How top brands create "wow" moments with data

David Spitz: We're not just thinking about the future but who are operating in it on a, on a daily basis, whether we're talking about mobile centric experiences like these or omnichannel ones like these, what you guys are building are the future of customer experiences writ large. And it's really the epitome of customer obsessed business as opposed to competitor obsessed or company obsessed. And these days you have to be customer obsessed in a world of social media, GDPR, amorphous boundaries between different industries, tons of consumer choice.

If you're not customer obsessed, you're in a lot of trouble. And the opportunity and challenge for all of you in this room, both for your brands and you personally, is that most companies in this world really suck at customer experience and it's only getting worse. Customer expectations are going up and companies at best, have flat lined in terms of their ability to deliver on those expectations. Forester runs a cx index every year and 2017 was the first year where the average brand saw no customer experience improvement or really twice as many brands saw declines in customer experience as saw improvements. And they believe that in 2018, 30 percent will see further declines in experience. So what you could do about it is really two fold to make it really simplistic--culture and infrastructure. So culture, of course you need people working together across teams like never before.

You need a new set of metrics that are based not just on short term KPIs, but did we meet and exceed customer expectations? Did we create experiences that they're going to go and tell their friends about. And you need leadership with Jeff Bezos being the prime example of a leader who leaves a chair open in every room for the customer and in his most recent shareholder letter, if you hadn't seen it, he took time out to talk about how even he is worried about how divinely discontent customers are and how yesterday's wow quickly becomes today's ordinary. So everyone reads the Forrester reports and everyone has read the Bezos letters and if you ask companies, half of them will say that customer experience is a top priority, but it's not getting any better. Which gets really to the second point of data and infrastructure. Bad data is the enemy of all these great intentions.

And what I mean by that is that you need to be customer-obsessed about your data. So putting the customer at the center of your, of your understanding of who they are across every single device, where you might encounter them. Deep context, not just say their relationship histories, which might come from a CRM system or their behaviors which might come from some analytics system or their exposures which might come from some sort of marketing system, but also their context right now, where are they in space, where are they moving, their geolocation? And you need to be able to action on that understanding in real time seamlessly. And that's, that's really hard for most companies. Forrester came out with this report a couple of weeks ago where they, they observed that the typical customer journey, well there's only one experience. It crosses over all these different types of systems, that are organized by systems of engagement, orchestration, insights, identity management on one level.

And then on the vertical, different platforms like mobile, offline, digital. And you have these 12 different buckets. And I'll tell you, as most of you probably know, the reality is much worse than this. It's not 12 different buckets. If you read Mary Meeker's latest Internet Trends reports, she talked about how in marketing alone, the average company has 91 different cloud services. If you look at a MightySignal or Apptopia, you can see that most mobile companies have dozens of SDKs in their app. All these different point integrations that at best capture a little tiny bit of the customer journey and they certainly aren't, aren't real time. So if you haven't guessed where I'm going with this, that's the problem that mParticle is focused on solving. These systems are not going away and if anything there's going to be more systems in the future, more, more, more tools and analytics as there become more devices and more channels in that journey.

But we want to be, be sure that you're able to bind those things together to integrate that data, to have a single point to synchronize all the different identities across these systems, to orchestrate these journeys in a unified way. So you can think of it as a data layer or data infrastructure or whatever you want to call it. When we first started coming to MAU three years ago, there was no name for this. Now the term of art is customer data platform or CDP, and funny enough, the same day that Forrester published this report, an ad appeared, a graphic appeared in AdExchanger with this image, which is sort of tongue in cheek, but it also does capture the fascination that people have with the ability to integrate data across all these different systems and elements of the journey. But it also conveys that it seems like it's something of mythic proportion.

And I want to break it down a little bit for you based on some real stories of people who are in this room today to show you that this is not something of mythic proportion. You could climb the stairway to customer experience, but you have to be looking up. You have to be looking torwards the customer and not looking down at all the operational challenges and the short-term KPIs that, that lay in your path. So let me give you a couple of examples. We've helped now hundreds of companies simplify their mobile data infrastructure. And the customer benefits for that are really threefold.

So first and foremost, safeguarding consumer trust, the worst experience in the world is to violate someone's trust with a privacy or security breach. And by having a more consolidated data layer, you're able to protect against that and not be in a reactive position, which a lot of companies are now trying to address GDPR, but really to have proactively considered privacy by design. The second, the second benefit of simplifying your infrastructure and reducing down the number of standalone SDKs is just engineering productivity. If your engineers are spending time integrating data, they're not spending time building products that customers love. And third, as Lilly Pulitzer found by simplifying the way that data is integrated, you'll see a faster, more stable experience, fewer app crashes, fewer needs to deploy and redeploy the app, which is just super annoying to the user experience. So that's an example of simplify three examples of simplify. And the great thing about once you simplify your infrastructure, then you can start to join things together and really understand your customer better. And Lauren Picasso from Jet spoke at MAU last year on a panel and she said, "You don't want to be looking at marketing and a silo. You want to look at how your marketing is affecting web, how web is affecting app. And with mParticle we can send any data we wanted to third parties, we could send it back to mParticle and most importantly we could send it to our own internal databases."

So you'll hear more about Walmart's stack and Sam's Club's stack in a little while on different panel on this stage. But why would you want to do that? I mean an obvious example is just a better view of attribution. So having a longitudinal understanding of not just how I acquired a customer, maybe they download my app or made one purchase, but really their entire lifetime value. It also helps you understand the value of the app in an omnichannel experience such as in travel, where a lot of people browsing the app and then buy on the web. So it's a much stronger understanding of the overall customer journey.

And companies like Postmates have expanded this understanding beyond just marketing. So Postmates has integrated Braze, AppsFlyer, Amplitude, Zendesk, and dozens of others that I'm probably missing through mParticle. And with that understanding, they're able to see the impact of product changes on lifetime value and also the interaction effects between things like customer service, marketing, product, how a change in marketing might have affected those other things. So it really did create a complete understanding of the business and get better product intuition. So of course once you understand the customer journey better, you're going to want to start to want to act on those insights. I was talking to Ori Klein last night from Via, the ride sharing service, and he reminded me how when he opened the Via app, because of the integration through mParticle with Leanplum and Radar location, a data company, you're going to get a personalized experience based on your location at that moment. But that's not all. It's not just a marketing experience. If you open the app and there's not enough drivers in the area, they're going to send a message to the driver app and tell people that there's demand in an area and to try to send drivers to that area and then they'll again come back to you if you didn't book a ride and say, "Hey, you might want to have the second look. There's more drivers in the area." And these things are all happening through automated data flows in a very real time basis.

Notice I haven't spoken about advertising yet. Advertising is important, but most of the customers that we work with are looking at maxing out their organic channels first and foremost. And then when it comes to advertising, very often the first thing they want to do is suppress advertising. Like SeatGeek has done. They take all the mobile ids and they're constantly thinking that with Facebook and Snapchat to make sure they're not spending a dollar of UA budget on acquiring people that they've already acquired. And if they are advertising against those people, they're giving them a much more relevant message and much more relevant experience. Which in the case of Snapchat alone has saved them 30 to 40 percent of wasted wasted impressions.

So last point on this stairway is about scale and if you notice really, so far we've been talking about predefined segments and orchestration role. So if someone opens up at this location, given this experience, if someone has mobile ID, don't give them this ad on Snapchat. But what Craig Kelly at Overstock is doing is much more nuanced than that. He consolidates all the data into mParticle and then sends it to a machine learning engine which uses predictive analytics to score your users along different dimensions. So how likely are you to respond to email versus advertising? What time of day is the best time of day to reach you? What's gonna be your value? If I pay to acquire you, what can I expect? And those are all written as attributes back into mParticle and then modeled together and can be sent for execution through advertising, messaging channels like email, through web personalization, and then also the mobile app. So all of this is happening in real time at a scale that's much faster than anything we had, we had discussed before.

So to go back to this picture, we see a lot of people starting with cleaning up mobile and that's a great place to start off because mobile is the centerpiece of the customer experience. And then after that we see people cleaning up their understanding, their systems of insight, and then after that starting to tie in offline and web and, and other forms of engagement. And then after that, people like Craig Kelly, they look at this and they say, "This is the wrong graphic overall. We have uni-directional data flows is where they should really be bi-directional. We have three platforms on top (mobile, offline, digital), but it is 2018. Connected devices have reached critical mass, wearables and, you know, other IOT, intelligent agents, voice. These are all at real scale right now. And then most of all, you realize you need the user at the center of your understanding of your technology stack. So user centric, bi-directional, and then infinitely extensible, as more devices become more of a central part of the customer experience.

So let me sum up, first of all, mobile is at the epitome at the center of the modern customer experience and the customer-obsessed culture is what you need, but it's necessary but not sufficient. It's not enough. You also need infrastructure, so you need to focus on your data infrastructure, getting that in order, if you want to keep pace with what Jeff Bezos says is the wow of tomorrow. And then finally, CDPs are great way to organize your data for future machine learning applications. But really you got to master the fundamentals first if you want to keep up with the change.

And speaking of change, we have some change to announce as well. We spoke about how the customer journey is now multithreaded. We spoke about the importance of bi-directional, not just uni-directional data, thinking of mParticle more as a data bus than a data router. And we spoke about they really paramount importance of a security and privacy by design. And with all those things in mind, we felt it was time for a change for our brand image and identity and we're happy to kind of show this audience first and foremost what that looks like. And here it is. I hope you like it. This is the first time that we've kind of shown anyone the new look. We're going to have lots of goodies at the booth that you can pick up. And you know, we really wanted to thank you all for your partnership over the years. We hope you enjoy the conference and we hope you come by and share your stories. Tell us where you are in your evolution and how we can help. Thank you.