John Koetsier, Author at Singular

Singular ROI Index 2019: The unmissable advertising ROI webinar

Singular’s ROI Index is the largest study that ranks top ad networks globally based on their ability to deliver ROI for advertisers. We’ve already published the Index and made it available to the world, giving you the ability to find the best advertising ROI available.

But now it’s time to dig deeper.

This webinar goes beyond the Index to talk about not only where individual media sources rank, but also what some of the key differentiators are.

Meet the experts

To do that, we’re going to bring in the experts: Susan Kuo, Brian Sapp, and Christen Luciano. (Yours truly, John Koetsier, VP of Insights at Singular, will moderate.)

Susan and Christen have deep insight into how various ad partners performed in the Index. Brian has an even deeper insight into what mobile marketers look for, and what they need in terms of advertising ROI from ad networks.

Susan Kuo
COO, Head of Business Development
Susan has an extensive background in mobile ad tech, analytics, and gaming. Prior to Singular, Susan held senior leadership roles at Onavo and InMobi. Susan is an active member of the mobile community and serves on the advisory board for several mobile-focused start-ups.

Brian Sapp
VP, User Acquisition Marketing, Jam City
A mobile veteran with previous roles at Tapjoy and Web Games, Brian manages user acquisition for Jam City, which currently has six of the top 100 highest-grossing games across the App Store and Google Play.

Christen Luciano
Director of Partner Development
Christen oversees Singular’s relationships with key partners. Prior to Singular, she was a product marketing manager with Kenshoo and held multiple additional marketing roles. Her focus is collaborating with top marketing platforms to help advertisers grow reach and maximize performance.

We’ll review the 2019 Singular ROI Index, but also talk about fraud, things marketers need to know about their ad campaigns, some of the biggest surprises, and the role SANs (self-attributing networks like Facebook and Google) should play in marketers’ ad campaigns alongside some of the mid-tier players.

Advertising ROI is critical, of course, but it doesn’t happen in a vacuum.

So we’ll also talk about how to find niches of profitable growth, new innovative players, and what to look out for.

One of the things that the 2019 Singular ROI Index makes very clear is that Snap and Twitter have made significant moves recently in terms of the value they offer to advertisers. We’ve seen that in their recent quarterly reports: Snap grew quarterly revenue almost $100 million year over year, and Twitter had record quarterly earnings.

We’ll talk about what we’re seeing in the platforms that is driving increased advertiser adoption, and we’ll talk about everything else the Index reveals about advertising ROI.

We asked 1500 marketers how they choose ad networks, and the answer was ‘all of the above’

Is it scale? Quality? Lack of fraud? Personal service, or a great digital experience? Amazing technology? Or perhaps a tight focus on your particular niche?

We recently asked 1,500 marketers a simple question:

How do you choose ad networks? And what are the most important elements of that decision?

According to the responses, it’s pretty much all of the above. If they were absolutely forced to just pick one, completely compelled to isolate one single most important factor — on pain of losing their quarterly bonuses or maybe even the free triple-venti-soy-no-foam-lattes at the office — it’d probably be scale and reach.

But it’s a tight competition with the other options.

We only surveyed marketers who actively run ad campaigns. And the results make it clear that ad networks have their work cut out for them, because marketers are not easy customers. Quite simply, when it comes to choosing an ad network, they want it all, and they want it now.

most important factors when choosing an ad network

As we all know, when everything’s a priority, nothing is a priority.

Looking at the results, we’d almost be tempted to say that when marketers are asked to choose ad networks, they don’t have a clue what the most important factors are.

But that’s probably unfair.

Individual marketers probably have a pretty good idea what works for them … and how to improve it. However, it is clear that marketers as a group lack consensus on what’s most important in finding new ad partners.

And that might just be the nature of the beast:

It’s not like this is easy.

Of course fraud protection is important. Of course scale matters. Of course a media source’s target tech can be a difference-maker. It never hurts when an ad network has special ability to focus on your specific vertical. And getting the best quality traffic, users, or customers is essential.

So it’s no surprise which ad networks marketers trust most.

We asked the same marketers that question, and the top four were names your grandparents recognize: Google, Facebook, Amazon, and Apple. They’re all massive companies, name brands, and have largely walled garden ad ecosystems, which typically means extremely low fraud.

But your marketing can’t end there.

Why?

We know that most marketers who are successful use many ad networks. In fact, they typically achieve 60% more conversions with 37% less cost. That’s not easy, and it takes work. Profitably scaling media sources is hard.

When everything matters, all your decisions are challenging. Because not all ad networks have huge scale, or super-strong fraud protection, or amazing targeting. But there are typically pockets of profitable growth spread in many different media sources.

Singular Korea launches with new office and business unit, leading expansion in Asia

Singular is pleased to announce that it has established a new office and business entity in Seoul, Korea, which will help Singular serve both Korea and the broader Asian market.

Seven of the top 10 mobile gaming publishers in Korea are Singular customers, and Singular’s team in Korea has grown 10X over the past year.

Leading Singular Korea and wider Asia Pacific operations is General Manager Alvin Kim. A mobile veteran, Kim has had executive positions with Opera (AdColony), TUNE, and AppDisco after founding his own mobile marketing company.

Singular Korea general manager Alvin Kim – Kim has a Master of Business Administration from Sogang University, and is well-known and respected in the industry.

“The mobile marketing market is changing rapidly and marketing risks are increasing due to unpredictable variables,” says Kim. “With this complex and intricate marketing performance analysis, Singular is helping marketers run faster and more sophisticated marketing. South Korea is also one of the fastest growing markets in the world and has important implications for entering Asia. Singular Korea will support local marketers and will play an important role as a beachhead for Japan and China.”

Korea is pivotal for Singular.

The country is one of the most highly penetrated mobile markets on the planet.

“Korea is an incredible market,” says Singular CEO Gadi Eliashiv. “The marketers here are extremely savvy, their scale is big, and their challenges are real. That makes this a perfect fit for Singular’s product and technology. In the past year we have built a massive infrastructure here, and have already started taking top market share in key verticals.”

Singular powers profitable customer acquisition by combining upper-funnel campaign and spend data with bottom funnel conversion, attribution, and customer behavior data in one unified view. Deep integrations with more than 2,000 global marketing and advertising partners including official measurement partner status with Google, Facebook, Twitter, Apple, Pinterest, and Quora enable unprecedented data completeness and integrity.

The result is total marketing intelligence: big picture and ground truth. Aggregation, and granularity.

The new office in Seoul will help Singular serve local customers better, and help Singular expand in both China and Japan.

200 CMOs on marketing data: ‘Actionable insights’ are top priority for 2019, followed by consumer privacy

What do brands need most out of their marketing data in 2019?

Actionable insights, consumer privacy protection, and full marketing data unification, chief marketing officers say.

I recently asked 199 CMOs, VPs of marketing, and other marketing leaders what their biggest challenges for marketing data will be in 2019 for a story in Inc. (There was far too much to write there, so this post became necessary.) Tops on marketers’ lists of priorities? Actionable insights in an avalanche of data. But just behind it in today’s climate of consumer privacy breaches was privacy – and trust.

Here’s how Felicity Carson, CMO for IBM’s Watson division, put it:

“Among all the marketing data challenges, the biggest in 2019 will be how marketers instill trust in data – both for the marketing discipline and customers – balanced with the need to improve customer experience.”

The 800-lb gorilla in the room?

Marketers have far too much data already. That’s a consumer privacy risk, but it’s also a potential marketing intelligence nightmare.

“Marketers are drowning in data from various analytics systems,’ says Jo Ann Sanders, VP of Product Marketing at Optimizely. “What marketers are going to have to do going forward … is to go beyond analytics data … and adopt new, agile test and learn practices.”

Marketers don’t need more data.

What they need are actionable insights drawn from the data they already have. Marketers’ third priority, unifying all their marketing data, will help.

“With the exponential growth of data over the past decade and into the new year, it’s becoming harder daily to turn information into action,” says SurveyMonkey CMO Leela Srinivasan. “While more data has the potential to deliver more meaningful insights, prioritizing an action plan to address it is critical.”

Consumer privacy and data security

Insights are essential for growth, that’s clear.

But a strong brand untainted by consumer privacy breaches is also essential for growth. Anyone who feels otherwise, just ask any company that experienced a privacy breach in 2018 … and look at its stock price impact.

That’s why, almost shockingly, marketers’ second-biggest concern has now become consumer privacy, the security of consumer data that brands now possess, and regaining the trust of their customers.

“The single biggest challenge B2B marketers face in the coming year will be balancing privacy and personalization to regain the trust of their audiences,” says Penny Wilson, CMO of social media marketing platform Hootsuite. “That starts with respecting [consumers’] privacy, being open and transparent about when and why data is collected, and then leveraging the data that customers are willing to share to create personalized one-to-one experiences that deliver unique value.”

This requires a massive change in data collection policy.

“Going forward, brands must focus less on maximizing reach, and more on generating transparent, quality engagements that add value to their customers,” Wilson adds.

This is not business as usual for marketers and advertisers, who have typically wanted as much data as possible. In fact, a new “social contract” between brands and consumers will become so important, says Lloyd Adams, SVP at SAP North America, that data ethics will become more important than data analytics.

Unifying marketing data: a top-3 priority

What else do marketers care about?

Not far behind privacy/security/trust, marketers rank unifying marketing data as a top-three priority.

The challenge is obvious.

In a universe of 7,000 marketing and advertising technology tools, marketers are both doing and learning so much more from their prospects and customers. But most of those actions and insights are being generated in siloed, dispersed systems.

“The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration,” says Tim Minahan, CMO of Citrix. “Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.”

The result is not pretty.

“Everyone’s data is a mess,” says Peter Reinhardt, CEO of Segment.

Identifying insights from your marketing data and then unifying them for a single view of customers – and a unified understanding of marketing success – is critical to cleaning it up.

“Data lives in different places — sales, customer service, digital marketing,” says Selligent Marketing Cloud CEO John Hernandez. “The biggest data-related challenge [for 2019] will be consolidation and a full 360-degree view of the customer relationship.”

That’s a difficult challenge, Hernandez says, and CMOs agree.

And in fact, not only is it hard right now … it’s getting harder.

“The biggest issue with marketing data is federating it into a meaningful whole picture,” says Eric Quanstrom, CMO of Cience. “As CMO, I live in (literally) a dozen different dashboards, daily. And that number is growing.”

Marketing data used to be fairly simple: survey data, market data, customer data, product use data, and probabalistic reporting on ad performance in traditional channels. New digital channels offer deterministic reporting possibilities, but with web and mobile and apps and wearables and IoT – to say nothing of platform proliferation like email and social and messaging and search – it’s getting harder.

And all of that proliferation leads to siloed data sets.

The problem with siloed data is that fragmentation subverts complementarity, says Rebecca Mahoney, CMO at MiQ. When data isn’t complementary and doesn’t add up to a complete picture, the marketing results is an inability to detect new opportunities, or see weak links in existing marketing campaigns, she says.

Data lakes may not save marketers, says Daniel Jaye, founder of Aqfer, a data lake provider.

In fact, they can actually exacerbate the problem because most data lakes inevitably become data swamps, Jaye says. Widespread data proliferation, chaotic file partitioning and sharding practices, and the lack of traditional data management tools all cost marketers the opportunity to achieve integrated insights.

Marketing intelligence unifies data insights

But there is hope.

Good marketing data practice does result in growth.

“With a holistic view of data, powered by marketing intelligence, campaign performance will drastically improve, and otherwise unidentified business opportunities will become unlocked,” Mahoney says.

It’s true that not every marketer will have a single marketing cloud for all their marketing technology and data needs. And even most marketing cloud customers also use additional tools to engage and understand their customers.

That suggests that centralization of marketing insights, particularly on paid but also on organic marketing efforts, is what will help marketers the most. Engagement happens where the customers are and data lives in the tools a brand uses to connect with them. Marketing intelligence aggregates then insights from the entire gamut of customer engagement into one single unified view.

(Learn more about that here.)

Other top concerns: quality, quantity, and AI

Marketers are also concerned about the quality of the data that they have, and its accuracy. 13% said that accuracy was a top concern in 2019. Another 12% said they have too much data.

“In many ways, marketing has too much data on its hands,” says David Meiselman, the CMO of corporate catering company exCater.

As Citrix CMO Tim Minahan said above, we’ve put too many tools in place to collect and analyze marketing data. The result is frustration.

A potential savior?

Artificial intelligence.

“We … believe marketing and customer engagement will be an excellent first use-case for enterprise AI,” says Patricia Nagle, CMO at OpenText. “AI systems can analyse structured and unstructured data to identify opportunities for marketing outreach, customer support, and other actions that enhance overall customer experience.”

That’s true, and AI is a tool that marketing is already seeing results from in fraud reduction, creative reporting, and other areas.

But it does some with some dangers as well.

“Deep learning models have been shown to be vulnerable to imperceptible perturbations in data, that dupe models into making wrong predictions or classifications,” says Prasad Chalasani, Chief Scientist at MediaMath. “With the growing reliance on large datasets, AI systems will need to guard against such attacks on data, and the savviest advertisers will increasingly look into adversarial ML techniques to train models to be robust against such attacks.”

And finally … all the other quotes

When you ask 200 top marketers for their insights, you get a lot of insights. And they’re too good to bury.

So here are many of the additional quotes that marketers provided, broken down into categories that I’ve chosen. Some of them are partially referenced above, but are given in complete form here. Each of the responses is answering a simple question:

What are brands’ biggest challenges with marketing data in 2019?

Marketers need: Data accuracy and quality

Peter Reinhardt, co-founder and CEO of Segment

The biggest challenge for marketing data in 2019 will be data correctness. Everyone’s data is a mess. Consumers are bombarded with tons of noise, much of it based on wrong data, names, and locations. As a result, customers are burned out. It doesn’t matter how much a company invests in personalization if the underlying data is incorrect. For businesses to truly succeed in 2019 and beyond, they need to prioritize making sure their data is clean and accurate.

Martha E Krejci, The Tribefinder

The biggest challenge with marketing data in 2019 will be determining how good the data really is. Before this rise in cookie awareness people weren’t really flushing the cookies or clearing their cache as much, which lent itself to long-standing good demographic data. Now, the data isn’t as deep, therefore not as reliable. In 2019, businesses will need to learn to re-target.

Joanne Chaewon Kim, Junggglex

Not surprisingly, war against fraud will be the biggest challenges mobile marketers will have to face. In addition to common fraud cases like SDK spoofing and click spamming, more and more new types of fraud will stop developers from obtaining real users. Our job as mobile marketers is to keep educating ourselves about different types of fraud and the pattern of each fraud cases, so that we can take a proper action when we find them.

Marketers need: Actionable insights and marketing intelligence

Mark Kirschner, CMO, Albert

The best tools solve the disconnect between data, insight, and action, incorporating multiple sources of data to execute, allocate, attribute and optimize digital campaigns across channels.

Tara Hunt, CEO + Partner, Truly

Marketing data still struggles with insights and it would be amazing to see more of a focus on this essential craft. There are endless tools for gathering the WHAT – numbers and histories and basic information about your customers – but very little that helps us figure out the WHY. The big challenge in 2019 (and likely for a few more years) is going to be training people to understand how to read the what to get to that why.

Phil Gerbyshak, Digital Selling and Marketing Strategist

With all the data collected, the biggest challenge with all the marketing data is finding the most meaningful data, and then figuring out the most actionable insight from that meaningful data. Too often reports for reports sake are created, even with AI to help us find the patterns. Taking the time to think about what you want to accomplish and setting up your data accordingly will challenge marketers and delight stakeholders in 2019 and beyond.

David Berkowitz, Principal, Serial Marketer

There is so much data out there that ‘big data’ is no longer the priority; there is a need for actionable data that means something to marketers. The other challenge is that the biggest winners on the platform side are increasingly closed and stingy with their access, which may be necessary for consumers and benefits the platforms but hurts marketers. Finally, marketers will have to grapple with a savvier base of consumers who are constantly reading mainstream press coverage about data abuses; marketers will need to determine how cautious they want to be with collecting and accessing consumer information.

Douglas Karr, CEO, DKnewmedia

What is the biggest data challenge for marketers in 2019?

Building actionable results based off of accurate data. We continue to see an inability of our clients to properly read analytics and come to assumptions. I hope continued AI and machine learning will add tools to assist.

Felicity Carson, CMO, IBM Watson Customer Engagement

Among all the marketing data challenges, the biggest in 2019 will be how marketers instill trust in data – both for the marketing discipline and customers – balanced with the need to improve customer experience by identifying meaningful patterns buried deep within the deluge of data. Compounding this challenge is the need to break down compartmentalized martech and adtech stacks that house this information, coupled with the need to have contextualized understanding of aggregated customer data across the organization such as commerce and digital teams. Marketing teams will need to rely on AI to achieve this level of high performance at scale, particularly in the new era of the ‘Emotion Economy’ that requires organizations to engage with customers in relevant ways on issues that personally matter to them.

Julie Huval, Beck Technology

The biggest challenge with marketing data in 2019 will be to decipher which of the outlier [datapoints] are leading indicators into new market growth.

Leela Srinivasan, CMO of SurveyMonkey

Today, we have access to more data than ever before, but with the exponential growth of data over the past decade and into the new year, it’s becoming harder daily to turn information into action. A study by IDC bleakly projects that by the end of 2025 only 15% of global data will be tagged; of that, only 20% will be analyzed and approximately 6% will be useful.

While more data has the potential to deliver more meaningful insights, prioritizing an action plan to address it is critical. In 2019, B2B marketers will be laser-focused on finding a way to cut through the massive troves of data available and identify the insights that matter most.

Christina Warner, Walgreens Boots Alliance

The biggest challenge with marketing data is the ability to find the useful insights to create concrete actionable next steps. We have so much data, but not enough of an efficient way to sift through the noise accurately for truly useful data.

Lauren Collalto-Rieske, CMO, Contap Social

The biggest challenges we have as a startup are: having easy-to-use data that doesn’t require a ton of training like a Nielsen or IRI platform and being able to triangulate all of our data among a two-person team. Right now, we are using about 8 different vendors to analyze one or more stages within the customer lifecycle, and while it’s great to have all of this data, it’s not easy to triangulate it. It would be great to have 1 platform that could assess all or most of our marketing program’s performance, but those platforms usually come with a large price tag that we can’t afford.

Moshe Vaknin, CEO and CO-Founder, YouAppi

One of the biggest challenges marketers will face in 2019 is how to better analyze consumer behavior and turn those insights into effective marketing. Consumers spend 40 hours a month and three hours a day in apps, mobile time spent will surpass time spent in TV in 2019, so marketers need to change their traditional planning behaviors for this brave new world. They must integrate their traditional teams with their digital teams, combine their video teams into one cohesive team, and integrate the data across all channels so that they can be smarter about how they find their most valuable customers. It is also getting harder with privacy, however, companies with strong technology especially predictive algorithms can predict users intentions based on less data. We are just scratching the surface on data analysis and with new data privacy laws, this challenge will only get harder.

Tim Minahan, Chief Marketing Officer and SVP, Citrix

Every marketing challenge can be whittled down to a mathematical equation – whether it’s measuring customer sentiment, tracking conversions, or weighing the return on a particular campaign. Data-driven marketing can eliminate much of the he-said/she-said friction that has historically muddied sales and marketing relationships. It can cut through emotional biases and drive the right course of action to reach and win the market and deliver the best results. The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration. Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.

To tackle this problem, marketing organizations need to tap into intelligent technologies like machine learning that can make data-driven marketing smarter and easier to execute. Machines can recognize patterns and analyze things with greater speed and efficiency and automatically deliver insights and intelligence that humans can use to make more informed decisions and engage customers and prospects in the most optimal way. And beyond tools that automate tasks and make marketing more efficient, we need to equip our teams with solutions that enable them to push the envelope. Like using artificial intelligence and machine learning to see data in new and innovative ways. Or leveraging augmented reality to create entirely new worlds where we can interact with customers in insanely personal ways.

Julia Stead, VP of Marketing, Invoca

As marketing tools and automated solutions continue to flood the market, the biggest challenge marketers will face is applying data to create timely, emotionally-reciprocal experiences. More and more consumers desire a human to human connection and want to communicate with an empathic human rather than a bot or an algorithm. The year ahead will be a pivotal milestone for marketers and brands, the ones that use their data to better understand consumer behavior and leverage it to create more personalized, human connections will succeed, while the ones that do not will risk losing loyal customers.

Tirena Dingeldein, Research Director, Capterra

In 2018, if you’re a marketing professional that listened to recommendations of marketing experts everywhere, you collected a lot of customer data and used it to formulate campaigns. The problem of moving marketing forward into 2019 is two-fold; security and recognizing changes in data before solid patterns are defined. Data security, obviously, will be most important for maintaining trust between marketing and their audience, whereas recognizing emerging patterns in the data deluge will mean the difference between cutting-edge marketing or just ‘catching up’ marketing in the new year.

Sid Bharath, growth marketing consultant for tech startups

The biggest challenge with marketing data is figuring out what signals to pay attention to and how to prioritize them. With an explosion of data, the bottleneck moves to how fast you can execute on what the data tells you, and unless you have unlimited resources, you need to prioritize them.

Kent Lewis, Anvil Media

The biggest challenge with marketing data in the coming year will be gaining actionable insight from a flood of data generated via a diverse and numerous set of online (and offline) channels, including social media, website, email, events, PR and advertising.

Daniel Raskin, CMO, Kinetica

The Marketing Data Scientist will be focused on deriving detailed insight about customer behavior and producing reliable predictive and prescriptive insights based on complex data models and machine learning. These models will evolve from historical analysis into real-time applications that transform how products are delivered to customers.

Gennady Gomez, Director of Digital Marketing, Eightfive PR

As marketing data becomes not only more accessible but also much more bountiful, there will be an exponential increase in analysis paralysis. As a result, we’ll start to see the focus in martech shift from data mining to insights reporting, driven by data science and machine learning. These new breed of tools will be critical for marketers as they sort through, identify, and filter actionable data.

Jordan Bishop, Partner, Storied Agency

Until our ability to glean insights from all this data catches up to our ability to capture it, we’ll face the same issue as a city with plenty of cars and not enough roads: traffic. Don’t confuse having more data with having more insights.

Marketers need: Unified data

John Hernandez, CEO, Selligent Marketing Cloud

The biggest data-related challenge will be consolidation and a full 360-degree view of the customer relationship. As it stands, data lives in different places — sales, customer service, digital marketing — and migrating it into a single platform and making sense of it all is going to be difficult. I hope that in a year’s time, we’ll see a lot of progress and proof that leveraging data to focus on delivering personalized, more relevant experiences is the optimum path for better engagement, stronger sales pipelines, and more meaningful marketing results.

Latane Conant, CMO, 6sense

Emerging technology has improved marketing strategy, but the challenge marketers are facing is the daunting task of managing a large number of applications. In the next year, more CMOs need to take a platform approach. Investing in a platform that can be integrated into an existing CRM allows organizations to easily unify their revenue teams, and with the addition of AI incorporated into the platform, unified teams have insight into the behavior of modern buyers with the use of real-time data.

Meisha Bochicchio, PlanSource

Connecting the dots between marketing touch points and giving proper attribution has been and will remain a major challenge for marketers in 2019 … it can be hard to get a full 360-degree view of the true marketing and sales funnel … it is still nearly impossible to combine data from multiple touch points … to paint a full picture of marketing efforts and sales results.

Dietmar Rietsch, CEO, Pimcore

Many marketers have so much data from multiple domains on hand, but no way to streamline and manage it in one centralized location to gain valuable insights.

Eric Quanstrom, CMO, Cience

The biggest issue with marketing data is federating it into a meaningful whole picture. As CMO, I live in (literally) a dozen different dashboards, daily. And that number is growing.

Daniel Jaye, Founder, Aqfer

2019 will be the year enterprises discover that serverless data lakes are a thing, and that they inevitably become data swamps due to widespread data proliferation, chaotic file partitioning/sharding practices, and the lack of traditional data management tools. As marketers are still floundering to piece together the data and figure out whether or not campaigns truly succeeded—they will realize that they can’t keep their heads in the sand on data any longer, and must work to get a better grasp on data management in order to get to the truth about their customers.

Kelly Boyer Sagert, Dagmar Marketing

The biggest challenge will be how to tie all the data together to clearly identify what marketing channels are working or not working. There are multiple touch points to a buyer’s journey and it’s very common to see multiple marketing channels involved in the buyer’s decision, which makes it hard for analytics tools to attribute accurately what marketing channel contributed the most.

Amanda Romano, Twenty Over Ten

The biggest challenge in 2019 will be the ability to bring together … multiple sources of data to connect the dots, make informed decisions and act quickly on those insights.

Aman Naimat, CTO, Demandbase

The marketing technology landscape is increasingly fragmented and that’s not going to slow down. But marketers will need to find a solution to stop isolated data sources from negatively impacting their marketing capabilities in 2019. By integrating key marketing technologies such as CRM, marketing automation and ABM platforms, marketers can start to share data across these applications and get the complete customer view that they crave.

Rebecca Mahoney, CMO, MiQ

Businesses have a wealth of valuable marketing data available to them, but complications arise when this data remains in siloes pertaining to the different departments within that business. This prevents the data from being complementary, and businesses cannot detect potential weak links or new opportunities. With a holistic view of data, powered by marketing intelligence, campaign performance will drastically improve, and otherwise unidentified business opportunities will become unlocked.

Brian Czarny, CMO, Factual

In 2019, marketers will be faced with the challenge of data implementation. Marketers know how valuable data is, but struggle to make sense of it as they’re faced with the challenge of navigating numerous fragmented platforms and systems to get accurate and quality data. The goal is to gather data from multiple sources that work together to achieve optimum success, but there isn’t one standard way to streamline data. Eventually, unlocking this will give marketers the capability to improve context, relevance, and develop creative that resonates.

Eric Keating, VP Marketing, Zaius

The key is to centralize … data and connect every interaction to a single customer ID. Then you can actually understand how your customer behaves across channels and devices. But even more importantly, that data has to connect to your marketing execution platforms directly, so you actually use those insights to power your marketing.

Marketers need: AI and machine learning

Prasad Chalasani, Chief Scientist, MediaMath

The increase and abundance of data that is available now due to integrated marketing platforms will demonstrate the flaws in various deep learning models. Deep learning models have been shown to be vulnerable to imperceptible perturbations in data, that dupe models into making wrong predictions or classifications. With the growing reliance on large datasets, AI systems will need to guard against such attacks on data, and the savviest advertisers will increasingly look into adversarial ML techniques to train models to be robust against such attacks.

Pini Yakuel, CEO and Founder, Optimove

Marketers are equipped with more consumer data than ever before, which can give them valuable insights into their customer base. Many are eager to use AI to automate and personalize communications, but lack the proper infrastructure and data know-how for AI to work properly. There are countless marketing AI platforms available, but until brands are able to properly segment their datasets and make their data truly work for them, they won’t have the ability to conduct innately intelligent marketing. What does this kind of marketing look like? All the marketer needs to do is set the framework, and the AI takes it from there to create personalized messaging for consumers. In 2019, we can expect to see a push from brands to organize their data within a framework that allows them to hyper-personalize communications.

Patricia Nagle: Senior Vice President, CMO, OpenText

Analytics continue to be a critical way to review the impact of marketing on business objectives. In 2019 the continued adoption of dashboard reporting and analysis systems will improve how we measure marketing programs and tactics. With better understanding of all marketing functions, organizations can take a more strategic approach and focus on what’s performing best. We also believe marketing and customer engagement will be an excellent first use-case for enterprise AI. AI systems can analyse structured and unstructured data to identify opportunities for marketing outreach, customer support, and other actions that enhance overall customer experience.

Jonathan Poston, Director, Tombras

We are collecting and analyzing real time data using AI powered platforms … we are telling the story, giving shape and voice to the billions of data points that would otherwise be a bottomless inkwell of unrealized potential.

Brandon Andersen, Chief Strategist, Ceralytics

Marketing data and insights [will become] cheaper due to marketing AI platforms. It will no longer take big budgets, multiple data vendors, and a team of analysts to get actionable insights.

Marketers need: Data security, consumer trust, privacy

Lloyd Adams, SVP, SAP North America

Data ethics will become more important than data analytics.

Jeremiah Owyang, Jessica Groopman, Jaimy Szymanski & Rebecca Lieb, Kaleido Insights

In 2019, marketers will struggle with the social contract of data exchange between consumers and brands. They’ll wrestle with these questions: How will users be compensated beyond personalization? How can marketers do this without being “creepy”? And, as more biometric data emerges, how can marketers use in an ethical manner?

Augie Ray, Director, Gartner

Making better and more critical decisions about what to collect, how to protect it, how to combine it, and how to use it. The idea of a “360-degree view of the customer” has encouraged brands to collect as much data as possible, but this should never be a goal because it raises risks such as privacy concerns, data breaches, GDPR compliance, and customer distrust. Marketers and customer experience leaders need to focus on prioritizing their data needs, better assessing risks, and developing a data strategy that prioritizes and centers on what data is essential and how it will be used over accumulating more of it.

Penny Wilson, CMO, Hootsuite

The single biggest challenge B2B marketers face in the coming year will be balancing privacy and personalization to regain the trust of their audiences. In many ways, 2018 was a tumultuous year for brands, marketers, and customer experience leaders. Concerns around fake news, fake followers, and data privacy led individuals to question their trust in politicians, media outlets, social networks, and businesses alike. Those same concerns extended to how brands — both B2C and B2B — forge relationships with customers, and the data they use to do so. The priority for B2B marketers in 2019 must be to reassure customers – and their customers’ customers – their data is safe and secure. This has to be achieved in the changing climate of customer expectations. Increasingly customers — be they businesses or individuals — are expecting content that is important, interesting and timely to them. That starts with respecting their privacy, being open and transparent about when and why data is collected, and then leveraging the data that customers are willing to share to create personalized 1:1 experiences that deliver unique value. Going forward, brands must focus less on maximizing reach, and more on generating transparent, quality engagements that add value to their customers.

Mike Herrick, SVP, Urban Airship

The biggest challenge marketers will face in 2019 is activating their first party data and growing its use. Brands are facing a privacy paradox as customers increasingly expect personalized service, but both data regulations and consumer privacy controls whittle away at third-party data and tracking. To remain compliant and provide great customer experiences, brands will increasingly rely on data customers willingly provide in the course of direct interactions across engagement channels–websites, apps, messages, social and in-store interactions and more. The best brands will go beyond gaining opt-ins, subscriptions and followers, and use these interactions to collect context and content preferences for each individual.

Tifenn Dano Kwan, CMO, SAP Ariba

A greater focus needs to be on being data compliant as well as on the ease of leveraging data.

Kedar Deshpande, VP, Zappos

The biggest challenge with marketing data stems from the fact that marketers have so much data available to them today, which they’re able to use to reach customers in a very precise way, yet there’s currently a huge lack of communication between brands and customers as to how and why that data is being used. Without more transparency with customers around why personalized outreach is happening and how it’s benefiting them, the immediate reaction is one of distrust, uncertainty, and even fear or anger. In 2019, brands need to focus on clear messaging that explains to customers why they’re using personalization tactics, how their privacy is protected, and what they stand to gain from it.

Briana Brownell, CEO, PureStrategy

With ad-blockers becoming ubiquitous and privacy concerns reaching a fever pitch, marketers need to rebuild the trust that has been lost with consumers. Some of the most successful marketing campaigns in recent times have been honest and authentic, sometimes to the point of distress: KFC’s apology for running out of chicken and Nike’s partnership with controversial quarterback Colin Kaepernick. The biggest challenge in 2019 and beyond will be to create a new normal between marketers and consumers.

Len Shneyder, VP, SendGrid

May 25, 2019 will mark 1 year since GDPR came into force in the EU. This privacy law sets concrete standards on how EU citizen data has to be treated in addition to strict guidelines on consent. Successful senders will have taken stock of this law and enacted internal processes to ensure compliance with European law.

Ben Plomion, CMO, GumGum

As data protection regulations like GDPR become increasingly prevalent in 2019, marketers will struggle to target customers with individually customized online advertising. The most successful marketers will be those who can deliver individualized experiences, without individual user data. Computer vision and other contextual analysis technologies will be necessary to anonymously align ads with the likeliest potential customers.

Esteban Contreras, Senior Director, Hootsuite

We have more data than ever before in history and that in itself is a challenge. One of the most important problems to overcome is how to effectively handle and leverage data – data engineering, data analysis and data science – with legitimate consumer empathy. We need to consider privacy by design. The ethical use of big and small data is ultimately about creating value (e.g. personalizing and contextualizing experiences) without misleading or dehumanizing anyone.

Marketers need: Less data (or at least, smarter data)

Alyssa Hanson, Intouch Insight

The biggest challenge with marketing data will be having too much of it, specifically for B2C organizations.

Marketers crave access to information, but we’re drowning in a virtual quagmire of data. We want to get granular, digging deeper into every data point, but we’re stuck with analysis paralysis — unable to prioritize actions that will have the greatest impact on our KPIs.

Marketers will need a cutting-edge customer experience platform that recommend strategic actions tied to specific KPIs.

Hillel Fuld, Strategic Advisor

Noise. There is a lot of it and it is increasing exponentially. As data volumes increase, the tools we will need to filter it all and extract the valuable components will have to increase in their abilities accordingly.

Tom Bennet, Head of Analytics, Builtvisible

The sheer volume of data being collected is itself posing a challenge to marketers. As we move into 2019, the ability to separate out meaningful patterns and relevant trends from the vast quantities of background noise will be a real test for many marketing teams.

Neil Callanan, Founder, MeetBrief

Because there’s just more and more data with disparate KPIs coming from different sources, the biggest challenge will be in deciding what to ignore and what to value.

Alicia Ward, Flauk

I predict a big challenge for marketers in 2019 will be remembering to use data as only part of the story and keep an eye on the bigger picture. How many times have any of us been hit with poor targeting because of something else we’ve liked or clicked on? It will be important for marketers to remember that the people they are marketing to are real, complex people who should be considered as more than just a few data points.

Matt Hogan, Head of Customer Success, Intricately

The biggest challenge for marketers is focusing on the data that matters. There is a lot of noise out there and each team member needs to know which data is significant to their success. But, it’s not just about having the data but putting it into context to make strategic revenue-driving business decisions. If you aren’t able to execute on your marketing data, it is useless.

Zachary Weiner, CEO, Emerging Insider

I think the core problem moving into 2019 where marketing data is concerned is that with ever increasing amounts of data, marketers are still looking at each marketing silo individually or in small affiliated clusters as opposed to cross-analyzing insights across the entire marketing, sales and customer service value-chain. Often silo based marketing teams will look individually at social data, demand-gen, PR, sales and customer service rather than studying where they intersect and interact. This has always been faulty and is continuing to be a greater problem as each and every silo continues to yield more data.

Jo Ann Sanders, VP of Product Marketing, Optimizely

The biggest challenge marketers will face in 2019 is getting access to the right data to know definitively what their digital users want. Marketers are drowning in data from various analytics systems that provide a historical view of the past. They then ideate ways to improve based on this past data, spend resources to deploy updates, and then re-measure to see if their ideas worked. This process of guessing at what will improve conversion metrics can take weeks or months.

What marketers are going to have to do going forward to succeed so they can keep pace with rapid innovation is to go beyond analytics data that tells them where they have been and adopt new, agile test and learn practices. This will take the guesswork out of what users want, and better ensure that they are rolling out winning user experiences quickly.

With the proliferation of marketing data the challenge will be how to use the latest tools to narrow 1000 points of data down into the few key quality ones that are needed to improve business operations and to better communicate with your customer.

David Meiselman, CMO, exCater

In many ways, marketing has too much data on its hands. The challenge is to figure out which data helps the most to optimize targeting, messaging, and conversions. Traditionally, marketers would work their way through countless A-B tests to determine what works. Today, machine learning and artificial intelligence is helping us accelerate that process to detect correlations and causal factors to improve marketing outcomes across the board, from which people to target for highest conversion to what message to send when for greatest effect.

Tim Minahan, CMO, Citrix

The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration. Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.

Matt Buder Shapiro, Founder & CMO, MedPilot

For many years we’ve been trying accumulate as much data as possible, and we’re now ironically in a difficult position of potentially having too much data. We need to remember to sit back and discover what is actually happening at different points in time, so that we can figure out how it all fits together. We also can never forget that the most important data point when building attribution is still “Where did you hear about us?”

Marketers need: Many more things

These quotes don’t fit an exact category. But they’re too good to not use.

Jenni Schaub, Strategic Planning Director, DEG Digital

But always still remember, a mountain of data is not a replacement for empathy

Stephanie Smith, Co-Founder and President, MOJO PSG

Thoughtfully exploring and formulating the question you’re actually trying to use data to answer is a key challenge that marketers must face in 2019. Without taking the time to define the problem we’re solving for, we end up wasting a lot of time swimming in seas of data and even potentially misusing the data we uncover. Marketers must also find a balance between using data to inform, rather than dictate, decisions, as the marketing craft will always be a blend of art and science.

Scott Gifis, President of AdRoll Group

Measurement is hard. For SMBs and mid-market companies, it is harder, and the stakes are often higher. Although last click measurement is an archaic way to measure performance and impact, many marketers still rely on it because they don’t see accessible alternatives, as sophisticated tools are often difficult to set up or not flexible enough to work within their data model.. Yet, marketers are hungry for change and searching for a better way to provide visibility and optimize their campaigns. I see 2019 as the year modern marketers stop relying on vanity metrics and outdated measurement models and start looking at what is actually driving sales. Further, marketers need to embrace multi-channel adoption and prioritize creating connected stories across all touchpoints.

Norman Guadagno, Head of Marketing, Carbonite

The biggest challenge for marketers will be navigating the evolution of what marketing is in a post-truth world. In 2019, marketers will need to ask themselves the difference between truth and propaganda.

Summary

Thanks to all the marketers who participated in this research, which was initially for my column in Inc, but grew beyond that.

Clearly, there’s a significant change in marketing data policy coming. Marketers know that it’s not about quantity of data but quality. They also know that insights on next best actions is the thing they need their data to reveal. And they are more than cognizant now that consumer privacy matters, and companies that violate their customers’ and prospects’ trust do get punished, both financially and in reputation.

We have to give the last word to Jolene Rheaulot from The Bid Lab.

She said this, which every marketer should remember:

The biggest challenge with the breadth of marketing data available to a company is to keep the data human.

. . .

Looking for a platform to unify your marketing data and derive smart insights on how to grow?

Get a demo and see if Singular is for you.

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.

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.

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.”

Why?

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.

“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 Grow.co.

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.

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.

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!

Top Takeaways From Singular’s ‘Spot the Fraud’ Event

Singular recently hosted our first-ever “Spot the Fraud” event, where mobile marketing and product leaders from companies like Airbnb, Instacart, Postmates and N3TWORK gathered to discuss the future of mobile ad fraud prevention.

At the event, Singular CEO Gadi Eliashiv unveiled Singular’s enhanced Fraud Prevention Suite as well as The Singular Fraud Index, a first-of-its-kind study revealing the industry’s most effective fraud prevention methods along with the 20 mobile ad networks driving the lowest rates of fraud.

The full presentation can viewed by clicking here and below are the top takeaways from the presentation.

Mobile Marketers, Still Unprotected

In the process of analyzing fraud data from hundreds of the world’s largest mobile apps, Singular’s Fraud Prevention Team uncovered a startling stat: 63 percent of marketers do not utilize fraud prevention techniques in their mobile marketing systems. Part of the blame lies with analytics providers that treat fraud prevention as a luxury, offering it to marketers as a “premium” add-on rather than a feature deeply embedded in the core platform. Equally problematic is the complexity of existing fraud offerings — for instance, attribution platforms that place the burden on marketers to run their own statistical analysis to detect fraud.

The Threat of Attribution Manipulation

Today the majority of mobile ad fraud is perpetrated via attribution manipulation, whereby fraudsters steal credit for installs from organic and paid channels. Each month, attribution manipulation attacks account for roughly 70 percent of prevented ad fraud, recent data from Singular shows, costing ad networks and marketers money and corrupting performance data in the process.

But big tech players are working to fix the analytics holes that have allowed fraudsters to steal credit for installs. For instance, Google’s latest analytics release, the Google Play Referrer API, helps marketers and their attribution providers combat attribution manipulation with Referrer and Timestamp data received directly and securely from Google.

Fraud Keeps Getting Smarter

Singular’s Fraud Prevention Team uncovered a new form of fraud being perpetrated by malicious mobile apps, some of which have millions of users. This form of fraud, called Referrer Injection, leverages Android’s internal messaging system to inject a fake referrer into an attributed ad click, thereby assigning credit to the fraudulent source. Because attribution systems prioritize referrer messages over other touchpoints, Referrer Injection is a particularly effective way for fraudsters to steal credit. Thankfully, Google’s new Referrer API allows Singular to stamp out this form of ad fraud. However, Referrer Injection highlights the fact that marketers must reject complacency given the constantly evolving threat of fraud and implement fraud solutions that adapt to increasingly sophisticated fraud tactics.

Safe Havens

Even with fraudsters siphoning off billions from advertising budgets each, there are safe havens for mobile ad dollars. Singular analyzed mobile ad fraud data anonymously collected from mobile marketers within a 30-day range to identify the most secure mobile media providers, or those with the least fraud. The 20 most secure media providers are capable of driving both significant volume to marketers while keeping fraud rates well below the industry average. To view the complete list of of mobile ad networks driving the lowest rates of fraud, download the full report here.

Comprehensive Protection

As The Singular Fraud Index shows, currently there isn’t one fraud prevention method that reigns supreme in blocking the majority of mobile ad fraud. Singular’s breakdown of the most effective fraud prevention methods reveals that the marketing industry uses a handful of prevention methods to combat mobile ad fraud, with each method blocking its share of total fraud prevented each month.

That’s why Singular’s new Fraud Prevention Suite utilizes all known prevention methods to provide maximum protection against existing fraud threats as well as unknown threats to come.

“You don’t want to chase fraud manually,” Gadi said in his presentation. Marketers don’t have the time and, in most cases, the expertise to identify what is fraud and what is legitimate activity.

Singular is excited to equip its customers with a transparent, flexible and proactive fraud solution that analyzes countless fraud signals at the most granular levels and automatically applies rules at the time of attribution to stop fraud in its tracks, keeping sources clean and media budgets focused on quality users.

Learn more about Singular’s enhanced Fraud Prevention Suite here and download The Singular Fraud Index here.

How Singular Delivers Blazingly Fast App ROI Analytics

Mobile app marketers need access to increasingly granular data to accurately measure app ROI — which inevitably requires processing huge volumes of data on the fly. This can dramatically slow down database query times, creating bottlenecks for marketers and preventing them from optimizing as quickly and as often as they’d like to. Call it the Catch-22 of modern-day mobile marketing: an ever-increasing need for speed amid an ever-increasing flood of data.

At Singular, the issue came to the fore ahead of our latest analytics offering for marketers, Publisher ROI. Publisher ROI allows marketers to quickly expose a breakdown of an ad network’s inventory by publisher and determine the individual sites and apps driving the best performance.

Early testing of the feature showed that customer queries for publisher-level data required an enormous increase in computing power — to the tune of 50-100X the data normally being ingested and processed for queries in Singular. As we saw query times spike during testing, it became clear that we had hit a major startup milestone: We had outgrown our database technologies.

In order to launch our latest innovation, and continue offering mobile app marketers fast and flexible access to increasingly granular marketing data, we would need to introduce a new data pipeline and datastore — one that was capable of enabling ad-hoc queries on a billion rows with sub-second performance.

In this post, we’ll describe how we rebuilt certain components of our database technologies and dramatically increased the speed of our customers’ queries — in some cases by a factor of 150X.

But before we dive into how we accelerated our customers’ queries, it’s worth giving some background on the evolving needs of mobile app marketers, and the sheer size of the data challenges we face in providing them with an analytics platform as flexible as Singular.

From the early days of Singular, we kept a close eye on the kinds of queries our customers were running in Singular. We tried to spot patterns in order to build systems that anticipated the dimensions a marketer might use in their queries. But we quickly found that there was a huge diversity in the reports and queries customers were running, with countless combinations of different dimensions and metrics.

Think about it in terms of rows in a table. Say you advertise on an ad network that runs your ads on 100 different publishers. You might check the overall ROI of the network — with Singular, that’s just one line of data. To then expose a breakdown of each individual publisher’s performance in order to segment high-performing from under-performing publishers, you would need to render 100 rows of data. Now say you’re running 4 multi-country campaigns and you want to see if certain publishers are performing particularly well in certain Geos — now you’re looking at 400 rows. Want to a break out data by iOS and Android? — that’s 800 rows.

This kind of complexity led to our first conclusion about the database architecture that could support our needs. Because usage of Singular is so diverse, with countless combinations of query dimensions, we needed to support ad-hoc queries, or queries that cannot be determined prior to the moment they are issued. As most data engineers know, databases that are truly optimized for ad-hoc querying are usually not good at updating data after it is ingested. We therefore needed to ingest data into our database in its final form.

Data Ingestion at Singular

At Singular, we run around 10,000 marketing data collection tasks a day. Each collection task is responsible for collecting data for a specific customer from one of its third-party marketing vendors from a window of 1-30 days back. Our ingestion pipeline is distinctive in the volume of data each task collects (granular Facebook stats for 30 days is huge) and because we collect data from vendors who tend to update data retroactively on a regular basis, which requires Singular to constantly swap out old statistics with newly updated data.

Our ingestion pipeline previously loaded data into MySQL and kept running various ingestion logic by querying the data and using updates. After the data was available, the queries triggered by our dashboard and API would hit MySQL as well.

This has been working well for us — that is, until we introduced publisher-level collection and querying. With the large increase in data volume, loading to MySQL became slower, creating bottlenecks in our pipeline. In addition, running analytics queries on this volume of data was simply too slow.

Designing a New Ingestion Pipeline

To support an infinite number of tasks, with an ever-growing size of ingested data, we aimed to build a pipeline that was horizontally scalable (unlike MySQL). The choice of Amazon Simple Storage Service or “S3” to support these dependencies was obvious. We had already been using S3 for backing up our data before inserting it into MySQL. Plus it is horizontally scalable, requires zero ops and offers fast download/upload speed when working within Amazon Web Services.

Thus, our new ingestion architecture relies on S3 with only the metadata stored in MySQL. Instead of querying and updating MySQL, each component of our pipeline receives an S3 file as input and passes on another S3 file containing the data it received together with the new information the component produces.

The end of our pipeline sends the data to an S3 bucket, containing the most up-to-date statistics per customer, marketing source and date. This enables running data collection tasks in parallel, and makes this bucket the source of truth for our system.

Towards a New Datastore

With our data in its final form, ready to be queried in S3, our choice of datastore was super flexible. We had previously built a small abstraction layer between our API and MySQL, which could be adapted to support any query language or schema. Thus, in evaluating new databases, we knew beforehand that the decision wasn’t final, as switching costs were so low. In the end, we selected Druid, an open-source data store developed for the exact need of aggregate queries over marketing analytics data.

Once implemented, we were thrilled with the results: With Druid, queries that once 60 seconds took 1-2 seconds, while queries that once took 30 seconds took less than a second. In certain cases, we saw improvements in database query times as high as 150X compared to the old system.

All these developments bring us to earlier this year, when we began switching on Publisher-Level ROI for select customers in a closed beta test of the feature. The beta would serve as the ultimate stress test for our new architecture.

Granularity & Speed for the Win

As a refresher on Publisher-Level ROI and why it’s so groundbreaking, here’s a little industry background. Ad networks typically purchase inventory consisting of ad slots in hundreds, sometimes thousands, of sites and apps. These sites and apps, known individually as “publishers”, are where marketers’ ads run.

In recent years, mobile app marketers have demanded more visibility into publisher-level performance in order to identify pockets of their most valuable traffic. Networks have responded by providing Publisher IDs in the performance data they expose to marketers. Marketers, in turn, use these Publisher or Site IDs to optimize, increasing spend in high-performing publishers and decreasing spend or “blacklisting” under-performers.

Historically, however, publisher optimization across multiple networks has been an arduous and error-prone process, requiring marketers to toggle between multiple dashboards and manually update unwieldy Excel files. The process is particularly painful for marketers who wish to analyze the performance of publishers not merely by click-through rates or raw install count but rather by the actual quality of those users, as measured by ROI.

Singular automates the process of collecting all your marketing data under one roof, before cleaning and combining the data with revenue and events retrieved from tracking links in order to expose app ROI and other full-funnel business metrics.

But, as we’ve shown here, once ingested, enriched and combined, making publisher-level data fast and flexible is a whole ‘nother beast. Which is precisely why we invested so heavily in our new pipeline and datastore. Mobile app marketers need both granularity and speed — and we’re proud to say that the results speak for themselves.

As we’ve rolled out Publisher-Level ROI to our beta test customers who are now running on our new Druid-based system, customers have reported lightning-fast load times, even with the massive increase in data volume.

And the performance improvements aren’t limited to publisher-level querying. With Singular, similarly data-intensive querying — to expose Campaign, Country, Creative and User-Level performance — is now faster than ever thanks to these advancements in our new database technologies.

Top Takeaways From AppBoy’s LTR Summit

At Singular, our goal is to help grow the app industry by participating in key mobile strategy discussions wherever they occur. Last week Singular attended AppBoy’s Long-Term Relationship Conference, where mobile marketing strategy and product leaders gathered to discuss the future of mobile marketing and user communication. The event focused on today’s rapidly evolving mobile app marketing stack and featured talks with innovators at companies like Lyft, Ibotta, OkCupid and Wallapop (all Singular customers!). Here are top mobile marketing strategy takeaways from the event:

1. An inflection point for “buy vs. build”

OkCupid historically built most of its mobile app analytics services in-house. Yet things have changed in recent years as the team has started to hook more third-party services into their mobile app marketing stack. “For most our history we felt we were ahead of the curve, but many of these components have rapidly advanced over the years,” said Mike Cirello, Software Architect at OkCupid, who mentioned mParticle, Looker, Amplitude, and AppBoy as some third-party tools used by his team. Cirello’s sentiment echoed that of several speakers who reported that their mobile app marketing teams are using more third-party vendors to achieve efficiency gains in areas like data management, data processing, product experimentation and customer support.

For Lyft, the decision to build or buy components of its mobile app marketing stack largely comes down to speed. As Milan Thakor, Lyft’s Passenger Engagement Lead, said:

“We need to know [the third party] moves really quickly and will build faster than us, and that their vision is aligned with ours.”

2. The danger of disconnected data feeds

In recent years there’s been an exponential increase in the number of mobile marketing data feeds inside organizations, said Michael Katz, Founder of mParticle. Marketers, meanwhile, have quickly learned that siloed data can lead to poor user experiences. For instance, if mobile app customer data is not connected to marketing automation, a user who submits a complaint because of an incorrect order might still get emailed with new deals prior to the complaint being resolved. Or an iOS or Android app user visiting a city might receive location-specific offers in that city even after they’ve departed. It’s clear how those two experiences could frustrate app users. To avoid such messaging mishaps, companies must ensure that their marketing tools effectively communicate with their customer data.

3. Optimizing for downstream events

Bait and switch ads might drive high iOS and Android app ad click rates, but they don’t pay off in the long run, said Rich Donahue, Ibotta’s SVP of Marketing. Instead, Ibotta optimizes its ads and messaging for downstream events, including testing 97 different onboarding flows in its Android or iOS app. In addition, Ibotta runs cross-channel messaging tests that leverage interconnected analytics systems — for instance, tests to determine how paid ads affect the open rates of emails and push notifications.

The Wallapop business, a mobile marketplace for secondhand goods, is similarly focused on optimizing its user acquisition and re-engagement for key actions in its app. Users of Wallapop who haven’t opened a conversation with a seller in the first 7 days after registration are much more likely to drop off, said Nicolás Herrero, Wallapop’s Lead Data Scientist. Such mobile app strategy findings have led to Wallapop building campaigns around custom events and triggering messages if a user hasn’t performed a certain action within a given period of time.

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