Ad Ops is constantly evolving”the industry isn't what it was a year or even two years ago. Big data is a large driver of this evolution with its increasingly important role in the latest technologies available. Ad ops professionals are now responsible for overseeing data and providing insight into measuring ad effectiveness and recommending strategies for ad optimizations. Data has become vital to Ad Ops.
The power of analytics enables us to make smart business decisions, have far more efficient operations, and see happy publishers. In this webinar, Lila Hunt, Head of Publishing Solutions at Sortable and James Murphy, VP of Monetization at TextNow discuss why using deeper analytics is critical to maximizing earnings, which metrics to watch and why, and looking at real examples.
If you're interested in learning about Sortable Analytics or any slides in this presentation, please contact us at Sortable.
Craig Ling: Hey everybody, thanks for attending. We're just going to give people a few more minutes to join and then we'll start webinar.
Craig Ling: [00:02:06] Okay, hello everybody, and welcome to today's webinar on analytics and day-to-day ad ops. My name is Craig Ling, and I'll be your moderator. I work on the marketing team here at Sortable, and I'm really excited to be hosting a session today. Co-moderating will be Jaime Murphy, VP of product here at Sortable. I'm pleased to introduce today's speakers, Lila Hunt, head of publishing solutions here at Sortable, and James Murphy, senior vice president of monetization at TextNow. Lila has almost a decade of senior technical experience in the ad ops industry, and is often a guest speaker at conferences and sits on many PreBid.org committees, helping to shape and guide the future of the tech ecosystem. James' entire career has centered around digital media, having worked in sales, operations, and tech-focused roles. James has over a decade of industry knowledge and is currently responsible for all advertising for TextNow's properties. We are so honored to have James participate and share his knowledge with us today.
Craig Ling: Before I hand the mic over to Lila, I have a few housekeeping items to cover about this presentation. First, we will be recording today's webinar, and everyone registered will receive an email within a few days with a link to the recorded version. We'd love to hear from you during this webinar. If you have any questions for our speakers, please feel free to send it through the question tab in the webinar software, and we will try to answer as many questions as possible at the end of the presentation. So, without further ado, I'd like to kick things off by welcoming our head of publisher solutions, Lila. Lila, over to you.
Lila Hunt: [00:04:01] Thanks Craig, and thanks very much James for joining us today. I'm going to start off by talking a little bit about who we are at Sortable and what we do. So, we serve a global portfolio of publishers which represents over 20 billion monthly ad requests across more than 300 customers. We're primarily a tech company headquartered in Kitchener-Waterloo, Canada. We often describe ourselves as the Silicon Valley of the north. It's a tech hub with some of the world's best engineering talent. 70% of our employees are technical and focus on using technology to solve our industry's greatest challenges. We find this approach really helps our publishers focus on their business, creating content and driving growth through user retention and by acquiring new audiences.
Lila Hunt: So, just a little bit about our product suite. One of the common themes our publishers often share with us about what we do is they say Sortable does a lot, and that's very true because we started as publishers ourselves. We grew really frustrated by the obstacles and monetizing our own websites. Some of the challenges included lack of transparency into how advertisers who were spending on our sites, and the convolution of technologies that were required to monetize a digital business. We started building tools to solve these challenges for ourselves, and then we began sharing our platform with peers in the industry who were voicing similar frustrations. Today, we help publishers with monetization through managed solutions that execute optimizations across their businesses, and we offer server- and client-side header bidding and fully transparent analytics platform. We also work to bring ad services for fraud, discrepancy, malicious ad monitoring into a single platform.
Lila Hunt: TextNow and Sortable partnered last year, and so I'm going to pass it over to James so he can tell us a bit about his business.
James Murphy: Thanks, Lila. It's nice to chat with all of you today. So here at TextNow, we're a ten year old company, also based in the Waterloo, Canada area. Our free calling and texting app is the leading app in that category in the United States. On the Android platform, we're a top 5 utility app. On the iOS platform, we're a top 20 social networking app. So for that part of our business, we really focus obviously on monetizing our free customers through advertising and in-app purchases. We also have a fully-built out wireless business, and we act as a telco, offering unlimited LTE plans, texting and calling plans, and competing with the MetroPCS's or Boost Mobiles of the world. What we're working on this year is having those two businesses converge, so looking at offering our customers free calling and texting not only when they're on a wifi connection, but also through cellular data. So look out for more updates from us in that category moving forward.
James Murphy: You can see the metrics here, but we're a sizable app across kind of all of our properties, Android, iOS, and desktop. We have about 6 billion monthly ad impressions. Our monthly active users are about 20 million, and our daily actives are 2.5 million. We'll continue to focus obviously on growing our user base. We've benefited from really having a lot of our users coming to us organically. What differentiates us on the free side of our business is we always give our users a dedicated phone number. We're always free calling and texting as long as you're on a wifi connection, which is a differentiator to our competitive set, which you have to earn calling points or obviously pay for that. So that's our business in a nutshell; if you could go to the next slide...
Lila Hunt: Sure. So last year we also did a case study, and this is available on Sortable's website if anybody is interested in digging into the more broader content of the case study. James, could you share some of what your challenges were before you partnered with us, and what were some of the results once you transitioned to our platform?
James Murphy: Sure. Yeah, so working on the desktop side of things, we had a lot of challenges as far as optimizing and maximizing revenue, specifically with the larger partners like Google, and looking at ways to really offer the most viewable inventory, and that's obviously very important from a monetization standpoint. And sort of what really helped us by iterating on the things we were doing in those categories and really looking at things to offer more ad requests when we have viewable inventory, which would translate obviously to the higher CPMs, more fill and overall more revenue for our companies. So we've seen a lot of success.
James Murphy: We've moved pretty much all of our desktop inventory over to Sortable. The logic that they have and the algorithms as far as maximizing the things I mentioned and passing on viewable inventory and looking at the most optimal refresh rates going through the larger partners, we've seen a ton of success. So, moving forward, we're going to be working with Sortable to monetize more of our in-app inventory where we have a bigger opportunity, being a utility for texting and calling there. So given that we've seen so much success on the desktop side, and the algorithms and logic that's within the platforms that they manage, we're very optimistic that we're going to see very positive results expanding into the in-app space.
Lila Hunt: Thanks, James. I think another really important thing to focus on is, I mean nobody doubts desktops is hard; app is so much harder to build for because of challenges with SDKs and app weight and app speed, and so that's where I'm really excited about our opportunity to work together to build really groundbreaking solutions for the industry in that space.
James Murphy: Exactly.
Lila Hunt: All right. The focus of our webinar today is on how James and I work through, on a regular basis, using analytics and data from our platform to really monitor trends, talk about performance, and look at opportunities to optimize their business. The place where I thought it made most sense to start would be at the beginning, which is monitoring top-line goals. Here you can see a chart that is just basic revenue CPM and impressions by day, day over day, and we chose Q4 into Q1 as a visual. And then you can see that infamous drop on January 1st when the advertiser's budgets reset.
Lila Hunt: James, would you describe how you measure your business, and how do you know you're on track with your goals?
James Murphy: The key metric that we look at is really the ARPU (Average Revenue Per User), the average revenue per user, so given that text now, we control a user base. People come to us for the product that we offer and the service that we provide around texting and calling, so given that we control users, we look at a user level, so we're not looking at monetizing our website or app, it's really at the specific user level and how do we maximize efforts at that user level. Given that we have the ability to monetize those users through advertising, we also have options to push them over to in-app purposes, or obviously convert them to a wireless customer. So we're really looking at maximizing total revenue at the user level and obviously key metrics that are important to us also things like retention and making sure that the ad experience isn't too intrusive that we make our users leave. That's really the key metric that we look at, and everything's centered around ARPU or [inaudible 00:12:15].
Lila Hunt: Very interesting. The next slide focuses on taking some of those top-line KPIs and looking at benchmarking through seasons or across different events. Here we surfaced sessions and session RPM, and it would make sense because you guys have a utility service that session volumes look really consistent through Q4 into January, and you can see how session RPM has changed with the change in the demand landscape. I like focusing on session RPM because it helps us understand that value of a user's journey and I think it complements what you're describing with understanding the revenue per user that you're looking at from your business.
Lila Hunt: Can you talk a little bit about what session value means to your business. I know you started talking about retention and maybe you can get in a little bit more about how you allocate inventory for marketing and how you really drive to convert and measure those users.
James Murphy: Yeah, of course. Obviously, there's seasonality that affects any business, and obviously Q4 is much bigger than Q1. The luxury that we have, given that we have obviously a product where we offer free texting and calling, and we have a way to upgrade those users to a paid wireless customer or subscriber.
James Murphy: When there's less demand in Q1, we'll allocate more of our inventory towards internal products and services to drive up the value of the inventory that we're offering in the open market. If you have the same amount of inventory available when demand's low, obviously that's going to yield lower CPMs, less fill. During times like that, we promote our own internal products more and we, obviously like I said, have fully built out LTE plans that we can offer users. We have texting and calling packages for as low as $9.99. By making less inventory available, and people want, obviously our user base performs well for certain brands and agencies, that'll drive up CPMs in times when demand's lower. So that's something we're always focused on, and speaking to the [inaudible 00:14:49] side of things, given that we're a utility for texting and calling, if you make the ad experience too intrusive, like I said, too many ads in places where people are texting, for example, it's going to cause lower session times and obviously hurt retention.
James Murphy: So probably even more important to us, believe it or not, than maximizing revenue is keeping our users happy and making sure we have high retention and highlight time value of our users. That's the whole business, right? When you're in a business like ours, if you're turning users and people are leaving at a high rate, you don't have a business, so the first metric we're always looking at is how do we retain our users, how do we make them happy, and then how do we make money off of them, whether it be through advertising, or like I said, we could promote obviously internal products and convert them to a subscriber-based plan.
Lila Hunt: Yeah, great. That makes a lot of sense. So how do you balance the value of the user through advertising compared to the value of the user through a subscription model?
James Murphy: It really goes back to that ARPU. What is our average revenue that we're earning through our advertising for a given user? We then have different offerings. It could be obviously converting them to a wireless customer where it could range anywhere from $9.99 a month for texting and calling to $39.99 for unlimited LTE. But then we have the ability for users to turn off advertising for $2.99, and that's something we look at based on your point, like how much money are we earning on average per user through ads, and does it makes sense to give them the ability to turn off ads for X price. It really just goes back to the economics of things. Again, if we're able to make a higher ARPU by giving the ability to turn off ads, that's great, and then they're happy and then we just obviously drive them to that in-app purchase funnel. As you can imagine, a lot of our revenue comes from advertising though on the free app side, but there's constant economics and metrics that we're look at in that regard.
Lila Hunt: Okay. On the next slide is where we start to dig into some of the dimensions more granularly. Generally, we work together on looking at trends and then identifying changes to those trends, and then digging into where maybe those trends have room to optimize or where something has changed and why. In this chart, we're looking at really high level changes in fill rate. Fill generally helps us understand demand density, or if you have the right amount of supply based on the market or the right amount of inventory based on the market. I think that really aligns with what you were describing and understanding do we need more inventory because we have really great demand performance, or should we be spending some of that inventory on internal marketing. I think CPM is another metric that helps us articulate that inventory value as well so we can track CPMs over time and understand again how that's impacting session RPMs and to tie back to your ARPU metric.
Lila Hunt: Talk to us a little bit about inventory scarcity and how you manage inventory based on changes to the demand density like we see at the beginning of Q1.
James Murphy: I think that's a common mistake a lot of publishers make. It's always more equals more, right? The more inventory I make available, the better chance I have to monetize it even though fill might be less. But in our opinion, that couldn't be further from the truth. What Sortable's helped us do, which has been great, is when we have high value inventory, like when it's viewable, for example, at a high percentage, you make more of that inventory available, even when there's less demand. People always want inventory, especially on desktop, that's a viewability rate over 70% for example. For less desired inventory types or formats, we have the luxury to promote, like I said, internal products and so forth.
James Murphy: I think it's just a common mistake that we see, and I'm from the platform side of the business. Now being on the publisher side, I understand that we see what it looks like to be at the edge, but I also understand what it looks like to be at intermediary level. It's a common mistake that you see in the industry; just make more available, flood the market with more of your inventory, and we have a better chance of monetizing it, but what's happening at the buyer side, or the DSP side, is they're just going to start randomly hunting more of your requests because they see so much of it. You want to make sure that you're maximizing your efforts around the inventory that the demand side actually wants. Obviously change the structure of things if it's not desired at all, or when demand's lower, like I said, promote internal products. Or even, when you don't have that luxury as a publisher, just don't make that inventory available because you'll drive higher CPMs and more fill from inventory that people actually want.
Lila Hunt: Exactly. An example that we implemented at the start of Q1 was we actually changed the refresh rates because we saw CPMs drop, and so we turned down the refresh rates, which helped encourage the CPMs to lift back up. What we saw was a more aggressive recovery, I think, than normal because there wasn't this, like you said, flood of inventory based off how much demand was actually available at that time. Then once the budget started to come back in, that CPM stayed high and we were able to increase revenue and maintain that upward performance.
Lila Hunt: I know [crosstalk 00:21:14]. I know platform's also really important dimension for you because you run app and also a web app. Talk to us a little bit about the trends you observe on different platforms.
James Murphy: It's very different. The Android versus iOS, even on the app side, it's a different mix of users. People on the iOS platforms tend to have newer iPhones; it's a different demographic than you see on Android platform. For example, obviously you see different behavior as a result. So it's really looking at all different metrics. We have internal AB frameworks where we can test all these different things, even specific within one platform like the Android platform. Certain devices and how they perform from a monetization standpoint. We're constantly looking at these things. Both of those users that then could use either our desktop application or browser based service, so then we have the ability to look at those metrics as those people visit on the desktop side. You really have to look at just going back to your business at a user level.
James Murphy: Given that we offer products where we give people a free utility, we get a lot of information about those users so we know, in many cases, age and gender. We can infer things like ethnicity because we have a lot of content around texting. We could obviously look at the behaviors based on that, and then make deterministic decisions on how to monetize these people better, how to make that inventory of a higher value to the demand side. We're constantly looking at these things, and it's a very a tech-driven business., getting deterministic data to make decisions and not just doing on a hunch or feel, if you will.
Lila Hunt: Great. There's a few questions that are coming in about the inventory optimizations, actually that segues really well into the next slide, which is specifically on optimizing inventory. I'll try and maybe touch on those questions a little bit as we go through here. Essentially, philosophically at Sortable we believe that machines really should do a lot of the heavy lifting when it comes to granular optimizations. There are things that we work on together that have to do with more manual implementations, changes to sizes, formats, ad units, and refresh rates. We typically look at by different dimensions and then make decisions about how to set them for the site or against different sections of inventory. Then there are facets that are better left to machines at a really granular impression-level decision, and that's where flooring and timeouts generally happen in our platform informed by statistical modeling per impression. For the higher level metrics that we look at, we can look out performance against the dimensions and then make recommendations, and then A/B test different configurations to understand where performance really is better.
Lila Hunt: One of the questions that's come up so far is what kind of analysis goes into matching of inventory to market demand, and how do you know when more inventory is overall harmful. I think really once CPMs come down really aggressively, that's where I would say there's a red flag on both our sides. Would you be able to comment a little bit on...I guess maybe a little more elaborate on streamlining these optimizations and how we make decisions together about when that performance is critical to react-to.
James Murphy: Sure. There's constant optimizations that you do obviously around the things you see here. We talked about the device side, or around sizes, we're constantly looking at do we have the right mix in front of our users? Are those formats viewable? All these things that matter. What we love about Sortable is the transparency and the communication we have all the way down to the actual buyers and understanding what they want, in a feedback loop from one edge to the other is how we like to say it, us being on one side as the publisher and Sortable representing the demand side with full transparency and visibility to what they actually want and giving us that feedback to say, hey, these units have a higher demand density; we should run more of those. Or, you have these ad units we can make available, for example. Making refresh rates around refresh rates that people care about, not just doing it in a kind of random way; let's have a higher refresh rate because it creates more ad inventory. No, let's make a higher refresh rate when those ads are viewable, and make that available to the demand side. That's constantly things that we're looking at, and we continue to iterate in that regard, and obviously timeouts and setting floor pricing is a natural thing to find that right mix of the pricing that people are going to buy at based on the things they want to buy, right?
Lila Hunt: Right. In addition to our algorithmic flooring, you also do use manual minimum floors to help control how inventory gets exposed to buyers. Can you describe a little bit how you use minimum floors?
James Murphy: Like I talked about earlier, we have our own internal products and services, i.e. our wireless business that we're saying below X price for this format, for this geo, for this portion of our app or this screen on desktop, we're going to make this the floor based on data that we have with seasonality and all the different metrics we look at like I talked about earlier. We have that luxury to say, okay, if we can't monetize about X price for the different matrix of things that I mentioned, we're going to run our own internal promotions.
Lila Hunt: All right. If we go to the next slide, we have an example here that we're currently working on; we haven't finished implementing this, but we cooked it up together. Here you can see we've got really obvious higher CPM on the 300 by 600, which makes sense because it's a large format unit. Even though the 300 by 250s have lower CPMs, we're look at potentially breaking up the 300 by 600 into two 300 by 250s, and again we can look at A/B testing this to see which configuration actually drives more revenue and more demand density. This is an area where a 300 by 250 may...there may just be more campaigns available, so there could be stronger fill; there could be maybe not necessarily stronger CPMs, but more top-line revenue.
Lila Hunt: I think that's an example of how we look at demand density. We may look at participation rate as well from different bidders on those units to see how they're performing. Do you have anything to add about format sizes and testing different ad layouts?
James Murphy: No, this is a great example. We're looking at exactly that. The relationship between CPM and fill, obviously equates to the revenue that we're going to earn. So how do we maximize these things? You mentioned that we see units, you're going to have higher CPMs, most likely less fill, so what's that rate balance? I think that's what Sortable provides. They give us a kind of outlook on that. Like you mentioned, Lila, through A/B testing and understanding, great, of course we want the highest CPMs, but we also want to monetize more of our inventory, so what do the actual buyers want? We want to fill our inventory at the highest rate, but they're going to fill more at X rate, so should we focus more of our efforts there? It's really about that balance; it's not one extreme versus the other. It's finding that right mix or right recipe, if you will.
Lila Hunt: Right. That's a great segue into the next section of the webinar. We have done a lot of work after we partnered through the end of the year into Q1 to really get the inventory optimized and performing well, and now we're looking at ways to, again, influence the demand landscape. I think, to start the conversation off with respect to demand, I wanted to look at transparency because it's a huge theme in our industry. It's a really, really often used buzzword by a lot of different types of companies. Everyone wants it. Many claim that they're transparent, but what does that really mean?
Lila Hunt: Would you be able to talk about what transparency means to you and why it's important when you're looking at demand?
James Murphy: Yes, of course. It's extremely important, and the two key things that we look at around transparency is, first and foremost, the fee structure. What we've learned, myself coming from the platform side, is, even though your rev share may be 85-15 or 80-20, whatever, what they give in exchange, what is that based off of? What is revenue, and how is it defined? We, first and foremost, get clear definition around what gross revenue means and have a rev share based off of that that we both agree on, and then really around the demand base. Who's monetizing our inventory? Gone are the days where it's a black box of this exchange and we don't know what's behind it. We obviously mandate that we get full transparency in the demand mix, meaning the DSPs behind the exchange and even further beyond that, the actual agencies and brands. What we love about Sortable is they provide that whole chain. You hear the big buzzword about SPO and how do we maximize our efforts on the supply side and so forth, but it's okay obviously working with all the different players in the industry, but we need that transparency. As long as you have, going from our edge being the publisher, all the way to the demand side, and knowing what fees are being taken in the middle and who's actually monetizing our inventory, that's what we're comfortable with and that's what we mandate. To us, that's what transparency means.
Lila Hunt: Yep, beautiful. We definitely are huge advocates of transparency. I think one of the things we believe really strongly in here is that log-level data is really important to figuring out different pieces of the puzzle of how dollars are flowing, and that's one of the services we provide is we make log-level data accessible and easy for publishers to access.
Lila Hunt: I think the other thing that often comes up with respect to demand and the demand landscape are market fluctuations. CPMs change, and it's often really hard to explain why, especially if there hasn't been changes on the publisher side in terms of inventory or user base or general products for their users. This graph is looking at the exchanges and how they're bidding based off of viewability. Viewabilities are really important metri