History Repeated? – Part 2
Conversion Economics
In the world of performance-based advertising, the price per action correlates directly with quality. The higher the quality, the greater the payout. Let’s look at two examples, one from the lead generation world and one from the subscription world. In the lead generation space, e.g., auto insurance, the data purchased by a lead buyer has no real value to them. It only matters if the leads turn into policies. The greater the lead to policy ratio, the greater the value the buyer can and will pay for that lead. In the subscription world, the signup has some value, for users must enter valid credit card data, but more often than not, the advertiser must pay an initial bounty that exceeds what they earn from that initial charge. The longer the average user stays subscribed, the more the advertiser can afford to pay.
We can now at two examples from the subscription world that appeared as choices for the user wanting to earn their Lunch money – Netflix, which requires a credit card, and IQ Challenge, which requires a mobile subcriptions. Netflix pays the user 15mm L$. (As an aside, that L$ doesn’t have a corollary with real dollars is very wise.) That price is after the payment platform makes its money. In the default situation, this means a 50/50 split between the app owner and offer platform. Assuming that to be the case with Lunch Money apps, the rate to the platform is 30mm. But, what is 30mm L$ in actual dollars. One way to figure it out is to use the hard currency L$ ratio for a clue – $9.99 for 100mm L$. That implies the Netflix offer has a value of roughly 1/3 or $3.00. As a user, you’d be much better off paying $9.99 for 100mm L$ than converting on Netflix for 15mm where you will receive a charge of at least 9.95 on your credit card. The challenge with this math is that the dollar/point ratio doesn’t always give us a good sense for the actual economics. If anything it shows us the propensity for users to select an offer over paying hard dollars. If the system were truly aligned (ad dollars and offer dollars), the user would probably receive at least 100mm because Netflix pays Offerpal at least $20 for that user. At $20, the publisher receives $10, with $10 being roughly equal to 100mm L$ according to the exchange rate. Right now, though, users don’t understand the offer economics the way someone in the performance marketing space would, so they wouldn’t naturally look to question the point spread.
The second example, mobile subscription offer IQ Challenge, pays 7mm L$. By knowing the market rates, we can back into a dollar per point value. In the affiliate space, this offer would pay between $6 and $10. Given this is incentive traffic we will assume the low end, $6 of which the publisher would see $3. The publisher received $3 and the user earns 7mm, showing an exchange rate of just greater than 2 to 1. It is still not commiserate with the 10 to 1 ratio when directly purchasing L$. But, it is enlightening when we use this price point to try and estimate what Netflix might pay. If the mobile offer pays $6 for for 7mm to the user, then Netflix could pay as little as $13 for 15mm to the user. The wrinkle in the analysis is that many of the offers do not come direct from the advertiser.
Traffic Blend
Despite their growth, the jury is still out on the offer platform companies’ traffic quality. We know that they are better than the free iPod offers, but we don’t know how much better. Is it Scenario A, where they are closer to the incentive promotion space or Scenario B where they are either somewhere in between true intent (search) or even closer to true intent than they are incentive promotion?
The jury is still out because not surprisingly, the results seem to differ by advertiser. Making it harder, not all advertisers who receive traffic from the platforms realize that they do. This does not mean deliberate deceit, especially on the part of the offer platforms. But, it doesn’t imply complete ignorance either. The CPA Networks that supply them the offers also don’t yet know the traffic quality, so they hedge their bets. They make sure that the traffic from the "apps" (both the applications and the alternative payment platforms) doesn’t comprise too great a percentage of the total traffic to a given advertiser. That way if the traffic isn’t as good as they estimate, it won’t hurt their relationship with the advertiser. A second reason for blending is that they know many of their advertises wouldn’t necessarily give permission to run their ads on the apps, so the cpa networks take the ask forgiveness route rather than permission route. While it might seem better to operate on full transparency, there are some quirks which prevent a fully transparent system from being the best solution.
When we say the platforms aren’t completely ignorant, it is because they know they have more traffic for a given advertiser/campaign than a given cpa network gives them. As a result for some campaigns, they end up getting it from multiple providers. Unlike Trialpay, who largely doesn’t play in the app space, those in the app space still rely on third-party providers for many of the ads. That is to say that while they do have direct relationships, it’s not unrealistic to assume that more than 50% of their revenue still comes from third-party providers (cpa networks). Complicating matters further, the platforms might have Netflix (as an example) direct but also run it from a third-party company. This happens all too commonly in the performance marketing world where one company has a lower limit than what they can deliver and another a greater. Plenty of offline parallels exist for that, but whether it is a good or sustainable practice online remains to be seen.
Standing Hypothesis
First, the bad news. Pricing will probably go down. The "app" ecosystem makes more than it probably should on per unit basis. The good news is that the traffic quality in my opinion more closely resembles Scenario B than Scenario A. In other words, I do not foresee the impending doom of Facebook apps or the companies that help them monetize the traffic. The not so eloquent answer as to why they won’t die comes from the world the world they mirror at some level – the good ol’ incentive promotion space. It is an industry that just won’t die, and it continues to morph as the audience and traffic sources change. If it can survive, how is it that the offer platforms, with their much higher intent, would not? More specifically, here are two other reasons:
- One to one – while users are still participating in offers in order to earn soft-money, which by its definition is not only incentivized but also lower intent than a consumer choosing to seek out the service, there is a big difference between how users engage with these offers versus those that are part of the free iPod offers. Users engaging in the app process pick a specific offer from a list of offers. While still somewhat limited, it is still a choice. In addition, users aren’t being asked to jump through major hoops. Contrast that with the free ipod approach where much of the disconnect comes from users being funneled through a flow in which they see more than a hundred opt-ins, none of which actually help them achieve their end goal. Plus, once they finally get to the final page, instead of being a simple process, it is quite cumbersome (number of offers, additional people, etc.) and designed for breakage. They make more if you don’t finish; not so with the offer platforms. They only make money if you do complete it.
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Accountability – in the incentive promotion space, users enter skeptically and/or with false expectations. Additionally, the incentive promotion path doesn’t have a connection nor does it really try to build a connection with its users. The exact opposite is the case in the app environment. The user has a vested interest in the app. It is tied to their personality, their profile. The action that they take or don’t take reflects directly on them. Want to cheat the system? You will get caught. But, that is not always a strong deterrent because people don’t realize that. So, the offer platforms have become very explicit and obvious regarding the requirements for credit. Take Netflix for example, "Purchase required to receive L$ within minutes. L$ awarded upon registration for home DVD delivery. New members must order and receive initial movie order or L$ will be reversed." Very clear. So too is the one for Zone Alarm, "Purchase required to receive L$ within minutes. L$ awarded when you buy now." Perhaps my favorite are seeing the incentive promotion guys’ language, "Free! No purchase required to receive L$ within an hour. L$ awarded after submission of a valid email address, personal information, and navigation to the final offers page where you must click on an offer." Good luck. Where things get tricky is with lead generation (my area of specific focus). Here, the users have a better chance at gaming the system, and it partially explains why few true lead generation offers exist. The one from above, has the following disclaimer, "Free! No purchase required to receive L$ within minutes. L$ awarded upon Complete insurance quote request. Fraudulent information will lead to expulsion from application." But, no matter how strict the language, it doesn’t require much sophistication for valid look fraudulent data to be entered.
Saving Grace
Whether the current model employed by the alternative payment platforms stays this course almost doesn’t matter. At some point, it’s expected that users should wise-up and realize that they can play better games for free elsewhere. Not all will, but the enthusiasm and take rates we see now won’t hold. But again, that won’t impact the longevity or long-run success of these payment platforms. App developers can assist for the better by not being greedy and create balance between what they ask users to do with what the users get in return. One could argue that users must do a little too much, and that relatively speaking, they get so little in return. Two higher value offers would get them a full game on XBox 360, but luckily for this ecosystem, users aren’t rational and thinking about alternatives.
Ultimately, the platforms have an incredibly valuable asset that assures them a role in the barely developed world of social media monetization – access. They own prime real estate, and if there is one thing that the ad networks have shown, it truly is location, location, location. It is why an ad network with poor tech but great inventory will outperform one with amazing optimization but lesser traffic. Whether they intended to be or not, as opposed to the banner ad networks that work with app publishers, the offer platforms are the real gate keepers, and they can transform themselves much the way the old incentive guys have as the traffic and advertise base changes. And luckily for the platforms, they will have no shortage of mediums with which to play – social media, iPhone today, game consoles tomorrow. While intent may still always be questioned, their relevancy will not be.
