The next generation of user-level ad monetization: Introducing support for impression-level revenue data from MoPub

Without complete and accurate ad monetization data, app marketers can’t optimize growth decisions. Today, that means they need to include ad monetization data as well as in-app purchase data in their ROI calculations.

App marketers need to measure ad revenue on two distinct levels: aggregate and granular.

Granular ad revenue

Mobile app marketers need the ability to see user-level ad revenue so that they can accurately understand their return on ad spend for user acquisition. Without granularity you won’t know which users are ad whales … and which are ad duds.

Plus, you’re not sure where they came from. Or where to get more of them.

“Granularity is critical in mobile ad monetization,” says Singular CEO Gadi Eliashiv. “Understanding the relative value of their ad impressions helps mobile publishers optimize their apps for maximum revenue. It also helps them improve user experience by making decisions that can minimize irrelevant and wasted ads.”

Aggregate ad revenue analytics

You also need aggregated data so that you know exactly where you stand with ad-based revenue across all partners, plus of course IAP and product/service purchase data. Only then can you get a full picture of your growth efforts.

You also need to understand ad requests and fill rates.

“Smart companies check the fill rate all the time to optimize their waterfall,” says Singular CEO Gadi Eliashiv.

MoPub’s new impression-level revenue data

Singular has been providing ad monetization services for almost a year with a variety of partners, including IronSource. Now, MoPub is providing revenue information to mobile app publishers for every single ad impression. Not only that, MoPub is also surfacing what supported demand source was able to fill the ad slot and what country the user is in.

This is extremely powerful.

With this data, you can understand ad-based life-time value of your users. That’s increasingly important, because just 2% of mobile app users are converting to paying customers via in-app purchases.

Ads are one of the key drivers of monetizing the other 98% of your users, so it’s no shock that ad monetization is increasingly critical for app marketers. In fact, 60% more apps are monetizing through ads in 2019 compared to last year, and ad revenue now represents more than half of many app publishers’ total revenue.

Available today

Starting today, Singular supports MoPub’s impression-level revenue data product, enabling marketers to measure granular ad revenue.

The result is better data precision, more accurate and complete LTV models, superior user acquisition and monetization strategies, and ultimately, the potential to earn more revenue.

And all of it, of course, right inside your Singular dashboard, providing a single pane of glass to understand your cost and revenue.

Learn more about Singular’s Ad Monetization solution here, and set up a demo to go deeper with one of our specialists.

5 things to do when your mobile retail sales crash

This is a guest post by Ryan Gould, VP of strategy and marketing at Elevation Marketing

Mobile commerce sales are expected to reach approximately $420 Billion by 2021.

That’s massive, and it’s only going to grow. More importantly, people who use their mobile devices to make purchases usually spend twice as much as other customers.

It’s no surprise that mobile e-commerce is a very important channel for retailers to sell their products and services through. However, in the volatile economic environment, we live in, mobile retail sales can crash, for myriad reasons.

That’s why it’s smart to know what to do if your mobile retail sales collapse. In this article, we’ll give you five concrete things to take action when things go south with your mobile sales.

Let the action begin!

#1: Read the data to figure out why mobile retail sales are crashing

Before you start taking any action on improving your mobile retail sales, it’s best to investigate why your sales are falling in the first place. Never assume what the reason could be, until you’ve explored it.

Here’s a great list of questions you can use to get to the root of the problem:

  • When did mobile retail sales start crashing?
  • Was there any event that occurred before mobile retail sales started crashing?
  • What is the size of the sales drop, in dollar terms?
  • Which products have caused mobile sales to drop?
  • Is there any trend that’s being revealed by the sales numbers?
  • Are my site visits and app sessions down, flat, or growing?
  • Is the buyer’s journey ending on one particular screen?
  • Did my pricing change, or did currency fluctuations in foreign markets recently happen?
  • Is the number of abandoned shopping carts vastly growing?
  • Did a competitor release something attractive to my users and customers?
  • Is my store suddenly rejecting more credit cards?

Make sure you confirm that you know the reason, so your plan of action is relevant to the problem you’re wanting to address!

#2: Revamp your mobile site/app design

There are a bunch of things you can do to restyle your mobile e-commerce app and optimize it for conversions. Your e-commerce website or app should be easy to access on any mobile device, so people find it easy to transact with you.

Start by enlarging your mobile retail product images and text so people can see your products clearly. You should also enlarge your buttons so people with ‘fat fingers’ can click on your calls to action with ease.

Another way to make your mobile site or app user-friendly is by only including one call-to-action button per page. It makes the buying decision simpler for customers, by giving them lesser choice and making it super simple for them to transact.

Make the navigation experience super simple.

Your mobile website or app experience should be significantly different compared to your desktop version. Using ‘responsive design’ so that your website fits any mobile device, whether smartphones or tablets, is a great way to provide a universally consistent user experience.

But almost nothing beats a native mobile app for usability.

#3: Send great mobile emails (and maybe a push notification)

If you notice your mobile retail sales plummeting, it’s best to reconnect with your subscribers.

And the best way to reconnect with subscribers is to send them beautiful mobile emails. More than 67% of retail consumers check their email on their mobile device.

Sending mobile emails is an art. You can use them creatively, for various reasons such as finding out why your customers have stopped buying, what would interest them, and what you can do as a retailer for them. Nearly 20% of all mobile sales are initiated by email marketing, so it’s worth the time investment to utilize the channel as best as you can!

Some tips for sending great mobile emails are:

  • Keep them simple. It’s best to come to the point, as people have very short attention spans these days. So only send them the message they need to hear!
  • Use visually appealing images, with less text. Images get the message across in an interesting and engaging way, and consumers will love you for it.
  • Have a specific, clear and simple call to action. Emails should make it easy for customers to transact with you too.
  • Use catchy subject lines to grab the attention of your consumers. The better your subject lines are, the higher the chances are of your consumers clicking on them!

If you’ve got highly engaged users, and you have an offer that won’t cause them to uninstall your app, you can also send a smart push notification that’s tailored to who they are, what they want, and what they’ve been doing recently.

#4: Invest in search optimization (SEO and ASO)

Just like you need to invest time in optimizing your website for SEO for desktop searches, you also need to invest time in optimizing your mobile website for mobile searches. And for apps, you need to optimize your App Store and Google Play descriptions for search on those platforms so that you can rank well.

Organic channels (and paid channels) are complementary, so increased success in one often spills over to the other, so it makes sense to enhance these different channels together.

58% of all searches are on mobile. Inevitably, you need to put some effort into this.

Some steps you can take to enhance your mobile SEO are as follows:

  • Make sure your website is responsive: If your website doesn’t fit on a mobile device, the ones that are will outrank yours.
  • Optimize your content for mobile devices: This will help in loading content on your website faster and optimize your website for speed. By reducing the image sizes and placing meta tags in the right places you can enhance your search rankings.
  • You can use the Google Search Console for checking your website’s mobile usability issues so you can fix all the errors that are stopping it from being found by people. It’s a great way to determine how you can spend your time wisely on mobile SEO.

Mobile commerce now represents a third of all retail sales in the U.S. according to one report and is growing almost 15% year-over-year.

Some steps you can take to enhance your app ASO are as follows:

  • Pick the right category. Remember, Twitter switched from social, where it was always trailing massive competitors, to news, where it instantly became number one. A higher ranking means more installs.
  • Get more (and better ratings). Look, ratings are table stakes: all the top apps have lots of them. But continually adding new and updated ratings for your app is critical to even having the opportunity to get good placement.
  • Build your offline footprint. Most people who install an app have heard of it before and went searching for it. Without some brand identity and awareness, it’s hard to get drive-by installs. And, they’re much less likely to result in engaged long-term users/customers.

#5: Make sure you keep the checkout experience as simple as possible

The checkout experience is the make or break moment for mobile retail. That’s why it’s so important you avoid asking for unnecessary information from your users during checkout.

You can run a survey with your customers to understand what they like or dislike about your mobile checkout experience so you can add what’s necessary and eliminate what’s not needed. As a general guide though, implementing the below steps is great for mobile eCommerce:

  • Allow users to pay through multiple sources: Your checkout page should allow users to pay via credit card, paypal or bank transfer, whatever makes it easy for them to transact.
  • Simplify the UI elements of your app to entice your users to take action. Some colors are more appealing than others for shoppers to click on the ‘buy’ button. For instance, using shades of orange or green are better for enticing users to take action compared to red which puts the ‘halt’ signal in the human brain.
  • Remove all the content that’s unnecessary for checking out. You can include complimentary products for upselling them at checkout, but don’t annoy customers with any irrelevant promotional offers.

Wrapping it up

By implementing the above steps, you can minimize the temporary setback.

Mobile retail sales can be cyclical, abrupt, and vary depending on the nature of the industry your business is in. Reading the data and taking appropriate action is the best way to know which is the best cure for the problem.

Ryan Gould is Vice President of Strategy and Marketing Services at Elevation Marketing. From legacy Fortune 100 institutions to inventive start-ups, Ryan brings extensive experience with a wide range of B2B clients. He skillfully architects and manages the delivery of integrated marketing programs, and believes strongly in strategy, not just tactics, that effectively aligns sales and marketing teams within organizations.

Jam City optimizes campaign performance and creative strategy with Singular

We got to sit down with Jam City’s VP of User Acquisition Marketing, Brian Sapp, to discuss how his team is using Singular to optimize campaign performance and improve their creative strategy. Watch our discussion on Jam City’s use of campaign analytics below!




My name is Brian Sapp. I’m the VP of UA (User Acquisition) Marketing at Jam CityJam City is one of the leading mobile casual gaming developers in the West. We have a fairly large portfolio of games. Some of our tentpole games are Cookie Jam and Panda Pop. But recently we launched Harry Potter Hogwarts Mystery, [and] that game has been a big success.

Connecting fragmented marketing data

Singular right now we use to ingest data from all of our ad networks and as you can imagine, when we spend with over 40 networks, that’s a lot of data. The manpower it would take to go into each network and pull in that API, do the work, or pull it in manually, would be extremely time-consuming.

Singular solves that for us, solves it in a much faster time, and more efficiently than we could do it ourselves. And then, having that data in the dashboard, especially for someone like me who’s spending across 8-10 titles, we have a massive portfolio, the dashboard really gives us the ability to easily pivot that data whether it be by spend, by channel, by paid installs, by tracker installs, impressions, it’s very, very useful, as well as creative. Having all of the data, especially creative data, plus images, plus the data behind the creative, in one dashboard is extremely valuable for us.

Aligning with Creative Product Marketing

So we actually have a team called Creative Product Marketing that focused on our creative roadmap/creative strategy and they’re using Singular to look at our performance by game, by channel, and right now it’s the fastest, easiest way we have to do that across all the different data sources.

Next-level Performance Analytics

Singular collects a lot of the ad network data for us and we’re using that to look at CPI by campaign, CPI by geo, paid performance, scale, spend, organics versus paid installs. And so we’re also ingesting data from our attribution partner which allows us to kind of marry the two, and so we get very granular on Singular’s reporting for whatever questions we have.

I use it for executive reports, building massive pivot charts, visuals that I want to see across the portfolio. The combination of our internal tools plus Singular really gives me everything I need.

Ready to take your growth marketing to the next level? Let’s connect!

Nexon transforms marketing data into granular performance insights with Singular

We got the chance to catch up with Nexon‘s Director of Acquisition, Warren Woodward, and discuss how his team uses Singular to analyze and optimize the performance of their sophisticated user acquisition program. One topic we covered was how challenging it can be to analyze the performance of ad creatives, especially when advertising multiple titles across many ad partners. Thankfully, Nexon overcame this challenge. 😊Check out our discussion below!




My name is Warren Woodward, and I’m with Nexon. I’m the Director of User Acquisition. Nexon is an international gaming company. We have games for PC and mobile across the world. We have a couple of major IPs, such as Maple Story, and the biggest video game series in China, Dungeon and Fighter.

How Singular fits in Nexon’s growth stack

At Nexon, we leverage Singular in a few different ways. We use it as our source of truth. We also use it as a way to join data from multiple sources for day-to-day campaign optimization. Singular for us is a great way to look at all that data in one place. And for me as Director to look in on everything that everyone is doing and see it all in an apples-to-apples comparison to understand how to best move budget around.

Reaching growth goals

Singular helps us reach our growth goals ultimately because it saves us time in any number of ways. With the number of titles that we’re buying for, we don’t have the time to go into every separate source, every separate title, and look at it all à la carte. So the ways that we can slice and dice, and stack rank what’s important to us to see what’s giving us the highest ROI… everything across the game, where are we spending the most, what’s bleeding, let’s us judge how we can use a finite number of hours in the day to get the most impact to our campaigns.

Singular let me see it all in one place, slice and dice it. If I just want to see all of the performance for any given country or OS, or maybe just dive really deep to a particular ad network. It’s nice to have one dashboard that can quickly make all these ad-hoc reports. And also to do a creative analysis and collaborate with the creative team.

Perfecting storytelling

So one of the ways that we use this on a daily basis is to get our creative team talking about performance, the same way that we do; to be looking at a creative level across the dozens of creatives who might have any given time for a game. Understand the trends that are working. It helps us identify what we want to make next, what’s really working, and we start seeing a better return on investment for the creatives themselves when we can see how they’ve been performing in the ecosystem.

Ready to take your growth marketing to the next level? Let’s connect!

N3TWORK optimizes marketing spend and aligns internal teams with Singular [Video]

We recently had the privilege of sitting down with Nebojsa Radovic, Director of Performance Marketing at N3TWORK, to talk about how his team is leveraging Singular’s Marketing Intelligence Platform to optimize marketing spend and align their internal teams with a single source of truth for marketing performance. Check out our discussion below!



Hi, my name is Nebojsa Radovic, but most people in the industry know me as Nebo. I’m a Director of Performance Marketing at a company called N3TWORK, which is the developer behind Legendary Game of Heroes.

How Singular fits in N3TWORK’s growth stack

We’re currently using Singular pretty much as our marketing stack. We’re using [Singular] as both an attribution and cost aggregation partner. We’re getting spend data from our ad partners and at the same time, we’re getting user-level data that tells us where the installs are coming from.

The importance of granular performance insights

Singular was very important for us simply because it unlocked certain opportunities that we were not having before. Think about optimizing at the publisher and creative level, combining those two, and trying to spend more dollars in the places where it makes sense. Without that data, it’s pretty much impossible to extrapolate manually and figure out what’s working and what’s not.

Let’s say if you’re trying to scale your spending from $100,000 a month to $10 million a month. You really need very granular, accurate data that comes in on time… When you’re spending a few thousand dollars a day, maybe you don’t need granular data. But if you’re trying to scale the spend across different channels and different geos you really need accurate and granular data to be able to do that. So thank you Singular!

Aligning internal teams with a single source of truth

Singular helped us a lot with aligning the Finance team with the User Acquisition team. And within the User Acquisition team, we have a media buying team, data analytics team and marketing creative [team]. All four teams, Finance and the three sub-teams of the marketing team are looking closely into the Singular data and trying to understand how to do their jobs better.

In particular, Finance is estimating what the spend is at the end of the month or week, whatever is that time period we’re looking at, and they’re estimating what the payback windows are going to be and the financial health of the company at a very high level. At the same time on the User Acquisition side, we’re just trying to make better buy decisions by using Singular data. This is crucial to do this job successfully.

Ready to take your growth marketing to the next level? Let’s connect!

Marketers are boosting 2019 ad spend on Amazon, Facebook, and Google (but especially Amazon)

Recently we surveyed 1,500 marketers who actively run ad campaigns. It’s no shock that marketers are looking more and more to Amazon as a media source for advertising — especially those in consumer goods and retail.

But Amazon’s not the only one growing.

Both Facebook and Google will be growing significantly as well. Amazon, however, as the newer competitor in the advertising world with, of course, less historical business, will grow the most. In fact, 63% of marketers who run ad campaigns are planning to increase their spending on Amazon.

Google and Facebook aren’t left out, however. More than half of marketers — 55% — are growing their ad spend with Facebook, and 61% of marketers are also planning to increase their spend with Google.

This should not be a surprise.

Google and Facebook both did exceptionally well in the Singular 2019 ROI Index, where we ranked over 500 ad networks by their return on investment. Both were at the top of virtually all categories and geographies.

Let’s dive deeper into what marketers plan to do with each platform:

Facebook ad spend growth

We’ve already mentioned that more than half of marketers will be increasing their ad spend on Facebook. Only 10% say they’re decreasing it, while 35% say they’re keeping it the same.

Facebook topped the global iOS and Android ROI rankings in our recent Singular ROI Index, so it makes sense that marketers are doubling down on success.

Google ad spend growth

Similarly, 61% of marketer say they’ll spend more on Google. 33% say they’ll keep their spending the same, while only 6% plan to spend less.

Google showed massive strength in the Singular ROI Index in gaming sectors as well as regional dominance in Americas, EMEA, and APAC regions. Again, marketers tend to keep doing what works … and generally do more of it.

Amazon ad spend growth

While Amazon is the newest entrant into the advertising ecosystem among these big three, and has a relatively small share of the overall digital ad market, it doubled in ad revenue over the last year and has been ramping continuously for several years.

In 2019, it will grow the fastest.

One huge advantage: massive amounts of purchase data as well as browsing history, which helps Amazon gain good understanding into what people want and what they’re most likely to click on.

63% of marketers plan to increase their ad spend with Amazon in 2019, with another 34% planning to keep their spend the same. Only 3.5% of marketers who run ad campaigns are planning to decrease their spending.

Most trusted ad networks

We surveyed the same 1,500 marketers on multiple other topics, including which ad networks they trust the most, and what the most important elements that marketers consider when choosing new ad networks.

We can’t reveal all of that publicly, however.

To get that data, contact us and ask for the “most trusted ad networks” data.

To build or not to build: making build vs buy decisions for mobile attribution and aggregated campaign analytics (part 1)

Some of the larger marketing organizations we talk to in EMEA think about building aggregated campaign analytics and ROI insights themselves. They generally don’t see the full difficulty and continuous maintenance this project involves. In this article, I explore the challenges of building and why a solution like Singular meets and exceeds these need. This is part one; part two will arrive in a month.

EMEA is a hub of marketers big and small representing every type of app developer and web-centric marketer you can think of. The data explosion has affected each one. It has made actionable insights, which make all the difference in this competitive landscape, the holy grail of every growth marketing team.

Build vs buy

One question that is a serious challenge for them all: should we build an in-house mobile attribution solution or buy it from a third party?

Our customers are smart and between them own over 50% of the top 100 grossing apps. So it’s no surprise that they employ intelligent engineers and data-savvy growth teams who already have the knowledge of how to achieve aggregated campaign analytics and could have a good shot at the greater challenge of getting ROI in an accurate, timely manner … although getting ROI at the most granular levels would be a massive challenge.

Therefore, it’s not a question of whether they can do it, but rather should they do it. We found that when addressing this question, the same considerations led even the largest enterprises out there to outsource this crucial work to a marketing intelligence platform like Singular.

The first thing to take into account is the cost of undertaking such a huge project and the time to completion.

Engineering time is not cheap and a company can rack up several hundred thousand dollars to build the required infrastructure even before considering the ongoing cost of maintenance. Not to mention that a project of this size and complexity will take months to complete and in such a fast-paced industry, this is long enough to start falling behind the competition.

Cost is not just measured in currency

However, the cost of this is not just monetary.

Valuable technical resources likely need to be diverted from core product projects, which impedes innovation and custom developments that address the specific needs of the business, allowing even more breathing room for competitors.

Getting the foundations right is no easy feat: you have to get a framework for your BI system, make sure that your MMP matches that framework, and then map your cost APIs into it correctly to get full aggregated campaign analytics. Furthermore, if your marketing efforts extend beyond Google and Facebook, you will have to set up multiple APIs with all the different networks you run with and for any new networks you want to test in the future.

If engineering time is limited, as it often is, and new networks are not integrated – what is the impact of the inability to test on the business? The cost of passing on new inventory and networks with new targeting and ad format capabilities cannot be underestimated.

Once you have your APIs connected, additional work is required to configure the internal dashboards to display the new data. It’s a manual process that is prone to human error which can easily render datasets inaccurate and therefore unsuitable for optimization purposes. If you’re going down the build route, you’ll need to put in place time and resources for checking accuracy before you even start thinking about which data visualization platform you’ll use to make sense of it all.

From aggregated campaign analytics to marketing intelligence platform

That’s another reason why our customers choose Singular, a marketing intelligence platform built with the modern growth marketer in mind, addressing their requirements of instant access to reliable data for granular optimization.

Even if all the above is accomplished so that data is flowing in and is accurate which we’ve seen can be done, the issue of combining it with internal data sets poses a true challenge.

Filling in the gaps and delivering the insights requires a complex infrastructure with strong identifiers for combining purposes to enrich campaign and publisher granularity, which almost certainly still leaves creative level combining — and therefore creative ROI — beyond reach.

All this means a lot of data and heavy queries that slow down the internal systems.

Our research and customer feedback reveals that the above challenges, opportunity cost, and continuous and expensive maintenance of self-built infrastructure are what drives small and big enterprises alike to a conclusion that a third party is a better solution for this essential need.

What you actually buy from Singular

Here at Singular, we understand these challenges well — after all, we went through the pain of building it ourselves.

Our product is our bread and butter and we’ve gone far beyond the basics to build a true marketing intelligence platform that frees up engineering time of our clients to build marvelous things that uniquely aid their goals while giving growth marketers the tools that they need.

What you buy from Singular is beyond the aggregation and standardization you’d expect to build yourself: you buy a world-class solution that is focused on continued innovation and automation, to give you unrivaled insights and optimization capabilities.

You buy teams that build and support integrations, improve infrastructure and system performance, and constantly work to add new features. You buy a data science team that make it their business to spot discrepancies, a support team that handles data flow errors and API issues, and a stellar (if I may so so myself) customer success team that makes sure the platform is serving your business.

If you had engineering and BI time to spare — what would you build?

See how DGN Games grew 85% and saved 15 hours each week with Singular.

Next month we’ll hear from an EMEA customer about how Singular has enabled their business and aided their growth strategy. If you have ambitious goals and are thinking of buying or building, reach out to us about a demo to see what Singular could do for you.

Introducing global-first Cross-Device, Cross-Platform ROI analytics

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?

Find out what Singular can do for you

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 suggest 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, 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.


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.

Mobile attribution webinar: Your Top 27 ‘No BS’ questions answered

We know, it’s sad. You missed our mobile attribution webinar last week. We missed you too!

But we have a solution. Two of them, in fact.

First, if you missed our “No BS Mobile Attribution Webinar” last week, it is still available on-demand. We had fun doing the webinar, and we think you’ll enjoy listening to it as well. But second, if you don’t have 30 minutes to spare, it might be faster to read the answers we provided here.

First, a quick recap: content & speakers

Mobile attribution can be confusing, and it can seem pretty detailed and technical sometimes. That’s why we hosted the attribution webinar with friends from Vungle and Liftoff. And we had three experts, who are also providing the answers you see here …

Barbara Mighdoll
Senior Director of Marketing

David Bennett
Sales Engineer

Rina Matsumoto
Performance Optimization Lead, US

OK. The mobile attribution webinar questions (and answers)

1) What is mobile attribution?

Rina: Mobile attribution is the way mobile marketers understand from which marketing channels their app users are acquired.

It’s incredibly important to know which traffic sources are bringing not only users but high LTV users into your app. This will allow you to invest your marketing budget in the right sources.

2) From Andrew at Flipboard: “Can you please touch on challenges and capabilities for tracking attribution from a mobile app?”

Barbara: Well, this is a fairly broad question that could be taken in so many directions, and since we are just starting the discussion I’ll keep this high-level.

Mobile attribution at the core is the bridging together of advertising and mobile technologies. The challenge to attribution is being able to keep up with this constantly evolving technology, and I’ll also add the constantly evolving ecosystem threats like fraud. However, when done right, the insights from mobile attribution allow marketers to execute and evaluate their mobile marketing campaigns with proper app conversion metrics.

2) What are tracking links? How do they work?

David: There are multiple types of tracking links, impression tracking links and click tracking links. These links are used to gather data around what partners are driving impressions and clicks for you. They also allow us to track what users are downloading your app after seeing an ad.

This helps you assign attribution.

The tracking links also help us route users to the App Store, the Google Play store, or other app marketplaces. In the case of re-engagement or retargeting campaigns they can also be setup to route users directly to your app. In general, they make data collection for digital marketing possible.

As for how they work, they send information to your MMP when impressions are shown or when ads are clicked. The information that they send contains device data as well as a few other key pieces of information. Since they contain device data it allows you to track when users are installing your app because of your advertising efforts and what actions they are taking in your app because of your advertising efforts.

3) What is deep-linking? Why does it matter?

David: Deep-linking is a technology that allows you to link to your app directly from your ads [editor’s note: whether in an app or on the mobile web]. For re-engagement campaigns this means a smoother user experience.

This is important because it allows you to minimize the number of steps that your users have to complete in order to reach the desired event. This usually leads to better performance and increased ROI.

Barbara: Just to add a quick comment here, I think this technology has become a pretty standard part of an attribution stack, and because of that most users now expect when they click on an ad with a particular CTA, the app will open in the correct location.

3) What are postbacks? Should I be getting them?

Rina: Postbacks are the way networks receive in-app data from clients, whether that’s installs or post-install events like in-app purchase or tutorial completion.

These postbacks will be key depending on your network’s buying model or optimization methodology. So it’s important to consult your network partners on what postbacks they’ll be needing.

David: This enables you to share user behavior with your advertising partners.

4) What is a SAN?

David: Self attributing networks such as Facebook, Google, and Twitter inform your attribution partners which installs and actions they drove.

5) What is granularity? Why do marketers need granularity?

Barbara: Granularity describes how deep a marketer is able to analyze their data.

For example, basic granularity usually includes drilling down to the app & source level, while sophisticated marketers are able to go deeper into the campaign, publisher, keyword and even creative levels. With this level of detail, marketers can decide when they should shift budget. They also can better inform how to spend their time optimizing – and know exactly where to optimize.

Advanced marketers who have been able to achieve scale and see massive growth are the ones who are able to optimize at deep levels of granularity. For example, as part of our Marketing Intelligence Platform we offer creative reporting where we are able to pull in your ad creative so you can easily match your data to your ads.

One of our customers who started utilizing these creative level insights saw ROI increase 40% within 2 months.

Rina: I agree with Barbara. Granularity helps you understand what types of users were acquired and how they were acquired. Are these users from iOS 11? Were they acquired from a specific type of creative?

It’ll also help in investigating any issues with discrepancies and potential campaign or fraud issues, by being able to drill down to specific parameters.

6) Why do marketers need to combine customer-level mobile attribution data and campaign-level marketing data?

Barbara: This is a great question, and one that we address frequently because the complexity of this is often misunderstood.

Before I jump into the why marketers need to combine this data, I first want to touch on why combining it is even a challenge.

Marketing data is only available in aggregate like ad spend, while attribution data is available at the user-level like app installs. By nature, aggregate and user-level data do not fit together – it’s like trying to assemble a puzzle with pieces from different sets.

This means that marketer’s datasets are often left incomplete and inaccurate. Left this way, marketers do not have the ability to dig into granular levels of insights. And this is a core problem Singular solves – we redefined how attribution data matches campaign data with the experience we’ve acquired over 4 years of mapping this ecosystem.

So to answer why marketers need to combine these two datasets, the answer is pretty simple: to unlock ROI at granular levels like the campaign, publisher, keyword and creative-levels.

Rina: User level data are data points like device type, OS version, and country. Campaign level data are data points like publisher and creative information. Only once you marry this data do you have a full understanding of your marketing campaigns.

7) Can I see where ad networks are running my ads? If so, how?

Rina: At Vungle, we try to provide as much transparency to our advertisers as possible. We share publisher site names with all of our clients to give full transparency into their campaigns.

This transparency allows advertisers to better understand their user base and buy more intelligently on our platform.

8) What are the most critical reporting needs in mobile attribution?

Barbara: First of all, discrepancy and transparency are critical. No matter how your attribution provider is getting install and cost data (i.e. via API or tracking links), there are bound to be discrepancies between your provider and your ad networks. Being able to analyze these discrepancies is extremely valuable to avoid making decisions based on incorrect data.

Shameless plug:
One of the advantages of using Singular, is we allow you to compare data sets side by side without having to toggle between dashboards. And using our transparency feature, marketers can select their preferred source for each metric, then easily locate discrepancies in their data, while even setting-up alerts when discrepancies exceed a threshold.

In addition, ROI (return on investment) is the single most important metric for mobile marketers. However, most attribution providers are only able to provide ROI insights at the source level because they are unable to reliably match cost and campaign data with user level data. True ROI data empowers you to optimize your advertising by the quality of users it’s driving, instead of just install and revenue data. It’s also a must-have if you want to scale your programs while maintaining or even improving efficiencies.

David: In my experience at Liftoff, when there are some discrepancies in between different reports the first two places that we would look are fraud and tracking issues. If the discrepancy is due to fraud we revamp what we are doing and work hard to protect our customers.

If the discrepancy is caused by tracking issues we work with our customers and their attribution providers to get tracking functioning as expected.

9) What kinds of ad fraud are most common? How can I avoid them?

Barbara: Today there are two main forms of fraud: fake users and attribution manipulation. Fake users involves bots, malware and install farms to emulate clicks, installs and in-app events, causing advertisers to pay for activity that is not completed by a real user.

Attribution manipulation is an especially dangerous form of fraud since it not only costs marketers their spend but also corrupts performance data, causing marketers to make misguided acquisition decisions. The two most common types are click injection and click spamming.

David: Click fraud is a major form of fraud that we are seeing right now. It can be anything from click farming to click spamming to click injection to ad stacking. These types of fraud are meant to drive a high number of clicks, reduce the CPC of a campaign and possibly steal attribution from users that could convert organically.

Another example of fraud would be install-fraud through something like install farming or click spamming to steal install credit. These types of fraud are done to drive a higher number of installs to reduce the CPIs of a campaign. In order to combat both click-fraud and install-fraud Liftoff recommends focusing campaigns on actions that users perform through CPA goals or KPIs or through setting ROAS goals or KPIs.

Other ways that we help our customers avoid fraud are blacklisting suspicious traffic, blacklisting traffic from suspicious sources, we even go so far as to reject anonymous traffic, or traffic that doesn’t have advertising IDs or IP addresses associated with the devices.

10) How can I avoid ad fraud?

Rina: Attribution partners and ad networks will have their own technology to prevent and detect fraud.

Something that you can do as an advertiser is take a look at ROAS data, which can be useful to spot install fraud or fake users. However, click fraud or attribution manipulation will typically snipe organic users that usually have high LTV.

At Vungle, we recommend marketers take a closer look at their CTR/CVR and click to install time distributions to find any anomalies. Any abnormally high CTR or low CVR can signal that the clicks aren’t real. A click-to-install time distribution that is skewed beyond the one hour mark is also an indicator that most users didn’t download after a real click that redirected them to the store.

11) Should I pay extra for fraud protection?

Barbara: The biggest mistake marketers can make is to think that fraud is a “nice to have” feature, or that they can “block fraud manually”. Even traffic that looks great i.e. good retention, high ROI can actually be fraud due to attribution manipulation. That’s why we at Singular offer fraud prevention for free.

Also be careful of the actual type of fraud prevention your provider has. With fraud costs so high and growing every year, you need to ensure that your attribution platform not only detects fraud but proactively prevents fraud in real-time.

And by this I mean some attribution providers do not offer actual prevention, but only detection. That means they offer “alerts.” where you then have to manually look at the data and fix it in retrospect. Be on the lookout for prevention types including IP blacklists, geographic outliers, hyper engagement, install validation, and time to install analysis – and the more included the better.

12) How can I ensure brand safety in my mobile advertising?

David: We have customers that worry about brand safety and focus on targeting specific verticals and avoiding others. This is done by setting up either blacklisting or whitelisting for specific types of apps. An example of this would be to blacklist violent apps.

13) Getting app installs is great, but it’s just the first step. What are the most important post-install events to measure?

David: App marketers need to determine which post-install events are the best indicators for future conversions and revenue. Once these events have been determined, these become the events that should be tracked and used to set goals for your campaigns.

These events might be adding an item to your cart or reaching level ten in a game. The idea is that these events indicate a high LTV.

Rina: Understanding short-term metrics as a proxy to determine long-term LTV is the key for performance marketing.

Often times ROAS in the short term is strong indicator of high LTV.

If users often monetize later in their user lifetime, looking at other benchmarks like level completions or retention could be the solution for campaign optimizations.

14) Data is critical to mobile marketing success. Why do I need API access to my attribution partner’s datastream? What kinds of data should I have access to?

Barbara: One of the critical elements to pay attention to if you are in the search for a new attribution provider is data accessibility. After all, your data is only valuable if it’s readily available and in a usable format. This is especially important for marketing organizations with centralized internal reporting.

Regarding what kinds of data you should have access to, there are two types:

  • Aggregate
    This includes LTV, retention, or other in-app KPIs grouped by any number of segments (app, media source, campaign, ad ID, etc).
  • User-level/device-level
    Why do you want this? Just one example: you may need to join that device-level data with offline or proprietary data and perform internal analysis on that combined dataset.

15) Do I have to use one attribution solution across all my apps?

David: The short answer is no … but the long answer is a lot more complicated but really comes down to how many tools you want to worry about integrating and how many tools you want your employees to have to learn.

The more attribution solutions you use across your portfolio the more complexity you add to your portfolio.

Barbara: Yes, complexity is the issue. Do you want to have multiple dashboards? Different workflows?

16) Measuring installs is great, but we do have attrition. How important is uninstall measurement?

Barbara: Uninstall measurement is a useful metric when it comes to understanding your users.

Uninstall data by itself is interesting, but its best used in conjunction with other lower-funnel events to understand the behavior of your users and of your marketing activities.

Aside from the insights, uninstall data can be provided to partners to be used in campaigns for retargeting audiences.

17) Can I use attribution to know how much ad revenue I’m generating from each mobile app user? Or from each network?

Rina: Analytics providers are starting to develop features to ingest ad revenue data to be able to track true LTV of acquired users. As ad revenue on the user level data becomes more readily available, I expect this feature will be widely used by developers.

Barbara: The short answer is yes. It’s a developing technology that we have some customers using right now. The best thing I can say is … talk to us!

Next steps: mobile attribution master class

Quick-witted readers may be wondering: How did 27 questions turn into 17? The answer: via the magic of multiple queries within each one.

But you may still have unanswered questions.

The solution: get a copy of our 7 things your mobile attribution tool doesn’t do (but should) report! Alternatively, get a full demo of Singular’s mobile attribution capabilities.