How LinkedIn, Lyft, Poshmark, and Calm align teams for maximum ROI

In some fantasy world, growth marketers have all the cash, corporate support, creative assets, and analytics they need, and can do their jobs in splendid isolation. In the real world? No marketer is an island, every team is an integrated component of the overall organization, and marketing alignment is a tough challenge.

Which means that kindergarten lessons still apply.

And marketers need to play nice with others … for their own good.

Marketing alignment in fast-growing companies

That’s exactly what we recently discussed with key executives at fast-growing Lyft, LinkedIn, Poshmark, and Calm during our recent UNIFY conference.

Specifically, we asked them how marketers should align internal teams to achieve ROI.

On the panel: Esther Hwang, Director of Growth at Poshmark, Ben Shanken, Director of Product and Growth at Lyft, Jake Bailey, Senior Manager, Digital Marketing and Strategy at LinkedIn, and Dun Wang, VP of Product and Growth at Calm. Fabien-Pierre Nicolas, Head of Marketing at SmartNews, moderated.

Fabien-Pierre Nicolas, SmartNews; Esther Hwang, Poshmark; Ben Shanken, Lyft; Jake Bailey, LinkedIn; Dun Wang, Calm.

Here’s a summary of their insights.

Aligning with executive teams

Aligning with the executive can be challenging. Most CxOs don’t know growth marketing, and they may also have a different time-frame for decision-making than campaign-driven marketers. Achieving marketing alignment requires tight coordination.

“At Calm we have three KPIs,” says Calm VP Dun Wang. “It’s purchase conversion, subscriber engagement, and subscriber renewals, so all of the conversations come back to those three metrics.”

That simplifies conversations, because those three key performance indicators are identical all the way up and all the way down the organization. Every decision can be weighed by how it contributes to at least one, and hopefully multiple of the top KPIs.

At Lyft, with 1,600 employees, alignment requires structural thinking.

“We actually invest a lot in building a structure for how we think, and disseminating that structure across the whole company, so that people can be in line with how we think,” says Ben Shanken, Director of Product and Growth.

But it’s also about investment, and investment carries risk.

And that’s something else to consider at the executive level.

“We think about things in terms of how much risk we want to take in terms of learning,” says Shanken.

Aligning with finance teams

Marketing alignment with finance and the CFO matters too. And it’s often not without some history.

“Historically the relationship between finance and marketing has been kind of contentious, because one is the money-spender and one is the money-protector,” says Poshmark Director of Growth Esther Hwang.

That means marketers need to educate finance.

Finance teams typically don’t understand growth activity or marketing, and nuance escapes them. For example, when one channel is killing it, finance might think: invest all your dollars there. Growth marketers, on the other hand, might know that channel, understand its capacity, and understand that there is not enough scale there to withstand doubling or tripling the budget.

But finance often sees things that marketers don’t.

“At the same time the finance team is a really great ally,” says Hwang. “From their vantage point they have a really great way of looking at certain blind spots that the marketing team might have. For example, at Poshmark it was the finance team that pointed out to us the difference in very long LTV for our male users versus our female users … which the growth team, operating much more short-term, weren’t keeping as close an eye on.”

That’s relevant at LinkedIn too:

“From a finance perspective we have to understand the full evolution of a user,” says Jake Bailey, Senior Manager, Digital Marketing and Strategy at LinkedIn. “We have finance partners that are very baked into our everyday engagement.”

Lyft does the same thing: add a finance executive to the marketing and user acquisition group, says Ben Shanken. It’s easier to run the numbers on LTV and budget allocations — and ensure tight feedback loops — when finance has a seat at the table.

Aligning with engineering teams

Science and art. Data and creativity. Marketing and engineering.

Sometimes it seems like marketing and engineering are oil and water. One promises, and the other has to deliver; one builds, and the other has to market. And they don’t always speak the same language.

That’s not the case in the world’s best companies, however.

“We’re fortunate to have very commercially minded engineers,” says Calm’s VP Dun Wang. “They want to know … if they’re going to spend a week working on a feature, how does that affect the user experience and how does that tie back to more revenue for Calm? So we’re super-transparent with that.”

For Poshmark, it’s all about the relationships.

“Our VP of Growth is an ex-engineer … who has a lot of personal relationships [with engineers],” Director Esther Hwang says. “He still makes it a habit to set up unstructured time with engineers … and that’s proven to be very helpful.”

Just one example: Poshmark has set up car pool routes that intentionally mix staff members across departments. In one case, a growth marketer complained to an engineer about the cost of marketing on Facebook. The engineer brainstormed a solution that involved using Facebook social logins as part of the registration flow. It was super-easy to implement, and had a significant benefit.

“That low-hanging fruit improved our registration conversion rate by about five points,” Hwang says.

Lyft engineers collaboration right into standard workflow and employee organization, says Director of Product and Growth Ben Shanken.

“We have a social pod which is an engineer, a data scientist, a program manager, and a marketer,” he says. “We want the engineer to be a channel manager [and] we want the manager to be a marketer.”

The result?

First of all, Lyft has changed the career path of engineers from building technology to making an impact. And secondly, they’ve empowered engineers with ownership of metrics.

Marketing alignment … with other marketing teams

It may sound silly, but marketing does need to align with marketing. Growth marketers have different imperatives, techniques, technologies, and budgets than brand marketers. Performance marketers and user acquisition marketers look at the world differently. Creative teams are not always aligned with marketing managers.

It’s about size.

“As you scale you’re going to run into these more siloed teams in the marketing space,” says LinkedIn’s Jake Bailey. “You have to find a way to bring those together.”

One way LinkedIn has done it is by creating an internal digital agency.

The agency is horizontal, and flows across silos. It leverages what is working in one team with the others, and derives a whole-company number for ROAS, return on ad spend.

“[This] allows us to work together to grow the business as a whole,” Bailey says.

Lyft has a different way of solving a similar problem, and it involves sometimes intentionally building inefficiencies into the system. It sounds paradoxical — or nonsensical — but it’s actually necessary.

“We have huge brand dollars that we do not control,” says Ben Shanken, Lyft’s Director of Product and Growth. “We can try to align our roadmaps … but every time we do that it sort of fails. It all comes down to agreeing on goals … if you do that, then it becomes easier to sequence how we do things.”

One example: brand marketers tend to like the most efficient ways of buying brand: national advertising. But, if you want to be great at measurement, local spend is the way to go.

The solution: sometimes being less efficient at one goal (in this case, brand advertising) to enable long-term efficiencies in another goal (in this case, local performance-oriented advertising).

Aligning with creative teams

Mistakes are great teachers, and Lyft saw this first-hand.

“We did a really bad thing … we gave the marketing team and the creative team a goal to replace all creative within four weeks with winning creative,” says Shanken. “They started cranking out huge amounts of creative, but the downside was they were cutting a lot of corners on analyzing this stuff … and rolling out creatives that weren’t that amazing.”

Lyft adjusted team OKRs (objectives and key results) and fixed the problem.

But this isn’t easy, as Calm also learned.

“For us it was really hard to align creative and UA,” says Dun Wang. “[There were] too many opinions on what ads we should launch and why … most of it not founded on data.”

What helped Calm move faster was empowering user acquisition directors to lead creative as well. Each UA team received design resources … and UA managers were given some leeway in marketing.

“We’re not so precious about the brand,” Wang says.

Aligning with BI/Analytics

Growth marketers live and die by the numbers. So it’s no surprise that the best marketers want super-tight relationships with business intelligence and analytics pros.

“Incorporating biz analytics into your process early is the key to success,” says LinkedIn’s Bailey. “Include them early and include them often. For us, they are the core of the team … without them nothing else would exist.”

Lyft’s Ben Shanken agrees:

“Data science is hugely important to each channel for us, especially as we start to automate and build programmatic,” Shanken says. “Because they’re building the models … they are arguably the most important part of the pod. They are the person making the actual model and algorithm working with the engineer and the marketer to translate logic into model.”

The same is true at Poshmark and Calm, where Wang says that data analysts work on every project and with every team.

Summing up

It’s not often that you can get some of the world’s top marketing experts and user acquisition leaders to open up about the core challenges of their jobs. Watch the whole video to get every last detail.

And one more thing:

Go deeper: check out how top marketers use Singular to get the data-driven insights they need to accelerate their growth.

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.


“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

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.

Solving cross-channel and cross-platform marketing with a modern tech stack

How do you build a modern marketing tech stack for cross-channel and cross-platform marketing? A good start might be emulating some of the best practices of top marketers from Instacart,, HER, and Riot Games.

Dominic Kelly SVP Sales, Singular; Tim Hsu, Head of Growth, Riot Games; Noa Gutterman, Head of Growth Marketing, HER; Guillaume McIntyre, Head of Digital Marketing, Instacart; James Peng, Consultant (formerly:

But don’t expect it to be easy.

Finding the right solutions is tough.

“The martech landscape has grown over 40% year over year,” Tim Hsu, head of growth for Riot Games, said recently at Singular’s UNIFY conference. “The 2018 version of the martech landscape came out in April … in 2011 there were 150 solutions.”

“In 2018 there are 6,800 solutions by 6,200 providers in over 48 categories,” he added. “That is really complex.”

Adding to the challenge are all the new telemetry points you can track as a brand.

IoT adds data from internet-connected fridges, smart door locks, and app-controlled lighting. OTT movies and shows add data from providers like Hulu, Netflix, Apple TV, and Chrome TV … and the emerging ad networks that advertise here. Add it all up and you’re dealing with billion of additional data points even compared to marketing five years ago, Hsu pointed out.

And that’s not even mentioning new avenues marketers are exploring: Alexa skills and Google Actions, augmented reality and mixed reality, plus the whole messaging explosion via Facebook Messenger, WhatsApp, SMS, and other platforms.

James Peng dealt with those challenges at Match, one of the biggest dating services on the planet.

Singular SVP Dominic Kelly

“Match is a two-decade old business … they kind of piled on the marketing stack,” he explained. “My job was to adapt to mobile … how to consolidate all the data from all the sources was challenging.”

As a company with its roots in the dot-com explosion, Match was initially web-based. Making that mobile was the right way to go, but trying to report on cross-platform marketing data — web and mobile data together in a simple, normalized, usable fashion — was challenging, to say the least.

But executives need a single source of truth to sum up overall performance.

For Match, Peng decided Singular was the right solution.

“Singular … was a way to attack that entire structure and allow reporting across all the platforms in a linear fashion,” Peng said. “Singular was a core solution for reporting and replaced the need for the same solution on the desktop side … the solution actually solved for web also as well as mobile at the same time. That was a nice plus.”

One big benefit?

Having your attribution provider and your overall marketing analytics reporting together reduces your need to standardize events, and pre-emptively avoids many of the complications and discrepancies that otherwise marketers have to solve with BI staff or data science experts.

It’s an even tougher challenge for Noa Gutterman, who is the head of growth marketing for HER. Gutterman’s data requirements include meetups and other live events.

Attendees at the UNIFY conference by Singular

“We use 10 to 15 solutions at any given time … we spend most of our money on Google and Facebook, but look hard for non-traditional sources,” Gutterman said. “Assessing metrics from live events is a big struggle … the data we were missing was data from the ticketing platform.”

For Guillaume McIntyre, the head of digital marketing for Instacart, the way to find the right marketing technology solution is in the wisdom of crowds … as long as those crowds are composed of smart marketers.

“You have to be very curious and open-minded to assess new solutions. But you can’t just talk to new vendors all the time, or that’s all you’ll be doing every day,” he said at UNIFY. “I’ll try to talk to smart people, and if they all mention one solution, I’ll investigate it.”

For Instacart, it’s also all about prioritization.

“As soon as you bring in all the sources, the complexity increases significantly,” McIntyre said. “We really prioritize what data what we need.”

Managing complexity is a massive component of digital marketing success today, especially for cross-platform marketing.

Without organization, marketers drown in data. With consolidation and normalization, marketers make smart real-time data-driven decisions that boost performance and turbo-charge ROI.

“I was an early customer of Singular when I was at Twitter,” Hsu said. “We were using two dozen supply sources … so the data explosion that Gadi talked about was very real for us. The reason we partnered with Singular is that I had my data science pod doing the work initially … and it’s the opportunity cost of what they could be doing otherwise. Partnering with a platform that has done the data integrations and has done the sanitization is a pretty big deal.”

That’s true for both “traditional” customer acquisition and, on mobile, user acquisition.

Dig deeper: See how the best marketers are making sense of cross-channel and cross-platform marketing data.

Data explosion: The ugly truth facing modern marketing technology stacks

Marketing technology is a fast-growing industry. It’s worth $230 billion each year and growing 20% year over year, Singular CEO Gadi Eliashiv said recently at UNIFY.

But that’s slow growth compare to marketing data itself.

“Marketing data is exploding,” Eliashiv said. “It’s growing much faster than the industry itself.”


There are more connected people, many with multiple devices. That’s more digital activity, all of which generates more data and more statistics. There are more software solutions for both martech and adtech, and each of them ingests, consumes, and generates additional data.

And with that increased digital activity — more of the customer journey is digital now than ever before — marketers have built more metrics to understand what visitors and users and customers are doing.

The current marketing tech stack for an enterprise can easily include more than 100 martech tools, Eliashiv said. The average enterprise currently has 91 cloud services for marketing, according to Netskope data cited by Kleiner Perkins and “chief martech” Scott Brinker.

This puts huge power in the hands of marketers.

But it’s also a huge problem.

“This creates major challenges for marketers,” Eliashiv says. “The data is siloed, the data is non-standardized, and the data is not actionable.”

If it was only siloed, the solution might be simple, though tedious: logging into multiple dashboards, downloading multiple PDF reports, exporting multiple Excel spreadsheets, and combining them all in an internal BI system, or a monster spreadsheet.

And … doing the same task every single week (unless you want more real-time data, in which case you could do it more often.)

But the data is also non-standardized. Naming conventions differ. Definitions of terms like “viewable” differ. Percentages are on different base figures. Conversions mean different things in different systems. So the data needs to be normalized in order to make sense.

Only then is it truly actionable.

Singular CEO Gadi Eliashiv
Singular CEO Gadi Eliashiv

“We make sense of it all,” Eliashiv said. “We built an infrastructure that will collect all the information from every solution possible, and then offer insights on top of it.”

That includes marketing data: what the team is doing, where they’re spending money, and what campaigns are going on across all channels and partners. It includes attribution data, which is simply linking that marketing data with outcomes. And it includes customer data: the KPIs or actions that marketing departments are trying to drive.

“The core challenge for marketers is how you make your data actionable,” Eliashiv says.

“To help marketers succeed in this fragmented space, we’re doing three things: connecting all the data from all the silos, standardizing this information so it is ready for consumption and analysis, and analyzing the information and making it actionable.”

Those three simple-sounding steps?

They take the data explosion — an ugly, inconvenient challenge for many modern marketers — and make it an incomparable asset.

Go deeper: Find out how Lyft and Match accelerate their growth.

Unify: Bringing the Marketing World Together

A little over a month ago we held our inaugural UNIFY conference.

The dream for this conference started years ago. Singular is a community, and our employees, partners, and customers are our family. Our family’s mission is to unify data across the marketing ecosystem, and we do that for the best and brightest in the industry.

Our goal since day one — and our goal at the UNIFY conference — was to share the insights we unlock to marketers everywhere.

The best part about UNIFY?

We learned from some of the best about how to beat the rest. A literally all-star cast of speakers shared some of the ways they became all-stars.

Something even better, however, is that over the next week or so, we’re going to share their insights with you … right here on the Singular blog.

That includes top executives from Lyft and Poshmark. Senior leaders from LinkedIn, and VPs from companies like Calm, JamCity, Postmates, and N3twork. We learned about fraud from IronSource’s head of growth, and multi-touch attribution from Lyft’s head of marketing science. Top marketers from Instacart, Kabam, Small Giant, and Riot Games shared how they build their tech stacks and what drives outsized growth. Yelp execs spoke, along with leaders from Nexon, SmartNews, and

And Singular’s own CEO, Gadi Eliashiv, shared what’s changing in marketing technology, how those changes are impacting growth teams, and what marketing leaders can do to win today.

Here’s just a taste of the atmosphere and environment:

As you can see, the quality was amazing. And the feedback was incredible.

But there’s more. And it’s just for you.

We’re going to be sharing detailed insights on how all of these marketing superstars lead their world-class organizations … with full video.

I’ll update this post with the links as those posts go live over the next 7-10 days. So I strongly advise you to check this space regularly to learn from the leading stars of our industry. Over the next few days, you’ll get a chance to peek inside the curtain and see part of what made them so successful.

Our goal? Providing the tools that you need so you can join them.

Here’s the list of coming posts and videos:

  1. Data explosion: The ugly truth facing modern marketing technology stacks
  2. Solving cross-channel and cross-platform marketing with a modern tech stack
  3. 8 reasons why digital marketers need need need granularity (from experts at Kabam, Yelp, Nexon, N3twork)
  4. Marketing alignment: How LinkedIn, Lyft, Poshmark, and Calm align exec, finance, tech, creative, and BI teams for maximum ROI
  5. Mobile ad fraud: 6 ways fraudsters win via dirty tricks, nasty scams, illegal tech, and cutting-edge camouflage
  6. The hype is real: Lyft head of marketing science Alok Gupta on marketing measurement

If you came to UNIFY: thank you. You helped make it a truly special occasion.

But if you couldn’t get a ticket this year … we look forward to seeing you next year!

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.

Newcomer’s Guide to Mobile App Tracking

The mobile app tracking category is well established, and most leading app publishers already leverage attribution to measure their marketing effectiveness. But the dynamics of the cell phone app business are such that new companies are constantly entering the arena, launching branded apps in a variety of categories, from gaming, to retail, to travel, to on-demand services, and more.

That means that there are always smart, strategic marketers who need an introduction to mobile app tracking — this very different form of attribution. Mobile phone app tracking is fundamentally different from web-based marketing attribution, which relies on cookies and pixel tags. This post is designed to help those people understand how mobile app attribution works for Android and iPhone apps, how it differs from other forms of digital attribution, and why its processes are different from those you may be used to.

This post is focused on what sophisticated, data-centric app marketers do for mobile app racking. Such companies use third-party mobile device app attribution systems to track and attribute installs and remarketing events, much as web-based marketers use an ad server like DoubleClick to track and attribute display ad campaigns on the PC web. Because Singular focuses on Android and iPhone app tracking for enterprise marketers, we will confine this explanation for how such large app publishers get the breadth and depth of information necessary for attribution and campaign optimization.

Web-Based Tracking Versus Mobile App Tracking

If you’ve been active in digital for more than 7 minutes, you’re probably somewhat familiar with both third-party cookies and pixel tags, and how they are used for marketing attribution. Third-party cookies are used by ad servers to anonymously identify users across a variety of touchpoints. When a user’s browser requests a web page that will contain an advertiser’s promotional creative, the server places a cookie on their device and assigns it a unique user ID. When the user’s browser requests other pages containing ads from the advertiser, the cookie on the device delivers the unique ID to the server, so that the various ad views can be associated to the same user. In this way, a third-party cookie is designed to associate all of a user’s exposure and actions in that browser to one ID. When a user converts, the completion action is tied back to specific marketing activity through the cookie ID.

Cookies are the go-to technology for most web tracking, but they have serious shortcomings because:

  • Many consumers clear their cookies or set their browsers to block them.
  • Most cookies have expiries — often 28 or 30 days after they are initially placed.
  • In addition, many people use multiple browser instances, like one on a home and another on a work PC.

A cookie ID by itself can only track a user’s activity within one browser instance. To connect a user’s behavior across multiple browsers and devices, other technologies must supplement.

Mobile App Tracking

Many PC marketers who transition to the app industry erroneously assume that cookies and pixel tags will also play a central role in these mobile analytics use cases. But cookies are problematic in mobile for a variety of reasons.

Both Google and Apple have deliberately designed their respective iOS and Android device app ecosystems to limit tracking with cookies. If you want accurate information for attribution and optimization, you need an entirely different system.

Downloads, Installs, and “Installs”

When a user installs an application, they must first download the software. Once downloaded, it is installed on the device automatically. But an install can only be counted — and can only be confirmed and attributed — at the moment of first launch. Think of all this as a multistep process:

  1. A user clicks an ad
  2. They visit the app’s page in the appropriate app store
  3. They click to download the app in the app store
  4. The app automatically installs on the device
  5. The user then opens the app for the first time

An iOS or Android install can be counted only after step five is completed. Thus, when advertisers refer to installs, what they really mean are apps that are installed AND THEN used once. This might sound like a pedantic nuance, but it’s important to understand this to get the full value from the rest of this post. This additional step adds further complexity to an already complex and opaque system.

Let’s dig a little deeper into the steps and the way that desirable consumer actions like installs can be attributed to specific marketing activity. To do that, we need to draw some distinctions between the processes for Android and iOS, the two dominant operating systems. For both OS, the key task is to connect activity that occurs post-app-store with marketing activity that drove the visit to the app store. But beyond that basic similarity, there are some significant differences.

Google Play Versus App Store

There are some process differences between iOS and Android app tracking that require explanation. There is no measurement standard common across both systems. Google Play has been designed to enable some tracking through Google’s sister product, Google Analytics. Google offers an SDK, or software development kit, which enables a referrer url and parameter to be passed to Google Analytics when a user clicks on an ad. If the user installs, the marketing activity can be easily credited. Using the referral parameter, you can track back all post-install activity to the referral source.

WIth Apple, things are a little more complex. The App Store does not permit activity tracking within its walled garden. To connect specific installs to the marketing activity that drove them, you need a separate measurement solution that can trace the device ID to specific marketing activity.

Enter Third-Party Mobile App Tracking

Brands are naturally very interested in tracing desirable marketing outcomes to the marketing activity that drove them. Third-party mobile app tracking, like that offered as part of the Singular Unified Analytics solution, makes it possible to connect paid installs across Android and iOS back to the marketing programs that drove them.

To overcome the measurement issues discussed above, most third-party mobile app tracking is delivered using an SDK that is installed within the publisher’s app.

The SDK connects the marketing activity to the desirable action like an install by matching the device advertising ID, which is a (semi) permanent device identifier specifically developed to enable advertisers to measure marketing effectiveness. There are two leading device IDs you will hear about a lot.

IDFA: For iOS (Apple) devices, the ID is called the device identifier for advertisers, or the IDFA. IDFAs help an advertiser identify the specific phone where the ad action takes place. The Apple IDFA doesn’t change unless a user decides to change it in their phone settings. Few consumers feel a need to take this action, so IDFAs can offer a great foundation for a persistent and anonymized consumer profile. Apple introduced IDFA to offer consumers a choice when it comes to interest-based advertising and tracking IDFA is the only ID that Apple allows advertisers to use to understand the advertising actions on its phones.

Android Advertising ID: The Android or Google equivalent to the IDFA is called an Android Advertising ID. These IDs share critical characteristics with IDFAs, in that they are persistent unless or until the user decides to change them. Before Android Advertising ID, advertisers could track actions on Android phones using a device identifier called Android ID (or ANDI.) Users have the option to opt out of Android Advertising ID tracking, or to change their ID periodically.That said, few consumers feel the need to take such action.

With most mobile app tracking, these advertising IDs are the means through which pre-app-store activity like ad clicks are connected to post-app-store activity like first launches.
Sometimes, though, it is not possible to link ad activity to an install with a device advertising ID.

This can be because the consumer has changed their advertising settings by choosing to Limit Ad Tracking on their device. In those situations, a second attribution method called fingerprinting can be deployed. Fingerprinting users other signals to match marketing activity to an install. Such signals are collected by using non-personally identifiable information like IP addresses to infer a connection between an ad click and an install. The accuracy of matching through fingerprinting varies based on the signals available and utilized by the attribution provider, but such matching can often approach the level of accuracy available by matching device IDs.

Attributing Credit for an Install

Advertisers want to know if their paid marketing programs are driving desirable customer actions like installs. Not every install, after all, is driven by advertising. Some installs will occur naturally, without advertising. Others will occur after a user clicks (or views) an ad. By connecting installs and ad clicks to the same device ID, we can identify which of our installs were driven by marketing activity.

But advertisers want to know more than just whether an install was driven by paid marketing. They want to know which programs, partners, creatives etc. were responsible for the install. When a user clicks only one ad prior to an install, it is very straightforward to connect that install to a specific campaign, media vendor and execution.

But many installs occur after a user has taken multiple ad actions. For those instances, attribution providers play a critical role in pinpointing which marketing program and partner was ultimately responsible.

To attribute credit, attribution providers usually leverage “last-click” attribution, which attributes 100% of the credit for an install to the last partner that drove a click. Think of it as an assumption that the last click is the one that got the user to install.

Last-click is the generally accepted model for attribution even though most people in the industry recognize that it has some shortcomings. Its likely, for example, than clicks other than the last click prior to an install deserve some of the credit for that install. That said, last-click is viewed as the best available option given the complex measurement dynamics.

One key issue is that many of the largest vendors are “self-attributing” ad networks. In fact, self-attributing networks make up ⅔ — or more — of media spend across the industry. Here’s how a third-party attribution provider can capture necessary information from a self-attributing network.

A self-attributing network must be queried after an install has occurred to determine whether they drove an ad click. By contrast, most partners automatically report all ad clicks immediately after they occur. Here is a simplified version of the steps for querying a self-attributing partner:

  • The attribution provider captures the device ID when a user first launches a new app.
  • The attribution platform queries all self-attributing partners, asking whether the device ID was influenced by marketing activity on their platforms.
  • Any self-attributing partner responds by telling the attribution provider about the last click that occurred in their networks for a given app’s advertising, and when it occurred.
  • The attribution provider compares the timestamps from those self-attributing networks to the timing of installs recorded by other partners.
  • The most recent click prior to an install is credited with the install.

Since self-attributing networks do not report every click — only the most recent one, there would be no way to attribute installs using a method other than last-click. All partners accept last-click attribution as an attribution method.

Third-Party Attribution Tools for Mobile App Tracking

Without a third-party attribution platform, it would be impossible for marketers to understand which program and partner drove an install. Further, attribution partners ensure that an install is credited only once. This is so that an app publisher doesn’t double- or triple-pay multiple vendors for the same install.

To properly credit every paid install to a marketing program, your attribution provider must have visibility into activity across all your media partners. While many media partners will integrate with any attribution provider, some strictly limit such integrations to a small number of partners.

Facebook, for example, limits access to attribution information, including timestamps, to a handful of companies that they have identified as high quality partners that adhere to stringent data and privacy regulations. Since Facebook often represents more than 40% of an advertiser’s spend, visibility into this leading platform is a critical component of a robust attribution offering. These partners are called Facebook Mobile Measurement Partners, or MMPs.

Similarly, other self-attributing networks choose a select set of partners for attribution. Singular is very proud to offer its clients universal visibility into all of their app media providers, including

In addition to tracking installs, attribution providers also track post-install events like registrations, purchases, and the like. These can also be tracked back to the last-click media partner.

Re-Engagement Tracking

Marketers are increasingly investing time and ad spend to drive desirable consumer actions other than installs. For example, many brands now use advertising to drive incremental purchases or to get cart abandoners to return and transact. Mobile App Tracking providers can also be used to track in-app actions like purchases to the media partner that drove them.

Mobile App Tracking without an SDK

Some brands do not want or permit the addition of SDKs into their apps. For these companies, server-to-server-based mobile app tracking offers a viable measurement alternative. In such cases, mobile app tracking, tasks are still executed by the attribution provider, but the transmission of information becomes the responsibility of the advertiser.

Server to server integrations are fairly uncommon. For Singular, SDK-based attribution accounts for more than 95% of our client business.

View-Through Attribution

An increasing number of advertisers are now measuring “view-through” attribution when no clicks precede an install. View-through identifies the media partner or campaign that displayed an ad to the user, even if there were no clicks. View-through measurement is generally only used when no click precedes the install.

Get in touch with Singular to learn more about our attribution services and our unified mobile analytics platform.

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