does it mean when your data is product focused versus when your data is customer-focused?


Jimi Li: [22:23] Sure. So from a technology standpoint, it is how you store the data, how you utilize that data, how your system is set up. So it's basically designed to accommodate the product line, existing product lives that you have, for example, for Newscorp and News American marketing, their product or their in-store product. Um, they're printing product, and they have a totally separate digital channel. So all those data were siloed, and they were stored in twenty different systems. Oh Wow. It's incredibly difficult to unify that data, to look at that data, to make sense of it. So that's one I'm saying to change that you'd not only have to bring all those data into an external system and try to make sense of it. You have to slowly evolve your fundamental or core system design, to design for the customer focus data structure.


Allison Hartsoe: [23:20] And so then the customer focus data system. This is what you were saying before. I oftentimes think of it as like one record that has a very wide table with all sorts of detail about the customer.


Jimi Li: [23:32] And that also I think is related to how your system were touch points interact with a customer, right? So you have to structure data with use cases in mind to really understand their journey.


Allison Hartsoe: [23:45] And is this what happened at News Corp?


Jimi Li: [23:47] We were in the process of doing that, and we did all, I actually did a lot of work.


Allison Hartsoe: [23:52] In the process of moving all of their data together. What were the big hurdles that, you know, would a CDP have solved that for them faster or was it something they had to do internally because of the heavy lifting and the security requirements?


Jimi Li: [24:10] Um, for a large corporation like them, they actually did have to go through a lot of internal processes, and what they end up doing is they build some internal data solution for the data repository. Um, they did utilize some other vendor for the unification or identification to form the single customer view, but on top of that, they utilize a CDP like vendor. At that time it was not called CDP but more of a personalization vendors, so they utilize a vendor called Aquia, so Aquia we'll provide the personalization engine is also capable of generating that single customer view, apply those across different touch points that they have.


Allison Hartsoe: [24:55] Got It. That makes sense. I can see how that would be functional. Do you have another example of maybe a different company that was moving in a different direction or maybe more of an e-commerce traction?


Jimi Li: [25:06] Sure. The other example I can share it is when I was working at L'Oreal, looking back, I think they were more in the learn stage, so they already have a data system in place. They are kind of data-driven. I will say they have a very clear goal in mind in terms of what the use case is, what they want to do. So they end up adopting a personalization engine called reshare relevance, right. So in today's world, I think that there is a lot of buzzwords about customer intelligent platform. So what that is is really a customer profile, and those so intelligence engine that house all of your system touchpoints, what to do for which customer. So it's everything on CDP would have but with more advanced we're customized algorithms so you can test and learn different scenarios and really tried to improve things like for the eCommerce business, improve their conversion rate. So it was very effective actually. So it's not meant to be a replacement for an enterprise level customer data system, but rather a bottom layer that provides that extra intelligence where that brain power to direct different channels to work in unity.


Allison Hartsoe: [26:25] Now that's an interesting concept about what is essentially I think becoming a new category, the CIP system, the customer intelligence system. And I just heard this the other day when I was asking what another guest who is going to be on the podcast. And I said to her, you know, we're getting ready to do the CDP, episode and what do you think of the CDP that you're using? And she surprised me because she came back and said, well I don't think of this company as a CDP at all. I think of them as more of an intelligence platform. So I think we are seeing some companies, particularly in the smaller fast-growing space using one system to knit the data together and another system to tell them what to do. Yup, that's exactly right. And actually, I should extend that a little bit to say not just tell them what to do, but um, as you said, activate on that knowledge. Be able to pipe it into different places.


Jimi Li: [27:21] Yup. Data activation is a, is really important.

Allison Hartsoe: [27:24] Yeah. Yeah. You know, I'm a big believer of use the right tool for the right purpose. You know, a tool that was built to track analytics is not the same as a tool that was built to manage content for example. And in this scenario, is there really a hard divide between CDPs that are coming at it from an engineering perspective versus CDPs that are coming at it from more of a use case or maybe an intelligence perspective?


Jimi Li: [27:55] The way I look at it, I don't think in the CDP space there will be a one size fits all player such as the say salesforce. You really have to look at the different flavors that they provide, and uh, whether that satisfy the need of your company. So I almost think that for companies that choose CDP solution, they need to look at their use case number one, and also to determine what kind of flavors they want. Treat it like a separate system. Don't be confused by the Buzzword of CBP. Look at what it actually does and what you actually need.


Allison Hartsoe: [28:33] And I can't emphasize that part about buzzwords enough. I was literally on a call the other day with a company that I didn't think was a CDP at all, and suddenly the word CDP came out of their mouth along with a raft of buzzwords. And I'm pretty good about understanding what's signal and what's noise. But even I was having a hard time parsing out all of the hype, there was so much hype, and I think this is indicative of the fact that I think it was an almost $600 million that's been invested in the CDP space, but the sales figures or something like not even cracking 100 million. So there's a lot of pressure on this space to get sales, and I think we're starting to see that in the pitches.


Jimi Li: [29:16] Definitely. And that's also why you'll see that the majority of the CP sales happen in the small to midsize company, but not in the large company category.


Allison Hartsoe: [29:24] Yes, yes. And I think, you know, to your point before CDPs probably are well suited for small to mid-size companies, and would we define that as maybe 200 million in smaller? Is that about the right range?


Jimi Li: [29:40] Yes. I will say is sometimes it's hard to categorize by the number of sales. Depends on, you know, what kind of product you sell it, right? But I will say sales is a good measure, but you have to look at the resource that you have. And those are the maturity of the culture of a company. Are you really data driven? Right? Do you have the resource even you have the tools, do you have people to use it? And when I talk about the Coucher, I'm really talking about the data-driven mindset, and the behavior of I'd say continuously improvement, uh, test and learn those things. So those things will actually decide if you're ready for the advance capabilities, the CDP, or CIP system will provide you,


Allison Hartsoe: [30:23] Oh, that's an excellent point. And that, that gets right back to the maturity curve. But basically, if you're not in the learning stage, if you're in the listening stage, then really you just need something to knit it together. You don't need the hottest personalization system out there. But if you're in the learning stage, then you really do need some more intelligence and horsepower to drive those systems for you. That makes perfect sense. That's correct. A lot of companies come in, and they want to know the Roi on a system, and you know, any sales personnel tell you, oh we get this kind of Roi or that kind of Roi. How should people think about getting some measurable result back from this particular tool?


Jimi Li: [31:08] Yeah. It's funny. I often tell my clients that when a salesperson tells you that they can easily calculate the Roi for you. Don't believe them. It's not that straight forward. So it really comes from the use cases that you're dealing with right? And you really have to think about this before starting looking at the different data system or CDP providers. What we use it for, is it personalization, increase conversion rate or different goals really have different KPIs to measure. So, for example, for email, you know, it can be operated clear sight for social engagement, you know, impressions and uh, you know, for a website it could be just the content, the unique visitors, the time they spend on the website, but the actions taken. So Roi doesn't necessarily always miss sales, revenue, and there's no one single measurement that can tell you, okay, here's the Roi. So is not in the traditional financial sense I would say.


Jimi Li: [32:15] So for example, if you have an e-commerce channel, yes you can calculate that Roi and tie into the numbers. Let's say personalization helped to increase conversion rate. So it is something that you can calculate, make assumption and, and the result is sales lift. But when it comes to now e-commerce business, there's no exact formula how you do that. So will you talk about digital advertising? You know, how your campaign advertising campaign or all your content or social campaign value that helps with a product launch, you have to look at the potential increase of awareness and a lot of time is the estimated base on quite a wide variety of data points. And based on that, you translate that into exposure measurement, and you know, sometimes you have to rely on assumptions. We're relying on some, uh, layer in some of the external data from whether it's retailers or marketing research company to complete that Roi Assessment. I will say is just the, it really is a complex manager based on different goals that you had at different channels. At Valence, we actually do a lot of those work to help customers to really present that Roi and tell the story.


Allison Hartsoe: [33:33] Yeah, I'm going to assume that the time to figure out what you're going to do with Roi or how you're gonna measure success is as you're evaluating vendors, not once you've brought it in the door, and it's not too late once you brought it in the door. But in a way that use case and how you measure the performance will also dictate the kind of tool you pick. Right?


Jimi Li: [33:54] That's right. Um, I will argue that that process should even happen before you look at the vendors. Right? So, use case has a warm measurement KPIs. That is something that when you have those that information, it will help you much better to select the corresponding vendor.


Allison Hartsoe: [34:13] And in fact, I'm gonna argue that that probably sounds like the first thing you should do. And we think about, you know, okay great, I want to get a CDP. What should I do first, second, third? And it sounds like you just answered that as the first step is the use case. What are you going to do with it? Do you have the resources to actually, I often say stick the landing, you know, if you bring it in house, can people actually take action on the things that are coming through? That use case is the number one most critical piece, yes?


Jimi Li: [34:45] That's right. That's exactly right.


Allison Hartsoe: [34:47] Okay. So what else should people be thinking about as they try to figure out the right CDP for them?


Jimi Li: [34:52] So I would really look at what kind of company are you? Are you a data-driven organization, or aspiring to be one? How about management support? There's management understand important of data, and do you have the resource, the budget to support that vision? Also important in a lot of people tend to ignore that, they think, okay, a CDP vendor can help me to integrate with all of my data. But that really depends. So it depends on what stage are you technically. So what are the existing application, the system, the processes that you already have in place, and whether those things will work nicely with a CDP bender that you have chosen? There's usually a lot of nuances, a lot of needy, gritty details that need to be considered before you can make that purchase decision.


Allison Hartsoe: [35:45] Can you use that same kind of framing to understand what if I've made a mistake, how do I know if I've screwed up?


Jimi Li: [35:53] I think one of the things that you want to do is really do an audit first or assessment. List all those factors, and asked the CDP vendors, whether that's engineering team, or presale team to give you a plan and do a POC kind of thing or you know, hiring an external agency that can of help you to go through that process. I think it is a very important homework before you make a significant investment in CDP.


Allison Hartsoe: [36:24] I completely agree. And so along those lines of you know, getting support for something like this, how can people reach you if they want to get in touch and you know, they want to bounce off different CDP idea is or understand more specifics about a CDP that they might be using. How should they contact you?


Jimi Li: [36:42] Sure. Uh, they can call valence directly us through our website, or Linkedin is definitely a good way to contact me. So after the podcast, so I'll put up my uh, contact information and email address there.


Allison Hartsoe: [36:53] Okay. So we'll include that in the show notes, and make sure people have the ability to reach out and get in touch. So as always, links to everything we discussed, including Jimmy's contact information and some of this framework will be translated on the ambition page. Jimmy, thank you for joining us today. Really appreciate it.


Jimi Li: [37:16] Thank you. It's a pleasure to be here, and hopefully, our audience will also enjoy the discussion.


Allison Hartsoe: [37:21] Yeah, it's been very helpful for me as I look at this vendor soup in the space and try to sort it out, so very valuable. Thank you. Remember everyone, when you use your data effectively. You can do customer equity. It is not magic. It's just a very specific journey that you can follow to get results. 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, ambitiondata, one word to, three, one, nine, nine, six, (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

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