Over the past decade we’ve seen the rise of the marketing technologist, who has one foot in the marketing department and another in engineering. And we’ve seen the data scientist role jump from almost nonexistent to being one of the fastest-growing jobs in just a decade.
Increasingly, as marketing is changing, technology is central to how marketers perform. Growth is now a key unifying function in brands and enterprise, and we’re also seeing the rise of the Chief Growth Officer.
We’re releasing a report on that in about a month.
But … our CEO Gadi Eliashiv gave a sneak peak at some of the results recently at Mobile Apps Unlocked in Las Vegas.
The rise of chief growth officers
Ultimately, the way chief growth officers lead their organizations is by using data-driven insights. Some of the most successful leaders drive those insights via marketing intelligence platforms like Singular.
The primary function of a marketing intelligence platform?
To provide insights for growth by connecting effort with outcome at granular and aggregate levels.
Ultimately, that’s how CGOs and other growth leaders get the score. Understand if they’re winning or losing. And know at both as high level and as granular as they want: how successful are our marketing, our campaigns, our ads, our creative.
Knowing that — and getting smart insights for optimization — powers breakthrough improvement in conversions and ROI. And that’s exactly what most brands, enterprises, and companies need.
In the simplest possible terms, a chief marketing officer’s role is to implement strategy that ultimately increases sales. A chief growth officer’s role is even simpler and more explicit: grow the company.
But how?
And what tools do they need to achieve those goals?
Singular is privileged to work with growth marketers at companies like Lyft, LinkedIn, Rovio, Wish, AirBnB, DraftKings, StitchFix, plus many more. We’ve seen what the best growth marketers the planet do, and we know what technology they use.
“Marketers are drowning in data,’ says Jo Ann Sanders, a VP at Optimizely.
That’s the problem.
“With the exponential growth of data over the past decade … it’s becoming harder daily to turn information into action,” says SurveyMonkey CMO Leela Srinivasan.
Marketers are drowning in data thanks to the unprecedented data exhaust of our digital lives.
We browse the web, we install apps, we watch four million videos on YouTube every minute, we search on Google 40,000 times a second. The world will soon have almost six billion mobile subscribers, and American adults now spend more than 3.5 hours a day on their phones in branded apps, sponsored media, and ad-supported sites.
At the same time, marketers are dealing with an exponential rise in tech tools, more digital channels than ever before, and more billion-user platforms every year.
Add in global competition, and 76% of CMOs say they can’t measure marketing performance accurately enough to make truly informed decisions.
Marketing intelligence platform
What marketers need most is actionable insights for growth. So CMOs’ (and CGOs’) biggest challenge is simply mining nuggets of gold from all that data. That requires real-time measurement and analysis at scale across potentially hundreds of platforms, partners, and channels.
That’s why Singular built what we call a Marketing Intelligence Platform.
The new marketers are different. They speak data and write code. They form hypotheses and run experiments; then measure results and optimize. These new marketers are marketing scientists, and they need tools of their trade.
With a Marketing Intelligence Platform, marketers achieve three critical things:
Unprecedented visibility at scale
On-demand flexible reporting
Full customer journey insights
That’s seeing not just your data, but your ROI on every activity. It’s slicing and dicing not just by campaign, but getting CAC per creative asset. And it’s measuring not just conversions, but cross-device and cross-platform journeys that led to customer action.
This requires at least nine components, combined into a single platform, grouped in three sections. We’ll take a very brief look at each. For a full in-depth overview, however, check out our complete Marketing Intelligence Platform report.
The three things that CGOs and CMOs need to drive and accelerate growth are …
One: Unified marketing data
You can’t get the golden nuggets of actionable insights without mining your data, and that starts by unifying it.
Unifying marketing data includes:
Data governance
Data ingestion
Data processing
Attribution
Dimensional data combining/synthesis
Data governance ensures clean data from every source, and enables processing, enriching, and combining later on.
Ingestion is getting all your relevant data from every source, and it’s not easy. Processing is essential to standardize and normalize it, at which point you can conversion outputs to marketing inputs. Combining and synthesizing top-funnel and low-funnel data reveals deeper trends and granular results.
Two: Intelligent insights at scale
At a high level, marketers need to know the score: across all their campaigns, are they winning or losing? At more granular levels, they need to know if a specific campaign, partner, publisher, or creative is performing.
Generating intelligence insights includes:
Reporting and visualization
Actionable insights
Reporting and visualization shows marketers what’s happening, and actionable insights provide clues for future profitable growth. Some of those insights are pull, but some need to be push: alerts about out-of-scope campaigns, click-through rate drops, poorly performing ad partners, and so on.
Three: Automation
The volume of data flooding marketers’ dashboards, reports, and spreadsheets cannot be handled manually at scale. Automation is required, and it includes:
Data transport
Alerts, fraud, audiences
And much more
It is not useful to have a system that only ingests data. Marketing data needs to move from systems of deployment to systems of analysis to systems of engagement, and sometimes in multiple directions. So building in the ability to do that via API, exports, or S3 to internal BI systems and hundreds if not thousands of external partner systems is critical.
And while modern scientific marketing is not a set-it-and-forget-it activity, marketers increasingly need to be able to automate actions within set parameters.
That includes automated creation and distribution of audiences for retargeting, look-alike campaigns, or suppression lists. It also includes built-in on-by-default configurable mitigation of fraud, along with both whitelisting and blacklisting of sources and publishers in paid media campaigns.
And at higher levels, it includes automation of bids and buys for ad campaigns at scale.
Results: what a marketing intelligence platform delivers
What does a marketing intelligence platform deliver?
Find out soon in part two of this blog post, coming next week.
Intelligent data that drives insights for growth requires three key ingredients:
Accuracy
Granularity
Actionability
In order to obtain all three ingredients, you need to ensure the reliability of API integrations with each of your marketing platforms. This is where you find the Singular difference. Singular is the only measurement partner to have two separate API integrations with Twitter, along with over 1,000 additional marketing platforms, providing you the most comprehensive solution for ROI down to the creative level.
This is what we call “dual integration.”
WTH is the Dual Integration approach?
Before you can understand the importance of API integrations (and dual integrations) you first should understand the type of data you need to collect in order to have anything meaningful for your campaign optimization efforts. Simply put, there are two key data sets you need to collect from your marketing platform, whether that is from Twitter, Snapchat, Pinterest, Facebook, Google, Vungle, Unity, Amazon: you name it.
First, you need your campaign analytics data (aka pre-install data) to answer questions like:
“How much did I spend on this campaign?”
“How many impressions did that creative get?”
“How many clicks came from each publisher?”
Second, you need your attribution data (aka post-install data) to answer questions like:
“How many installs did that campaign generate?”
“What was the revenue on this creative asset?”
“How many people went to level two as a result of this keyword?”
Only by combining these two datasets with a robust cost aggregation solution can you really know your ROI by campaign, by creative, by keyword, and by individual ad. This gives you the power to optimize at the most granular as well as aggregate levels, providing your best opportunity to maximize profitability.
To do this manually, you would need to standardize the hierarchies (some sources offer only campaign and ad level, while others go right down to the keyword) and the taxonomies (names and terms differ) across every source, and then calculate your ROI by each dimension … every single time you need it.
Sounds like a pain in the @$$?
Good thing Singular has already done it for you!
This is the dual integration approach
Singular has spent years building API integrations for both sides of the puzzle across over 1,000 additional marketing platforms, and automatically combines this data to show you ROI at the most granular levels.
Unlike other analytics platforms who are only accountable for your “pre-install data” or other attribution providers who are only accountable for your “post-install data,” Singular is accountable for both. Which is why we are the only Twitter measurement partner to have integrations that collect BOTH datasets, just as we do for hundreds of other marketing platforms: so we can do dual integration for you, out of the box.
Inherent flaws with tracking links
You might be asking: So why can’t I just use tracking links to collect this data? My attribution provider uses tracking links and says they can do campaign ROI.
Great question! While the tracking link is the easiest way to collect the necessary macros for a given network, this method has some inherent flaws.
It is not retroactive
You are only receiving data at the time of the click, therefore if the numbers reconcile after the time of the click, this will not be reflected in your reporting.
Not all networks support passing all macros
For example, you might be able to receive campaign cost and clicks, but you may not get site ID or publisher ID.
No creative assets!
Singular is the only solution on the market to provide you the most complete reporting of your creative asset ROI across the most visual networks. However, creative assets and their performance can only be reported by an API integration.
Data loss and discrepancy is HIGH
In a recent study, we compared a number of customers who were using Singular along with a third-party attribution provider. In observing their “campaign data” collected via our API integration against the same data set collected via the tracking link by the third-party attribution provider, we saw a 31% discrepancy … with the numbers reported from our API integration matching identically to the number on the final bill.
Of course, we too sometimes rely on the tracking link for those marketing platforms that do not offer an API to collect campaign analytics. However, in the rare case that we cannot collect data via an API, we will also rely on alternate integration methods to ensure accuracy of the data.
For example, a daily email report, or a CSV file upload to an S3 bucket.
We understand every marketer is different, and how you look at your data may be completely different from your competitors. We are flexible and here to ensure the data you see in Singular matches your internal systems.
Heck, we even have a bi-directional API to push and pull data to your source of truth.
Already a Singular customer and looking to take advantage of our dual integration with Twitter? Check out the help center for details on how to configure your Twitter integration.
Today, Google officially announced its latest solution for mobile app performance marketers with the release of App campaigns for engagement. Combined with Singular’s support of this new campaign type, marketers have all the insights they need to maximize revenue and the lifetime value of every single user.
In November of 2017 Google introduced its AI-powered solution for optimizing mobile app campaigns which provides huge improvements to conversion rates. However, the question remained: “now what to do with all those new users?”
ENGAGE!
Google App campaigns for re-engagement runs on the same powerful AI to help marketers re-engage with their customers and encourage them to take specific, in-app actions. The goal of App campaigns for engagement is to improve customer retention and long term revenue by increasing active users, generating sales, and reducing churn.
Have a group of high-value customers that you want to keep happy? Engage them with a customer loyalty offers. What happened to all those users who added something to their cart but never purchased? Target them with a discount to complete their order. What about all the users who you know downloaded your app but never opened? Message them with an incentive to check out “what’s inside”.
Getting started with Google App campaigns for engagement is simple.
Singular makes it easy to set up conversion tracking, create deep-links into the relevant points in your app, and measure the performance of every event from the first time a user engages with your campaign, to the last time they engaged with your app. Get more details from your Singular Help Center.
If you are as excited about Google App campaigns for engagement as we are, reach out to your Google account manager to apply to for the whitelist.
Still, have questions? Reach out to your Singular Customer Success Manager or email us at contact@singular.net for more information.
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?
The world’s biggest gaming market banned new games from entering the market starting March of 2018. China stopped approving games amid a regulatory overhaul triggered by growing criticism of games for being violent and allegations that they were causing myopia as well as addiction among young users.
Just recently, however, that changed.
In December, China decided to approve the release of 80 new games after months of no action. Now that the Chinese government has lifted its ban on new gaming releases, gaming app developers are chomping at the bit to launch their new mobile gaming apps on Chinese app stores.
The Chinese mobile opportunity
Vast opportunities are on the horizon as approvals begin to flow again.
China accounts for one out of every four US dollars generated globally from mobile games. The revenue generated by apps in China in 2017 is an estimated $35 billion USD, and app downloads from Chinese Android stores are expected to reach almost $90 billion by the end of this year. Additionally, according to the China Internet Network Information Center (CNNIC), the country’s internet user base now stands at around 772 million, 97% of whom are smartphone users.
This is one massive dragon of an addressable market.
But as a rule, China’s licensing system requires that foreign publishers obtain government approval that often involves a complex process before releasing their games on one of the country’s app stores. This process can take months and has had a significant impact on some (but not all) foreign publishers, deterring some from launching locally. One consequence of the increasingly challenging regulatory environment: at the time of the complete ban, foreign developed games accounted for only 25% of the top 250 mobile game downloads on China’s App Store. That could start to change as approvals are starting to flow again.
With China’s recent reversal in attitude and policy, the tide appears to be turning for non-domestic publishers. 2019 and beyond looks promising for game developers who wish to tap into the Chinese market.
Here are a few important things to know before entering the market.
Complex app store landscape
While the Apple App Store lives very successfully within the great firewall, Google Play is strictly blocked, along with the rest of Google’s services. Instead there are over 400 Chinese alternative app stores where you upload your product for review.
Baidu’s mobile app store
The major ones are often owned by China’s biggest tech companies. For instance, Tencent, Baidu, Huawei, Vivo, China Mobile, and Oppo run major Android app stores. Of course, every store has its own terms and conditions, as well as specific requirements.
In recent years, some of the top handset manufacturers came together to form an alliance to standardize some of the app development and publishing features between app stores.It’s still early to determine how effective this will be.
Different advertising channels
With so many foreign internet services and apps blocked by the great Chinese “firewall” including Google, Facebook, Instagram, one of the key things that advertisers need to be aware of is that the advertising ecosystem in China is extremely different.
Ad channels and ad networks that have worked well for them in other markets may not necessarily render the same results in the Chinese market. In many cases, they may not even exist in China at all.
One way we can help: Singular houses the largest database of global advertising performance data and has successfully helped marketers to identify and work with the most effective ad channels globally, as well as in China.
(If you would like to speak to one of our in-house client success consultants, we would happy to share our list of top performing ad channels in China.)
Culture, language, and UX
WeChat’s opening screen
Chinese culture, language, governance, and mobile user habits are very different from the rest of the world. While the world’s average smartphone user has around 80 apps on their phone, in China users have over 100 … including and especially WeChat, the top social media app with over 200 million daily active users. WeChat has over a million mini-apps … including payments, services, stores, and just about anything else that run within WeChat.
This unique climate means that simple translation won’t suffice, and more complex redesign is often required.
Working with a local developer and translator is highly recommended, and success in China often means re-inventing your game or app for Chinese preferences and habits. Chinese customers typically shun apps which appear translated, so it’s important to make the app look as if it were made in China.
User monetization
In China, most paid and subscription-based apps don’t generate revenue, as free unofficial versions are readily available. This has led to the majority of companies monetizing apps through ads. Interstitial ads are one of the most popular methods of app monetization, with nearly all of the most prominent local apps implementing them to promote in-app purchases and other relevant products.
Banner ads and video ads are also prevalent. One challenge: as a large and populous country, China has many different dialects, which app publishers have to remember as they localize their apps.
APK fraud
Thanks in part to the proliferation of app stores, APK fraud is a challenge. Scammers grab the source code for your app or game, change it slightly and add their own monetization. Then they simply re-upload it to multiple app stores as their own, and benefit from an ad revenue stream, or in-app purchases.
Overall, the Chinese internet and mobile ecosystem is probably the most complex in the world. But since it is also the biggest in terms of consumer app spending, the rewards for getting it right can be massive.
Getting started
Singular has helped top global advertisers to successfully enter the China market.
We welcome you to reach out to speak to one of our in-house experts on the Chinese market and share more in-depth learnings for entering the market successfully.
Is it scale? Quality? Lack of fraud? Personal service, or a great digital experience? Amazing technology? Or perhaps a tight focus on your particular niche?
We recently asked 1,500 marketers a simple question:
How do you choose ad networks? And what are the most important elements of that decision?
According to the responses, it’s pretty much all of the above. If they were absolutely forced to just pick one, completely compelled to isolate one single most important factor — on pain of losing their quarterly bonuses or maybe even the free triple-venti-soy-no-foam-lattes at the office — it’d probably be scale and reach.
But it’s a tight competition with the other options.
We only surveyed marketers who actively run ad campaigns. And the results make it clear that ad networks have their work cut out for them, because marketers are not easy customers. Quite simply, when it comes to choosing an ad network, they want it all, and they want it now.
As we all know, when everything’s a priority, nothing is a priority.
Looking at the results, we’d almost be tempted to say that when marketers are asked to choose ad networks, they don’t have a clue what the most important factors are.
But that’s probably unfair.
Individual marketers probably have a pretty good idea what works for them … and how to improve it. However, it is clear that marketers as a group lack consensus on what’s most important in finding new ad partners.
And that might just be the nature of the beast:
It’s not like this is easy.
Of course fraud protection is important. Of course scale matters. Of course a media source’s target tech can be a difference-maker. It never hurts when an ad network has special ability to focus on your specific vertical. And getting the best quality traffic, users, or customers is essential.
So it’s no surprise which ad networks marketers trust most.
We asked the same marketers that question, and the top four were names your grandparents recognize: Google, Facebook, Amazon, and Apple. They’re all massive companies, name brands, and have largely walled garden ad ecosystems, which typically means extremely low fraud.
But your marketing can’t end there.
Why?
We know that most marketers who are successful use many ad networks. In fact, they typically achieve 60% more conversions with 37% less cost. That’s not easy, and it takes work. Profitably scaling media sources is hard.
When everything matters, all your decisions are challenging. Because not all ad networks have huge scale, or super-strong fraud protection, or amazing targeting. But there are typically pockets of profitable growth spread in many different media sources.
Need help? Two ways we can help you choose ad networks:
Of course, that’s where the challenge lies. And doing it is not nearly as easy as saying it. But, as we’ve seen in our Scaling Mobile Growth report, top marketers get more and spend less, helping their companies achieve breakthrough growth.
A great product is a necessity, a great team helps, and a great offer is important, but great marketers know that to maximize their results, they also have have to successfully manipulate four key levers: creative, media sources, bids, and budgets.
Get them right consistently, and you win.
Screw up any one of them, and you risk blowing budget, wasting time, and killing credibility.
Brendan Lyall
Brendan Lyall knows more than most about being a top 10% marketer. He was a growth marketer at RockYou! and Storm8, then built businesses in mobile marketing: Grow Mobile, which was acquired Perion Networks, and Downstream.ai.
He’s currently helping Snap build out its ad solutions for marketers.
I spent some time with him recently to talk about marketing, growth, and moving beyond what is safe and known in order to achieve outsized results.
Essentially: how to become a top 10% marketer.
Koetsier: There’s a comfort level for digital marketers in using ad partners they’ve always worked with before. But what’s the risk in that?
Lyall: I’ve been a marketer and I’ve been on the ad network side too.
It is always risky for marketers to get too complacent or comfortable with their current ad vendors. The ad ecosystem is a constantly changing landscape of ad partners and that also includes ever-changing performance of ad partner inventory quality and install value.
There are also inward changing variables that app marketers need to keep in mind to keep they their UA campaigns running efficiently. As many mobile apps evolve, so do their user bases, features, monetization strategies and a countless number of other variables, and this can directly impact the app’s ad campaign performance.
One common scenario is, your ad partner breakdown at one stage in your mobile app lifecycle might be a great fit and provide excellent yield, making the ad partner choice and reliability appropriate, but as the app transitions to another lifecycle phase this can result in certain ad partners being no longer effective or the best choice for a marketer’s ad partner stack. Active and savvy marketers should always consider and test new partners and track the performance fluctuations in correlation to the changes to the app.
It’s important to never allow ad partners to run unsupervised with no or minimal optimization. A marketer’s comfort can lead to complacency and while we all know building a efficient and ROAS-rich strategy is not accomplished overnight. Always stay on top of your marketing campaigns and constantly validate and iterate your ad partner prioritization.
All of the quality ad partners in the mobile ecosystem have evolving products, ad units, optimization algorithms and publishers, so continue to stay up to date on your ad partner’s product offerings and how they benefit your marketing strategy. Marketers should test new channels continually and optimize their campaigns to ensure that their ad partners remain relevant throughout their app’s lifecycle.
Koetsier: The same applies to old versus new ad formats. What have you seen happen when marketers try new ad formats?
Lyall: This is something that has been a constant struggle for a lot of marketers. New formats are really exciting, but can be challenging if you don’t have the resources. Creative and ad formats are often the one of the most crucial part of a performance marketing campaign and can often get overlooked.
Quantitative optimization often takes the front seat for obvious campaign changes since they can be most closely A/B tested and correlated to certain results. Creative and ad formats are the hardest to optimize effectively and to quantify accurately.
One thing that Snap has been very conscious of is user experience and how different brands mesh with that quality standard. As mobile users we are constantly finding ways to subliminally block out ads, this brings up the importance for both marketers and ad partners to constantly iterate on ad units and formats. Testing new creatives is something we encourage our marketers to do frequently. Snap ads are a full-screen experience and this is a unique and immersive way to interact with an app or a brand, and when people spend time with them, they demonstrate high levels of intent.
It’s no surprise that ad solutions that allow for strong customization for natural and native experiences perform the best. For marketers who do not have the luxury to do high production ad formats, it’s important to iterate and test the formats that are within reasonable scale to your budget and resources.
We often see marketers test Snapchat Ads for the first time get impressive results. With thoughtful optimization and iteration within our Snap Publisher Tool, they have been really pleased with the new segment of users coming from Snapchat through the immersive ad units. User experience is very important to Snapchat which is why the ads team has continually iterated on new ad formats that resonate best with Snapchat’s audience of users while also presenting relevant ads for them to interact with.
Ultimately, new kinds of ad types have created new opportunities for stronger adoption and better performance.
Koetsier: What’s working best on Snap right now? What kinds of campaigns for what kinds of brands?
Lyall: From a performance perspective, we see a lot of scale when it comes to gaming and commerce. We’ve also had very significant scale in dating and travel.
Many of these are very performance-driven campaigns, and we see a lot of advertisers who have very specific downstream metrics and post-install events being able to scale very well with Snap. In commerce, deeplinking has been very successful for specific sales, either to another app or an external website.
Koetsier: What are the common characteristics of the best marketers — top 10% marketers — that you’ve seen?
Lyall: The Snapchat Ads self serve ads manager tool is used by a wide range of marketers and advertisers based on budget size, business category and needs.
To speak more towards the relevancy of this blog post, app advertisers have shown really significant adoption and success in the ads manager’s short history. Our most successful UA managers who generate app installs from Snapchat exemplify a heavy quantitative and non-biased approach towards their ad partners and constantly iterate and test on a wide range of campaign variables.
They also are able to understand that while the quantitative optimization is one piece of the puzzle, the creatives and ad formats are much more difficult to quantify and take a scientific approach to how they evaluate creatives and ad units. Overall, a tireless effort from UA advertisers who are willing to get their hands dirty and optimize campaigns and constantly iterate and test.
Koetsier: Thank you for your time!
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To learn more about becoming a top 10% marketer, get a copy of our Scaling Mobile Growth report. We analyzed over $10B in ad spend and a trillion ad impressions to learn what the best marketers are doing, and are sharing the insights with you.
What do brands need most out of their marketing data in 2019?
Actionable insights, consumer privacy protection, and full marketing data unification, chief marketing officers say.
I recently asked 199 CMOs, VPs of marketing, and other marketing leaders what their biggest challenges for marketing data will be in 2019 for a story in Inc. (There was far too much to write there, so this post became necessary.) Tops on marketers’ lists of priorities? Actionable insights in an avalanche of data. But just behind it in today’s climate of consumer privacy breaches was privacy – and trust.
Here’s how Felicity Carson, CMO for IBM’s Watson division, put it:
“Among all the marketing data challenges, the biggest in 2019 will be how marketers instill trust in data – both for the marketing discipline and customers – balanced with the need to improve customer experience.”
The 800-lb gorilla in the room?
Marketers have far too much data already. That’s a consumer privacy risk, but it’s also a potential marketing intelligence nightmare.
“Marketers are drowning in data from various analytics systems,’ says Jo Ann Sanders, VP of Product Marketing at Optimizely. “What marketers are going to have to do going forward … is to go beyond analytics data … and adopt new, agile test and learn practices.”
Marketers don’t need more data.
What they need are actionable insights drawn from the data they already have. Marketers’ third priority, unifying all their marketing data, will help.
“With the exponential growth of data over the past decade and into the new year, it’s becoming harder daily to turn information into action,” says SurveyMonkey CMO Leela Srinivasan. “While more data has the potential to deliver more meaningful insights, prioritizing an action plan to address it is critical.”
Consumer privacy and data security
Insights are essential for growth, that’s clear.
But a strong brand untainted by consumer privacy breaches is also essential for growth. Anyone who feels otherwise, just ask any company that experienced a privacy breach in 2018 … and look at its stock price impact.
That’s why, almost shockingly, marketers’ second-biggest concern has now become consumer privacy, the security of consumer data that brands now possess, and regaining the trust of their customers.
“The single biggest challenge B2B marketers face in the coming year will be balancing privacy and personalization to regain the trust of their audiences,” says Penny Wilson, CMO of social media marketing platform Hootsuite. “That starts with respecting [consumers’] privacy, being open and transparent about when and why data is collected, and then leveraging the data that customers are willing to share to create personalized one-to-one experiences that deliver unique value.”
“Going forward, brands must focus less on maximizing reach, and more on generating transparent, quality engagements that add value to their customers,” Wilson adds.
This is not business as usual for marketers and advertisers, who have typically wanted as much data as possible. In fact, a new “social contract” between brands and consumers will become so important, says Lloyd Adams, SVP at SAP North America, that data ethics will become more important than data analytics.
Unifying marketing data: a top-3 priority
What else do marketers care about?
Not far behind privacy/security/trust, marketers rank unifying marketing data as a top-three priority.
The challenge is obvious.
In a universe of 7,000 marketing and advertising technology tools, marketers are both doing and learning so much more from their prospects and customers. But most of those actions and insights are being generated in siloed, dispersed systems.
“The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration,” says Tim Minahan, CMO of Citrix. “Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.”
The result is not pretty.
“Everyone’s data is a mess,” says Peter Reinhardt, CEO of Segment.
Identifying insights from your marketing data and then unifying them for a single view of customers – and a unified understanding of marketing success – is critical to cleaning it up.
“Data lives in different places — sales, customer service, digital marketing,” says Selligent Marketing Cloud CEO John Hernandez. “The biggest data-related challenge [for 2019] will be consolidation and a full 360-degree view of the customer relationship.”
That’s a difficult challenge, Hernandez says, and CMOs agree.
And in fact, not only is it hard right now … it’s getting harder.
“The biggest issue with marketing data is federating it into a meaningful whole picture,” says Eric Quanstrom, CMO of Cience. “As CMO, I live in (literally) a dozen different dashboards, daily. And that number is growing.”
Marketing data used to be fairly simple: survey data, market data, customer data, product use data, and probabalistic reporting on ad performance in traditional channels. New digital channels offer deterministic reporting possibilities, but with web and mobile and apps and wearables and IoT – to say nothing of platform proliferation like email and social and messaging and search – it’s getting harder.
And all of that proliferation leads to siloed data sets.
The problem with siloed data is that fragmentation subverts complementarity, says Rebecca Mahoney, CMO at MiQ. When data isn’t complementary and doesn’t add up to a complete picture, the marketing results is an inability to detect new opportunities, or see weak links in existing marketing campaigns, she says.
Data lakes may not save marketers, says Daniel Jaye, founder of Aqfer, a data lake provider.
In fact, they can actually exacerbate the problem because most data lakes inevitably become data swamps, Jaye says. Widespread data proliferation, chaotic file partitioning and sharding practices, and the lack of traditional data management tools all cost marketers the opportunity to achieve integrated insights.
Marketing intelligence unifies data insights
But there is hope.
Good marketing data practice does result in growth.
“With a holistic view of data, powered by marketing intelligence, campaign performance will drastically improve, and otherwise unidentified business opportunities will become unlocked,” Mahoney says.
It’s true that not every marketer will have a single marketing cloud for all their marketing technology and data needs. And even most marketing cloud customers also use additional tools to engage and understand their customers.
That suggests that centralization of marketing insights, particularly on paid but also on organic marketing efforts, is what will help marketers the most. Engagement happens where the customers are and data lives in the tools a brand uses to connect with them. Marketing intelligence aggregates then insights from the entire gamut of customer engagement into one single unified view.
Marketers are also concerned about the quality of the data that they have, and its accuracy. 13% said that accuracy was a top concern in 2019. Another 12% said they have too much data.
“In many ways, marketing has too much data on its hands,” says David Meiselman, the CMO of corporate catering company exCater.
As Citrix CMO Tim Minahan said above, we’ve put too many tools in place to collect and analyze marketing data. The result is frustration.
A potential savior?
Artificial intelligence.
“We … believe marketing and customer engagement will be an excellent first use-case for enterprise AI,” says Patricia Nagle, CMO at OpenText. “AI systems can analyse structured and unstructured data to identify opportunities for marketing outreach, customer support, and other actions that enhance overall customer experience.”
That’s true, and AI is a tool that marketing is already seeing results from in fraud reduction, creative reporting, and other areas.
But it does some with some dangers as well.
“Deep learning models have been shown to be vulnerable to imperceptible perturbations in data, that dupe models into making wrong predictions or classifications,” says Prasad Chalasani, Chief Scientist at MediaMath. “With the growing reliance on large datasets, AI systems will need to guard against such attacks on data, and the savviest advertisers will increasingly look into adversarial ML techniques to train models to be robust against such attacks.”
And finally … all the other quotes
When you ask 200 top marketers for their insights, you get a lot of insights. And they’re too good to bury.
So here are many of the additional quotes that marketers provided, broken down into categories that I’ve chosen. Some of them are partially referenced above, but are given in complete form here. Each of the responses is answering a simple question:
What are brands’ biggest challenges with marketing data in 2019?
Marketers need: Data accuracy and quality
Peter Reinhardt, co-founder and CEO of Segment
The biggest challenge for marketing data in 2019 will be data correctness. Everyone’s data is a mess. Consumers are bombarded with tons of noise, much of it based on wrong data, names, and locations. As a result, customers are burned out. It doesn’t matter how much a company invests in personalization if the underlying data is incorrect. For businesses to truly succeed in 2019 and beyond, they need to prioritize making sure their data is clean and accurate.
The biggest challenge with marketing data in 2019 will be determining how good the data really is. Before this rise in cookie awareness people weren’t really flushing the cookies or clearing their cache as much, which lent itself to long-standing good demographic data. Now, the data isn’t as deep, therefore not as reliable. In 2019, businesses will need to learn to re-target.
Not surprisingly, war against fraud will be the biggest challenges mobile marketers will have to face. In addition to common fraud cases like SDK spoofing and click spamming, more and more new types of fraud will stop developers from obtaining real users. Our job as mobile marketers is to keep educating ourselves about different types of fraud and the pattern of each fraud cases, so that we can take a proper action when we find them.
Marketers need: Actionable insights and marketing intelligence
The best tools solve the disconnect between data, insight, and action, incorporating multiple sources of data to execute, allocate, attribute and optimize digital campaigns across channels.
Marketing data still struggles with insights and it would be amazing to see more of a focus on this essential craft. There are endless tools for gathering the WHAT – numbers and histories and basic information about your customers – but very little that helps us figure out the WHY. The big challenge in 2019 (and likely for a few more years) is going to be training people to understand how to read the what to get to that why.
Phil Gerbyshak, Digital Selling and Marketing Strategist
With all the data collected, the biggest challenge with all the marketing data is finding the most meaningful data, and then figuring out the most actionable insight from that meaningful data. Too often reports for reports sake are created, even with AI to help us find the patterns. Taking the time to think about what you want to accomplish and setting up your data accordingly will challenge marketers and delight stakeholders in 2019 and beyond.
There is so much data out there that ‘big data’ is no longer the priority; there is a need for actionable data that means something to marketers. The other challenge is that the biggest winners on the platform side are increasingly closed and stingy with their access, which may be necessary for consumers and benefits the platforms but hurts marketers. Finally, marketers will have to grapple with a savvier base of consumers who are constantly reading mainstream press coverage about data abuses; marketers will need to determine how cautious they want to be with collecting and accessing consumer information.
What is the biggest data challenge for marketers in 2019?
Building actionable results based off of accurate data. We continue to see an inability of our clients to properly read analytics and come to assumptions. I hope continued AI and machine learning will add tools to assist.
Felicity Carson, CMO, IBM Watson Customer Engagement
Among all the marketing data challenges, the biggest in 2019 will be how marketers instill trust in data – both for the marketing discipline and customers – balanced with the need to improve customer experience by identifying meaningful patterns buried deep within the deluge of data. Compounding this challenge is the need to break down compartmentalized martech and adtech stacks that house this information, coupled with the need to have contextualized understanding of aggregated customer data across the organization such as commerce and digital teams. Marketing teams will need to rely on AI to achieve this level of high performance at scale, particularly in the new era of the ‘Emotion Economy’ that requires organizations to engage with customers in relevant ways on issues that personally matter to them.
The biggest challenge with marketing data in 2019 will be to decipher which of the outlier [datapoints] are leading indicators into new market growth.
Leela Srinivasan, CMO of SurveyMonkey
Today, we have access to more data than ever before, but with the exponential growth of data over the past decade and into the new year, it’s becoming harder daily to turn information into action. A study by IDC bleakly projects that by the end of 2025 only 15% of global data will be tagged; of that, only 20% will be analyzed and approximately 6% will be useful.
While more data has the potential to deliver more meaningful insights, prioritizing an action plan to address it is critical. In 2019, B2B marketers will be laser-focused on finding a way to cut through the massive troves of data available and identify the insights that matter most.
The biggest challenge with marketing data is the ability to find the useful insights to create concrete actionable next steps. We have so much data, but not enough of an efficient way to sift through the noise accurately for truly useful data.
The biggest challenges we have as a startup are: having easy-to-use data that doesn’t require a ton of training like a Nielsen or IRI platform and being able to triangulate all of our data among a two-person team. Right now, we are using about 8 different vendors to analyze one or more stages within the customer lifecycle, and while it’s great to have all of this data, it’s not easy to triangulate it. It would be great to have 1 platform that could assess all or most of our marketing program’s performance, but those platforms usually come with a large price tag that we can’t afford.
One of the biggest challenges marketers will face in 2019 is how to better analyze consumer behavior and turn those insights into effective marketing. Consumers spend 40 hours a month and three hours a day in apps, mobile time spent will surpass time spent in TV in 2019, so marketers need to change their traditional planning behaviors for this brave new world. They must integrate their traditional teams with their digital teams, combine their video teams into one cohesive team, and integrate the data across all channels so that they can be smarter about how they find their most valuable customers. It is also getting harder with privacy, however, companies with strong technology especially predictive algorithms can predict users intentions based on less data. We are just scratching the surface on data analysis and with new data privacy laws, this challenge will only get harder.
Tim Minahan, Chief Marketing Officer and SVP, Citrix
Every marketing challenge can be whittled down to a mathematical equation – whether it’s measuring customer sentiment, tracking conversions, or weighing the return on a particular campaign. Data-driven marketing can eliminate much of the he-said/she-said friction that has historically muddied sales and marketing relationships. It can cut through emotional biases and drive the right course of action to reach and win the market and deliver the best results. The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration. Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.
To tackle this problem, marketing organizations need to tap into intelligent technologies like machine learning that can make data-driven marketing smarter and easier to execute. Machines can recognize patterns and analyze things with greater speed and efficiency and automatically deliver insights and intelligence that humans can use to make more informed decisions and engage customers and prospects in the most optimal way. And beyond tools that automate tasks and make marketing more efficient, we need to equip our teams with solutions that enable them to push the envelope. Like using artificial intelligence and machine learning to see data in new and innovative ways. Or leveraging augmented reality to create entirely new worlds where we can interact with customers in insanely personal ways.
As marketing tools and automated solutions continue to flood the market, the biggest challenge marketers will face is applying data to create timely, emotionally-reciprocal experiences. More and more consumers desire a human to human connection and want to communicate with an empathic human rather than a bot or an algorithm. The year ahead will be a pivotal milestone for marketers and brands, the ones that use their data to better understand consumer behavior and leverage it to create more personalized, human connections will succeed, while the ones that do not will risk losing loyal customers.
In 2018, if you’re a marketing professional that listened to recommendations of marketing experts everywhere, you collected a lot of customer data and used it to formulate campaigns. The problem of moving marketing forward into 2019 is two-fold; security and recognizing changes in data before solid patterns are defined. Data security, obviously, will be most important for maintaining trust between marketing and their audience, whereas recognizing emerging patterns in the data deluge will mean the difference between cutting-edge marketing or just ‘catching up’ marketing in the new year.
Sid Bharath, growth marketing consultant for tech startups
The biggest challenge with marketing data is figuring out what signals to pay attention to and how to prioritize them. With an explosion of data, the bottleneck moves to how fast you can execute on what the data tells you, and unless you have unlimited resources, you need to prioritize them.
The biggest challenge with marketing data in the coming year will be gaining actionable insight from a flood of data generated via a diverse and numerous set of online (and offline) channels, including social media, website, email, events, PR and advertising.
The Marketing Data Scientist will be focused on deriving detailed insight about customer behavior and producing reliable predictive and prescriptive insights based on complex data models and machine learning. These models will evolve from historical analysis into real-time applications that transform how products are delivered to customers.
Gennady Gomez, Director of Digital Marketing, Eightfive PR
As marketing data becomes not only more accessible but also much more bountiful, there will be an exponential increase in analysis paralysis. As a result, we’ll start to see the focus in martech shift from data mining to insights reporting, driven by data science and machine learning. These new breed of tools will be critical for marketers as they sort through, identify, and filter actionable data.
Until our ability to glean insights from all this data catches up to our ability to capture it, we’ll face the same issue as a city with plenty of cars and not enough roads: traffic. Don’t confuse having more data with having more insights.
The biggest data-related challenge will be consolidation and a full 360-degree view of the customer relationship. As it stands, data lives in different places — sales, customer service, digital marketing — and migrating it into a single platform and making sense of it all is going to be difficult. I hope that in a year’s time, we’ll see a lot of progress and proof that leveraging data to focus on delivering personalized, more relevant experiences is the optimum path for better engagement, stronger sales pipelines, and more meaningful marketing results.
Emerging technology has improved marketing strategy, but the challenge marketers are facing is the daunting task of managing a large number of applications. In the next year, more CMOs need to take a platform approach. Investing in a platform that can be integrated into an existing CRM allows organizations to easily unify their revenue teams, and with the addition of AI incorporated into the platform, unified teams have insight into the behavior of modern buyers with the use of real-time data.
Connecting the dots between marketing touch points and giving proper attribution has been and will remain a major challenge for marketers in 2019 … it can be hard to get a full 360-degree view of the true marketing and sales funnel … it is still nearly impossible to combine data from multiple touch points … to paint a full picture of marketing efforts and sales results.
Many marketers have so much data from multiple domains on hand, but no way to streamline and manage it in one centralized location to gain valuable insights.
Eric Quanstrom, CMO, Cience
The biggest issue with marketing data is federating it into a meaningful whole picture. As CMO, I live in (literally) a dozen different dashboards, daily. And that number is growing.
Daniel Jaye, Founder, Aqfer
2019 will be the year enterprises discover that serverless data lakes are a thing, and that they inevitably become data swamps due to widespread data proliferation, chaotic file partitioning/sharding practices, and the lack of traditional data management tools. As marketers are still floundering to piece together the data and figure out whether or not campaigns truly succeeded—they will realize that they can’t keep their heads in the sand on data any longer, and must work to get a better grasp on data management in order to get to the truth about their customers.
The biggest challenge will be how to tie all the data together to clearly identify what marketing channels are working or not working. There are multiple touch points to a buyer’s journey and it’s very common to see multiple marketing channels involved in the buyer’s decision, which makes it hard for analytics tools to attribute accurately what marketing channel contributed the most.
The biggest challenge in 2019 will be the ability to bring together … multiple sources of data to connect the dots, make informed decisions and act quickly on those insights.
The marketing technology landscape is increasingly fragmented and that’s not going to slow down. But marketers will need to find a solution to stop isolated data sources from negatively impacting their marketing capabilities in 2019. By integrating key marketing technologies such as CRM, marketing automation and ABM platforms, marketers can start to share data across these applications and get the complete customer view that they crave.
Businesses have a wealth of valuable marketing data available to them, but complications arise when this data remains in siloes pertaining to the different departments within that business. This prevents the data from being complementary, and businesses cannot detect potential weak links or new opportunities. With a holistic view of data, powered by marketing intelligence, campaign performance will drastically improve, and otherwise unidentified business opportunities will become unlocked.
In 2019, marketers will be faced with the challenge of data implementation. Marketers know how valuable data is, but struggle to make sense of it as they’re faced with the challenge of navigating numerous fragmented platforms and systems to get accurate and quality data. The goal is to gather data from multiple sources that work together to achieve optimum success, but there isn’t one standard way to streamline data. Eventually, unlocking this will give marketers the capability to improve context, relevance, and develop creative that resonates.
The key is to centralize … data and connect every interaction to a single customer ID. Then you can actually understand how your customer behaves across channels and devices. But even more importantly, that data has to connect to your marketing execution platforms directly, so you actually use those insights to power your marketing.
The increase and abundance of data that is available now due to integrated marketing platforms will demonstrate the flaws in various deep learning models. Deep learning models have been shown to be vulnerable to imperceptible perturbations in data, that dupe models into making wrong predictions or classifications. With the growing reliance on large datasets, AI systems will need to guard against such attacks on data, and the savviest advertisers will increasingly look into adversarial ML techniques to train models to be robust against such attacks.
Marketers are equipped with more consumer data than ever before, which can give them valuable insights into their customer base. Many are eager to use AI to automate and personalize communications, but lack the proper infrastructure and data know-how for AI to work properly. There are countless marketing AI platforms available, but until brands are able to properly segment their datasets and make their data truly work for them, they won’t have the ability to conduct innately intelligent marketing. What does this kind of marketing look like? All the marketer needs to do is set the framework, and the AI takes it from there to create personalized messaging for consumers. In 2019, we can expect to see a push from brands to organize their data within a framework that allows them to hyper-personalize communications.
Analytics continue to be a critical way to review the impact of marketing on business objectives. In 2019 the continued adoption of dashboard reporting and analysis systems will improve how we measure marketing programs and tactics. With better understanding of all marketing functions, organizations can take a more strategic approach and focus on what’s performing best. We also believe marketing and customer engagement will be an excellent first use-case for enterprise AI. AI systems can analyse structured and unstructured data to identify opportunities for marketing outreach, customer support, and other actions that enhance overall customer experience.
We are collecting and analyzing real time data using AI powered platforms … we are telling the story, giving shape and voice to the billions of data points that would otherwise be a bottomless inkwell of unrealized potential.
Marketing data and insights [will become] cheaper due to marketing AI platforms. It will no longer take big budgets, multiple data vendors, and a team of analysts to get actionable insights.
Marketers need: Data security, consumer trust, privacy
Lloyd Adams, SVP, SAP North America
Data ethics will become more important than data analytics.
In 2019, marketers will struggle with the social contract of data exchange between consumers and brands. They’ll wrestle with these questions: How will users be compensated beyond personalization? How can marketers do this without being “creepy”? And, as more biometric data emerges, how can marketers use in an ethical manner?
Making better and more critical decisions about what to collect, how to protect it, how to combine it, and how to use it. The idea of a “360-degree view of the customer” has encouraged brands to collect as much data as possible, but this should never be a goal because it raises risks such as privacy concerns, data breaches, GDPR compliance, and customer distrust. Marketers and customer experience leaders need to focus on prioritizing their data needs, better assessing risks, and developing a data strategy that prioritizes and centers on what data is essential and how it will be used over accumulating more of it.
The single biggest challenge B2B marketers face in the coming year will be balancing privacy and personalization to regain the trust of their audiences. In many ways, 2018 was a tumultuous year for brands, marketers, and customer experience leaders. Concerns around fake news, fake followers, and data privacy led individuals to question their trust in politicians, media outlets, social networks, and businesses alike. Those same concerns extended to how brands — both B2C and B2B — forge relationships with customers, and the data they use to do so. The priority for B2B marketers in 2019 must be to reassure customers – and their customers’ customers – their data is safe and secure. This has to be achieved in the changing climate of customer expectations. Increasingly customers — be they businesses or individuals — are expecting content that is important, interesting and timely to them. That starts with respecting their privacy, being open and transparent about when and why data is collected, and then leveraging the data that customers are willing to share to create personalized 1:1 experiences that deliver unique value. Going forward, brands must focus less on maximizing reach, and more on generating transparent, quality engagements that add value to their customers.
The biggest challenge marketers will face in 2019 is activating their first party data and growing its use. Brands are facing a privacy paradox as customers increasingly expect personalized service, but both data regulations and consumer privacy controls whittle away at third-party data and tracking. To remain compliant and provide great customer experiences, brands will increasingly rely on data customers willingly provide in the course of direct interactions across engagement channels–websites, apps, messages, social and in-store interactions and more. The best brands will go beyond gaining opt-ins, subscriptions and followers, and use these interactions to collect context and content preferences for each individual.
Tifenn Dano Kwan, CMO, SAP Ariba
A greater focus needs to be on being data compliant as well as on the ease of leveraging data.
The biggest challenge with marketing data stems from the fact that marketers have so much data available to them today, which they’re able to use to reach customers in a very precise way, yet there’s currently a huge lack of communication between brands and customers as to how and why that data is being used. Without more transparency with customers around why personalized outreach is happening and how it’s benefiting them, the immediate reaction is one of distrust, uncertainty, and even fear or anger. In 2019, brands need to focus on clear messaging that explains to customers why they’re using personalization tactics, how their privacy is protected, and what they stand to gain from it.
With ad-blockers becoming ubiquitous and privacy concerns reaching a fever pitch, marketers need to rebuild the trust that has been lost with consumers. Some of the most successful marketing campaigns in recent times have been honest and authentic, sometimes to the point of distress: KFC’s apology for running out of chicken and Nike’s partnership with controversial quarterback Colin Kaepernick. The biggest challenge in 2019 and beyond will be to create a new normal between marketers and consumers.
May 25, 2019 will mark 1 year since GDPR came into force in the EU. This privacy law sets concrete standards on how EU citizen data has to be treated in addition to strict guidelines on consent. Successful senders will have taken stock of this law and enacted internal processes to ensure compliance with European law.
As data protection regulations like GDPR become increasingly prevalent in 2019, marketers will struggle to target customers with individually customized online advertising. The most successful marketers will be those who can deliver individualized experiences, without individual user data. Computer vision and other contextual analysis technologies will be necessary to anonymously align ads with the likeliest potential customers.
Esteban Contreras, Senior Director, Hootsuite
We have more data than ever before in history and that in itself is a challenge. One of the most important problems to overcome is how to effectively handle and leverage data – data engineering, data analysis and data science – with legitimate consumer empathy. We need to consider privacy by design. The ethical use of big and small data is ultimately about creating value (e.g. personalizing and contextualizing experiences) without misleading or dehumanizing anyone.
Marketers need: Less data (or at least, smarter data)
The biggest challenge with marketing data will be having too much of it, specifically for B2C organizations.
Marketers crave access to information, but we’re drowning in a virtual quagmire of data. We want to get granular, digging deeper into every data point, but we’re stuck with analysis paralysis — unable to prioritize actions that will have the greatest impact on our KPIs.
Marketers will need a cutting-edge customer experience platform that recommend strategic actions tied to specific KPIs.
Noise. There is a lot of it and it is increasing exponentially. As data volumes increase, the tools we will need to filter it all and extract the valuable components will have to increase in their abilities accordingly.
The sheer volume of data being collected is itself posing a challenge to marketers. As we move into 2019, the ability to separate out meaningful patterns and relevant trends from the vast quantities of background noise will be a real test for many marketing teams.
Because there’s just more and more data with disparate KPIs coming from different sources, the biggest challenge will be in deciding what to ignore and what to value.
I predict a big challenge for marketers in 2019 will be remembering to use data as only part of the story and keep an eye on the bigger picture. How many times have any of us been hit with poor targeting because of something else we’ve liked or clicked on? It will be important for marketers to remember that the people they are marketing to are real, complex people who should be considered as more than just a few data points.
The biggest challenge for marketers is focusing on the data that matters. There is a lot of noise out there and each team member needs to know which data is significant to their success. But, it’s not just about having the data but putting it into context to make strategic revenue-driving business decisions. If you aren’t able to execute on your marketing data, it is useless.
I think the core problem moving into 2019 where marketing data is concerned is that with ever increasing amounts of data, marketers are still looking at each marketing silo individually or in small affiliated clusters as opposed to cross-analyzing insights across the entire marketing, sales and customer service value-chain. Often silo based marketing teams will look individually at social data, demand-gen, PR, sales and customer service rather than studying where they intersect and interact. This has always been faulty and is continuing to be a greater problem as each and every silo continues to yield more data.
Jo Ann Sanders, VP of Product Marketing, Optimizely
The biggest challenge marketers will face in 2019 is getting access to the right data to know definitively what their digital users want. Marketers are drowning in data from various analytics systems that provide a historical view of the past. They then ideate ways to improve based on this past data, spend resources to deploy updates, and then re-measure to see if their ideas worked. This process of guessing at what will improve conversion metrics can take weeks or months.
What marketers are going to have to do going forward to succeed so they can keep pace with rapid innovation is to go beyond analytics data that tells them where they have been and adopt new, agile test and learn practices. This will take the guesswork out of what users want, and better ensure that they are rolling out winning user experiences quickly.
With the proliferation of marketing data the challenge will be how to use the latest tools to narrow 1000 points of data down into the few key quality ones that are needed to improve business operations and to better communicate with your customer.
David Meiselman, CMO, exCater
In many ways, marketing has too much data on its hands. The challenge is to figure out which data helps the most to optimize targeting, messaging, and conversions. Traditionally, marketers would work their way through countless A-B tests to determine what works. Today, machine learning and artificial intelligence is helping us accelerate that process to detect correlations and causal factors to improve marketing outcomes across the board, from which people to target for highest conversion to what message to send when for greatest effect.
Tim Minahan, CMO, Citrix
The problem is, we’ve put too many tools in place to collect and analyze marketing data that are too hard to use and it’s causing a lot of frustration. Marketing professionals are spending way too much time searching for information and clicking through multiple pages in applications to gather the insights they need to design, execute, and measure effective campaigns.
For many years we’ve been trying accumulate as much data as possible, and we’re now ironically in a difficult position of potentially having too much data. We need to remember to sit back and discover what is actually happening at different points in time, so that we can figure out how it all fits together. We also can never forget that the most important data point when building attribution is still “Where did you hear about us?”
Marketers need: Many more things
These quotes don’t fit an exact category. But they’re too good to not use.
Jenni Schaub, Strategic Planning Director, DEG Digital
But always still remember, a mountain of data is not a replacement for empathy
Stephanie Smith, Co-Founder and President, MOJO PSG
Thoughtfully exploring and formulating the question you’re actually trying to use data to answer is a key challenge that marketers must face in 2019. Without taking the time to define the problem we’re solving for, we end up wasting a lot of time swimming in seas of data and even potentially misusing the data we uncover. Marketers must also find a balance between using data to inform, rather than dictate, decisions, as the marketing craft will always be a blend of art and science.
Measurement is hard. For SMBs and mid-market companies, it is harder, and the stakes are often higher. Although last click measurement is an archaic way to measure performance and impact, many marketers still rely on it because they don’t see accessible alternatives, as sophisticated tools are often difficult to set up or not flexible enough to work within their data model.. Yet, marketers are hungry for change and searching for a better way to provide visibility and optimize their campaigns. I see 2019 as the year modern marketers stop relying on vanity metrics and outdated measurement models and start looking at what is actually driving sales. Further, marketers need to embrace multi-channel adoption and prioritize creating connected stories across all touchpoints.
The biggest challenge for marketers will be navigating the evolution of what marketing is in a post-truth world. In 2019, marketers will need to ask themselves the difference between truth and propaganda.
Summary
Thanks to all the marketers who participated in this research, which was initially for my column in Inc, but grew beyond that.
Clearly, there’s a significant change in marketing data policy coming. Marketers know that it’s not about quantity of data but quality. They also know that insights on next best actions is the thing they need their data to reveal. And they are more than cognizant now that consumer privacy matters, and companies that violate their customers’ and prospects’ trust do get punished, both financially and in reputation.
We have to give the last word to Jolene Rheaulot from The Bid Lab.
She said this, which every marketer should remember:
The biggest challenge with the breadth of marketing data available to a company is to keep the data human.
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