Quick response (QR) codes are just that – quick and responsive. Anyone with a smartphone can scan a QR code and instantly be taken to a webpage or app to access information, perform a task, or engage with content. But what if they were more? 

By pairing QR codes with Kochava SmartLinks, marketers can gain in-depth user journey insights and visualize down-funnel conversions in real-time making QR codes quick, responsive and insightful.

Focus Brands, gleaned remarkable information after placing SmartLinks-enhanced QR codes within their brand’s stores.

Focus Brands is a leading developer of global, Fast Casual brands such as Cinnabon, Jamba, Auntie Anne’s, Mcalister’s Deli, and Schlotzsky’s. Their collection of brands is united under one company that’s leading the industry through product innovation, cutting edge business practices and an expansive media presence.

In an effort to elevate its mobile ordering capabilities and boost overall user engagement across its suite of mobile apps, Focus Brands initiated a plan. Given the expansive reach of their locations, the marketing team brainstormed strategies aimed at encouraging customers to embrace the app, particularly during their in-store visits.

Through careful analysis, Focus Brands observed that the strategic placement of QR codes on tables yielded significantly higher levels of customer engagement compared to QR codes positioned at the registers. This observation provided valuable insights to the marketing team, enabling them to optimize the placement of QR codes within their stores for maximum effectiveness. Consequently, this strategic realignment of QR code positioning led to a notable increase in overall customer loyalty and stickiness.

Between May and June of 2023, Focus Brands found that over 40% of all their attributed mobile app installs were driven from SmartLinks-enhanced QR codes. They also saw a 19.5% month-over-month increase in in-app engagement driven from SmartLinks-enhanced QR codes.

The merging of QR codes and SmartLinks has transformed these familiar tools into something far more valuable than mere convenience. By delving into the user journey and real-time conversion insights, QR codes have evolved into powerful marketing tools. The case of Focus Brands serves as a testament to the immense potential these enhanced QR codes offer. 

In the ever-evolving landscape of marketing, embracing innovations like SmartLinks-enabled QR codes is a strategic move that not only keeps you ahead of the curve but also unlocks a world of data-driven possibilities. So, as you consider your marketing strategies, remember that QR codes are not just quick and responsive; they are also incredibly insightful tools poised to revolutionize your campaigns and drive your brand’s success.

Looking to get started with SmartLinks, QR codes, or both? We have resources that can help! If you have a QSR app, QR Codes for QSRs is an informative blog that highlights the use of QR codes throughout store locations and best practices when placing QR codes. Also, for a more in-depth look at QR codes and how they function with Kochava SmartLinks, download the free guide QR Codes & Your Marketing Strategy.

For more information, contact us a support@kochava.com or request a free demo here.

The question of how SKAN (SKAdNetwork) works is not an easy one to answer. In fact, the complexity of its functionality increases with each new version. However, by deconstructing its intricate processes into comprehensible steps, understanding how SKAN works becomes a little easier. Through careful examination of the ensuing flow diagrams, you will establish a robust grasp of SKAN’s operational framework, thereby enhancing your readiness to effectively harness this privacy-enhancing technology.

The left side of the diagram explains view-through attribution, when the user does NOT click on an ad. The right side explains click-through attribution, when the user does click on an ad.

As you can see, steps 1 and 2 of each flow start off the same – an ad network serves an ad, and the ad is presented in an app or website (starting with SKAN 4). Depending on the user’s action (no click or click), the attribution lookback window drastically changes. With a click, the user has a longer time (up to 30 days) to install the app, but only 24 hours if they only view the ad. The intent of a click holds a heavier weight and offers more time for attribution to be awarded.

If the app is installed within the attribution window, the user then has 60 days to launch the app for the app to call its first conversion value update.

Once the user launches the app for the first time, the process that follows is quite different between SKAN 2-3 vs SKAN 4. As such, we will unpack them differently.

At this point, the app has been downloaded but has yet to be opened. For SKAN versions 2-3, when the user launches the app for the first time, a timer starts (24 hours). The left side flow demonstrates when no conversion takes place (eg, the user opens the app but does not complete any in-app action which results in a conversion value update). The right side shows when an in-app action takes place, triggering a conversion value update call. When this happens, the 24 hour timer restarts and will continue to reset until (A) a lack of user interaction, (B) an end of conversion value range, or (C) a forced stop in the app.

As soon as the second timer expires in either flow (left or right), the privacy threshold is applied and the install validation postback is sent to the ad network. When the ad network receives the postback, it is then forwarded to the advertised app’s mobile measurement partner (MMP) with any necessary campaign metadata mapping appended.

About SKAN timers

Apple users timers in SKAN to randomize responses to ad networks and advertisers – a mechanism to obfuscate data and prevent re-identification of individual users or devices. 

About SKAN privacy thresholds

To protect user privacy, Apple applies minimum privacy thresholds before sending any postbacks. 

Additionally, Apple may redact certain values (e.g. source app ID, conversion value) from postbacks that are sent if a certain volume of conversions aren’t reached. The exact privacy thresholds are not publicly known. 

About SKAN postbacks

Beginning in SKAN 3, Apple added the ability for influencing ad networks (not just the ad network that won attribution) to receive a postback. This enabled multi-touch attribution insights in SKAN for the first time. Additionally, Apple added the ability for advertisers to receive their own copy of postbacks, as opposed to the ad networks being the sole recipient.

About SKAN campaign metadata mapping

In SKAN versions 2 – 3, ad networks are restricted to use of campaign ID values (0-99). Rather than ONLY being able to see campaign-level insights, different ad networks mapped ad groups, ad sets and other campaign variables to the different digits in order to achieve more granular insights. An MMP helps decode this information across integrated partners for standardized reporting to the advertiser. 

The final diagram illustrates the post-app launch on SKAN version 4+. SKAN 4 brought forth several noteworthy updates for Apple, most notably the inclusion of multiple postbacks across three predetermined conversion windows. This extension offers ad networks and advertisers a substantially longer period to observe user behavior and assess post-installation quality. This stands in contrast to the single conversion postback option provided by SKAN versions 2-3.

SKAN is not an easy topic to digest and it becomes even more difficult when the mechanisms change with each new version. On SKAN 4+ in particular, crowd anonymity in conjunction with the conversion window, impacts several postback data points. These include: 

• Source App ID or Source Web Domain
• Source Identifier
• Conversion Value

There are also changes to the privacy thresholds with SKAN 4+. Similar to previous versions, an initial, minimum volume threshold must be reached to receive any postbacks. However, after that initial volume threshold is reached, postbacks will be received, but the granularity of data points included in the postback will be dependent on four tiers of crowd anonymity.

If you would like to learn more about these changes, gain more in-depth knowledge from The Ultimate Guide to SKAdNetwork (SKAN), free to download here.

Not sure if you need to use SKAN or not? We can help you find the answer in this blog.

If you have any questions or want to get started with SKAN, feel free to contact us at support@kochava.com.

Mobile measurement partners (MMPs) were created as an independent third-party platform to track, organize, and visualize mobile app data to give marketers a unified view of campaign performance across channels and partners.

Many stakeholders in the mobile advertising industry work and/or partner with an MMP. They can include the following list:

• Mobile advertisers and marketers running mobile advertising campaigns across different channels and platforms rely on MMPs to accurately track and measure the performance of their campaigns. They need an MMP to understand the effectiveness of their marketing efforts, optimize their strategies, and allocate budgets based on data-driven insights. Without an MMP, marketers would have a very fragmented view of performance across the different reporting dashboards of each partner. Getting a sense of the bigger picture wouldn’t be possible.
• App developers and publishers require an MMP to track user acquisition, measure app installs, and attribute app events to specific marketing campaigns. They rely on MMPs to gain insights into user behavior, engagement metrics, and monetization performance, which helps them optimize their apps, improve user experiences, and drive revenue.
• Ad networks and ad exchanges partner with MMPs to provide advertisers and marketers with accurate measurement and attribution capabilities on their ad inventory. They integrate with MMPs to track ad impressions and/or clicks, and independently attribute the conversions that result. The attributed conversion outcomes are syndicated back to these partners for campaign optimization. Essentially, the MMP enables them to demonstrate the value and performance of their advertising inventory.
• Agencies and media buyers partner with MMPs to gain visibility into campaign performance across various channels and platforms. They rely on MMPs to provide them with accurate and granular data to optimize media buying strategies, allocate budgets effectively, and demonstrate the success of their campaigns to clients.

All of these interested parties can benefit from partnering with an MMP. These partnerships enable them to measure, analyze, and optimize their mobile advertising efforts, ultimately driving better results and return on investment (ROI).

There is no exact threshold that needs to be reached before utilizing an MMP. For any of the stakeholders mentioned above, deciding when to use an MMP can depend on a variety of factors. When determining if you need an MMP, consider the following:

Your budget

The first thing you need to establish is your marketing and operational budget for your mobile app. Do you have room in your budget for an MMP and, if so, how much can you allocate to this service? 

The cost of an MMP can vary depending on the scope of services required, the scale of the ad campaign(s), and other tools or features the MMP might provide. Most MMPs provide different pricing models that are structured based on factors such as volume of ad spend, attributed conversions, number of monthly active users, levels of support, etc. 

Even if you only have a small budget for an MMP, it could be beneficial to start using one at a low cost so that you have room for growth. If you can, incorporate with an MMP early so that you can gain at least some valuable insights into your ad campaigns. These insights can make it easier for you to optimize your campaigns and save you money on future efforts.

Your media mix

When you’re just starting out, you might only be running campaigns on one or two channel partners (e.g., Facebook, Instagram, Google, etc). During this time, it might not be necessary to use an MMP because you’re probably using the platform of whichever partner you’re running with to view campaign activity and data. 

However, once you start to grow your media mix and spend with other partners, you should seriously consider an MMP. In this situation, an MMP serves as a centralized platform allowing you to collect, measure, and analyze all of your ad campaign data across every partner, channel, and platform. The unified view of your campaign performance enables you to compare and evaluate the effectiveness of different advertising sources in one place, becoming the single source of truth. It should be noted that some media partners (eg, TikTok) require that you use an MMP to advertise on their platform.

Overall, leveraging an MMP when working with multiple advertising partners enhances your ability to track, measure, optimize, and make informed decisions based on reliable data. It simplifies the management of your advertising efforts, improves campaign performance, and maximizes the value you derive from your advertising partnerships.

The app’s popularity

Once you expand your media mix, your app’s visibility and, hopefully, its popularity will expand too. If your app is doing well and you are gaining more downloads, daily active users (DAU), monthly active users (MAU) and in-app event activity, it’s probably time to employ an MMP.

An MMP will provide you with precise and reliable measurement of your app’s performance metrics, such as installs, engagements, and conversions. It also employs advanced attribution and measurement to accurately attribute these actions to specific marketing channels, campaigns, and partners. This data helps you understand the effectiveness of your marketing strategies and make informed decisions to optimize your campaigns further.

All of this data can be used for in-depth analysis and reporting, offering insights into user behavior, user acquisition channels, conversion funnels, and user lifetime value. These insights help you understand your audience better, identify user trends, and optimize your marketing strategies accordingly. The advanced analytics provided by an MMP can uncover valuable data points that contribute to the growth and success of your app.

Outside factors/requirements

Not only do MMPs help measure and analyze your app data, they also are vital in the ever-changing ad tech privacy and regulation landscape. MMPs are well-versed in privacy regulations and industry standards and can be helpful in guiding and facilitating your compliance efforts. They help ensure that your data collection and measurement practices align with different policies across platforms (iOS and Android), marketing partners (Facebook, Google, Snap, etc.), and government regulations (California Consumer Privacy Act, General Data Protection Regulation in the EU, and more). An MMP also helps you adapt to new privacy-enhancing technologies like Apple’s SKAdNetwork on iOS and Google’s Privacy Sandbox for Android. 

By working with an MMP, you can navigate the vast web of privacy requirements more effectively and efficiently.

As you incorporate more partners and channels into your media mix and your user base grows, it will be important to employ an MMP. There are a handful of leading MMPs to choose from. Once you determine your budget and your needs, do research into the MMPs that will best fit your needs.

For more information and help choosing an MMP, download this free request for information (RFI) template to guide you in your MMP research.

Want to learn more about Kochava’s MMP solutions? Take the next step here.

Once long ago, in the year 2018, Apple Inc., an American multinational technology company, introduced SKAdNetwork, short for “StoreKit Ad Network”, also commonly referred to as SKAN. 

SKAN is a framework that revolutionized mobile advertising attribution and privacy in the digital marketing landscape. Introduced with iOS 11.3, SKAN emerged as a response to growing concerns over user privacy and the need for more privacy-centric advertising practices. 

With the increasing adoption of mobile apps and the tracking capabilities of various advertising networks, users were becoming increasingly wary of their data being collected and shared without their knowledge. SKAN sought to address these concerns by providing a privacy-preserving way for app developers and advertisers to measure the effectiveness of their ad campaigns without compromising user data. By leveraging SKAN, developers can obtain aggregated performance data while preserving user anonymity, thus laying the foundation for a more secure and privacy-respecting mobile advertising ecosystem.

In this blog, we will expand on the history of SKAN and where this technology is headed.

SKAdNetwork (SKAN) has been around for a minute. In fact, it was first released by Apple back in 2018. Since then, four versions have been created with the most recent, v5.0, announced at WWDC 2023. 

While five long years have elapsed since the first release, SKAN is still finding its stride with iOS marketers and hasn’t gotten the traction it might have initially anticipated. Will we see more adoption after the release of 5.0? Let’s take a look into what SKAN 5.0 will look like and how it stacks up against previous versions.

Up until now, SKAN support has been limited to acquisition attribution only, but with version 5.0, there will be added support for re-engagement attribution. While Apple’s mention of this release was subtle, the new feature will potentially increase adoption rates. The inner workings of SKAN for re-engagement have yet to be revealed, but the ability to attribute ad taps that prompt existing users to return to the app is undoubtedly a welcomed addition. However, it’s important to acknowledge that re-engagement targeting on iOS already poses challenges due to the limited availability of IDFA (Identifier for Advertisers) since it’s availability became subject to user opt-in at the app level via the AppTrackingTransparency (ATT) framework in April 2021.

It remains to be seen how fast the industry can finish adopting all of the SKAN 4 updates introduced at WWDC 2022 and then take the step up to be on v5 to gain the benefits of re-engagement attribution. 

Get more information on the SKAN releases from Apple’s release notes.

Each SKAN version builds upon the previous release, but some releases have made a bigger impact than others. Version 3 introduced support for influencer reporting and delivering copies of postback to advertisers (previously only the ad network received the postback, which then had to be shared/forwarded to an advertiser and their measurement partner) making this one of the most adopted versions. However, SKAN v.4 was a big jump from the previous versions, introducing so much change that it upended some learnings, practices, and optimization modeling that had finally gained a foothold for effective use with v2-3. 

Apple introduced 2 more conversion postbacks (for a total of 3), along with three fixed conversion windows spanning day 0 to day 35 with fixed time ranges that could be prematurely ended with a new feature called lock window. New types of conversion values were introduced, along with a more complex approach to privacy thresholds which deploy multi-tiered crowd anonymity…say that three times fast. To top it all off, a new parameter was created to replace the 2-digit campaign ID.

Let’s take a look at the lock window functionality. All the time-based cohort modeling that was innovated to help marketers with early predictions on performance based on more stable conversion windows in v2-3 is negated. As such, some partners recommend advertisers don’t enable the lock window because of the disruption it could cause. Separately, the 2 additional conversion postbacks are appreciated, but they arrive so late that many ad network partners have advised they won’t be factoring them into their campaign optimization modeling for the foreseeable future.

In July of this year, Apple introduced SKAN 4.0 but then quickly rolled back to v3.0 ten days later due to a significant bug between SKAN and the AdService API. After a few days, Apple claimed the bug was fixed and SKAN 4.0 was once again available. Due to the bug with v4.0 and the major changes arriving on the scene with SKAN 4, adoption has been understandably slow. Partners need more time to see how the version adapts to their strategy before implementing it at any scale. The chart shows each release and the changes that were introduced with each version.

The answer is: it depends on the ad networks you’re running with. Ask your trusted SKAN ad network partners what version of SKAN they’re ready for and sign ad signatures with AND best positioned to optimize using the postbacks from SKAN they receive. They’re also likely to have recommendations for the optimal SKAN configurations to select within your mobile measurement partner (MMP) dashboard (e.g. how long to set your measurement window for SKAN v2-3, and whether to enable lock window on SKAN v4, etc.). It’s important to remember that your SKAN configuration and chosen conversion value model is one size fits all, meaning you can’t customize it per ad network. As such, if recommendations from your ad network partners are in conflict, you may want to follow those of the partner you’re driving the most spend and success with. 

Last, but not least, you can update your app as the advertiser to be v4 ready ahead of your partners. Your SKAN settings with your MMP will be backwards compatible. Once your ad network partners begin signing ads with v4, you’ll be ready to roll.

While SKAN is certainly complex, below are just some of the pros of using SKAN across all versions. 

1. Enhanced privacy – SKAN prioritizes user privacy by limiting the amount of personal information shared with advertisers and their partners. This protects user data and ensures compliance with privacy regulations.
2. Attribution insights – SKAN provides a solution for advertisers who have limited access to user-level data, such as the Identifier for Advertisers (IDFA) on iOS devices. It allows them to maintain some method for measuring the effectiveness of their ad campaigns without relying on user-level data.
3. Fraud prevention – SKAN employs measures to prevent ad fraud by providing limited and aggregated data. This reduces the risk of fraudulent attribution and increases the accuracy of campaign performance measurement.
4. Compliance with Apple: Complying with Apple’s privacy guidelines and using SKAN is crucial for app marketers to maintain a positive relationship with the platform. SKAN ensures adherence to Apple’s privacy policies, reducing the risk of App Store rejections and other consequences that may arise from attempting to bypass SKAN.

Even though each SKAN release has included more features than the last, the confusion and frustration  around how it works have been major reasons why some advertisers have struggled to embrace it. With more education around the topic and as the push for user privacy mounts, SKAN will become more widespread. In the meantime, determine which SKAN version your preferred media partners are using as there’s a wide variation in version adoption across the partners that have invested in supporting SKAN for their ad inventory. 

If you’re new to SKAN or need to brush up on it, gain an in-depth dive into what SKAN is and how it works with  The Ultimate Marketer’s Guide to SKAN for free. You can also read all about Kochava support for SKAN 4.0 here, and check out Kochava SKAN solutions.

In Shakespeare’s poem, Hamlet presents us with a question – To be, or not to be. Since 1601 we have been contemplating his proposal, taking it upon ourselves to find the answer. It’s hard to believe that over four hundred years later marketers would be faced with a similarly difficult question – To SKAN, or not to SKAN. Unlike Shakespeare, we are here to help you find the answer.

Before we dive in, it’s important to note that using SKAdNetwork (SKAN) isn’t required just because you have an iOS app. However, SKAN can open up more opportunities as the app grows or when you expand your marketing efforts. 

SKAN, or SKAdNetwork, is a complicated topic and attempting to understand all of its nuances can be a daunting task. So let’s determine if you really need SKAN for your iOS app or if you can bypass it. Below is a simplified chart explaining if you should use SKAN or not.

In the realm of running paid media campaigns on iOS, employing SKAN becomes imperative if an advertiser seeks to collaborate with channel partners beyond ASA. SKAN stands as the sole privacy-compliant mechanism for effectively measuring campaign performance across all users, regardless of their opt-in or opt-out choices concerning the AppTrackingTransparency (ATT) framework.

For example, should a marketer intend to drive iOS user acquisition through platforms like Facebook, Google, Snapchat, Twitter, TikTok, and various other media partners, embracing SKAN is essential. Implementing SKAN requires a concerted investment of time and effort to comprehend its functionalities fully. Nonetheless, the payoff is invaluable as SKAN facilitates campaign measurement while respecting user privacy, regardless of their consent status via the ATT framework.

Although there might still be some volume of IDFA-based attribution available when iOS app users grant consent to tracking through the ATT framework, a significant majority of iOS app users opt-out of such tracking, irrespective of the appeal of an app’s ATT opt-in flow. Without SKAN, the visibility into this opted-out user segment remains entirely obscured, leading to an incomplete understanding of campaign impact.

By integrating SKAN, advertisers can gain comprehensive insights into campaign performance, even among opted-out users, ensuring a holistic understanding of user acquisition efforts across various channels. This strategic adoption of SKAN enables marketers to make data-driven decisions, optimize campaigns effectively, and adhere to privacy guidelines, thereby fostering long-term success in the dynamic landscape of iOS advertising.

In the context of user acquisition through paid media campaigns, the adoption of Apple’s SKAdNetwork (SKAN) warrants consideration based on specific marketing needs and strategies. If an organization does not engage in paid media campaigns with third-party ad networks, Demand-Side Platforms (DSPs), or other publishers to drive user acquisition, the implementation of SKAN may not be necessary. However, it is important to recognize the distinction that Apple Search Ads (ASA) represents a notable exception within this context.

ASA stands as a paid media partner that operates exclusively within Apple’s ecosystem atop the App Store. Remarkably, ASA provides deterministic reporting capabilities that extend beyond the confines of SKAN. This essentially means that ASA offers a more precise and detailed attribution process, allowing marketers to gain comprehensive insights into the performance of their campaigns.

As a result, businesses that exclusively utilize ASA for their paid media endeavors can capitalize on its deterministic reporting features without the need for SKAN implementation.

If you have come to the realization that SKAN is indeed necessary for your requirements, you are now prepared to embark on the next phase of your SKAN journey. As previously mentioned, the integration of SKAN entails a complex process, and prior to implementation, it is essential to acquire a comprehensive understanding of its functioning. 

For a detailed explanation on the workings of SKAN, we invite you to download “The Ultimate Marketer’s Guide to SKAdNetwork (SKAN)” here. This resource will serve as a valuable reference to facilitate a successful implementation and optimize your utilization of SKAN in your marketing endeavors.

Learn more about Kochava solutions for SKAN or get in touch with us.

Our once (fairly) calm ocean has been riddled with COVID swells, waves of shifting privacy policies, and overall economic surges that have left marketers tumbling. The possibility of a recession has been brought to the forefront of many of our minds, but we must remember that this isn’t our first storm. Let’s build a lifeboat, put on our water wings, and surf the waves of uncertainty until the winds die down. So how do we navigate ad budget cuts while staying afloat?

When it comes to any emergent situation like a flux in our economy, people are always surprised and not many of us are prepared, because we don’t want to admit to any negative changes. In these times there are two ways to proceed: (1) messy and scared or (2) accept the problem and get ahead of it. Let’s choose option two.

Here’s what we know: ad spend growth will likely decelerate in 2023. According to a survey by IAB, ad buyers revealed that there will be a 3.1% decrease in year-over-year ad spend growth between 2022-2023, versus 2021-2022.

Here’s the problem: Marketers will have less money to spend on advertising. But let’s reframe it: Marketers have the opportunity to reassess their budgets and optimize for future growth.

In many ways, ad budget cuts force marketers to get creative, reevaluate their techniques, optimize their spend, and proceed with more clarity and confidence. One might even say that a marketer can learn more and mature in their craft by weathering budget cuts, versus only operating in times of plentiful and growing spend.

When you’re in a stressful situation it’s best to take a step back and look at things from a different perspective. Before you can build a lifeboat, you need to determine what tools and supplies you have. What will safely get you over that next wave and keep you afloat?

It’s no surprise that in economic uncertainties, media budgets get evaluated more frequently. In fact, 63% of IAB survey respondents said that they will be evaluating and reforecasting their budgets more frequently in 2023. Of those reforecasting, 45% said they would be doing this on a monthly basis, with another 20% doing it on a daily or weekly basis. Continuous reforecasting can help marketers make better predictions on their future ad performance and adjust their budget accordingly. However, be wary of too much micromanagement. You need to give new strategies enough time to age, before deciding whether they’re a failure or a success. Finding a balanced approach is key. Ask yourself:

• What platforms and partners are actually pulling their weight? By reevaluating what partners and platforms you’re running ads on, you will be able to understand which one’s are providing you with the best long term value while avoiding the cannibalization of your audiences. In the past, you might have been quick to cut out partners that are not driving immediate results (e.g. installs), but you might be overlooking their ability to bring in high-quality customers further down the line. Partners who are bringing in immediate revenue but short term, low quality customers are not sustainable and could be a waste of your ad budget over the long haul.
• Have your customers’ habits changed? How your customers/users spend their own money can affect how a marketer spends their’s. During an economic downturn, your customers might be spending less overall or spending more on specific things. As a marketer, you might be wasting ad dollars pushing products or services that aren’t making you money because your customers have moved their focus elsewhere. Listen to your customers and observe how behaviors may have shifted, then and refocus your budget on what is actually making you money.

By looking both at your own marketing efforts and your customers trends, it will be easier to align the two and make ad budget cuts with more confidence.

When the sea is calm, as it was a few years ago, it’s easy to extend your resources. You might have had a generous marketing budget and you got used to spending money on large campaigns across multiple channels. Now with ad budget cuts staring you in the face, it’s overwhelming to imagine having a limited budget. With less ad dollars, you will have to allocate the amount you have more efficiently while still striving for a profit.

Start by improving the efficiency of your overall marketing strategy by checking in  on your key performance indicators (KPIs) and potentially evolving how you measure success. Specifically, look at user/customer lifetime value (LTV). It’s cheaper to keep acquired customers than it is to obtain new ones. If you focus on driving more engagement with your current customers, you can more efficiently boost growth and profitability.

Another telling KPI is the average revenue per user (ARPU). This metric is important because it indicates how profitable a product or service is based on how much revenue is gained from each user, giving you helpful insights into your overall growth and success. That being said, don’t be fooled by averages and be sure to check for outliers. If you have Bill Gates and this writer in a room, then you have 2 billionaires on average. As such, make sure you check for outliers that can steer important decisions. 

Compare your historical KPIs with current numbers, and continue to monitor LTV and ARPU to observe any changes. Efficiently allocate your ad budget to the high-value customers you’ve already acquired and who are more likely to turn a profit.

Finally, get creative. Use the data you have to think outside the box. Maybe you focus more on your owned media efforts and optimize your website and social presence. Maybe you utilize customer generated content via influencer marketing or an ambassador program. Out-of-home (OOH) marketing is becoming more and more measurable with cost-efficient techniques such as community events, pop-up shops, or chalk art.

Marketing efforts that were effective two years ago might not be effective now. Consumer behavior has changed and so should your advertising. Look to your customers and optimize for efficiency and profitability all while staying within budget. We believe in you.

For expert advice from marketing veterans, check out this recent  Kochava webinar event featuring Realtime Agency that covers how to continue driving growth in the face of economic downturn. You can learn how seasoned marketers can weather seasons of budget cutting – all the while maintaining healthy performance and growth.

Reducing your ad budget can be a complicated and overwhelming task, but it doesn’t have to be. Kochava suite of solutions offer actionable, data-backed steps that simplify the process and optimize your ad spend. 

To make informed decisions about your ad budget, consider the following:

For more information or if you have any questions, please contact us at support@kochava.com or visit https://www.kochava.com/smart-savings-for-marketers/.

AdTech is evolving at an alarming pace, accelerated by privacy-focused initiatives that upend longstanding norms of how user and device data is transacted – making it more and more difficult for marketers to measure the true impact of their ad spend. Mobile measurement partners (MMPs) have long been entrusted as stewards of data across the AdTech ecosystem, and as measurement has become more complex, MMPs have pressed onward, innovating to adapt to the many changes and challenges that have arisen. The goal of the MMP is to provide advertisers with actionable, directional insights they can use to continue making the best decisions with their ad dollars.

Kochava has been forging the way for advertisers since 2011. With attribution science progressing toward a more complicated aggregation of smaller disparate data sets, requiring the application of complex math, we too continue to evolve into a future-proofed, MMP of tomorrow.

Yes, modern attribution has become increasingly complex and will no doubt increase in complexity in the future. To really understand where attribution is headed, it’s important to look back on where it started.

Attribution used to be fairly straightforward. An impression or click occurred, and a conversion resulted, giving advertisers a simple one-to-one connection to understand which media exposure contributed to which conversion.

While this type of attribution is still in use in a number of scenarios, a renaissance of privacy-focused initiatives has led to a new era of privacy-first attribution that’s no longer one-to-one, but cohort-based and anonymous by design. This is leading to an increasing number of cohorts of aggregated signals needing to be reconciled and/or balanced with record-level activities of first-party data, all while making the bigger performance picture clear and understandable for the marketer.

It’s no small task, but MMPs are uniquely positioned to meet this need by managing the integrations, aggregations, and complex math to give marketers the best possible insight into the performance of their spend.

Apple largely spearheaded the privacy-first attribution revolution with their introduction of the AppTrackingTransparency (ATT) framework with iOS 14. The ATT framework essentially placed traditional one-to-one advertising attribution behind a user opt-in wall. At the same time, they launched the second version of SKAdNetwork, a privacy-enhancing technology that offered an anonymous and privacy-first approach to measurement that did not require opt-in. 

In 2024, Google is set to follow with their roll-out of the Privacy Sandbox for Android, which in many ways could be likened to SKAdNetwork for Android, although there are plenty of differences. While these privacy shifts play an important role, the lack of cohesive policy and implementation make it increasingly important for advertisers to work with an MMP that can help guide them through the complex web of attribution depending on channel, platform, region, and other variables.

According to a recent study by the IAB, 55% of respondents cited cross-platform measurement as their top focus for 2023.

Kochava helps marketers navigate cross-platform measurement complexities with solutions that provide turnkey attribution and data handling across the various privacy layers that exist, at the platform/OS level, the publisher/network partner level, and the government regulation level.

Throughout the omni-channel marketing landscape, Kochava operates on many layers of measurement methodologies that can be applied to extract performance insights for the marketer while staying in line with the complex web of privacy-first policies.

To learn about the finer details of how Kochava operates across these layers and ways you can leverage them in your omni-channel measurement strategy, contact us for an expert briefing.

Media mix modeling (MMM), also called marketing mix modeling, is becoming more and more essential as user privacy enhancements challenge marketers to find new ways to arrive at the performance insights they can use to optimize their spend. With MMM, the data collected from marketing and non-marketing sources is used to build a demand model that can be analyzed to determine the impact marketing has on overall conversions and business outcomes. With these insights, marketers can adjust their spend and optimize performance from a more holistic vantage point.

Kochava recently acquired Machine Advertising, whose Always-on-Incremental Measurement (AIM) platform, is a next-generation marketing mix modeling tool. AIM maximizes the effectiveness of the marketer’s budget by providing advanced control over factors such as incrementality, channel saturation, and seasonality. 

The more traditional approaches to MMM quickly become outdated without regular updates, making it time-consuming and requiring skilled resources in order to manage. This often made MMM a laborious exercise that only large organizations had the resources to maintain in-house or the budget to outsource externally. AIM is different in that it’s a sophisticated learning system that ingests new data daily and continuously updates and enriches its models. The always-on approach ensures that the insights it produces are always accurate, up-to-date, and ready to use – providing its users with turnkey recommendations for optimized budget allocations.

This is accomplished through a top-down measurement approach that leverages aggregated and anonymized data, as opposed to the bottom-up path of an MMP that traditionally relies on granular, row-level data. AIM works further down the measurement spectrum by starting with market-level aggregated data to analyze media effectiveness and then continues down the funnel to provide more granular actions to inform budget allocation by media partner.

These two methods feed into each other to help marketers improve processes and campaign performance. Utilizing AIM in conjunction with any MMP ensures that all aspects of the measurement spectrum are addressed and provides usable data to better inform buying decisions. 

As a prerequisite to the use of the AIM platform, you will need aggregated cost data by app, country, network, and day. Most MMPs offer cost aggregation tools, and the AIM platform can work with any MMP.

For marketers utilizing Kochava, Kochava Cost provides cost aggregation with data connectors to ingest cost metrics across all of your omni-channel partners. If you’re a current Kochava client and aren’t using Kochava Cost but have an interest in MMM, be sure to contact your Client Success Manager or email support@kochava.com about implementing cost measurement.

The future of attribution is already here; Kochava is continuously innovating and adapting to evolve along with the ever-changing advertising ecosystem. 

In preparation for Google’s Privacy Sandbox release in 2024 and the depreciation of MAID, Kochava is participating in Google’s beta testing. With only a year to go, advertisers should coordinate with an MMP that supports SKAdNetwork and will also be able to ensure their success on the future of Android.

Looking forward, Kochava will unify all aspects of modern attribution into one highly effective insights layer spanning omni-channel integrations, varying degrees of performance data aggregations, and juggling the complex math necessary to deliver a sensible read on your campaign outcomes.

MMPs are no longer last-touch measurement houses. For years, Kochava has been supporting fractional attribution, hosting the data that brands use to drive their own in-house media mix modeling, and performing one-off incrementality studies. The policy changes across major players have forced the industry to adapt, and as an MMP that prioritizes innovation, we’re ready to accept the challenge and help marketers thrive. 

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Data Revolt, a data marketing agency that started the revolution of data-first digital marketing in Eastern Europe, has officially become an authorized partner with Kochava, the leading attribution and analytics platform. The agency has made a name for itself in the global market with its digital solutions that empowers marketers with data-driven insights. As a Kochava Authorized Partner, Data Revolt can utilize the Kochava Marketers Operating System® (m/OS) to its full potential on behalf of the brands they serve. In this blog post, we’ll explore Data Revolt’s comprehensive marketing toolset and highlight how this newly formed partnership will be invaluable to the adtech ecosystem.

Unlike traditional marketing approaches, Data Revolt’s strategies are built on insights pulled from data collected through consumer interactions and engagement. This approach, known as data-first marketing, helps construct a propensity about future behavior and enables companies to make informed, data-driven decisions. Data Revolt offers a variety of services that can be tailored to suit any marketing strategy.

At Data Revolt, the focus is on using performance marketing, certified by data, to unlock growth opportunities for their clients. By leveraging this power, the brands they work with have access to the insights they need to develop specific strategies and take action to achieve growth. The success of this approach is reflected in their portfolio.

Data Revolt’s data-driven insights are complemented by Kochava’s powerful fraud prevention and detection tool, which helps businesses safeguard against ad fraud and recover lost revenues.

“We are thrilled to partner with Kochava as an authorized partner. Their powerful attribution and analytics platform, combined with our data-first approach to digital marketing, will enable us to provide even more valuable insights and measurable results for our clients. With Kochava’s fraud prevention, detection tools and advanced methodology for reporting in the SKAdNetwork era, we can ensure that our clients’ ad spend is protected and their campaigns are running at peak performance. This partnership represents a significant step forward for the adtech industry and we are excited to be a part of it,” said Marian Becheanu, Head of the Data & Analytics team at Data Revolt Agency.

Uber – Fraud detection & prevention

Uber enlisted the help of Kochava’s fraud solutions team to conduct an in-depth fraud audit. After successfully processing over 58 billion transaction records, the solutions team found significant evidence of ad fraud and violation of Uber’s IO terms. Kochava provided expert testimony and helped Uber recover over $6 million in damages. Learn more about this case study here. 

Traffic verification – Fraud detection & prevention

A major advance deposit wagering platform for betting was targeted by ad fraud during its peak season, with a surge of clicks and non-performing installs from states where online gambling is prohibited. Using Kochava Traffic Verifier, the team set filtering rules to block any campaign traffic originating from these states, reducing the percentage of fraudulent clicks and installs in their campaigns and proactively eliminating CPI payouts for install conversions in the prohibited states. Learn more about this case study here.

The partnership between Data Revolt and Kochava is set to transform the data-first marketing landscape. Data Revolt has built its reputation on providing innovative digital solutions that empower marketers with data-driven insights. Now, as an authorized partner of Kochava, Data Revolt can utilize the Kochava Marketers Operating System (m/OS) to provide even more insights and measurement possibilities for their clients. This partnership will enable clients to make data-driven decisions with more accuracy, even in the face of platform privacy upgrades and tracking constraints. With Data Revolt’s focus on performance marketing and Kochava’s comprehensive fraud detection and prevention, bespoke reporting, and integration with major ad networks and platforms, clients can rest assured that they are receiving the best in cutting-edge technologies and industry-leading solutions.

You can learn more about Kochava’s solutions here.

If you’re an agency interested in becoming a Kochava Authorized Partner, please contact us today. The process involves a series of educational Discovery Sessions on various topics, including:

*Measurement & Attribution session required, plus two additional sessions selected by the agency. Once agencies become a Kochava Authorized Partner, they will be listed as such in the Kochava Media Index, the largest advertising database in the world.

Over the years, there have been growing concerns around user privacy and data. In fact, 67% of internet users are more alarmed than ever before about the state of digital privacy. Yes, as consumers we want our online data to be secure and private but most of us also enjoy ads that are targeted towards our likes and dislikes, opening up our horizons to new products, brands, and services. Advertisers, too, would like to provide users with relevant advertising while limiting identified user data. If only we can have both…

A win-win is closer than we think. Privacy enhancing technologies are on the rise and will undoubtedly be the closest solution to complete user privacy to date. As we become more versed in how privacy-enhancing technologies (PETs) function and find relevant cases to utilize this category of technology, we must also consider ad measurement. Measurement and attribution will need to evolve with these new privacy technologies and mobile measurement partners (MMPs) are here for it.

PETs are technologies (hardware and software) that are designed to balance privacy with usability. Examples of PETs include contact tracing, user locations, and electronic payment processes.

These technologies are important because they can regulate the amount of data that is processed to help protect personal information. In this time of increased regulations on data privacy and protection, PETs play an important role. Privacy breaches and data loss are harmful. Keeping data secure and private impacts the reputation of businesses and the trust of consumers.

There are a number of PETs that can be used in a variety of ways. Any type of technology that increases security while decreasing data loss can be considered a PET. Below are some examples.

Data masking
Data masking is the technique of changing the values of the data while using the same format as the original dataset. This creates a fake but true version of the original data. There are a few ways to mask data, such as:

• Reliable VPN
• Pseudonymization and obfuscation
• Data minimization
• Communication anonymizers

Cryptography
Cryptography is the process of encrypting sensitive data by utilizing algorithms and decrypting it once it arrives at its intended place. Only the sender and recipient have access to the data by encrypting the data before sending it and then unscrambling it upon arrival. There are a few types of cryptography techniques which include:

• Homomorphic encryption
• Secure multi-party computation (SMPC)
• Differential privacy/obfuscation
• Zero-knowledge proof (ZKP)

In the near future, PETs will be, and in some cases already are being, incorporated into digital advertising to add an additional layer of privacy and security to user’s data: personal data will stay anonymized while targeted ads will be served to the correct audiences. Because of this, PETs and ad measurement will likely intersect to protect individuals’ personal data while still allowing for ad measurement.

One way PETs could be incorporated into ad measurement involves the use of differential privacy, which makes data unidentifiable while still allowing data to be measured and analyzed without revealing personal information. This would enable advertisers to measure campaign effectiveness without compromising user’s personal data.

Ad measurement could also utilize federated learning, a type of decentralized machine learning, which allows for the analysis of data across different devices and platforms without the need to aggregate the data. This could enable advertisers to gain insights into ad engagement across any device and platform without having access to private data.

Another potential solution involves the use of blockchain technology to allow reliable data sharing between advertisers and publishers, reduce fraud, and protect user privacy while still delivering the right ads to the correct audiences.

New technologies are on the rise to protect user privacy. We will likely see continued research and development between PETs and ad measurement, leading to better, more effective measurement strategies of personal data.

While privacy enhancing technology is beneficial, it certainly adds complexity to ad measurement. That being said, it should still be pursued as a solution because user privacy is something that is front-of-mind for advertisers, brands, and partners alike. So how can we pursue user privacy while continuing to do our job as marketers?

Thankfully PETs are not the first privacy tool to be utilized. Others include:

• Apple’s AppTrackingTransparency (ATT) framework requires user permission to track activity across the web and apps.
• Apple’s SKAdNetwork which provides anonymous, aggregated and delayed campaign attribution insights for iOS marketers.
• Google’s Privacy Sandbox,which is coming to Android in 2024, will implement anonymized forms of measurement, ad targeting, and more.
• The General Data Protection Regulation (GDPR) is the EUs law for data protection and privacy.
• The California Consumer Privacy Act (CCPA) enhances privacy rights and consumer protection.

These are just a few examples of laws that have paved the way towards better user privacy. As more PETs come into play, MMPs will need to find ways to provide marketers with the data they need while staying in compliance with these regulations. 

This is a great opportunity for growth and innovation within the ad tech space. As an MMP, Kochava wants to empower marketers and brands to embrace this new time of user privacy while also giving them the tools they need to succeed. Kochava has provided their customers with solutions such as a consent management platform for CCPA and GDPR, Privacy Profiles for the ATT framework, and compliant integrations and partnerships with super publishers and ad network platforms.

As user privacy becomes more optimized and secure with privacy enhancing technologies, Kochava will continue to be the trusted data steward between advertisers, privacy regulations, and users by providing privacy-first measurement solutions. Kochava empowers advertisers to do their work while providing them with the confidence that their data handling has met all the privacy regulations and laws.

If you are interested in learning more about Kochava tools, contact us at support@kochava.com or get started by checking out our solutions.