The new restriction of Apple’s device IDFA for iOS 14 to increase consumer privacy adds another hurdle in how the advertising industry interacts with users.

While the industry seems to be in a bit of an uproar about Apple’s announcement about its privacy initiatives at their Worldwide Developers Conference (WWDC) this week, I can say with great confidence it comes as little surprise to Kochava. Apple’s news of restricting the availability of the IDFA—the industry’s longtime device identifier for advertisers on iOS—forcing them and related adtech companies to rethink how they measure campaigns and understand user behavior is one of many industry pivots we have seen since the beginning of this year. Apple will now require publishers, advertisers, and related entities to request user permission to track them, among other privacy initiatives protecting consumer data and identity.

We are an ecosystem in transition but fully prepared to work diligently through the changes as we continue to put the privacy of user data at the forefront. As a leading attribution provider and long-standing partner with Apple, our mission aligns with theirs.

Let’s recap what we know from the recent news:

In addition to the opt-in prompt for IDFA access, Apple intends to use the SKAdNetwork to inform advertisers about attribution on ads displayed on iOS devices for those publishers that are registered with SKAdNetwork. Marketers will know an install occurred, but they won’t be able to connect a specific install with a specific device, thus preserving privacy. Because the SKAdNetwork was just formally referenced this week, there is no available inventory that is SKAdNetwork ‘ready’ and it’s unclear what will be available and when.

Although this is a major change in an industry increasingly being forced to focus on consumer privacy, the release of Apple’s resettable IDFA and Limit Ad Tracking (LAT) in previous years hinted that it would further restrict outside parties from an addressable identifier for distinct devices.

The announcement comes amidst Google’s countdown to the end of the cookie, and the California Consumer Privacy Act (CCPA), so advertisers have already been inundated with major industry changes coming to the mainstream way of marketing, measuring, and retargeting. However, those of us looking ahead at the direction of the industry have been preparing to solve for consumer identity in the absence of traditional device identifiers. For some time now, we’ve been incorporating privacy by design and developing alternative but unique mechanisms for identity and providing tools for user consent.

How do we see the future?

Kochava is prepared to support the ecosystem through several ongoing innovations. These include providing identity solutions, enabling contextual targeting (where no stable identifiers are used cross-property), and through frameworks like SKAdNetwork and XCHNG. We are working closely with clients, partners, and the ecosystem at-large on several solutions that will allow our clients to have a competitive advantage.

A mosaic of solutions in the absence of the IDFA

In preparation for the end of the cookie and increased limitation of the IDFA, alternative consumer identity solutions are now more important than ever.

At Kochava, we read the writing on the wall several years ago and began compiling identity solutions that are not reliant on a platform-specific advertising ID. We knew that to perform more effective and reliable attribution and measurement and create a holistic view of the consumer journey, we needed to look beyond the reliance on an IDFA.

Several solutions already exist within Kochava to aid marketers in identifying consumers with the first-party data they have. With respect to the restriction of the IDFA, here is a list of available solutions to maintain consumer privacy and in some cases enhance understanding of audiences.

Identity Solutions

Kochava’s Identity Solutions help brands connect consumer touchpoints in the absence of device IDs using other user identifiers such as hashed emails to enrich a marketer’s existing dataset with validated first-party data. Through Kochava’s IdentityLink®, marketers can further enrich their first-party data and have a greater understanding of their users with their own identifiers.

Options exist to perform identity resolution using hashed-email-to-device linkages, device connections by household, and other first-party identifiers key in solving for identity resolution and attribution. This is valuable to marketers, publishers, and ecosystem partners and we have tools prepared to enable the ecosystem to leverage their own 1st party data sets and resolve them in actionable ways.

If you’re managing a mobile app or property, you likely fit into one of these categories: 1) you are flying blind and not doing any promotion of your app, 2) you are buying media and flying blind—even worse because you’re spending money, 3) you’re buying media while using an attribution toolset that isn’t meeting your needs, or 4) you’re buying media while using an attribution toolset and feeling confident about how you’re attributing conversions to the right source.

Let’s review. In its most basic form, an attribution tool has two key objectives: to accurately give credit to the right source for a given action, and to record what happened so that there is an ability to audit it later.

Here’s the problem, as I’ve mentioned in previous posts:

• Not all attribution tools are created equal.
• Just because you’re using an attribution tool doesn’t mean that you’re accurately giving credit to the right source.

The reason for the above statement is multifaceted but essentially rests in the role of configurability in your attribution engine and the role of fraud. Every business has a different mix of media. The rules that determine credit need to be configurable, and Kochava has the greatest level of configurability on the market.

Now for the point of this post: Beyond attribution, the objective is to persist and maintain, as a system of record, the history of attribution.

Is your attribution tool persisting data? Do you know? Have you been told it’s only for 30 days “for privacy and regulatory reasons”? Or, is it for 90 days, and you’re told that the attribution tool has a postback engine so that you can store the attribution history yourself?

Let’s cut to the chase: Companies relying on the Kochava Unified Audience Platform enjoy 15 months of persistence out-of-the-box with the ability to extend longer as they desire. Here are four reasons why persistence is so critical:

1. Provide a system of record for attribution

As the system of record, an attribution tool must have long-term historical data to provide an independent record of transactions and attribution. Did one click come in before another? Were the attribution rules configured to provide credit for a particular partner because of a tight lookback window on a network or tracker? Did the postback signal get sent? Has a specific device already been attributed? For each of these questions, there must be a definitive answer. With Kochava, all of these transactions are recorded and persisted. Not providing long-term persistence is like using a bank that erases transactions beyond 30 days and says it’s up to you to keep your checkbook balanced. While balancing your checkbook is important, can you imagine being okay with a bank like that?

2. Avoid re-attribution

One of our competitors’ dirty secrets is that by having a short persistence history they can cut costs, and attribution for devices that have already been attributed become candidates for attribution again. This means that your media spend is likely higher than it needs to be simply because the vendor charges on a per attributed install basis and has a specific persistence policy that enables them to generate more revenue. We’ve done the analysis and up to 12% of devices would cross this chasm if they didn’t use Kochava.

3. Provide data replay to other ecosystem partners

Because Kochava holds record-level data across clicks, installs and postbacks sent to partners, it is very easy to re-send data programmatically to ecosystem partners if they missed signals or were unavailable for a given time band. A legitimate system of record should have these facilities because attribution is the centerpiece of the marketing equation.

4. Understand trends

By purging data at 30 or 90 days, one cannot fully understand trend data. Most trends are mapped by quarter or year-to-year. By providing 15 months out-of-the-box, Kochava customers can be confident in the ability to understand trends regardless of how the data is composed. Pro Tip: a chart showing “count of counts” does not represent long-term persistence. A “count of counts” is a rolled up or aggregated view of events or actions. Our competitors will often point to that and say, “we store data.” However, if you want to organize the data in any other way, you must retain the record-level data so you can build new aggregations or roll-ups as the business needs arise. One simply needs to look at our Funnel tool where marketers can selectively decide what user activity they want to depict and then can actually export device identifiers at each stage. This is out-of-the-box behavior for a tool that is properly supporting visualization of trend data.

Kochava has long been positioned as the most feature-rich attribution platform in the industry. Only the top marketers have historically selected Kochava to be their measurement tool of choice. Indeed, while other companies in attribution tout “market share dominance” because more apps have integrated their SDK, when you look at the apps that spend the most in ad spend, Kochava is the clear market leader.

In each of the four cases above, a marketer could cobble capabilities together by buying other tech and integrating those tools themselves. This increases cost of ownership, increases data debt organizationally and ultimately slows an org down—limiting their agility in making key decisions quickly. In reality, marketers who rely on Kochava for attribution see campaign lift, save money through fraud mitigation and deduped attribution and are increasingly able to get better value out of their media spend due in part to their access to historical, record-level data. No more flying blind. Our customers chart their own paths armed with clear data from the industry’s most configurable tools.

Regardless of where you are in building or promoting your mobile properties, I suggest you consider the importance of data persistence when you select an attribution toolset. While the Kochava Unified Audience Platform is certainly built for market leaders, Kochava offers Free App Analytics®, which provides a starter kit of attribution for emerging advertisers. If cost is your concern, you can start with Free App Analytics® and upgrade to the Unified Audience Platform when the time is right.

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About the Author

 

Last week I had the opportunity to share some perspective about how Cheap Attribution Tools Jeopardize Media Efficiency. The post proved timely as just last Friday AdExchanger published an article on how marketers are frustrated with our competitors lackluster offerings. While it was certainly provocative to those who are new to buying media at scale, it’s not new to marketers who really appreciate that a dollar spent in the right tool-set equates to thousands of dollars delivered in efficacy.

Each year, Kochava hosts the Kochava Mobile Summit. An intimate event that takes place at our HQ location of Sandpoint, Idaho, The Summit is filled with topics that are both strategic in nature and granular in tactical assessment. The top marketers in mobile are in attendance and because of our self-imposed attendee limits, it is incredibly potent. In addition to topics led by various customers, we have the opportunity to share our own observations about the industry, illustrating what we’re doing as a company for the coming year. It’s a bit of an “up-front” for measurement.

 

Kochava as the Bloomberg Terminal of Advertising

Since we started Kochava, the driving visual that I’ve used internally with our team, to illustrate what we want to become, is that of a next-generation “Bloomberg Terminal” for digital advertisers. The premise stems from the early days of Bloomberg where the company highlighted that this terminal was the difference maker for traders who were successful vs. those who were not. It was about speed, efficiency, and leveraging the right tools to make the right decisions on each buy and sell. Real-time data, visualization and integration with all trading desks were critical to success.

While the early versions of the Bloomberg Box lacked user experience, the notion was 100% correct, and it was the basis of Bloomberg’s success.

I regularly hear from our customers (marketers) that they have better insights on the audiences of their media sources than the publishers know themselves. These are the publishers own audiences—and the buyers know more than the sellers. This is where we came up with the mantra that Kochava delivers an unfair advantage.

While the Bloomberg vision has always been grand, our execution has been made up of incremental tactical steps leading to that objective. We started with core attribution. We progressed by providing the most configurable attribution in the market. We next provided enterprise analytics, then fraud monitoring and abatement. At the end of 2016, it was clear that calling our platform an “attribution product” was both inaccurate and disingenuous to the holistic offering we provide vs. other commodity single-use attribution tools. It is also the reason why new marketers will see such disparity between our platform (which is ROI based) and that of other attribution tools (which seem to be misaligned to the success of the customer).

Beyond providing additional tools to the marketer—we also added support for web measurement with unique capabilities enabling cross-media (web and mobile) and cross-device attribution and analytics. Marketers tell us they prefer our visualization, our attribution waterfall logic, and our configurability. They prefer our signaling capabilities, reporting capabilities, and APIs. For those reasons, they want to use Kochava as the system of record to unify it all on one platform.

 

The Unified Audience Platform

At the Summit, we announced the Unified Audience Platform which is a more accurate representation of what we’re doing in delivering the “Stack” for the marketer. Our platform incorporates all of the market-leading features of the Kochava attribution engine and gives credit to the platform for our support in the workflow of engaging with the stack. When we say workflow, we’re talking about what we call “The 5 Points of the Star” which are: Plan, Target, Activate, Measure, Optimize.

At the same time as we’re highlighting the Unified Audience Platform, Eric Seufert (Mobile Dev Memo) put together a great summary to help marketers appreciate that there are multiple ingredients for a user acquisition stack.

In his summary, he highlights that marketers need to understand the pieces and parts and discover the proper build/buy matrix for the components involved. The following is a graphic he put together, and it’s a great demonstration that we’re not alone in thinking of “full stack” solution capabilities vs. commodity attribution delivery.

 

For each part of the stack, I’ve linked how the Unified Audience Platform is a full implementation of it with flexible integration approaches enabling your own in-house toolset as needed (if you have them already). Further, I’ve outlined a technical Lego-block format of how our architecture uniquely positions Kochava as the standard for measurement.

• Front End Analysis: Kochava delivers flexible UI to render the Kochava Object Model (a real-time object model representing all Kochava data) in a meaningful way across our UI (e.g., App Overview, various analytics UI components). For custom visualizations, Kochava enables a no-limit, real-time API which is integrated with tools mentioned in the article.
• Business Intelligence and Data Warehousing: Kochava Analytics provides LTV, Cohorting and Media Cost aggregation embedded within the platform. In addition, Kochava Query provides SQL access to the Kochava Object Model. This approach provides row-level impression, click, install, and event data—for as long as you want.
• Campaign Optimization: The Kochava Optimization Beacon uses machine learning technology to auto-optimize media campaigns using the measurement signals managed by Kochava. The goal, assigned by the marketer, ranges from clicks, installs, engagement, or specific post-install events.
• Attribution/Fraud: We’re best known for our Configurable Attribution, and the Kochava Fraud abatement tools are second to none.
• Traffic Acquisition: With more than 3800+ ad network and media partner integrations—the Kochava Adapter framework integrates with any media source you want.

 

The following is a depiction of the Kochava Unified Audience Platform. It illustrates the transformation capabilities that we support (in real time) from data ingestion through configurable attribution to normalization and object model flexibility for visualization.

The beauty of Kochava and our enterprise-grade platform is that you don’t have to start with a cheap vendor first. You can start with Free App Analytics®. When you’re ready to upgrade, you don’t have to change your SDK. If you’re ready to leverage an enterprise platform today, jump right into the Unified Audience Platform, the measurement standard for marketers.

About the Author

Charles Manning is the founder and CEO of Kochava, the leading mobile attribution analytics platform serving tier-one advertisers worldwide. For nearly 20 years, he has been creating technologies that use data for system optimization, ranging from business service management (BSM) to information technology (IT) to attribution analytics. Charles began his career at Oracle and later held executive and C-Level positions at M-Code, Managed Objects, and PLAYXPERT.

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Our competitors, because of the absence of compelling measurement features and a full stack offering, are competing on price alone. They are unashamed in their attempt to commoditize their own business. They’ve raised large sums of money to subsidize the infrastructure cost, and they deliver a second-rate service all under the premise that the opportunity to win in the attribution game is a “land grab” to get developers to integrate their SDK. They augment this effort with a marketing message that attempts to pacify the industry with the belief that there are no special secrets behind attribution.

I disagree.

This trend started a couple years ago and really took shape in 2016. The reason? I believe it’s multi-faceted:

• Mobile is new
• Lots of new mobile-first marketers are coming online quickly
• Lots of traditional display marketers are crossing over to mobile quickly
• Measurement from display doesn’t work on mobile—mobile specific attribution tools are needed—which means the traditional tools selected by the group above don’t apply
• Few marketers have the budget to advertise at scale or they aren’t familiar with mature tools for mobile attribution and analytics
• Many marketers want to get started with something (anything) so they can learn

These factors have created a petri dish of chemistry in the market, enabling vendors with limited functionality to provide a cheap solution and find success along the way. If you look a bit deeper, there is a ceiling of capabilities that limit the marketer’s capacity to do what they were sold on in the first place—accurate media attribution and audience measurement.

The “New-to-Mobile” Dilemma

Every mobile marketer I know started by doing something other than mobile marketing. Everyone had to learn the dynamics of how mobile is unique, what the difference is between incent and non-incent traffic, the notion of re-brokering or the value of analysis by site or subsite identifier. The point is: There is an overwhelming amount of information a marketer new to the industry needs to learn and experience. They haven’t endured the pain and haven’t learned through maturity about what is needed to achieve success. Meanwhile, the marketers who have topped the charts over the last two years have perfected their craft, and they have maintained their position for a reason. What is a new marketer to do?

Everyone says that step 1 is finding an attribution partner. I agree—but the difference maker is in finding the right attribution partner.

For a new marketer, the qualifying questions to select an attribution partner are:

• Do the tools attribute by media source?
• Can I see a report?
• Does it work on the media sources I buy from?
• What does it cost/how is it priced?

These questions set a low bar and yet, you see how price wins out when the requirements are so limited.

For an increasingly progressive mobile marketer, the questions start to accumulate:

• Can I track post-install events? (needed to understand LTV)
• Revenue events? Ad revenue and in-app purchase revenue?
• Can I support re-engagement campaigns? (needed to understand how to re-activate dormant audiences)
• Can I ingest media cost data? (needed to understand ROI)
• Can I syndicate data to other tools? (needed to operationally manage campaigns at scale and understand patterns and relationships)

For every question, there is a pain associated with it. The customer (or their team) has experienced pain from lack of insight, understanding, and/or the ability to scale based on the absence of signals that matter to them.

Here is when feature comparison charts start to do a disservice to a new mobile marketer. For them, the desire is to have a clear-cut summary on what is important, what is not and then stack-rank on price. A typical feature comparison from any of our competitors attempts to include the above features in a limited capacity—and highlight that all vendors are generally comparable with price as the deciding factor. The reality is that these features are table stakes.

Of course, no one wants to spend more than they have to on anything (including measurement)! What is not clear to the new mobile marketer is that by stack-ranking on price, they are about to make the most costly mistake in their mobile marketing endeavor. Attribution and measurement costs pale in comparison to media costs when it is measured inaccurately or the system lacks key signals for measurement and optimization. Further, the lack of features for planning, targeting and activation limit the marketer in how they can scale their efforts.

Kochava provides the table stakes mentioned above—but also enables growth beyond the basics. The following are just a few examples:

• Traffic Verification is real-time verification that traffic meets the qualities and characteristics outlined by an IO. If you decide to pay a premium for iPhone 7+ devices, do you have a mechanism in your measurement tool to verify this in real-time and stop the attribution waterfall from triggering if all criteria isn’t met?
• Global Fraud Blocklist is real-time fraud monitoring and abatement to stop media fraud and potential attribution fraud. This blocklist is algorithmically maintained at a system-level across Kochava, observing patterns of fraudsters across accounts. When sites, device identifiers or IPs are used in fraudulent behavior, it is on the blocklist and your traffic is automatically pre-screened when using this capability. Do you have a real-time fraud abatement strategy across all of your media buys?
• Configurable Attribution are configurable lookback windows supported at the media source level with granular control of lookback settings by probabilistic attribution (see iOS 14+ restrictions) vs. device ID attribution—separately for view-through and click-through.
• Configurable attribution overrides further modifying lookback windows at the tracker level to separate incent vs. non-incent or to qualify higher-intent audiences with tighter attribution windows and larger payouts. The configurable attribution waterfall enables customers to change the way it works in Kochava for your conversion windows. It will match the intent of your IOs.
• Fractional attribution enables fractional credit to various assist/influencer clicks or views along the conversion funnel.

If confronted with all of the knobs and switches that any marketer should worry about having in their measurement tool—a new mobile marketer will think that the tool providing such capabilities is complicated and overly complex. Mobile is not a black box, and marketers must have key features to measure and control the signals of the user acquisition funnel in order to apply their media dollars efficiently. Without the right tools, the marketer is being penny-wise and pound foolish. Before you take my word for it, let me outline a few examples of what marketers confront on a daily basis when they don’t use Kochava tools:

• Organic users sniped by paid media sources. Marketers are paying media sources for users that were organically installing their app. In the world of mobile fraud, 50% of the fraud is related to media and 50% is related to attribution fraud where sub-publishers game the attribution tools to get credit for organic installs of their app. Was it worth paying $2 per install for 20K organic installs this month because you selected a cheap attribution tool?
• Quality media sources don’t receive credit for the traffic they drive. This de-prioritizes a marketer’s campaigns over others that use measurement tools with the ability to discern and optimize for the traffic most valuable to them. When your trusted sources deliver but aren’t attributed, you get less access to the traffic you seek to grow. Was it worth losing access to premium traffic (despite having the budget to spend on it) because you selected a cheap attribution tool?
• Composite media strategies (buying from various sources against the same audience to reach them at various times in the funnel) are not possible because you can’t measure or discern the signals and pay the right vendors for the value they are delivering in a multi-touch world. On average, Kochava marketers see over six touch points across different media sources prior to the last click. What’s the relationship between an influencer click vs. the last click? Is it worth not knowing and hoping for the best by selecting the cheap attribution tool?

Fee-Based Conflict of Interest

The cheap attribution tools out there charge on a per attributed install basis. This, at face value, appears as a good deal. It caters to the performance marketer in all of us. The vendor doesn’t get paid unless an attribution is made. We have heard these vendors evangelize that Kochava rips off customers because we charge for impressions, clicks and post-install events. In contrast, they claim to only charge per attribution so they are only being paid when they do their job. Here is the problem with that logic. They are essentially saying that:

• The signals in the funnel don’t matter
• The attribution is the chargeable event (at pennies, not fractions of a penny)
• They are motivated to make as many attributions as possible—irrespective of configurable rules that you may have in place in order to manage your media mix

The last point drives home the difference between Kochava and the competition. Wonder why these other cheaper vendors don’t give the kind of granular control over your media attribution logic? It’s because they don’t get paid. Wonder why they re-attribute previously attributed installs after their retention window (typically 90 days)? It’s because they get to charge for the attribution repeatedly.

The Industry is Maturing

This past week, MediaPost summarized a survey done by AdRoll based on a State of the Industry report. Of note in the survey, 60% of the respondents plan to change their attribution strategy in 2017 from a traditional first- or last-click model. The cheap attribution tools are not only ill-equipped to handle such a feature (Kochava is the only one that supports this today)—their business models are in direct opposition to the approach.

We are already seeing the maturation happen. It’s now a question of how quickly. In a recent post on LinkedIn by Kabeer Chaudhary, Director of M&C Saatchi Mobile APAC, he rebukes a vendor who has created a performance leaderboard by media source without taking into account the impact of fraud in the rankings. This is a distinction that Kochava makes for its customers. A leader of a major mobile agency actively highlighting this problem in public is a clear indication that the industry is undergoing change.

Avoiding/Reducing Switching Costs

Recently, as more marketers switch to Kochava from other vendors, we learned that one competing attribution tool charges a large fee to pull data out of the toolset to migrate to Kochava (a marketer would do this to avoid double attribution upon conversion to Kochava). To avoid churn, this vendor intentionally makes it difficult for customers to leave via limited tools and new surcharges. A marketer makes an investment when they wire their infrastructure around a measurement platform. How well do you trust a cheaper vendor who knows that they can make you dependent and holds you hostage if you want to leave?

This is the fundamental behavior of the companies who are, as a business strategy, raising money to subsidize the distribution of their SDK and actively convincing marketers to become dependent on their infrastructure only to change the total cost of ownership (TCO) equation over time.

Consider this when thinking about what provides real TCO vs cheap attribution at face-value.

1% Challenge: The Equation to Media Measurement Efficiency

We have been talking about our 1% challenge for the past several years but recently it has been receiving more attention. The reason is that enough marketers new to mobile have been using cheap attribution tools and are left wanting more. While they initially made the decision based on price, they now realize the TCO of measurement with a proper toolset.

The 1% challenge centers on the thesis that the Kochava service is effectively free if we can make a marketer’s ad budget at a minimum 1% more effective than before using our tools. This is because Kochava essentially costs 1% of a marketer’s media spend—but we charge based on the signals that we receive and the capabilities we enable for marketers. While we typically cost approximately 1%, we consistently see that Kochava delivers 5% to 7% or more in improved efficiency over other tools (and more when no tools were used at all). Delivering a return on investment (ROI) five times greater than Kochava cost in the first month isn’t bad either.

Selecting the Right Product to Support Growth

A marketer, by definition, is one part creative, one part analyst. If there is any person within an organization that should appreciate the value of ROI, it’s the buyer of an attribution tool! While this is true, one must recognize that the maturity of a growth team dictates the needs of the tools they use. For this reason, we have put together various packages that cater to marketers and upper management alike and meet them where they’re at in the maturity curve.

Marketers are not alone in having to select the right tool. Invariably, management or a CFO needs to sign-off on the prevailing toolset. It’s critical that marketers not only understand the power of selecting the right measurement tool—they must also articulate the ROI to the rest of the management team in the context of the economics against media spend.

If you are in a situation where you need to learn because you don’t know what you don’t know—I suggest you use our Free App Analytics®. Free App Analytics® is a limited feature version of Kochava that is available for free and was specifically created to help emerging marketers learn and upgrade at any time to either our Attribution Analytics package or our Unified Audience Platform (Enterprise Edition). By using Free App Analytics®, you can learn and avoid the pitfalls suffered by so many other marketers who selected the cheaper tools they ultimately had to move away from. You don’t have to believe the lie that cheap is your only option.

While Kochava provides the best ROI, I invite you to test our tools and learn what you need with Free App Analytics®.

About the Author

Charles Manning is the founder and CEO of Kochava, the leading mobile attribution analytics platform serving tier-one advertisers worldwide. For nearly 20 years, he has been creating technologies that use data for system optimization, ranging from business service management (BSM) to information technology (IT) to attribution analytics. Charles began his career at Oracle and later held executive and C-Level positions at M-Code, Managed Objects, and PLAYXPERT.