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Steve:
Happy New Year, everyone. It's that time of the year where we make resolutions to better ourselves. And one way a CX pro can better their programs is to make certain you access all your data.

Ashley:
Let's start looking, what is our programmatic objectives? What do we want to be achieving in six months, a year, three years, or even beyond? Because if we have that vision defined at the get go, we can start to design and integrate that data and bring it together in a way that will allow for those objectives to be met.

Steve:
We're talking about data integration as one of the eight essential themes driving CX evolution on this episode of The CX Leader Podcast.

Announcer:
The CX Leader Podcast with Steve Walker is produced by Walker, an experience management firm that helps our clients accelerate their success. You can find out more at walkerinfo.com.

Steve:
Hello, everyone. I'm Steve Walker, host of The CX Leader Podcast and thank you for listening. As we like to say on this podcast, it's never been a better time to be a CX leader. And we explore the topics and themes to help leaders like you deliver amazing experiences for your customers. This is our sixth episode in our series "CX Now: Eight Essential Themes Driving Evolution." We've been taking a close look at current topics and trends the pros need to embrace to be better leaders and take their programs to the next level. And if you need to catch up on the previous five episodes, you can find them on cxleaderpodcast.com. Collaborating with our partners at Qualtrics, we developed this series using feedback from more than 50 CX leaders. Customer experience pros rely on data – lots and lots and lots of data. And it's important that data can be accessed constructively so we can understand our customers needs and make better business decisions. And that is the theme of this episode: data integration. Now, to help us better understand this topic, I'm going to turn to my friend and colleague Ashley Hicks, who's an associate vice president at our client services group. Ashley, welcome to The CX Leader Podcast.

Ashley:
Hi, Steve. Thanks for having me.

Steve:
So, Ashley, this is your first appearance on The CX Leader Podcast, I understand.

Ashley:
It is.

Steve:
And how long have you been at Walker now?

Ashley:
Oh, we're just after a year. So you're in a couple of months.

Steve:
And how have you gotten away with this for now? 14 months. To not be a guest on the podcast.

Ashley:
I must be hiding well, working with our clients.

Steve:
Well, thank you for that. And hiding no longer, you cannot. Now you are a officially a guest on the podcast and I'm really glad that you're willing to come on and talk about this topic because I know our listeners want to learn a lot more about this. But just for a little bit of context, tell us a little bit about your background prior to Walker and what your CV looks like in the CX Pro space.

Ashley:
Yeah, absolutely. So I came to Walker with about eight or nine years of B2C experience management experience, working in the hospitality industry and building and creating our experience management program from the ground up. I had fantastic collaboration with business partners across the organization, but really driving that, that change that everybody is looking to to achieve. So I decided to come here to Walker and be able to share that that knowledge and experience that I gained client side and bring that to all of the amazing clients we have that come through our doors.

Steve:
Well, it's been our pleasure. So glad that you came and joined our team. I know you've had a lot. I've enjoyed getting to know you and appreciate it. Again, I can't believe it took us this long to get you on the podcast so. Well, as part of this series, Ashley, I've allowed each one of our experts to sort of define the topic. So for purposes of this podcast and for purposes of this series, how do you define data integration as it relates to a CX pro?

Ashley:
It's actually thinking about that as I was preparing for for today. And hopefully most people think about data integration more as an I.T. function or a part of that and where we're just connecting systems of data so they can speak together or operate together, interact with one another. But when I think about data integration within the context of CX or experience management, I think about it as an enablement tool. So how do we join the experiential data that we are collecting from the various listening posts? Combine that with the operational data that an organization is already so deep rooted in and allow us to create personas and segmentation or have deeper analysis or personalization, or even start to orchestrate specific journeys to take them along their customer journey in a specific way. That's how I start to think about data integration. We've got to take a step back from the tactical and start thinking about it a bit more strategic.

Steve:
I really like that definition. You know, I think this is one that's kind of going on a long time in our industry. And in fact, a lot of times it becomes an excuse not to do something because we can't get the IT people to put the data together. Well, heck, you know, sit down with your data and go talk to some of the people that service the clients and, you know, make sense of it as a CX pro. So I really like your approach and you also already brought in the X and O data, which is just a key concept for our CX pros to think about. We have to relate this experience data. X data is what we call it to the O data, the operating data that the business unit leaders or the functional leaders or the account managers or the sales managers are are looking at and making those two things talk together. So maybe with that as a nice definition, a nice kind of way to set the foundation, what's the end goal like? What are we trying to accomplish with data integration?

Ashley:
Exactly? You have to design and think about data integration with that end in mind. So one of the first things when advising our clients and starting to have these data integration conversations early on in our discovery process is we'll start not only with what are our our survey objectives or project objectives, but let's take that step back and then out to the side. Let's start looking what is our programmatic objectives? What do we want to be achieving in six months, a year, three years, or even beyond? Because if we have that vision defined at the get go, even if it's just out there in the clouds, kind of ambiguous, we don't have clear lines yet. We can start to design and and integrate that data and bring it together in a way that will allow for those objectives to be met.

Steve:
Oh, I like that. You know, a long term vision of kind of how all this data is going to go together. And it's okay if it's not perfect at the start, right? I mean, because we can tweak it and we can keep improving it as we go. I was actually just with somebody the other day, and it was a breakthrough for me because the group was really getting hung up on how we were going to measure success when we really had just kind of started on this initiative. And the facilitator just said, Hey, let's worry about that the next meeting or the or two meetings from now, let's just get some of this going and collect a little information. Then we'll set the targets down the road. And that was for me, even at my advanced stage of my career, it was kind of a key learning that I had there. So I really like that, you know, that one of the neat things about our businesses that we're we're constantly getting more information and we can just keep improving what we're doing. How do kind of the pieces of the journey, the customer journey, we always kind of talk about that as foundational. How does that play into the concept of of data integration?

Ashley:
Absolutely. So we always within the context of of a listening post, we need to understand what is, what's the experience that we're looking to impact, improve, identify an opportunity. And that customer journey will help dictate what some of those objectives may be. So I think of an example, let's say a program has more of a marketing or sales focus of trying to increase conversion. So taking a customer from point A to point B, make a purchase and we need to identify what what are those those data points within the customer journey that would help support and make that analysis more robust to start segmentation, segmenting the insights and identify where those opportunities are. So having a foundational understanding or awareness of that customer journey is critical when we start thinking about it.

Announcer:
Are you looking for a little recognition for your hard work? Well, here's just the opportunity. Applications are now being accepted for the US Customer Experience Awards. Finalists and winners will be named in 18 different CX categories, and you could submit an entry in multiple categories. This could be the chance for your team to finally get the recognition it deserves. To find out more and submit your entry, go to usacxa.com.

Steve:
I'm speaking with Ashley Hicks, who's associate vice president here at Walker on the topic of data integration. And we've covered the basics now and how that applies to the overall customer journey. But Ashley give us a few examples of what types of or categories or examples of what kinds of customer data we ought to be talking about integrating. I mean, obviously we think about surveys and but there's there's all sorts of customer data out there that companies ought to be thinking about integrating, right?

Ashley:
Yeah. So a lot of times when we start to think about those systems, so systems of records, CRMs and CDPs. But when we start thinking about the different types, a lot of times I align it to how we are going to use that information and use it in our analysis and our trying to achieve those objectives. So a lot of times I look for different schematics and groupings of how we're going to be looking at different different data types. You could go super basic of locations or different categorizations of financial metrics. But I think of it within the way of is this something transactional where we want that longitudinal history, we want to see what's taking place? Interaction over interaction? Or is it something where we just need to know it at one moment in time and it's okay if that information is overridden? So Customer one is always going to be classified to this group or and it's okay at the next point of listening, they're now in group two. So different ways of looking at it in that manner.

Steve:
Yeah. And one of the things I think that you point out is you've got to go out to the users of the information to and see what kind of data they already have around this. You know, for example, the way the contact center manager might look at this much more differently than somebody who's doing account management or who's involved in the supply chain. But all of them have legitimate metrics that they're looking at in terms of how they're delivering to customers. And that's really our job is to kind of come in and fill in those blanks. So I think that's what we mean by data integration, at least that's what I think I'm hearing. Let's talk about a couple of examples, if you don't mind. Like, for example, customer retention, what would the kind of data integration play be sort of in a generic sense for how we're looking at customer retention, you know, willingness to renew subscription or interest in expanding their relationship?

Ashley:
Absolutely. So when I start to think about customer retention, a lot of times you'll speak to loyalty or advocacy and immediately your mind goes to lifetime value and financial metrics that are associated with that retention. And I think it would be safe to say that most organizations are looking to have an upward tick associated with their the retention of a customer. So with every step of the way along their journey with that organization, their tenure, there's an increase in in that financial associated with them. So that's going to be one of the initial concepts to be thinking about with customer retention. So identifying some sort of financial metric that when you start looking at the relationship that that customer has with an organization, you can start tying differentiating factors within their relationship and their experience that allows for the identification of whether one type of experience or another drives some level of loyalty. And which ones do we want to really capitalize on?

Steve:
Yeah, I give the perfect generic example of how you could tie it to customer retention is if you have high NPS score group of customers and then you have, say, a low NPS score or in the Walker loyalty matrix, maybe you've got some clients that we would classify as truly loyal versus some that are high risk. And then you just take those two sets and start to kind of look at, you know, do they follow any sort of pattern and then look at some of those outcomes? That's that's going to be a, you know, a very practical data integration model that then you could go scale and you don't need a whole lot of effort to at least start that out, do you?

Ashley:
Absolutely.

Steve:
Let's talk about the account management side of things. How do we integrate the data from an account management side?

Ashley:
This is a fun one because assuming that there's a personal interaction, an account manager, so now you have personal experiences. How does one account manager interact and treat their their clients versus another? And you're able to now level the playing field and identify those differentiating factors. Proactivity or having additional guidance and really consulting with an accountant versus someone that's a little bit more passive, but similar to more at the relationship level, you're looking at the integration and interactions more holistically. And then how can you take it to the next level based on those differentiating factors?

Steve:
Yeah. You know, I was just as I'm listening to you talk, I'm thinking about one area of data integration that I think is very plausible and easy for our CX pros to think about is combining their CX and X results. You know, it's that what we've talked about as being a distributed business model. So if you have different locations where you can identify the employees and the customers who operate at that location and compare those to others, that's a really rich data set and a rich way to integrate your data to to try to find new insights. But I can see lots of… I could see other examples like buy account assignments. You could do it that way, too. So there's really the number of permutations of how you can apply this data. Integration is.

Ashley:
Sky's the limit.

Steve:
It's the same. Yeah, there's lots of different ways you can do it.

Ashley:
And I think it goes back to something that you you mentioned earlier is who are those end users? What types of data and attributes are they already looking at within their their operations? How can you then bring that into the experiential side and start using it for analysis and identifying differentiating experiences?

Steve:
Now let's kind of turn the discussion a little more practical, and let's just say I'm a relatively new CX pro, or maybe I've been in my job for a while, but I really haven't done a whole lot on the data integration side. What's kind of your advice for how you'd get started with enhancing your ability to integrate your CX data with other other sources of customer information?

Ashley:
You've got to step outside and break down any silos. Go talk to those those the owners of those data, the people that are using those data and get familiar with it, because you have to have a little bit of the contextual reference to be able to bring it in and use it accurately and smartly. So I think that's one of the biggest things, especially in our more work from home age, having those connections and making those those connections is going to be key. The other component that I start to think about is the value of documentation in your data usage and your data integrations. That's going to be a key component for longevity of your program. So if you're pulling in five pieces of data into your contact list and bringing it for utilization and analysis or segmentation, having a place of reference that says what it is, where it is, when was it last updated, that data dictionary, if you will. That way you always have record. It's quite a pain to get five or six years down the road and all of a sudden you don't know where this data is actually coming from. As the program has matured and morphed over time.

Steve:
You know, actually, as we've been talking, I keep thinking about people that don't have a lot of data to integrate, or they're making the assertion that they can't get a hold of the data. But there's actually the other side of the issue, which is sometimes people have way too much data, right? Kind of what's your advice there? When somebody is really data rich and it just starts to get overwhelming?

Ashley:
Yeah, I think of this almost like a diet. Everything in moderation. Yeah, you can have too much data associated with a customer in I know there's probably people out there that would say otherwise, but when we start to think about surveys and the types of experiences that we're trying to identify and make changes with, we're we're creating a system of insight. We're not making another CRM that we have to integrate with another place. We want to be able to transfer those insights back into that that data center. But we don't need to replicate what's already there. So it goes back to really designing this integration with that end in mind, what are those primary objectives and pulling in the information that's truly relevant or maybe even that you have a hypothesis for that you want to be able to prove out, and then whether or not it comes to fruition, then you can take it or leave it. So there really is something called of too much data.

Steve:
Yeah, in that case you really want to cull it down to what's important because it'll just intimidate everybody. And again, it's another distraction that'll get us off the real main point, which is to bring new insights and to help people put the data together with their own data. Hey, Ashley Hicks, we've reached that point in the podcast where I ask every guest for their take home value. That's their best tip or what they would say. If somebody is listening to this podcast, what's the one thing that they need to remember and take back and improve their program? So Ashley Hicks, what's your take home value for this podcast on data integration.

Ashley:
When getting ready to start a new program or project? Take the time early on to think about the end game. Think about what those program objectives are. What is it that we are trying to enable? And then thinking backwards of how do we actually get there? Because we can't create data integration. It doesn't happen automatically. You have to design it. So we have to think strategically to bring that to fruition.

Steve:
I think that's great sound advice, not not only for your data integration, but for your entire life in general. You know, design the kind of the outcome that you want to achieve and get working on the things that are going to get you there the fastest. You might never make the ideal. But it's about progress, not not perfection, right?

Ashley:
Absolutely. One step at a time. One data point at a time.

Steve:
Ashley Hicks is associate vice president in our client services group here at Walker and really happy to have her on as a guest. Ashley, thanks for being on The CX Leader Podcast.

Ashley:
Thanks, Steve.

Steve:
And if anybody would like to continue the conversation with you, how might they get a hold of you?

Ashley:
Well, I'm on LinkedIn and associate with Walker information. Reach out.

Steve:
All right. ahicks@walkerinfo.com or LinkedIn. Ashley Hicks. And if you want to learn about or talk about anything else you heard on this podcast or about Walker in general and how we might be able to help your customer experience, feel free to email me at podcast@walkerinfo.com. Remember to give The CX Leader Podcast a rating through your podcast service and give us a review. Your feedback will help us improve the show and deliver the best possible value to you, our listener. Check out our website cxleaderpodcast.com to subscribe to the show and find all of our previous episodes, podcast series and contact information. You can drop us a note on there. Let us know how we're doing. The CX Leader Podcast is a production of Walker. We're an experience management firm that helps companies accelerate their XM success. You can read more about us at Walkerinfo.com. Thank you for listening. And remember, it's a great time to be a CX leader. So go out there and help your organization integrate their data and provide better insights to all of your users to drive better business results. We'll see you again next time. Thanks for listening.

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