8 reasons why digital marketers need need need granularity (from experts at Kabam, Yelp, Nexon, Postmates, & N3twork)

Pebbles on a rocky beach are granular. The white sugar that we all hate to love is granular. The stars of the Milky Way that smudge together into a glorious sheet of light are, under closer inspection by a powerful telescope, also granular.

And so is the very best of digital and mobile marketing.

Why?

“Granularity sustains profitable scale,” says Singular’s Vice President of Customer Strategy Victor Savath. “Without granularity, you can scale… but it’s hard to monitor quality.”

Granularity is important both cross-channel and within channels, Savath said recently at UNIFY conference, where he interviewed experts from Yelp, Kabam, Postmates, Nexon, and N3twork on the topic. It’s important for creative. Granularity is also important for bids and CPIs. It’s critical to evaluating publishers and sub-publishers. And it’s something that impacts your daily budgets.

But exactly what is granularity?

And what does it achieve for digital marketers?

Granularity in digital marketing can be defined as the ability to dissect big blocky chunks of marketing activity and ad buys to see the smaller building blocks. For example:

  • If your ad campaign is spread over 15 different agencies, you can view each one individually
  • If each agency uses multiple ad networks, you can see how each is performing
  • If each ad network employs different publishers and sub-publishers in your campaign, you can dive into sub-publisher metrics
  • If you’re using varying creatives and forms of targeting, you can see how each performs
  • As users or customers engage, you can see their journey and react personally to their preferences and needs

As you can see in the video from UNIFY, experts from top mobile companies had a lot to say about the concept of granularity. Here are eight things they highlighted:

1. Granularity tells you how to maximize channels

Clearly, seeing which ad network or publisher is providing the best results is a good thing. But it’s sometimes even more important to really understand what’s working within a network or publisher.

“Obviously Facebook is the biggest social channel, but Pinterest, which is often overlooked, is an interesting play,” says Yelp’s Head of Performance, Eyal Grundstein.

The key to unlocking performance for Yelp on Pinterest was experimentation… and granularity.

Initial generic campaigns produced generic results, but when Yelp started targeting “odd things” like nail salons, click-through rates jumped 5X. Another finding: tattoos are huge on Pinterest, because people search for tattoos that they’ll consider. Targeting on tattoos and showing tattoos in the ads boosting conversions 10X.

“You can be granular not only in the targeting but also in the copy,” Grundstein says.

2. Granularity tells you which publishers are performing

Most ad networks fulfill impressions and conversions for their clients by purchasing inventory from publishers or sub-publishers. When this happens, sometimes advertisers lose the ability to optimize for maximum performance because they either lack the capability or are not looking below the top line campaign numbers to the sub-publisher results.

Hint: some will be rock stars; some will be duds.

“We have a two to three times per week process of pruning out the low performers,” says Eric Seufert, Platform at N3twork. “We kill them at the line-item level if they’re not performing.”

That process does vary from week to week, Seufert says, as publishers change. There’s some natural variance between good, acceptable, and bad, so some level of discretion is warranted. Still, the overall learning remains: advertisers need to be able to probe down to sub-publisher levels to really fine-tune performance.

3. Granularity helps you avoid ad fraud

Granularity is table stakes for avoiding fraud, says Grundstein. Impression-level data, for instance, is an absolute must.

It’s also a way to tie the technicalities of adtech to the ground-truth realities of customers, users, and your product. And there’s no better way, says Warren Woodward, Nexon’s Executive Director of User Acquisition, to really see what’s going on.

“Show me this ad in the wild,” Woodward will often ask his ad partners. “It’s amazing how many sources break down when you ask them… where is your traffic? Can you show it to me?”

And, just as source-level data allows you to pinpoint top performers, it also allows you to isolate potential fraud. Especially when you explicitly state your goalposts in the ad insertion order:

“This game that usually has a 90% tutorial completion… if we see a source as over ‘x’ number of installs and [it] deviates from that norm by over 50%… we’re going to consider that incentivized or some other type of fraud,” says Woodward.

4. Granularity helps you avoid bidding against yourself for adspace

Granularity on the publisher level helps us to “strategize and understand where not to overbid or bid against yourself,” says Yelp’s Head of Performance, Eyal Grundstein. “For example, if you’re buying on two different DSPs and they’re both buying on Mopub… they will bid up against each other potentially, especially on a particular placement if there is enough volume or if it is relevant enough.”

In other words, the ad space is complex and busy. And if you’re a significant advertiser, you’re probably using anywhere from ten to over a hundred advertising partners, which means you could potentially have campaign collisions.

There’s only one thing less cool than ad fraud, and that’s bidding against yourself.

5. Granularity helps you customize to different geographies

https://pixabay.com/en/hands-world-map-global-earth-600497/

Country and regional level data is critical when marketing, says Kabam’s Director of User Acquisition, Andy Park.

“How people consume media across geos is different,” Park says, noting that people in China like to like and comment on ads, particularly on Tiktok, the country’s top video platform. “[One] ad got 37,000 likes and 600 comments in two days.”

Creatives come in many different sizes, shapes, and user experiences, Park says. The key is being able to present different creatives to different audiences, and react appropriately depending on which ones work.

This also enables regional targeting, says Postmates’ Director of User Acquisition Patrick Witham.

“We operate city-level targeting,” Witham says, while noting that there are some limitations with ad network data for geotargeting.

Separating campaigns for different geographies can also make overall campaign analytics more challenging, he added, and does put some limits on scale. However, tighter targeting almost always leads to better results, and “specificity drives conversions.”

6. Granularity allows you to “try wild things” and still be successful

Some of the best things you’ll do in marketing are crazy.

At least, at first glance.

“Our approach has been to build tools that allow us to be radically experimental,” says N3twork’s Seufert. “We’re building about 50 videos a week… we deploy them to test and then deploy more universally.”

Some of those videos are going to be incredible. Some are going to be horrible. But by building the engine to enable creativity at scale and fast failure, N3twork is opening itself up to those rare oddball explosions of lightning in a bottle that drive mass conversions.

Nexon’s Woodward agrees.

“Try wild things,” he says. “You want something that’s going to stand out… when you have a completely different experience, it’ll be the biggest winner or a complete loser.”

One example for Nexon was an ad that featured almost no gameplay — an extreme rarity in the mobile game ad world. Instead, it simply showed fans talking about the game. Essentially, it broke every rule… and it was the company’s biggest winner.

“It carried about a quarter of our user acquisition,” says Woodward.

7. Granularity helps you avoid poorly performing genres of publishers

Sometimes you want to avoid one publisher in particular. Sometimes, though, you want to avoid an entire genre of publishers.

That’s exactly the scenario that Kabam’s Park found himself in (watch the video for full details… including precisely what he was trying to avoid.

Some things just don’t work for your company, your brand, your product, or your app. And granularity enables you to avoid them.

8. Granularity helps you test creative versus creative

Every marketer wants to know which ad units are performing. That’s table stakes… and yet also an example of granularity.

Smart marketers also want to know their conversions from different creative types: banner, text, interstitial, video… and playable ad. You just might be surprised at what you find.

For example, playable ads doubled Nexon’s app installs from one particular source, says Executive Director of User Acquisition Warren Woodward.

“Now we’re making as many playables as possible,” Woodward says. “If you’re not games, think about other ways you can make interactive ad units. The rest of us are… you won’t be in the game if you’re not.”

Summing up

Granularity isn’t just a nice-to-have. It’s an essential attribute for marketers who want to scale profitably.

The good thing: it’s easy to get.

Dig deeper into granularity: See how the best growth marketers achieve it with ease.

Ad Monetization Reporting & True ROI Made Easy

Since launching Singular 4 years ago, we’ve worked tirelessly to become the de-facto Marketing Data Platform for the top mobile brands around the world. Our clients use Singular to unify their core marketing data sets into a single source of truth. And we take pride in helping them sort through the complexities of the ecosystem and uncover insights to help grow their business.

Singular is dedicated to helping marketers uncover ROI across their entire customer journey. A lot of marketers have a single source of revenue, in the form of in-app purchases, but many others have an additional source of revenue called “Ad Revenue” (similar to how a little company named Facebook makes their money 😉). As a result, ROI shouldn’t solely factor “App Revenue”, but must also “Ad Revenue”.

At Singular’s first annual growth marketing summit, UNIFY, our CEO Gadi Elishav announced the launch of our Ad Monetization Reporting. This product addition is in direct alignment with our vision is to help marketers uncover their business’ unique customer journey and understand every touch point within that journey.

Singular’s Ad Monetization Reporting collects, aggregates and standardizes your ad revenue data from all of your monetization partners into a single reporting view. We’ve taken the same approach and technology that Singular is known for with our new Ad Monetization Reporting. For customers who also use Singular attribution – we will soon provide deeper insights into granular ROI, accounting for both Ad Revenue and In-App Purchases, commonly referred to in the industry as True ROI. We’ve already integrated the most popular monetization partners, and are consistently adding new partners.

 

This is a game-changer for User Acquisition and Monetization teams alike:

  • User Acquisition teams can finally account for Ad Revenue in their ROI formula.
  • With the ability to see the true ROI figures – User Acquisition Managers will be able to make better decisions about the actual performance of their campaigns and channels and scale their marketing efforts efficiently and more intelligently. Channels and campaigns that you thought had a specific ROI could look completely different once we factor Ad Revenue into the ROI calculation.
  • A centralized snapshot of all your Ad Revenue enables better insights and scaling app ad revenue down to the placement level.
  • Streamline work with finance, and have a true end-to-end view of your marketing profit and loss.

Are you interested in next-level Ad Monetization Reporting and analyzing more accurate ROIs? Let’s connect! Reach out to your Customer Success Manager today or contact us.

Apple Aims to Protect Data Privacy with SKAdNetwork

Wondering what Apple’s new privacy enhancements mean for you?
Watch our on-demand webinar iOS 14 & IDFA Changes: What you need to know

 

Quietly rolled out by Apple on March 29th, 2018 with their iOS 11.3 release, SKAdNetwork is an API that validates advertiser-driven mobile app installs. In Apple’s documentation, it’s stated that SKAdNetwork’s objective is to help marketers to measure the success of an ad campaign while maintaining user privacy.

What’s different about the SKAdNetwork API?

SKAdNetwork is a class that belongs to the StoreKit framework; Apple’s In-App Purchase Payment System that manages transactions for In-App Purchases. After installing the app, Apple shares only 5 items with the advertiser: ad network ID, transaction identification, ad campaign ID, app ID installed, and attribution code to link all.

Source: Apple Developer Documentation

There are two key postbacks associated with SKAdNetwork:

  • Initiating Install Validation: This Informs an ad network when users install and launch an app after viewing an ad. Ad networks initiate validation by providing signed information, including a campaign ID, when displaying the ad. Later, if the ad results in a conversion, Apple notifies the ad network with a postback that includes the same campaign ID.
  • Verifying an Ad Conversion: When a user installs and launches an app as a result of your ad, you receive a postback request that validates the installation. The request is sent to the ad network URL provided in registration.

What does this mean for advertisers?

It’s still too early to predict how SKAdNetwork will play out. Adding to the mystery, Apple has been very hush-hush about their motives and the rollout of SKAdNetwork. However, we think there are a few possible ways this could play out:

1. Apple doesn’t actively push SKAdNetwork, it doesn’t garner significant adoption, and nothing changes in the mobile marketing space.

One possible scenario could be that Apple doesn’t actively push SKAdNetwork to advertisers, resulting in minimal adoption. In this scenario, there wouldn’t be any significant change in the way that app marketers manage their attribution.

2. Apple pushes SKAdNetwork and Google follows suit with their own version.

Another scenario is that Google follows suit with its own version of the ad network API. This scenario could play out a few different ways:

  • Apple and Google don’t build out a robust attribution solution, which results in a lack of adoption by app marketers. Apple has made its mark in the world thanks to being an extraordinary and innovative hardware company, but they have never been accountable for providing analytics and insights to app marketers. If Apple and Google do not develop all the features that are necessary for an end-to-end attribution solution, (e.g. data extraction, all postback types, flexible attribution windows, easy BI integrations) then the industry will not adopt their solutions.
  • Apple and Google develop all the functionality needed for a robust attribution solution, leaving third-party mobile app attribution providers to potentially die-off in their current form. Who can compete with the operators of the mobile app stores we attribute from anyway? However, advertisers may still lose out in this scenario because they might encounter more complexities coming from running attribution on two separate platforms. The winners in this scenario would be third-party mobile app attribution providers that offer value-added services such as connecting multiple networks into a single view and aggregating all necessary features into a single API.

3. Apple pushes SKAdNetwork but Google does nothing.

In a third possible scenario, Apple could actively push SKAdnetwork to advertisers, while Google doesn’t follow suit with their own version. This would still result in complexities for advertisers who would need to manage attribution programs in silos across different OSs.

In this scenario, marketers would turn to attribution providers who could help them gather data from multiple sources, standardize it, and aggregate it into a single ROI dashboard.

So what’s going to happen?

It’s unfortunately too early to say, but one thing is clear: Apple wants to enhance users’ privacy. Apple has clearly positioned itself as a top privacy-conscious company and will continue to hold this stance as data privacy becomes more top-of-mind in the industry.

Mobile Analytics 101: ARPU versus ARPPU

This post is designed to help mobile marketers get more ROI from their mobile app businesses by better utilizing the data and measures in their mobile analytics platform. Here we are going to discuss how Average Revenue per User (ARPU) and Average Revenue per Paying User (ARPPU) can be used to make better investment decisions on App Install and Re-Engagement campaigns.

As always, we recommend using ROI (not ARPU or ARPPU) as the key metric for any effort to measure and optimize app marketing. ARPU and ARPPU can also be valuable mobile analytics because they provide guidance on appropriate CPIs for planning. They are critical components of ROI calculations.

Let’s start with simple definitions.

ARPU Measurement Defined

ARPU is one of the most useful measures in mobile analytics. It refers to the average revenue per user, meaning that it measures the total revenue driven by an app divided by the number of installs. You can use Singular to calculate this for all app installs, paid app installs, organic app installs or total/paid/organic installs for a particular time period. With Singular you can further parse your mobile analytics to measure ARPU data by country, vendor and campaign.

ARPPU Measurement Defined

ARPPU is a measure originally designed for subscription-based businesses, like a game that you pay a fee to use every month. The idea was to be able to examine the quality of paying game users by eliminating the free or non-revenue users from the math. This measure is particularly valuable for “freemium model” businesses where a small number of users are driving the lion’s share of app revenue. ARPPU data tends to be particularly relevant for game businesses that focus on sales of virtual in-app purchase sales (IAPs). Some chose to think of ARPPU as a measure of active users, but it’s more a measure of active payers.

ARPU Measurement and Install Campaign Vendor Allocation Decisions

ARPU is a powerful metric for both overall and comparative business analysis. Examining your ARPU data across all of your installs, or broad classes of installs like organic versus paid, helps you understand both overall business viability and the quality of your app experience. If, for example, you expected to drive a thousand dollars per user per year, and your business ARPU is running at $50 a year, you have experiential or other product problems that need to be addressed immediately.

Some apps are primarily designed not to drive revenue, but rather to improve overall user experience. These are usually non-game apps for industries like hospitality, where augmenting user experiences is seen as a way to drive loyalty and brand preference. An example would be a companion app for a hotel. Such apps often have relatively low revenue goals – perhaps to simply break even. In this case, you should compare your ARPU to your acquisition cost to see if your app is meeting this admittedly modest goal.

But ARPU data is primarily used to compare vendors and campaigns to one another to determine the quality of users that are being attracted. By examining user ARPU data from different vendors, for example, you can assess if certain partners are attracting higher or lower quality users/customers.

ARPU and ARPPU are both metrics you can calculate easily in the Singular unified analytics platform.

Real-World Example: Average Revenue Per User/Per Paying User

Now let’s look at an example of how ARPU data can help you make better media allocation decisions.

Suppose you worked with just three media vendors to drive installs for your game. All were using the same creative in the same campaign. Over the course of 90 days, you found the following ARPUs:

ARPU

VENDOR A $544.63
VENDOR B $536.51
VENDOR C $213.65

Vendor A is delivering the highest ARPU, at 1.3% above Vendor B and 155% more than Vendor C. Clearly, then, Vendor A and Vendor B are attracting a higher quality user than Vendor C.

That’s important to know because even if Vendor A offers a bit lower cost per game install (CPI) than Vendors A or B, it may not make up for the difference in revenue per game user. If your cost per install for Vendor A were $5, then the CPI for Vendor C would have to be less than $1.95 for it to be as cost effective as Vendor A.

ARPU is a valuable directional measure to consider for gaming budget allocation. If we assume, for example, that Vendor C charges $4 per install, then putting more money into Vendor C is far less profitable than putting it into Vendors A or B. That’s because the ARPU from Vendor C is far lower. But without ARPU, you might rely on CPI to make your allocation decisions. Many companies do, and end up pouring more dollars into channels and vendors that are actually LESS EFFICIENT at driving revenue.

Obviously here, we are focusing on a component of ROI as a way of comparing relative ROI figures.

In the analysis above we focused on differences between vendors’ ARPU. But the same method of analysis can also be used to compare campaigns and creative executions.

Using ARPPU to Analyze Your Game Business

Using ARPPU is most useful for app businesses with revenue coming from a small fraction of total users. For example, a freemium game. ARPPU is a useful measure with which to assess your app monetization process and buyer flow. Because only a small fraction of users are payers, it will be far easier for you to see the effects of a new monetization process on existing buyers.

Here’s what we mean. A 10% improvement in average revenue per payer driven by a better monetization process on a business with 1,000,000 installs but only 30,000 payers would be easy to spot in a test. Half your buyers go through the test process, the other half the control, and we would see a 10% difference. But if we used ARPU, we would be dividing the revenue difference across 500,000 installs, so effects would seem negligible. See below:

USERS IN TEST PAYERS IN TEST REVENUE ARPPU ARPU

TEST CELL

500,000 15,000 $137,500 $9.17 $0.275

CONTROL CELL

500,000 15,000 $125,000 $8.33 $0.250

In this example, a 2.5 cent change in ARPU doesn’t look like much. 2.5 cents. But based upon ARPPU the difference is almost a dollar!

Net, ARPPU is useful in certain circumstances on businesses with far more users than payers.

Singular enables data-oriented marketers to connect, measure, and optimize siloed marketing data, giving them the most vital insights they need to drive ROI. The unified analytics platform tracks over $7 billion in digital marketing spend to revenue and lifetime value across industries including commerce, travel, gaming, entertainment and on-demand services.For more information, click here.
If you’d like to learn more or see a demo of the Singular unified analytics platform, get in touch.