How do you grow ROI while maintaining CPA and scale?
This is a question marketers face every day. And answering this question has become more complex as they advertise on more platforms across more devices than ever before. When conversions happen, it’s a struggle to connect the dots and understand what caused them.
Back when Singular was founded in 2014, we focused on solving this challenge first for the complex, highly fragmented, mobile ecosystem: providing a single solution that automatically collects and combines spend data and conversion data to expose mobile marketing performance, including ROI, at unrivaled levels of granularity.
That is powerful. And we quickly became the de facto solution for unifying campaign analytics and mobile attribution to expose ROI.
But in 2019, the game is different
Top brands advertise over a wide range of platforms to users on multiple devices. A customer may see an advertisement for a product on her desktop, and later buy that product on her mobile app. With today’s analytics, it’s hard to connect the two experiences and measure the customer journey accurately.
For mobile-first brands, this often leads to two separate teams, one web, one mobile app, using different tools, and even different metrics, to measure the customer journey. For web-first brands, it results in limited investment in mobile apps, preventing them from diversifying their marketing efforts to bring in incremental users, leaving untapped growth potential on the line.
Moreover, inaccurate measurement leads to misguided decision-making. Matter of fact, poor data quality costs brands an average of $15 million annually, according to Gartner. Making an investment and creative decisions with inaccurate and incomplete datasets is just plain costly.
In true Singular spirit, we sought to solve this new challenge for our customers so they can drive growth more effectively and efficiently in this multichannel world. And I’m happy to say that we have leveraged our vast experience in attribution and marketing analytics to do just that.
Cross-device, cross-platform attribution
Today, Singular is announcing the first-ever cross-platform and cross-device ROI analytics solution for growth marketers.
With the release of Cross-Device Attribution, Singular’s Marketing Intelligence Platform connects marketing spend data to conversion results across devices and platforms. First, we ingest granular spend and marketing data from thousands of sources. Then we connect it with attribution data from our easy-to-implement in-app and web SDKs as well as direct integrations with customer data platforms, analytics solutions, and internal BI systems, bringing the full customer journey into a single view. Finally, we match the two datasets.
The result is the most accurate cohort ROI and CPA metrics available to marketers, at the deepest levels of granularity including campaign, publisher and even creative.
That’s ground-breaking. It’s revolutionary.
But bringing cross-device and cross-platform ROI into Singular and measuring it accurately, at granular levels, is only the beginning to driving impactful growth.
Granular data for growth
Marketers can now access granular ROI cohort reporting that is more accurate than ever, as you can get clear, combined revenue for users across all devices. This is critical to achieving profitable growth and only possible with Singular – a complete platform that innovates beyond a single attribution solution.
Moreover, marketers can also utilize the wide set of capabilities that Singular’s Marketing Intelligence Platform offers to make smarter decisions and optimize their growth efforts with additional cross-device visibility; plus, they have more visibility into essential context such as the exact creative customers engaged with and the audience segments they belong to.
For example, you may find that a web channel’s impact is much higher than expected for specific types of customers. And now you can analyze the impact of the same creative across mobile and web.
In fact, we won’t be surprised if marketers start shifting investments with this new level of clarity. We are excited to see how growth strategists are going to rise above the crowd using this new solution to become part of the future wave of sophisticated marketers. Gone are the days of attribution feature wars – Marketing Intelligence has arrived.
Launching Cross-Device Attribution is just another step towards achieving our goal: to be every marketer’s indispensable tool in driving growth. We keep working not only to ensure that you can innovate your growth processes and have access to the highest data accuracy but also to ensure that we bring you the right insights at the right time to help you make timely strategic and operational decisions.
Are you ready to take part in the future of growth?
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.
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.
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.”
“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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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?
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.
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.
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.
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.
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.
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.
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)
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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Looking for a platform to unify your marketing data and derive smart insights on how to grow?
I was recently speaking at a mobile marketing conference in San Francisco and saw a competitor’s booth.
In the booth, the competitor showed the relative market share of the various mobile attribution providers. Predictably, theirs was highest. Other players didn’t show very well, and Singular was one of them.
I loved it. Because they don’t understand what we do.
Playing a different game
Mobile Attribution is a very critical piece in a much larger puzzle.
That’s why we acquired an MMP, re-architected it as part of a holistic solution instead of a point solution, and that’s why we are winning over a massive number of tier one customers.
In fact, Singular has more customers, bar none, in the top 100 grossing apps on Android and the top 100 grossing apps on iOS than any of our competitors. 46% of the top 100 grossing iOS apps are Singular customers (and 50% of the top 50) and 46% of the top 100 grossing Android apps are Singular customers (and 50% of the top 50).
That’s because we offer something different.
Something bigger.
Singular is a marketing intelligence platform. Our mission is to provide actionable insights to our customers, the best scientific marketers in the world.
We do that by solving the massive problem of data explosion and fragmentation in the marketing ecosystem across mobile, web, TV, offline, as well as paid, email, push, organic and any other form of marketing. We go beyond the confines of mobile advertising and mobile attribution, and are the only single pane of glass for all your marketing activity.
Every company in the world needs this.
Looking to the future
Today, we unify the biggest spectrum of more than 2,000 marketing technologies. And it’s just the beginning.
For us what matters is having the best North Star. And that is the top customers. In every market, the top companies are a constant source of envy and imitation by the up-and-comers and smaller companies.
Since our launch in 2014, and up until this very moment of me typing this, these top customers are the strongest source of influence on our roadmap. That, combined with our vision, is helping us move forward.
We’ve got a lot in the kitchen. You’re going to start hearing more about it in January. Our vision is huge, and we’re well capitalized to make it happen.
For our amazing Singular customers, our sole mission is to be a great, innovative partner that will always put you two steps ahead of the competition. Accept nothing but relentless drive to serve, topped with the whipping cream of world-class innovation.
Today, Singular is excited to announce a new partnership to improve the ROI of your user acquisition strategy.
Quora, a platform for people to ask questions and read insightful answers, offers advertisers an opportunity to influence people during the consideration phase of their purchase process. Now, through Singular’s integration with the new Quora API, advertisers can accurately attribute user behavior and measure the true performance of their Quora campaigns all within the same Singular dashboard.
Luno, a power user of Singular and active advertiser on Quora, can attest to the power of bringing the two platforms together.
“Luno provides a safe and easy way to buy, store and learn about digital currencies. Advertising on Quora allows us to target people actively looking for more information on Bitcoin and Ethereum, and now with our data available in Singular we are able to uncover new insights and more effectively ensure the performance of our campaigns,” says Charlie Jobson, Growth Manager at Luno.
Quora has a worldwide audience of 200 million monthly unique visitors. The Quora advertising platform offers marketers the ability to target high intent audiences who are reading relevant questions and answers. Quora allows advertisers to target based on particular topics and then records metrics in the Singular dashboard at the campaign and sub-campaign level so you can measure ROI with granularity.
Adding Quora as a data source for campaign analytics in Singular is easy.
Once you log in to your dashboard, simply navigate to the “Settings” tab and click “Data Sources.”
From there, search for Quora and enter your Quora credentials.
Within 24 hours you will see your data populated in your reporting.
For more information on how to get started on Quora and how to include this data in your Singular dashboard, please reach out to your Customer Success Manager.
About Quora
Quora is a place to gain and share knowledge. It’s a platform to ask questions and connect with people who contribute unique insights and quality answers. This empowers people to learn from each other and to better understand the world. Since its founding in 2010, Quora has grown to more than 200 million monthly unique visitors. The product is currently available in English, Spanish, French, German, Italian, Japanese, Hindi, Portuguese and Indonesian. Quora launched its advertising platform in May 2017 and has more than 1,000 active advertisers across a spectrum of categories. Marketers can run text or image ads and access a range of strategic targeting options.
About Singular
Singular is a marketing intelligence platform that unifies marketing analytics, giving marketers actionable insights from previously siloed data. By connecting upper funnel marketing data with lower-funnel attribution data, marketers can measure ROI from every touchpoint across multiple channels and optimize spend down to the most granular levels. Singular currently tracks over $10 billion in digital marketing spend to revenue and lifetime value across industries including commerce, travel, gaming, entertainment, media, and on-demand services. Singular customers include companies like Lyft, Yelp, Airbnb, LinkedIn, Symantec, Zynga, Match, and Twitter. Singular is backed by Norwest Venture Partners, General Catalyst, Thomvest Ventures, Method Capital, Translink Capital, DCM and Telstra Ventures. Visitwww.singular.netto learn more.
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.
The European Union General Data Protection Regulation — GDPR is top of mind for many businesses, especially for those that engage in online advertising. This new privacy-driven regulation requires that all companies collecting, accessing, and processing personal data for EU residents must comply with new standards that will be enforced starting May 25, 2018.
Understandably, we’ve been getting many questions related to the GDPR over the past few months. To help shed light on the questions you may have, we’ve compiled the top FAQs for the GDPR.
General GDPR FAQs
1. When is the GDPR coming into effect?
May 25th, 2018.
2. Who does the GDPR affect?
It applies to all companies processing and holding the personal data of European Union residents, regardless of the company’s location.
3. What constitutes personal data?
Any information that can be used to directly or indirectly identify a user. It can be anything from a name, a photo, an email address, bank details, posts on social networking websites, medical information, device IDs, or a computer IP address.
4. What are the penalties for non-compliance?
Organizations can be fined up to 4% of annual global turnover for breaching GDPR or €20 Million. This is the maximum fine that can be imposed for the most serious infringements (i.e. not having sufficient customer consent to process data or violating the core of Privacy by Design concepts). There is a tiered approach to fines; a company can be fined 2% for not having their records in order (article 28), not notifying the supervising authority and user about a breach or not conducting an impact assessment. It is important to note that these rules apply to both controllers and processors — meaning ‘clouds’ will not be exempt from GDPR enforcement.
5. What is the difference between a data processor and a data controller?
A controller is an entity that determines the purposes, conditions, and means of the processing of personal data, while the processor is an entity which processes personal data on behalf of the controller.
6. Do data processors need ‘explicit’ or ‘unambiguous’ data subject consent – and what is the difference?
Consent must be clear, unambiguous, and provided in an intelligible and easily accessible form, using clear language. It must be as easy to withdraw consent as it is to give it. Explicit consent is required only for processing sensitive personal data – in this context, nothing short of “opt-in” will suffice. However, for non-sensitive data, “unambiguous” consent will suffice.
7. What about users under the age of 16?
Parental consent will be required to process the personal data of children under the age of 16 for online services; member nations may legislate for a lower age of consent but this will not be below the age of 13.
8. Does my business need to appoint a Data Protection Officer (DPO)?
DPOs must be appointed in the case of (a) public authorities, (b) organizations that engage in large-scale systematic monitoring, or (c) organizations that engage in the large-scale processing of sensitive personal data (Art. 37). If your organization doesn’t fall into one of these categories, then you do not need to appoint a DPO.
9. How does the GDPR impact policy surrounding data breaches?
Proposed regulations surrounding data breaches primarily relate to the notification policies of companies that have been breached. Data breaches which may pose a risk to individuals must be notified to the Data Processing Addendum (DPA) within 72 hours and to affected individuals without undue delay.
10. Will the GDPR set up a one-stop shop for data privacy regulation?
The discussions surrounding the one-stop-shop principle are among the most highly debated and are still unclear as the standing positions are highly varied. The Commission text has a fairly simple and concise ruling in favor of the principle, the Parliament also promotes a lead DPA and adds more involvement from other concerned DPAs, the Council’s view waters down the ability of the lead DPA even further.
GDPR FAQS for Singular Users
1. Is Singular a Data Processor or Data Controller?
Singular is a Data Processor — we do not determine the purposes, conditions or scope of how data is collected. You, our customer, who will often determine these will be defined as a Data Controller under the GDPR, but you should consult with your legal team to make such a determination.
2. What data does Singular collect and is it affected by the GDPR?
When using Singular for mobile attribution, Singular will track device data such as advertising IDs, IP addresses, and other device identifiers. We may also collect user-level events that advertisers send us through the Singular SDK. Under the GDPR, all of the aforementioned data is deemed as personal data and will be treated appropriately per regulations set by the GDPR.
3. How does Singular use personal data?
We use the personal data identified above for two purposes: a) to determine the attributed network, campaign, etc. b) provide our customers with analytics and reports based on the data we collect for them such as retention, ROI, etc.
4. Does Singular transfer this personal data anywhere?
By nature of providing mobile attribution, we need to report attributed installs and events to the marketing channels you’re running with, per the agreement you, the advertiser, has with these marketing channels. As a Data Controller, you are always aware of what data Singular sends to said marketing channels, and can be assured that Singular will never share your data with any other entity.
5. What are common GDPR-related requests that advertisers may get from users?
Under the GDPR, data subjects have several rights that need to be honored:
Right to Access and Right to Data Portability – both of these rights speak to the user’s (data subject) ability to request all data that has been collected on them in an easily readable format.
Right to Erasure speaks to the user’s ability to ask for their data to be deleted and is also commonly referred to as Right to be Forgotten.
Right to Rectification speaks to the user’s ability to request for their data to be corrected or completed.
6. How does Singular allow Data Controllers to honor such requests?
To easily comply with requests related to the GDPR, we’ve built several new REST API endpoints to accept requests in a programmatic and scalable manner. The API documentation is provided in our Developers Portal.
7. Are you compatible with the OpenGDPR initiative?
Yes, Singular’s SDK is GDPR compatible. We are also releasing an additional update soon to further support explicit methods for opt-in (for when a consent is explicitly provided), opt-out and unload options in the SDK to give you more control for user privacy.
9. I’m not using Singular for attribution or event tracking. Does GDPR apply here?
If Singular doesn’t collect personal (user level) data for your mobile app users, it is not technically a Data Processor in the GDPR context.
10. Do you have an updated Data Processing Agreement I can sign?
Yes, please reach out to your Customer Success Manager to get our latest DPA.
11. What else is Singular doing around the GDPR?
Built by security experts, Singular has always been security and privacy driven by design. We treat encryption, security, and privacy as core principles that determine how every new system is defined and built, and these are inherently embedded in the platform.
At Singular we welcome the EU’s initiative for increased transparency, ownership, and trust around personal data processing activity. We remain committed to these principles when working with our customers as their data processor. As such, we have made extensive investments to ensure that both Singular and our customers meet GDPR compliance standards, which you can read more about in our article “Hello GDPR: Stay Compliant with Singular”.
Disclaimer: The information provided by Singular is for informational purposes only and not for the purpose of providing legal advice. Please contact your attorney to obtain advice on specific issues or questions.
