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Aron Tremble, HP’s Senior Director of Software Experience & Product Portfolio, discusses their personalization journey with RichRelevance(now Algonomy).
So good afternoon, guys, welcome to the post lunch slot, we’re gonna make the most of it. My name is Aron Tremble, I lead the software experience in product portfolio for HP. The interesting thing about this is I’m actually not from the website, or from the marketing side, I’m actually from the product side. And we use Engage, to drive our customer welcome and greeting and orientation to new devices. So today, it will take a little time to tell you what we’re doing, how we’re doing it, and why and the direction that we’re taking in the future. And why we’re so excited about using this platform, we’ve been working with RichRelevance(now Algonomy) for about 12-18 months, took us about a year to go from idea to first deployment, and we’re just starting to ramp this up. Someone told me more about that. And one of the reasons is that we want to be able to tell the customer what makes that exact device spectacular. And as they utilize it, whether it’s the first our first week, first month, we want to be able to reinforce that and make sure that the particular features on that product are clear and very strongly presented to the customer. And then as they start to use it, we want to learn from that and take that data and personalize the way that we interact with them how to personalize channel with that customer who never had that before, right? Traditionally, we treated all of our customers the same way really stubborn problem, we gave them a lot of software and features that they may or may not want, because we didn’t have ability to do it any differently. So I think our engagement with which RichRelevance(now Algonomy) is really helping us get after some of these problems you see here. So when we went and talk to customers, we actually found software plays a huge role in this part of the experience. So specifically, they didn’t really like what they were getting pre-installed, right. And software plays a really important part in the future. And actually, it drives about half of the purchasing criteria or the needs and wants you want in your next device. But customers really aren’t satisfied what they’re getting out of the box. And because it’s very general. So with this strategy, we’re able to customize that experience much more directly to target it according to the segment that that device was made for, and the way it was going to be used.
The great thing is, we have an opportunity at the first use of the product, that’s very, very powerful. So the majority of the customer sentiment about a PC, for most computing devices, is formed in those first few moments of use the first few uses of a new device. And so that’s an opportunity to really start that introduction. And that’s what we have in market now. And our aspiration is actually extend that further and further with the use of personalization technology.
So we went out and talked to many customers about this, we did a panel level concept discussions with about 100 Customers live and then we had a significant scale of surveys and other types of research methodologies. In synthesizing, that is what you see here in the bottom right, or customer say, Don’t treat me like a unit, address me as a person as an individual. And don’t talk to me generically. Tell me what makes this product that I just bought and powered up in my own hands really special. So that’s the customer pain point we’re going after.
So the origins of this experience, really is to start with a welcoming companion that encourages and inspires you with the magic of HP computing. And they in turn internally for us, it also creates a significant, scalable monetizable channel because it gives us a direct dialogue that can be personalized with a customer. So I’m going to show you this product in context, we’re using Engage, as I mentioned, we’re very focused on content so we don’t have products or transactions built in. But I think that’s something that’s on the horizon for us.
It’s introduced to the customer when they first power on a new device, and it becomes more of a constant sort of perpetual companion to help them do more, because so many of our customers want to know how to do more with modern technology. So in this diagram, we see kind of left to right, what’s going on in our use of Engage. So first, we start with a covering animation that takes all these attributes of the device and anything we’ve accumulated about their customer over time. And we send that up to RichRelevance(now Algonomy). Right now, there’s some contextual attributes that we pre code but it can also learn as we go, when we use Engage to trade rules and logic for for actually several different attributes. One is the flow of screens you saw that changes by geography by product, as well as by customer. The second is the nature of those screens. That gives us split testing and some optimization, some experimental capabilities, actually, much like we heard about today. So now we can run tests on much tighter cycles with a much more scientific approach.
And then finally, the actual content, the panels that are shown here, we have nine placements, but our actual content library is, is growing significantly. And so we’re not a publishing company, right, that’s a given the whole team that sponsor that drive this entire effort is relatively small and modest, particularly by, you know, by our standards. So the thing we really like about RichRelevance(now Algonomy) is, every time we build a new product, like the device Magnus has back there, we can say, what what are the top three or five things that we really, really want customers to know about this device, what makes it awesome. And that becomes part of the product development process, we load that into our engaged system. And we let the platform do the work of figuring out what customers respond best to, and how to use that capability to actually get the most engagement here we can. And we’ve proven through all of our fieldwork, that more engagement at this point in the customer lifecycle creates happier customers, more engagement creates customers who will buy the right accessories, right and the right services to go with their product. So it actually drives both the sentiment measured through NPS score and economic return, measured on our panels.
So that’s what happens over here on the far right, we’re now continually increasing our content library, doing more experimentation, really building up that the science aspect of this solution.
So it’s early days, but so far, the results have been really strong. We started this effort in live in market around August. And throughout the holiday, we very quickly, you know, took our initial pilot deployments, up to a million monthly customers, and we maintain that level. And now we’re expanding that reach. I think the more interesting thing is the second and third graph, which is more descriptive of how customers are engaging with it. It’s pretty simplistic today, but every week we’re driving new content into this platform. So every week we get better and better. And we get smarter, and we can test and adapt. So in the center, you’ll see the average minutes of use. So month over month, the amount of time customers spend exploring this to learn about their new products is growing. And on the far right, you see the click through rate of content. So going from the first level to the second level of content to get more depth, I think we’re doing pretty well so far, and getting customers to spend time and go explore their. And we have proven already that the more time they explored, the more they do with their with their new device. And the happier they are, the more likely they are to recommend it. And that’s how we get past the history of being your father’s printing company. Right? helping our customers do more awesome things with their computer.
So looking ahead, our vision here is really to take that welcome aspect and expand it to be much more trusted, persistent and personalized. Because after your first use, we can accumulate more and more insightful information without PII. Alright, so that’s really not a part of where we’re operating today. But we can accumulate a ton of insights and then act on those using tools from its relevance. So I’ll take you through a few visual examples. Because the fun stuff, right, the visual storytelling. Here’s an example, a little bit of fear around a new product you might buy, we engineered this mouse to have not only like a beautiful aesthetic design, to go with that notebook. But to work better to have lower battery life more resilient, Bluetooth performance, all those sorts of good things. But that’s not worth very much if the mouse is not on shelf with the device, and no customers can find it. Alright, so we want to make sure when you buy a flagship device, we want the flagship accessories to have 100% awareness and a much higher connect rate. And actually think this RichRelevance(now Algonomy) experiences I think is going to take us from performance into teens to performance level over the 50% mark.
So you can imagine that this is your welcome experience actually gives you a product tour, it tells you what you can’t miss there. And then as you get into this, it gets richer and richer. So again, we mentioned we have multiple panels here. As you scroll, it has a vertical scrolling interaction model. Once you go down, then it’s a very dynamic space very open ended. We can talk about accessories, software, key features, partnerships, it’s extremely open ended, we actually don’t know what the perfect formula here is. So instead, we built a business process and a science where we can go test, adapt, and start to figure out what the what are the most effective formulas for different types of products and customer segments.
The great example here is if you buy a gaming product, so two of our most strategic categories right now, our premium in gaming. That’s where all the growth in personal computing is at this point in time and it’s also where all the margin is. So this is example what you might see on a on a flagship premium product. Let’s say you’re a hardcore gamer, and I guess there are at least a couple of you guys lurking in this room.
It might look like this completely different complexion. It takes on the personality, the look and feel of what our gaming brand is all about. And we have that same, that same platform capability behind the scenes to customize not only the welcome, but all the tips and recommendations and discovery to what’s most germane to this customer. So in this case, we’re talking about gaming platforms, and how to do very interesting things that are that are relevant to this customer like overclocking. And this is all powered by the same platform. And this actually, we have the prior version, in a simple manner in market today. So we’re also really excited about enriching this interaction, I think we started with something that’s fairly simplistic, we want to have more depth and more flexibility there.
So we have teams are doing quite a bit to envision what the she’d be like in the future. So this is Christina in our product team here, going through a workshop thinking about how to create the right customer interactions here. This takes time takes iteration. So we’re constantly taking what we’re learning through all of our instrumentation and driving that back into our product ideation and definition.
This is the fun stuff, by the way, some of my favorite parts of the job.
So longer term, what we really want to do is take this platform and extend it beyond just a welcome all the way around the customer experience, customer lifecycle. So I showed you earlier a little bit about our marketing. So want to make sure that the hero positioning and features that we market, that that extends all the way into the product. Right? And that we use that to create much stronger, happier customer sentiment. Right? My guess is that your sentiment about Windows PCs is not where I’d like it today.
How do I fix that? Right, I made sure that things we market and things that make us different, and special, are a core part of the ingredients of the product.
So wrapping all the way around here, you know, we’re pretty strong right now with our initial offer in the first few moments of use of the device. So that’s what I shared with you. It’s based on device and location, as Christine explained.
We want to get better, right throughout the next few steps of the customer lifecycle, whether it’s the next few months, or the next couple of years. So Lucius Fox is like an archetypal personality for us in the future, this product. And the reason we feel that way is because he’s actually an incredible character, he gives Batman all this phenomenal technology and toys, and things to go out and use in the world. But he’s so deferential to him, right, he gives him total respect, gives him total flexibility, he helps him do more, he empowers him, there’s always differential. And I think that’s a really good example for us of the archetypal persona that we want to build into the experience. And we’re going to do that with some of these additional sources of data, information about how you use your computer, which components are of value to you, you know, do you plug in certain peripherals or not?
You know, what kinds of things are you discovering? Are there unused features like magnetize that you’ve never used and we think might be a value to you. And then finally, you know, building out our content library and see what customers engage with. That gives us a lot of actionable data.
In the back half of this experience, you know, as your device is reaching its later in its lifecycle. We want to be able to tie in some of the things we’re doing support to be both more contextual, with more available touchpoints like a better dialogue between the customer and the company, and also start to get more and more predictive. So as you’re thinking about your next device, you have a clearer source of information, as you’re thinking about, you know, what’s going wrong with this, like, is it me? Is Windows right? What is it? How do I fix this, but you have a way of accessing information that’s very timely and contextual.
And this opens up a whole spectrum of opportunities for your next product or your next level of service that to us, we think is part of our continuous relationship with the customer. And now we have a much richer tool to go pursue that future. So I’ll give you a little bit of glimpse of what we’re doing, how we’re doing it and why. And I think many of you are already moving much faster in this general personalization space. And we are, but we’re really excited to be here. And we’ve learned a ton. So thank you for your attention. Appreciate it. Thanks a lot.
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