a16z Podcast - a16z Podcast: Data, Insight, and the Customer Experience

Episode Date: February 13, 2018

In 2017 The Economist declared data to be the world's most valuable resource. And yet “data insight” is one of those phrases that, while important, is now so ubiquitous it’s been numbed of meaning. So how do you actually get the most meaningful insights from your data, and what does that look like as you also think about crafting the best customer experience? When and what is the best way to use this information... without getting to the dystopian future depicted in, for instance, Minority Report? This episode of the a16z Podcast (based on a discussion that took place at a16z's annual summit event in November 2017) features Suhail Doshi, co-founder and CEO of Mixpanel; Gil Elbaz, founder and CEO of Factual; and Jeff Glueck, CEO of Foursquare; moderated by Lauren Berson. It covers everything from using data to understand context and one's customer base to what personalization really means and how data can impact the physical world. The views expressed here are those of the individual AH Capital Management, L.L.C. (“a16z”) personnel quoted and are not the views of a16z or its affiliates. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by a16z. While taken from sources believed to be reliable, a16z has not independently verified such information and makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This content is provided for informational purposes only, and should not be relied upon as legal, business, investment, or tax advice. You should consult your own advisers as to those matters. References to any securities or digital assets are for illustrative purposes only, and do not constitute an investment recommendation or offer to provide investment advisory services. Furthermore, this content is not directed at nor intended for use by any investors or prospective investors, and may not under any circumstances be relied upon when making a decision to invest in any fund managed by a16z. (An offering to invest in an a16z fund will be made only by the private placement memorandum, subscription agreement, and other relevant documentation of any such fund and should be read in their entirety.) Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by a16z, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Andreessen Horowitz (excluding investments and certain publicly traded cryptocurrencies/ digital assets for which the issuer has not provided permission for a16z to disclose publicly) is available at https://a16z.com/investments/. Charts and graphs provided within are for informational purposes solely and should not be relied upon when making any investment decision. Past performance is not indicative of future results. The content speaks only as of the date indicated. Any projections, estimates, forecasts, targets, prospects, and/or opinions expressed in these materials are subject to change without notice and may differ or be contrary to opinions expressed by others. Please see https://a16z.com/disclosures for additional important information.

The content here is for informational purposes only, should not be taken as legal business tax or investment advice or be used to evaluate any investment or security and is not directed at any investors or potential investors in any A16Z fund. For more details, please see A16Z.com slash disclosures. Hi and welcome to the A16Z podcast. Last year, the economists declared data to be the world's most valuable resource today. Big corporations certainly have more data now at their fingertips than ever before. So how do you actually create actionable insights and experience from your data for your customers without getting too close for comfort? This conversation includes CEO and co-founder of Mixed Panel, Suhail Doshi, Gil Elbas, the founder and CEO of Factual, CEO of Foursquare, Jeff Gluck, and is moderated by A16Z partner Lauren Burson. It took place at our summit event in November 2017.

So traditionally, IT invested in tools to store and measure and house data, but held the keys to the castle, making it difficult for marketers and business people to actually make sense of data and information about their customers. I think the quote I often hear is if it takes six months to answer a question, you probably stop asking questions. There is a key evolution here towards IT tools, like some of the ones that you have, democratizing data and bringing access to both IT individuals as well as marketers and business folks. Can you talk a little bit about the shifting roles and responsibilities and how this is playing out and affecting you?

So on the accessibility side, what we find traditionally is that pretty much everybody has a very large data pipeline that usually consists of ingesting the information and then transforming that information, storing it somewhere, graphing it, or querying it, and then from an executive,

finally being able to, like, get a dashboard where they can finally get that number. You know, we don't all want to be SQL experts. And so it's really important to find ways to give them the power to be able to do that. However, there is a privacy component that we all do have to tackle in a company because, you know, for example, Mix Panel works with a few banks.

And one problem with, of course, the banking industry, the financial services industry, is that there's just a level of information that they cannot divulge to us. And they have to keep even housed away from their own employees. And so therein lies this big problem with how do you make the data accessible while still empowering the rest of the company, even though they can't have access to that. And reporting is one way, but it's really about. using the best product to solve the most important problem that you have with the data. Large companies today try to find a one-size-fits-all tool, and that just doesn't work anymore.

What works is finding one tool that serves a major part of your organization so that it will really empower them. The lens that I look at it from is you have a cohort of extremely powerful data-first companies. These are software companies that don't sell software, the Googles and Facebooks who have this incredible DNA around collecting information, knowing how to make it actionable, and then building an incredible array of products that delight users and they're also monetizing users. And it's quite a threat to the broader industry.

We're saying new verticals where they're pursuing market share. And I think with this changing landscape, what it means is that all other companies have to figure out how are we going to orient our strategies around getting access to more data. First-party data, build one-to-one relationships with users so that we have it.

And then we have to ask the big questions. What data are we great at? What data do we absolutely need to be competitive but aren't great at? And what are the strategies going to be in order to have something that's equivalent? So I think about all the data that people are drowning in the digital world companies and how little they understand the real world. For Foursquare, we have 125,000 companies using our platform to build better mobile experiences. We're very much an enterprise company.

and 92% of the economy happens in the real world. And so when I was CMO and spent a billion dollars at Travelocity, I had the cookie. And I knew what advertising worked. I knew a lot about my users. And if you're a retailer, you have CRM, you have email, you have your website, you have all this data. But you know nothing about what your users are doing in the real world until they come in and use your cash register. And, you know, 92% of the economy is in the real world. So I think, you know, for those of us in the location intelligence business,

we are organizing all of that movement data in a mobile first world and making it actionable. So you don't need to train everyone in SQL. We will enable you to build contextual experiences. Let's talk a little bit more about how you really use digital data to transform a physical interaction. A lot of what we think of as great customer experience in the real world is contextual. And we talk about context.

it's all right. I mean, are you arriving at your desk for the 10,000th time, or are you turning the corner in Barcelona and you're near this incredible tapest place that you've never been to? You know, are you at home? Are you in a new restaurant or one that you've been to tons of times before? And is there content for you? We sat down with this company called Touch Tunes. It's a $500 million music business in 65,000 locations. And their problem was they have jukeboxes, right? Remember the dollar in the jukebox? This is a $500 million business. But increasingly, it's a $500 million business. But increasingly, on an app. But they have the 65,000 jukeboxes, and people, their users, who spend like

$15 a month on average, didn't know when they could control the music in the bar or the restaurant. So we enabled them through the RSDK to say, hey, are you at the perfect point? Jay-Z is really popular here. You love Jay-Z. Get the party started. They had like 400% increase in the click-through, and they had a 66% revenue increase, because it's a social message just the right time and the right place to the right person. It's almost like context is intent, right? It's like where you are says a lot about who you are and what you might want to do.

So I'm going to date myself a little bit in shift gears. When I worked at Citigroup in 2004, I ran direct mail campaigns and statement inserts and all these really sexy things to try and get card members to get excited about having a city card. And we had a channel called Personalization back in 2004. At the time, it was Banner Ads. That's what it was.

It was Banner ads that maybe said a different thing to different cohorts, but it had nothing to do with who you were. Point being, the term has been so overused, right? A term has been so overused, it's almost become numbed of meaning. So I'd love to hear what your definition of personalization is, and maybe what are some of the best examples of putting this to use. You're totally right about how people sort of perceive personalization, and it takes a monumental effort to build the perfect algorithm that will work perfectly for each individual and give them exactly. whatever they want. And the truth is that a lot of those algorithms are core competencies of the business. It's really hard for one company to know everything about your business. We try to, instead of thinking about personalization in the way that we've been thinking about it over the last 10 years,

but instead just think about it a little bit differently, which is that there's two extremes. One extreme is you make decisions in your business and they affect a wide, pretty much your entire customer base. We don't like that because that's not really optimizing for maybe what we want. There's the other extreme, which is personalization. And there's something right in the middle that I think is really valuable. And if you really take your entire customer base and you analyze their behavior, you understand where they're coming from, you understand location, you understand everything about them, you can actually break them up into groups. You can break them into groups of customers that are your new customers, your power user

customers, your most loyal customers, customers that are kind of what I would call casuals of your product, they kind of use your product. And I think what starts to matter more, is finding the core set of groups of users and then within the business trying to assign ownership to that, people that can really move the needle. So it's almost like reducing friction becomes more important than this holy grail of one-to-one personalization, which just seems so complex. It's like how do you even get started? So the hotel check-in, maybe if they knew your favorite drink when you ordered room service,

that might be a nice experience. Yeah. Or they just know that, you know, as a new customer, most people like that particular drink if they're in that block of rooms. even that's like a reasonable kind of solution to that problem that won't take a humongous effort to get right 100% of the time. Do either of you have a comment on even, you know, on personalization in general, but then also on a particular company that you think

is doing some interesting things in the space? I think one of the early innings of personalization. I mean, personalization is delivering the kind of experience that's sensitive to who you are and what you want and what you know the way that a best friend can be sensitive. And I think while we may not all agree, I think that the future is one where people are going to crave those types of experiences, the truth will play out.

We're in the early ending. It's all about location intelligence, understanding moments and time, circumstances we call them, where you might want to take a different action and deliver a different user experience. I think there's a long, exciting road ahead for that. Personalization is a broad topic. It can mean a lot of things. And I think at Foursquare, we really believe that consumer transparency and opt-in is a big piece of it. What is the value for the user?

I mean, we started with consumer services. There's still 50 million people a month used across our apps and our website. And we actually invested a lot in personalization at first, almost too much, because Dennis Crowley, our founder, believed that Yelp and Google gave people recommendations. And, like, no matter who you were, you said, where should I go to lunch in, you know, Paris or Chicago? And everyone got the same answer, right? And that's kind of broken. my wife who's a farm-to-table organic kind of person

and my dad who's a beef and potatoes kind of guy should not get the same recommendations. Everyone gets at 4Square City got an entirely different set of recommendations based on the kinds of places you go to and it used to be checking in. Now we just passively are able to understand when phones go in and out of 100 million places detecting it through Wi-Fi triangulation and Bluetooth and GPS

and all of these signals. And so we learned about each person and we can personalize recommendations. But that, you know, per se, I don't know how game-changing that is, because if I just want to, I feel like pizza, I just can ask Google for pizza. But I think where's really exploded is marketing personalization. And this is where, like, we always have the saying that, like, the places you go is the best indicator of who you are. Panera wanted to launch a salad line that was really healthy.

And so they wanted to go out and find 20 million Americans who would actually want a healthy salad. And so we'd profile 150 million Americans. based on the places they go, both through our own apps, but through a network of partners using our technology. And then, you know, it's very different than, you know, what we do for Anheiser-Busch, which is go out and match, let's say, a certain beer brand or spirits brand with, like, a 20-something going to craft cocktail bars, which are different than dive bars. And we understand every place, and so where you go creates this picture of your values.

And so we could assemble marketing for Panera and launch this thing and measure against millions of people, A, B, test in the real world, whether the ads drove people incrementally into Panera locations and we could show the ROI. So that kind of personalization that has a clear return on investment is exploding

because it is not necessarily a one-to-one marketing, but it is micro-targeting of different segments. And that's driving business. And these traditional offline businesses had no way of doing that the way a digital business did. It's going to be important to deliver the future to users at the same time that they are monetized, very

very, very effectively. Absolutely. And I think we're dependent on product developers to put more resources toward innovating in this area and not allowing just the Googles and Facebooks to own it. So in prep for this panel, I spent time rewatching Minority Report. And it's set in the year 2054. As you're walking around this world, everything is scanning your eyes to know who you are. And you were being marketed to very specifically, right?

This one-on-one use case of Lauren. I know you bought this at the Gap last week. to buy another pair in black, it's on sale. What I want to kind of get at here is kind of, you know, everything in this world is known, including future actions. So the question is, like, how do you ensure customer privacy and remove the creep factor from some of these experiences? And maybe on the flip side, like, will our behaviors change enough so that we don't care?

Well, it's a very interesting movie Minority Report. The consultants that helped create an image of this world, the technical consultants, formed a company called Oblong, to try to actually build. this future. At least the part of it where you can interact with a wall, a digital wall, then I've incubated the next company that Quindla Kramer has been working on is video conferencing that really, really works seamlessly. So here's something that I would love to see. Personalize. When I walk into a conference room, this is personalization. I want it, yes, I want it to take my image. I want to scan my damn retina. I want it to do face recognition.

I want it to know that I'm supposed to be on the call that I'm supposed to be on and let me in. and I don't want to have to knock, and it should just all work. So, yes, it does take trust. It's something we haven't talked about yet, but it does take a brand that commands trust from users that opt-in, and you're with the program. I think it comes back to we just really believe that users should be in control of the choice and transparency,

and so we try to live that. So there are data brokers out there, and there are, like, flashlight apps asking for your 24-7 location, information. Why should a flashlight app have your 24-7 look at it? What value is the flashlight app providing you? And we just don't believe that that is going to be sustainable. We don't participate in any of that.

I mean, everything we do is about creating a better user experience. It's giving you the right information at the right time or a coupon that you've signed up for. Remember to use it while you're at Walgreens, you know, or it's enabling, like, we enable for hotels, a bunch of hotels have gotten rid of their

concierges, and they're just using the four-square recommendation engine. in the hotels of the future. And so all of these things are about creating better user experiences, but they're very transparent. They know they're signing up because they're getting value. And so I think that's key. The bad marketing example in Minority Report is, like,

remember when people used to say, oh, the future of mobile marketing is if you're near a Starbucks, you're going to get a coupon for a Frappuccino. Well, I got news for you. Everyone is always fucking near a Starbucks. Like, you know, always. Like, it would be a nightmare. And so, like, we've really built the technology.

to understand, you know, that you're in this, like, really cool bakery that makes this incredible cupcakes or you're, you know, you're across the street at the gym. And those are very different moments. There's different contexts. And you've got to be super precise down to 100 million places to do that right. And so that's key, is not bothering people. You've got to be super relevant if you're going to tap them on the shoulder. And I think that's the future. I think traditionally, a lot of these experiences relied on you forgetting that you have this great coupon or offer, right? That definitely needs to change. and I think that's shifting a lot.

So I think that was an interesting point. Before we wrap up, I'm just going to throw this out there. Is this a misconception or is this true that good data scientists will find value for your business? The truth is that our tools are not necessarily always powerful for them. Good data science teams want to work on the hardest, most challenging data science problems that exist in the company. They don't want to be just trending a graph over time out putting it into or putting it into Excel and putting it into a deck. You've hired these people. They're extremely expensive and we utilize them to do very simplistic.

math on analyzing the business. And so what I think is valuable is trying to find a more sustainable way of handling this, which is that 90% of a business's questions are pretty reasonably easy to get to. It's just the data and the analysis, and there's some edge cases that you have to kind of figure out. That part's annoying and hard, but 90% of your questions are pretty easy. There's just 10% of really important, sophisticated questions that a business needs to answer, and the data science team is great for answering those extremely hard questions that really no tool can really answer for them. Okay. I think in a space that's so proud it, hopefully we have a little bit more clarity on how to balance privacy with personalization, how to remove friction, how to remove breakage. I'd also think about customer experiences that are surprised and delight versus solely for monetization. Thank you, Sue Hale, Gail, and Jeff.