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4th Annual Future of the Consumer Conference

Listen as Nitay Joffe, Founder & CTO of ActionIQ and Martin Casado, General Partner at Andreessen Horowitz and lead investor in ActionIQ’s Series B of $30M are interviewed by top-ranked Retail Equity Analyst, Oliver Chen, Managing Director at COWEN on April 3rd 2018, at Cowen’s 4th Annual Future of the Consumer Conference. Full transcript below! Drop us a note at daniela@actioniq.com, for any thoughts, questions – or should you like to join our influencer community.

Oliver Chen, Analyst, Cowen and Company (OC)

I’m thrilled to introduce ActionIQ. We are joined by Nitay Joffe, CTO and Co-Founder. Nitay founded ActionIQ to explore his passion for innovation in databases, distribution systems and big data. He was an instrumental engineer in Facebook’s data infrastructure initiatives, and the core contributor to open source projects HBase & Giraph. We also have Martin Casado who is General Partner at the venture capital firm Andreessen Horowitz. He was previously the Co-Founder and Chief Technology Officer at Nicira, which was acquired by VMware in 2012.

To give you a brief background ActionIQ is a marketing activation platform, which helps partner centralize and more efficiently leverage their existing data streams to improve CRM in personalized marketing. ActionIQ’s platform helps retailers unlock and access their own data streams including EDW, digital analytics, marketing and third-party data, which historically were siloed from one another and inefficient for business and marketing teams to use together, analyze and efficiently execute on.

With that, now let me turn the floor to Nitay and Martin for a brief presentation.

[Video Presentation]

Nitay Joffe, Founder and Chief Technology Officer, ActionIQ (NJ)

As it was mentioned, I come from kind of big data space. I was involved in a lot of Big Data Initiatives and the cost and everything kind of around had duped that – that whole world it’s my background. Most recently, I was at Facebook, I was setting a lot of their graph analytics.

My Co-Founder, Tasso Argyros, you see there. The founder of the company called Aster Data, which was later sold to Teradata. That was the Big Data warehousing company for enterprises. And so both kind of came together and the main thing that we saw was Big Data and that whole world had a lot of promises and it delivered a lot of value, at the same time, it also left a lot of holes. And those holes specifically were around unlocking that data and actually getting business value out of it.

At the end the day, you kind of got left with a better technology and data lakes and this and that, but where is the actual value coming out of that on the other side. And that’s really why we started ActionIQ to solve. We’re very fortunate to be working with some of the best investors around Queen City Capital Management and Andreessen Horowitz. Martin here from Andreessen specifically, is a killer when it comes to understanding markets and understanding kind of where the future is going. So any questions you have, he knows all about that.

At the bottom here you see some of the logos, some of the companies that we work with. The main thing to understand here is this is a problem that stems across all cohorts of different, large enterprise companies. You see obviously some retailers here, but as well subscription businesses, Telco, so on. We really the main thing to kind of understand from this is, we really thrive in complexity. One of the main things that we’ve seen is if you’re a small e-com shop, at the end of the day, you can do just some quick easy win that says I know, what my customer lifetime value is now, because I didn’t even use to know it and that gave me some initial value.

But if you’re one of these folks here and I am sure some of you in the audience, you already have a whole level of sophistication. You have data warehouses in-built and you have all the stuff. You need something to understand that complex and able to actually deliver value from it.

So going off that, this is kind of the landscape that we see today. And I’m sure this will resonate with many of you. And the last thing you’re seeing here is the existing data warehouses and different databases and data bars that exist in the customer. And the main thing to understand is the data is there. It’s ready to be unlocked. It’s ready to be utilized. But it’s siloed, it’s in many different formats. There’s a lot of different technical details there. 

One of my favorite images that you can imagine is if you’ve seen the likes of very old movie Waterworld, the businesspeople the marketers are kind of like those people on the raft, right. They’re surrounded by water, but they’re dehydrated, right. They can’t actually drink anything why because they have no idea how to get that – any of that, all right.

On the other side, you have the various channels and these are everything one has a platter of different vendors for an e-mail marketing, web, app, advertising so on. And all those channels are also siloed and that they don’t work together with each other, you have no idea how to actually measure is my acquisition through mobile app or is my acquisition through Google or Facebook, which ones is working better. Where should I allocate my funding? You have no clue how to do any of that.

And, so where that kind of leaves you today is poor marketer or poor business person kind of making sense of all that and solving it today essentially with heavy, heavy processes and a lot of manual efforts, right. So we’ve seen with some of our customers just the effort to go end-to-end with one initiative, one strategy, take so much back and forth growing and coordinating between all the different channels and coordinating between IT and data warehousing and so on. To even understand, who am I going to target with this strategy. I have this idea what will I actually reach.

So, that’s kind of the world today. Silo data, business processes and a lot of humans involved to make that happen. With ActionIQ, where we come in is really as I said unlocking all of that data. And we rarely much have a data first approach you can kind of see it in our DNA. I’ve fundamentally believed that the only way to solve this problem is with data technology, not just with throwing more bodies at the problem not just with throwing yet another vendor at it. We are also very much data and channel agnostic. And we’re one of the only players that you’ll see like this.

Because if we bring a different another vendor in, you just have the n+1 problem. But if you have bring in something like ActionIQ, you are able to actually unleash all of the different data you have on the left side and utilize it across all the channels on the right. One of the stories that I could tell here is, on the – specifically on the output side, I came from Facebook I thought firsthand something that you guys probably have all seen which is Facebook has spent years and years educating everybody that you need to get likes. Likes is the thing that you should care about. Why? Because it’s the only thing that they actually had control over measuring. And so all you want to do is brand awareness, sure, likes can be a good thing. But if you’re actually at the end of the day bottom line measuring revenue, measuring conversions, measuring transactions, and so on, Facebook has no clue, right. And the only way you can do that is going back to the datasets over here. And that’s really one of the things that ActionIQ enables, is true conversion measurement on true first-party data.

So real quick just to go through kind of how we built our technology. And okay this is very high level, but I’m sure that will be in the question portion. First off the thing to understand is when we connect to all the underlying data we have a whole new infrastructure and a way to do this to enable all the layers on top which is what we call the business variables. The main, the key thing I want you guys have to understand here is any existing vendor that comes in that first layer of getting data in requires a whole level of services and a whole level of – a whole bunch of technology, and ETL and all the stuff that essentially at the end the day means it’s asking the business to understand all the questions it wants to ask ahead of time.

So for example, I’ll come to you and say what is your notion of an active customer? Give us that definition. We’ll code it in, we’ll make sure it’s in the product when it’s deployed. But your notion of active customer actually changes over time, right. Let’s say you didn’t have a mobile app and now suddenly you launch your mobile app, or now there’s some different notion of an active customer who’s active just on mobile but not on web or anything else.

We’ve flipped that on its head by putting all of the logic, and the business variables and all of the governance around business definitions on top of the data layer. And so we take all the data in its raw form. We don’t care what it looks like. We allow you to define where the semantics are. And that’s a very, very different way of doing things. I don’t want to get too geeky here. But this is fundamentally a new approach to doing things and this comes a lot from our background.

Business variables is where our customers, our marketing folks are able to leverage that underlying technology to flexibly define their businesses initiatives. And that notion of flexibility is a very, very important one, because one of the things that we’ve seen that’s hampering all those processes and the manual efforts and everything is just the quickness with which you can iterate, right. How much – how quickly are you able to push out new strategies to segment by a whole new ways that you never thought of before, that is a fundamentally important question that we’ve realized with every customer that we’ve come through.

Finally, on top of that, you have the orchestration layer. So now that you’ve defined what an active customer is and that may change day to day, we define what does revenue look like for you, what is an active, or what is a valid order, what is a discounted order, and so on, now you can actually orchestrate across all of those different channels out there. And we truly do connect with all of the different channels and allow you to work with all of them together to drive that cross-channel kind of more one-to-one engagement that kind of stuff.

The last thing I’ll mention and I touched on this a little bit is we also get feedback data from those channels that ends up, that’s going back to our internal system so that you get not only the channel metrics, but you also get views into how much your Facebook ad is actually touching the conversion at the end of the day. We’re actually looking to link those two pieces together.

There’s a whole bunch of different used cases. I won’t go over these in detail, we can cover more of them in again question portion. But the main thing to notice here is there’s a couple of patterns that I’ve seen. In the first pattern, when we often go into our customers is we often – the way I’ve seen it is things are kind of bucketed into three buckets. Those are things that they’re doing today that are just keeping them float and it’s all they can manage, because that’s the amount of bodies, that’s the amount of people they have working out.

Those are the things they would love to be able to do, but they just haven’t figured out how. And then there’s things that they’re not even aware could be done. We often go and very quickly automate the first. We quickly gait to a point where you’re able to do some of the second and then – and now you’re thinking about some of the things in the third bucket. To give concrete example, the first bucket might be just the things are required to send daily promotion emails, right. Every day in your mind you have a different discount, you have new products coming out from your supply chain, whatever it is. That’s kind of keeping everybody just busy and keeping afloat. We quickly automate a lot of that.

The second bucket is hey what if I could actually understand my users from mobile behavior, and web behavior and absolutely give them different discounts according to do they even respond to discounts. So is that actually useful thing to utilize with them? The third bucket is things like, hey what if I had quick stream data. What if I had all the history for the past year of how you’ve interacted both in store, offline and online? And those are some of the things that we enable to leverage.

Question & Answer

OC

At Cowen and we do believe in humans meet machines and the reality of people in bricks and clicks. But there is so much data out there and as we cover companies there’s overflow. And people can’t necessarily know what to do with it and how. What are your thoughts about your products and really integrating that as well as the flexibility you have?

Martin Casado, General Partner, Andreesen Horowitz (MC)

Yes, so the biggest mistakes I’ve seen is companies saying we know how to personalize, we do one-to-one, we do 360, in reality all they are utilizing is 1% of their data. What I mean by that is they are using very thin kind of age, demographic, location that kind of basic stuff. And then the reality of today is with the likes of Amazon, Netflix, and so on people are getting used to a much deeper level of personalization. And that personalization only comes from that depth by understanding the specific touch points what Netflix knows about you is that on Thursdays at 8:00 p.m. you like to watch Alfred Hitchcock movies, right.

There is a lot that you can glean from that that has much more information than your 33-year-old male, right. So I think that that you talk about kind of the humanity of data, I think, that’s where the humanity comes in, is understanding your particular nuance. And that nuance is around your behavioral data much more so than just your profound demographics, what seems to be kind of the driving factor.

OC:

Yes, personalization is definitely the future of retail. The tools to do that in a way that logical make sense. Martin, it’s been exceptional you were a former Co-Founder and CTO of data network software company that was acquired for over $1 billion. So why did you invest $30 million in ActionIQ after Sequoia invest $15 million? What did you see here that was so compelling?

MC:

Yes, sure. So the reason is we tend to invest in technologies solving key technology problems that are disruptive. And with ActionIQ we kind of got a twofer. So for those of you who don’t know I actually did my Ph.D. with Tasso. And he was probably the – we started in 2000 he was probably the top student of our year. And then as all good founders do he left the program and he became famous with Aster Data. So I knew Tasso, I’ve known him for 15 years.

By looking at this problem it’s very clear that you need to understand data and big data. And so Tasso, he’d done a database program. Then I met Nitay also had been within kind of the revolution that’s happened in big data within Facebook. And so you have two technologists that understand the problem.

Now, when I came, I didn’t really understand kind of marketing a big data. And when I first started trying to reference it, I was a little bit appalled. I mean, like if you talk to many marketing organizations trying to use big data, it really is like this steaming pile of 15-year-old technology that’s being applied to the problem and not taking advantage of like the last kind of 10 years of big data research that’s happened.

And so as we are talking to customers and we’re understanding the problem we realize first a) there’s big need here, right, there’s more data. What was the quote I heard from a customer, we’re drowning in data and starving for knowledge. The solution to it is a deep technology problem that’s one that’s been hard one, I think, by the web scale companies. And so from our standpoint very large market, very compelling technology problem, very compelling founders, so for us it’s a pretty obvious investment.

OC:

Very, helpful and impressive. Nitay, what do you think of retailers should be thinking about marketing mix is a huge hot topic. I hear people really struggle understanding instrumentality, as well as engagement in the new world, as new medians and it’s very dynamic. So what’s your take there and helping a lot of your clients invest in digital?

NJ:

Yes, so I’ll be very, very blunt here. One of the things that I think is kind of a misnomer a bit is everybody talks about again 360, one-to-one, all this kind of stuff. And they are constantly thinking well let me just add more channels. Now there’s Instagram, now there’s this app, let me add, how do I reach my customers with this channel and that channel.

I think one of the things that happens that’s unfortunate in a lot of customers is kind of shortsighted thinking. And what I mean by that is either the – from the leadership down they are not willing to make the kind of monumental platform initiatives required to actually be differentiated and actually compete with Amazons and the likes. And specifically I think when you do that you can actually potentially leapfrog them as this almost a kind of Japan World War II kind of thing of like, they didn’t have all the legacy and all of that.

So if you actually invest in the right technology, you can actually not only compete with but get ahead of them because there’s a rich wealth of data there. At the same time, the customers that we’ve seen or companies out there that we’ve seen that are making those initiatives and those efforts, oftentimes are expecting too much kind of an immediate short-term value out of it.

And what I mean by that is it’s easy to say, okay, I just want to increase my lifetime value of my customers. So that’s why I’ll go to this vendor, they’ll improve my and they’ll fix my lifetime value problem. And then six months from now, 12 months from now, I want to improve my engagement and my conversion from free to paid account. And I’ll get another vendor that will solve that problem.

But by doing that you’re not actually solving anything holistically and you’re not actually improving the way you do things. You are just solving one problem at a time. And so I think that it requires investment by and large and actually a new way of doing things and it requires the understanding that why you’re investing in that new technology and why you’re investing in that new platform, you will get wins out of just incremental small things. There’s a famous paper – one of my favorites from Google that said that for Google, it’s all about roof shots not moon shots, the idea is you don’t get to the moon through one leaf, you get it by bouncing off a bunch of taller and taller roof.

So kind of that same image of, if you have a vision of doing 360 that’s a great vision to have. You need to bring in new technologies and need to bring in new things that will enable that. But at the same time you need to realize that if you have 15 channels, even just connecting two of them at the beginning and being able to do something across for example, one of our customers just utilizing email and Facebook together to understand those that unsubscribe being able to target them on Facebook or vice versa those that are actually active, email viewers and readers, the active email readers.

There’s no need to waste the money on them on Facebook, just that two channels thing, not to even mention the other 13 channels, already has a ton of value. And that’s kind of one of the things that we’ve seen those incremental leaps going from not expecting you to make that jump immediately.

OC:

Managing risk in innovation, Martin, Amazon is a hot topic of course, is it an enemy or is it friend or frenemy into the destroyer co-brands and as we look at Cowen and Company’s proprietary tracker like 80% of America is Amazon, over 50 million prime customers. So how does ActionIQ fit unless it’s a profound topic for all of retail?

MC:

Perhaps the best color that I can bring to, this is my experience with Amazon. So we partnered a lot with Amazon, routing my company over the last 10 years, and something I thought like really remarkable about Amazon and how tremendously data driven they are. Like the problem of like extracting insights from large amounts of data, they treat it as a first-class problem and let’s cuts across the entire organization.

For example, do you guys know what AWS is, they’re large cloud, they watch every workload, they know every startup that’s using it, they know what applications are run. And then they’ll decide as a result of that how to do capacity provisioning or what new services to offer. And of course, they do the same thing on the digital side. And so I think that’s something that Amazon has become very good at in which is why they’re so good across verticals, right, not just retail, but IT and media is because they’re taking this data-driven approach and what they’ve brought to bear on the problem is the last 10 years of technology innovation in the realm of understanding data.

So I do think what ActionIQ does, is it democratizes this ability to take in large amounts of information about customers extracting insights that are meaningful for the business. I think this can be directly applied to retail, to media and to a number of domains.

OC:

And Nitay, I am a huge believer in personally and professionally about what ActionIQ is doing, but there’s competition such as Adobe and Salesforce. Trying to solve similar problems, what do you think you’ll do in the long-term and how are you different?

NJ:

Adobe and Salesforce, are great companies but at the same time, they very much grew up before the kind of big data age and that means a few things. First, there’s no – I’ve yet to see anyone of them honestly be able to scale through level of personalizing the humanity of data that you talk about. They really are based off more than kind of age, gender demographics that kind of thing. Secondly, there’s kind of a natural vendor lock-in that they aspire for right by the very nature of their business. There’s Adobe Cloud, there is a Salesforce cloud and so on. And one of the realities that we’ve seen come about especially with some of our customers is actually the truth of the future is that every customer is going to be in a multi-cloud world, right.

And we honestly, I don’t know the single company that we’ve worked with that says. we’re just an Adobe shop and that’s it. We love Adobe, we use Adobe everywhere and we’re happy with that. More often than not at some of our companies literally have every single one under the sun, right, they have Adobe here, their response is there, they have Salesforce here and so on. And so more often than not what you need is actually some of the understand things across all of those.

And the last point kind of about the data DNA is, those guys because of kind of again the time that they grew up in, they very much expect you to sort of think channel down. What I mean by that is you want to do some retention email targeting or some discount promotion. You think, okay, I want to – I’m going to start from my email, hey, let me build my email. And then finally, at the end, you actually come up with who’s my target that I’m going to build that for.

The reality is that’s actually very much backwards from how humans actually want to think about it. And this is one of the things that came out of our – one of our customer engagements was that the Head of Marketing there said. Finally, I can actually think bottoms up. What bottoms up is, let me think of my strategy, great.

Here’s what I want to do? Here’s the rough kind of makeup of people that I want to target this to, now for some of these people email might be best. For others Facebook might be best, for others an engagement through the mobile app might be the best way. Adobe just wasn’t built with that mindset in mind of that kind of bottoms up start with the data, start with understanding your customers, your people. And then going in and targeting them with whichever channel maybe.

OC:

Thank you. The last question we’re asking everybody here is what is experiential retail mean to you? How will that evolve and your views, are the sector or particularly your product? Both of your views would be great.

NJ:

There’s a new generation that is expecting a much richer, much more personal touch, so to speak, both physically and personally in a store, but also online. And online that kind of came out again because of the Amazons and Netflix where they have that data first approach, but I think people are coming to expect that even in the real world. When they go into a store that they get that kind of personal feel, they walk into a store. They open up their apps. They have your beacons in the store or whatever it is, that already know who they are. Already direct them to where they want to go. Already know that they are trying to come in return an item or use a discount or whatever it is.

So I think that kind of behavior and that kind of understanding of customers is the thing that’s really going to win. And that could be again, very hard to execute on. But it’s a kind of thing that requires both the offline and online coming together under holistic approach and often requires again some top down. They will shift things, we’re going to put the customer first, what is that mean for our stores, what is that mean for our online, what is that mean for our app. How do those actually come together? That again all comes from the question of let’s understand our users, let’s understand the data, let’s understand how we utilize that to drive all those different channels and together as opposed to treating them as different things that’s happens to interact with a customer here or there and giving this kind of disparate, almost different brands experience.

OC:

Yes. The integrated contextualized view and it show them the power to make that customer experience real.

Thank you, Nitay and Martin. Thanks for your time.

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