Marketing Analytics
State of Play 2022

Data Capabilities& Aspirations

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Contents

Index

Click to view:

1
Executive summary >2
Key findings >3
Self-Assessment ofAnalytical Maturity >4
Current Data Capabilities >5
Data Aspirations for 2022 >6
Capabilities and Aspirations:Marketers Vs. Analysts >7
Capabilities andAspirations by Region >8
Capabilities andAspirations by Industry >9About the research >3Executive summary
As shown in part one of the Marketing Analytics 2022: State of Play,manual data wrangling was the biggest challenge for marketersand marketing data analysts in 2021.
From this challenge comes a sprawling mass of other issues, including lack of visibility, poor data accuracy, and a lack ofactionable insights. In part two of the report, we explore how close to analytical maturity marketing teams truly are, andhow these stumbling blocks could threaten marketing strategies for 2022.

Optimism over realism
On the surface, marketers and analysts are optimistic
about their analytical maturity, with two-thirds identifying
as analytically mature. However, digging deeper, we findtheir actual capabilities are much less advanced thanwe’d expect from an analytically mature organization.
For instance, 68% of respondents who strongly identify
as analytically mature say their marketing reports

are typically built on spreadsheets. Likewise, 77% of
respondents who strongly identify as analytically mature
say they have yet to achieve a single, unified view ofmarketing performance. Marketing teams are living in thepast when it comes to data and analytics. In reality, themajority of marketing departments rely on outdated data
and analytics practices.

Predictive analytics set to take center stage
Marketing teams see the value of predictive analytics
with almost two-thirds planning to implement predictivemodeling in 2022. Marketing is reaching a tipping point
as teams aim to take campaign optimization from reactive
to proactive. Similarly, 56% of marketers and analysts plan
to implement marketing mix modeling in the coming year.

Both these strategies require accurate, integrated data,and neither can be achieved in a meaningful way withouta certain level of analytical maturity. However, far too
often marketing teams still rely heavily on manual dataprocesses to get insights from data.

Marketers and analysts disagree on capabilities
Marketers and analysts have widely varying views on what
technology they need, and even what they already haveaccess to. 60% of analysts say they can run predictive
analytics, but only 42% of marketers agree. A cultural shiftmust take place so that advanced tech doesn’t gather
dust, either because manual data integration undermines
quality and eats up the time of the analyst, or because
marketers don’t have an advanced enough understanding
to use the tech at hand to get value from their data.

have a single place where they can see a full picture of
their world. Subsequently, marketers’ top data priority for2022 is to implement a single unified view of marketing
data, with 58% of marketers saying this will happen in
the next 12 months. The fact that this is still a work inprogress for so many organizations speaks volumes as tohow advanced marketing teams are analytically speaking,particularly when we take into account that analysts
appear to have jumped the gun by making predictive

Marketers say they have plenty of data, but they don’t

analytics their top priority for 2022 (69%).

Freeing the analyst
Many organizations are employing data scientists andthen filling up their time with mundane work like manuallypulling together data from different sources. Not only
does this undermine data quality, but it also meansthat analysts aren’t able to use the advanced skills they
were hired for. To be truly data-driven, businesses needto prioritize foundational data tools which automate

integration before they sink time and money into moreadvanced tech like predictive analytics.
Unless marketers and analysts can take a more realistic
view of their current capabilities and address the gaps intheir foundation, then it’s unlikely that they’ll move theneedle on predictive analytics.

State of Play 2022: Data Capabilities & Aspirations

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Key Findings
Top 5
Plans
for
2022

Developing a single, unified
view of marketing performance

62%

Very strong at campaign reporting

61%

Marketing mix modeling

56%

Incorporating artificial intelligence and/or machine learning into our analytics

54%
51%

Multi-touch attribution modeling
0

10

20

30

40

50

60

70

80

50%

4x

Of respondents are currently using predictive

Analysts who struggle with manual data integration

analytics, and 61% say they plan to achieve moreare nearly four times as likely to struggle with low

predictive modeling in 2022.

trust in data accuracy.

38%

48%

However, 38% of respondents who plan to use

Of analysts who plan to implement predictive

predictive analytics say they struggle withanalytics in the coming year say they struggle tomanual data wrangling.

trust their marketing data.

38%

Only 51% of respondents say their marketing data is accessible from a centralized
data lake.

66%
Of respondents say their marketing team isanalytically mature.

68%
However, 68% of respondents who strongly
identify as analytically mature say their marketing
reports are typically built on spreadsheets.

501Marketing Analytics
State of Play 2022

Self-Assessmentof Analytical
Maturity

6

Overview

The majority of marketing departments rely on
outdated data and analytics practices.
Despite this, a worrying number of businesses that see themselves as analytically mature,
while still wrestling with some elementary challenges. For example, 68% of respondents
who strongly identify as analytically mature say their marketing reports are typically built on
spreadsheets, and 77% have yet to achieve a single unified view of all their marketing data.
However, steps such as establishing a single source of truth and eliminating manual
spreadsheet-based data analysis are fast becoming standard practice for modern marketing
departments. Before you set out a strategy for 2022, it’s important to understand how
advanced your current marketing analytics strategy is, and where the gaps are.

State of Play 2022: Data Capabilities & Aspirations

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Most marketers and analysts consider themselves analytically mature
Analytical maturity is a long and ever-lengthening road,and it goes far beyond solving the data wrangling
problem. The most analytically mature marketing
forces are able to uncover insights from data, measure
the impacts of marketing decisions, and make better
decisions based on data not just in real-time, but
proactively. This requires a good data culture, and it

also requires the right tools to improve. Both are stillchallenges for many companies and marketing agencies.
Two-thirds of respondents say that their marketing teamis analytically mature, and 63% say they are data-driven.
But do our analytically mature respondents fit thesecriteria?

Which of these statements regarding your analytical maturity do you agree with?
Analytically Mature: we are constantly looking for ways
to become more advanced with our use of data66%

Data-Driven: we make strategic marketingdecisions based on objective data

63%

Test and Learn: we regularly test hypotheses and
let the results guide our marketing strategy

61%

Optimizie on the Fly: we closely monitor the performanceofmarketing campaigns and adjust in real-time

61%
0

10

20

30

40

50

60

70

80

Self-assessment Vs. Reality
The current landscape of marketing sees many teams still
grappling with manual data wrangling, and struggling to
get a single unified view over their data. This tells us thatamong marketers and analysts, there is a widespread lackof awareness around what analytical maturity is, and how
far teams still have to go to be truly data-driven.
Today, being analytically mature goes far beyond
spreadsheets and manual number crunching. Marketing
forces at the top of the data maturity curve are making
decisions based on predictive insights, often poweredby advanced AI. For these teams, automated data
integration and a single unified view of marketing
data are a given. However, more than three-quartersof marketers and analysts who say they’re data mature
still haven’t taken this first step towards data maturity.
Marketing teams need to take a critical look at theircurrent capabilities. Before they consider advanced tech
like predictive analytics, they must fill the gaps at theirmost basic level.

State of Play 2022: Data Capabilities & Aspirations

8

68%

Of respondents who strongly identify as
analytically mature say their marketing reports
are typically built on spreadsheets77%

Of respondents who strongly identify as
analytically mature say they have yet to achieve asingle, unified view of marketing performance45%

Of respondents who identify
as analytically mature struggle
with manual data wrangling

Analysts most likely to report advanced capabilities
Data analysts (72%) are much more likely to self-identify
as analytically mature than marketers (60%). While analysts
are closer to the data and the tools used to gain insightsfrom it, they have less of a view on how marketers are
actually using data to drive decisions. So while analysts
might have access to advanced analytics tools, thisdoesn’t translate into data maturity if marketers aren’t
using these tools to turn data into actions.
And as we found in our full Marketers Vs. Analysts report,
marketers often struggle to turn data into tangible

The CMOs’ view from the top
63% of CMOs say they make decisions based on data, butmore than half of those also say they lack data-driven insights
to drive marketing strategy — and 49% lack data-driven
recommendations to improve marketing performance.
Again, there seems to be a great deal of optimism when it
comes to higher-level questions, but when we dig deeper,at a more operational and tactical level, the reality doesn’t
seem to stack up.

insights. The CMOs’ view from the top 63% of CMOs
say they make decisions based on data, but more thanhalf of those also said they lack data-driven insights todrive marketing strategy — and 49% lack data-driven
recommendations to improve marketing performance.
Again, there seems to be a great deal of optimism when it
comes to higher-level questions, but when we dig deeper,at a more operational and tactical level, the reality doesn’t
seem to stack up.

63%

Of CMOs say they make decisions based on data. 
But 49% say they lack data-driven recommendations
to improve marketing performance.

My biggest pain point is the lack of tools we are given.
Data Analyst, USA, Specialist, Technology

State of Play 2022: Data Capabilities & Aspirations

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02
Marketing Analytics
State of Play 2022

Current Data
Capabilities
State of Play 2022: Data Capabilities & Aspirations

10

Overview

The majority of marketers and analysts are still
scrambling to gain a single view over all theirmarketing data.
With 58% still building routine marketing reports on spreadsheets. Marketing teams
understand that personalized content and predictive analytics will play a key role inbuilding out a competitive advantage, but they don’t have the foundations to sustain thiskind of tech yet. Until they face up to this, a proactive marketing strategy is off the table.

State of Play 2022: Data Capabilities & Aspirations

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Marketing reports are still built on spreadsheets.
through must be called into question. If data is beingtransferred from Facebook and Linkedin to Excel and theninto PowerPoint, this creates more cracks for human error
to seep in.

Shockingly, 58% of marketers and analysts say routine
marketing reports are still built on spreadsheets. In
part one of this research, our challenges and priorities
report found that manual data wrangling is still a major
stumbling block for marketing teams, and currently poses
the most significant challenge. Marketers and analysts
are still spending hours a week wrestling to get the samedatasets in one place when this time could be muchbetter spent getting value out of that data.

Currently, 58% of respondents build reports manually on
spreadsheets, and 65% manually transpose reports into
PowerPoint or Google Slides. If marketing teams can
automate these processes, they can save time by having
an automated dashboard ready to present at a moment’s
notice, while also avoiding the human error that comeswith manual data wrangling.

With 41% of analysts struggling to trust their marketing
data, the number of manual processes the dataset goes

The biggest external factor impacting marketing today is...

Presentations are developed inPowerPoint /Google Slides

65%

Our marketing team has self-serveaccess toreal-time reporting

58%

Marketing reports are typically built on spreadsheets58%

We combine our marketing data with otherdepartmentaldata to make company-wide decisions57%

We use a Business Intelligence tool to visualizeourmarketing data (i.e. Tableau, Qlik, Power BI, etc.)55%

Our reports show end-to-endperformanceof marketing campaigns

54%

The majority of our marketing reporting is provided
through a dedicated analytics / BI team53%

Our marketing data is accessible froma centralized
data warehouse / lake51%

We leverage predictive modeling in our analytics

50%
0

10

20

30

40

50

60

70

80

Marketing teams are scrambling for a single source of truth
Only 51% of marketers and analysts say their marketing
data is accessible from a centralized data lake. Thatmeans nearly half of marketing teams are still scrambling
to create a full picture of their marketing performancewith data from disparate sources.
And while more than half of respondents say that they
have self-serve access to real-time reporting, 47% of
these respondents also say manual data integration isa significant challenge. While the real-time data might
exist, if it requires extensive manual work to make it
usable, then it can’t be translated to real-time decisions.
Marketing teams are frustratingly close to having the data
to drive effective decisions, but dependency on manual
integration of these disparate data sources continues tohold them back.

State of Play 2022: Data Capabilities & Aspirations

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Teams using predictive modeling have stronger strategic
capabilities
Half of marketers and analysts say they are currently
using predictive modeling in their analytics — andthese respondents tend to have much stronger strategic
capabilities bolstering their marketing strategy.

Marketing leaders understand the necessity of a proactive
marketing strategy rather than a reactive strategy,
but sustainable predictive modeling relies on a solid
data infrastructure. Having all your data in one place
is a prerequisite for predictive analytics. While it’s not
impossible to do this manually, the amount of time andenergy it takes to run just one of these models without
automated data integration makes it unsustainable.
Subsequently, marketers and analysts who have a higher
adoption of more basic analytics tech are much more
likely to be running predictive models.

For example, marketing teams with strong campaign
reporting capabilities are two times more likely to beusing predictive analytics than those whose campaign
reporting needs improvement. Likewise, those with strong
campaign optimization are more than twice as likely to beusing analytics.
On average, marketing teams who have strong strategic
capabilities in a given area are 31% more likely to beusing predictive analytics.

Of those who have a central data lake 69% use predictive
analytics — for those who don’t this falls to 27%. Similarly,of the respondents who use a BI tool, 67% use predictive
analytics, for those who don’t this falls to 22%.

How many sources of data does your marketing team use?
80
70

66%

65%

62%

63%

61%

60
50
40
30

31%

30%

Campaign
reporting andmeasurement

Campaign
optimization

36%

32%

35%

20
10
0

Predictive analytics users who are strong
in this area

Precision
targeting(e.g. CDP)

Audiencebuilding andtargeting(e.g. DMP)

Personalized
content delivery/
customerexperience

Predictive analytics users who say thisarea needs improvement

My biggest pain point is that our platforms do not speak toeach other.
Data Analyst, USA, Specialist, Technology

State of Play 2022: Data Capabilities & Aspirations

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03
Marketing Analytics
State of Play 2022

Data
Aspirationsfor 2022
State of Play 2022: Data Capabilities & Aspirations

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Overview

The majority of respondents say they will achieve MMM andpredictive modeling in 2022.
While it’s promising to see the marketing industry understands the value of such technologies, we can’t ignore thegroundwork that needs to be done.
Manually inputting data into spreadsheets won’t cut it for predictive analytics, it takes too long to prepare, and causes
too many errors. Marketing teams need a single view of marketing data which is automatically integrated.

Laying the foundations for predictive analytics.
61% say they plan to achieve more predictive modeling in
2022. While it’s promising to see that so many marketers
and analysts understand the value of predictive analytics,
there are still some major stumbling blocks to address
before marketing teams can get value out of predictive
analytics.
Predictive analytics is incredibly time intensive for those
who still depend on manual data wrangling. However,
38% of respondents who plan to use predictive analytics
say they still struggle with manual data wrangling, and
67% still use spreadsheets to build marketing reports.

What’s even more concerning is that 48% of analysts whoplan to implement predictive analytics in the coming year
say they struggle to trust their marketing data. This issue
absolutely must be addressed before marketing teams
sink time and money into predictive analytics — as theold adage goes, garbage in, garbage out. If your data
isn’t accurate, the insights you get from it could end up
doing more harm than good. However, marketers andanalysts don’t appear to understand what groundwork
must be done before predictive analytics can be seriously
considered.

State of Play 2022: Data Capabilities & Aspirations

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61%

Of respondents say they plan to achieve
more predictive modeling in 2022

48%

38%

Of analysts who plan to implement predictive
analytics say they struggle to trust theirmarketing data

0f respondents who plan to use
predictive analytics say they
still struggle with manual data
wrangling

Creating a unified view
challenge, this jumps to 63% who struggle with data trust.
In other words, analysts who struggle with manual data
integration are nearly four times as likely to struggle with
low trust in data accuracy.

Data accuracy is often undermined by manual integrationand the human errors that come with it. We can see aclear correlation here where respondents who have lesstrouble due to manual data integration also have higher
trust in their data accuracy.

Before AI or predictive analytics can be sustainably
implemented, marketing teams need a single unified
view of their marketing data. 62% of respondents plan to

For analysts who don’t struggle with manual integration,
only 15% say trust in data accuracy is a significant
challenge, but for those who say manual integration is aachieve a single unified view of marketing data in 2022.

Analysts who struggle with manual integration Vs. those who struggle
with data trust

Manual data integration is a significant challenge

63%

Manual data integration is not a challenge

16%

0

10

20

30

40

State of Play 2022: Data Capabilities & Aspirations

50

60

70

80

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Mix modeling is edging out multi-touch
Similarly to predictive analytics, marketing mix
modeling algorithms can technically be done manually,
but the amount of integration and manual wrangling
this involves makes it unsustainable for those without
automation.

P&G, AT&T, Kraft, Coca-Cola, and Pepsi lead the way —but with cookie deprecation jeopardizing the multi-touch
attribution model, marketing mix modeling (MMM) isn’t
just for fortune 500 anymore. The majority of respondents
say they intend to incorporate MMM into their marketingstrategy in 2022.

Which of the following do you plan to achieve in the next 12 months?
Developing a single, unified view ofmarketing performance

62%

Predictive analytics to develop
forward-looking optimization

61%

Marketing mix modeling

56%

Incorporating Artificial Intelligence and/or
Machine Learning into our analytics

54%

Multi-touch attribution modeling

51%
0

10

20

30

40

50

60

70

“My biggest pain point is that marketing data is spread
across too many different siloed locations and we don’t
have a single source of truth to aggregate it.”
Data Analyst, USA, Director, Media and EntertainmentState of Play 2022: Data Capabilities & Aspirations

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04
Marketing Analytics
State of Play 2022

Marketers Vs.
Analysts
View our full deep-dive Marketers Vs. Analysts report
Download reportState of Play 2022: Data Capabilities & Aspirations

18

Overview

Marketers and analysts naturally have different priorities
But our data shows that this rift goes beyond just disagreeing on what marketing tech
they want. Concerningly, marketers and analysts can’t even agree on what tech is alreadyavailable to them.
If marketers aren’t aware of the advanced tech in the analyst’s arsenal, then something’s gone
seriously wrong. Whether it’s a problem with adoption, a miscommunication, or a lack of tools
and time to get accurate data, all of these issues will continue to crop up and cause bigger
problems as you add in more tech.

State of Play 2022: Data Capabilities & Aspirations

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Analysts report more data capabilities than marketers
Only 3 in 5 analysts have access to a centralized data
warehouse. This might explain why so much time is spent
wrangling data — 41% of analysts still haven’t centralized
their data. For marketers, the number jumps to 57% who
don’t have a centralized view of their marketing data,
and the fact that this number is so much higher may be
symptomatic of the rift between analysts and marketers.
Marketers and analysts both most commonly state that
presentations are developed in PowerPoint or Google
Slides. However, when it comes to marketing reports,
marketers say they build them in spreadsheets (56%),

while analysts’ second most selected capability is a BI
tool to visualize their marketing data (64%).
Again, this is a worrying disconnect. BI tools anddata dashboards offer a far more efficient, effective,
and accurate method for marketing reporting thanspreadsheets and PowerPoint. However, often times
marketers treat analytics as a black box — data goes inand insights come out. This means they might not be asaware of what tools are available to turn data into insights,
or of how much work goes on behind the scenes on thepart of the analyst.

Centralized data warehouse

59%

43%

access to a centralized

access to a centralized

data warehouse

data warehouse

Of analysts state have

Of marketers state have

Use of a BI tool

64%

47%

BI toola BI tool

Of analysts use aState of Play 2022: Data Capabilities & Aspirations

Of marketers use

20

Disagreement over use of predictive analytics
The gap between marketers’ and analysts’ reported capabilities is most prevalent for predictive analytics. While 60%of analysts say their organization has the capacity to run predictive models, only 42% of marketers say the same. While
analysts might be trained and capable of running predictive models, it seems that analysts and marketers haven’t beenable to agree on how predictive analytics can fit into their data strategy.

Use of predictive analytics

60%

42%

predictive analytics

predictive analytics

Of analysts use

Of marketers use

Analysts are more confident
in data maturity
Both marketers (60%) and analysts (72%) clearly say that
their departments are analytically mature and constantly
looking for ways to become more advanced with their useof data. And, overall, analysts are more confident in theiranalytical capabilities, reflecting how close they are to theanalytics process compared with marketers.

Both analysts (72%) and marketers (60%) clearly
say that their departments are analytically mature

Driving decisions with data
Both marketers and analysts are confident in their organizations’ analytical maturity, and say that departments are datadriven and use data to inform strategic marketing decisions. 58% of marketers and 69% of analysts agree with this.
However, at the same time, 41% of analysts don’t trust their data.

69%

Of analysts say they are data-driven

41%

Of analysts say trust in data is a significant challengeState of Play 2022: Data Capabilities & Aspirations

21

A unified view Vs. Predictive analytics
While 69% of analysts see predictive analytics as the
top focus in 2022, marketers are most keen to achieve asingle unified view (58%). Again, this reflects a focus fromanalysts on prioritizing capability while marketers show aclear preference for usability.

Analysts and marketers both agree that having a unified
view of marketing performance and developing theirpredictive analytics are the priorities for the next 12months, however, they disagree on the order.

Which of the following do you plan to achieve in the next 12 months? —Marketers Vs. Analysts
69%

Predictive analytics to develop forwardlooking optimization

53%
66%

Developing a single, unified view ofmarketing performance

58%
64%

Incorporating Artificial Intelligence and/or
Machine Learning into our analytics

44%
61%

Marketing mix modeling

51%
58%

Multi-touch attribution modeling45%
0Data / BI Analyst

10

20

30

40

50

60

70

80

Marketer

Multi-touch attribution is not a priority
For both marketers and analysts, multi-touch attribution is the lowest priority in 2022. This reflects how cookie-deprecationand tightening data privacy rules will have an impact on the effectiveness of attribution modeling. Marketers are moredecisive than analysts with more than half stating that multi-touch attribution is not on the roadmap for 2022.

Analysts plan to implement AI
64% of analysts have plans to incorporate AI into their analytics, ranking this much more highly than marketers. In fact,
analysts are 20% more likely to see AI and machine learning on their 2022 roadmap than marketers, making this thebiggest discrepancy. Again, this highlights a disconnect between the two roles with analysts firmly focused on improving
the capability of their analytics.

Freeing the analyst
While predictive analytics and AI are high on the list of priorities for analysts in 2022, their biggest challenge remains
the time and effort for manual data wrangling. This highlights a disparity between a desire among analysts to improvetheir analytics with more sophisticated capability on the one hand, and the reality of the day-to-day challenges they faceon the other. However, business leaders can support analysts by freeing them from the manual data integrations thatmonopolize their time and may be preventing them from delivering more advanced analytical insights.

State of Play 2022: Data Capabilities & Aspirations

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05
Marketing Analytics
State of Play 2022

Regional
Analysis

View our full deep-dive regional report
Download reportState of Play 2022: Data Capabilities & Aspirations

23

Overview

If your organization has marketing teams dotted around the world,
it’s likely these teams won’t have the same strengths, priorities,
or challenges.
Strategies are going to differ from one area to the next, and a big reason for this is variation in data privacy laws.
Respondents from Germany and the UK who must account for GDPR are much more likely to champion a strategy
that doesn’t depend on cookies.

Germany is less analytically advanced
Overall, Germany lags behind the USA and UK in termsof current analytical capability, with respondents 10-15%
less likely to currently have advanced capabilities. Thatsaid, Germany and the USA are the least likely to be using
predictive analytics, while Brits are the least likely to havea centralized data warehouse.

Despite confidence around current analytics capabilities,
the majority of marketers and analysts still use spreadsheets
for building market reports. However, this is lesspronounced in Germany, where less than half of marketers
admit to building marketing reports in spreadsheets. This
number rises to 3 out of 5 in the UK and US.

German analysts and marketers closer in opinions
In all three countries, there are significant differences
between the relative certainty of analysts and marketers;
however, this is much more pronounced in the US, withGerman respondents the least likely to disagree.

On average, German marketers are twice as likely
to agree with their data analysts about their current
capabilities than US marketers.

State of Play 2022: Data Capabilities & Aspirations

24

In the US

65% of analysts say they use predictive analytics compared to only 43% of marketers.

In the UK
65% of analysts say they use predictive analytics compared to only 43% of marketers.

In Germany
48% of analysts say they use predictive analytics compared with 37% of marketers.

Top 5 current analytical capabilities ranked by region

1

Presentations are developedin PowerPoint / Google Slides

Presentations are developedin PowerPoint / Google

Presentations are developedin PowerPoint / Google

2

Marketing reports are typically built
on spreadsheets

Our marketing team has self-serve
access to real-time reporting

We use a Business Intelligence tool
to visualize our marketing data (i.e.
Tableau, Qlik, Power BI, etc.)

3

We combine our marketing data withother departmental data to makecompany-wide decisions

Our reports show end-to-end
performance of marketing campaigns

The majority of our marketing reportingis provided through a dedicatedanalytics / BI team4

Our marketing team has self-serve
access to real-time reporting

Marketing reports are typically built on
spreadsheets

Our marketing team has self-serve
access to real-time reporting5

Our reports show end-to-end
performance of marketing campaigns

We combine our marketing data withother departmental data to makecompany-wide decisions

Marketing reports are typically built on
spreadsheets

State of Play 2022: Data Capabilities & Aspirations

25

Germany is less positive about data culture
US and UK marketers and analysts are highly positive
about the data culture in their organization with 70% of
American and 67% of British respondents believing theircompany is analytically mature, and constantly looking forways to become more advanced with their use of data.
By comparison, German respondents are much lessconfident in their data culture, and are 15-20% less likely
to agree that their company meets any of the options.

In particular, only 52% of marketers in Germany believe
their organization is data-driven compared to 68% of
those in the US. While to some extent this is reflective of
the overall cultural differences between the three nations,
it also goes hand in hand with German businesses’ toppriorities around getting value out of their data. That said,
while German respondents ranked the ability to optimize
campaigns on the fly and adjust in real-time, for the US
and UK this was ranked the lowest capability.

The % of marketers and analysts that agree orstrongly agree
Data-Driven: we make strategic marketing decisions basedon objective data

68%

66%

52%

Test and Learn: we regularly test hypotheses and let theresults guide our marketing strategy

67%

60%

54%

Optimize on the Fly: we closely monitor the performanceof marketing campaigns and adjust in real-time

61%

63%

58%

Analytically Mature: we are constantly looking for ways to
become more advanced with our use of data

70%

67%

59%

Top analytics priorities: Creating a single view of data, andpredictive analytics
In all three countries, the top two analytics priorities in
the next 12 months are developing a single, unified viewof marketing performance and leveraging predictive
analytics. In this category, the responses from Germany
are on a very similar level to the USA and UK, suggestinga certain amount of optimism from German marketers andanalysts that they can close the gap in terms of analyticalcapabilities within the next 12 months.

While in Germany, analysts and marketers agree thatcreating a single, unified view of performance is thenumber one priority in 2022, in the USA and UK, data
analysts disagree. For British and American analysts,
predictive analytics is the main focus, with some 73%
of US and 70% of UK analysts seeing forward-looking
optimization as a key priority in the next 12 months,
compared to just 55% and 56% of marketers respectively.

State of Play 2022: Data Capabilities & Aspirations

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Top 5 analytics priorities in 20221

Predictive analytics to develop forwardlooking optimization

Developing a single, unified view ofmarketing performance2

Developing a single, unified view ofmarketing performance

Predictive analytics to develop forwardlooking optimization

3

Multi-touch attribution modelingMarketing Mix Modeling4Marketing Mix Modeling

Incorporating Artificial Intelligence
and/or Machine Learning into ouranalytics

Incorporating Artificial Intelligence
and/or Machine Learning into ouranalytics

5

Incorporating Artificial Intelligence
and/or Machine Learning into ouranalytics

Multi-touch attribution modelingMulti-touch attribution modeling

Developing a single, unified view ofmarketing performance

Predictive analytics to develop forwardlooking optimization / Marketing Mix
Modeling

US counts on cookies while UK and Germany prefer market mix
modeling
In both the UK and Germany, multi-touch attribution is the lowest priority whereas in the USA this remains a relatively
key strategy for 2022. This may reflect the relative strength of GDPR regulations compared to the varying legislation
regulating data privacy in the USA. Consequently, both the UK and Germany rank market mix modeling, a cookie-lessmethod of performance tracking, much higher than US marketers and data analysts.

State of Play 2022: Data Capabilities & Aspirations

27

06
Marketing Analytics
State of Play 2022

Capabilities
and Aspirations
by Industry
State of Play 2022: Data Capabilities & Aspirations

28

Overview

Different industries will be focusing on different
strategies for 2022.
Continuously, we see that tech and eCommerce respondents are further along when it comesto advanced analytics, while telecoms and media companies are lagging behind.

State of Play 2022: Data Capabilities & Aspirations

29

Data capabilities vary according to industry
On average, Tech and eCom have the most datacapabilities. While tech organizations have a well-rounded
suite of data capabilities, eCom tends to be more focusedon the use of a BI tool, combining marketing data withother departmental data, and self-serve real-time accessto marketing data.
Finance and marketing agencies are in the mid-tier ofdata capabilities. Both say they combine data acrossdepartments to make decisions. Finance organizations

are more likely to use a BI tool, and centralized data.
Marketing agencies more commonly have self-serve
reporting and end-to-end marketing.
Telecom and media have the fewest capabilities on
average. Media tend to have more capabilities aroundreal-time, centralized data and end-to-end reporting,while telecom is much more likely to have a BI team todeliver marketing reporting.

37%
43%

47%
43%

63%

63%

Agency

33%

58%
59%
54%
55%
52%
47%
53%

Finance

40

54%
46%
43%
53%
43%
53%
39%

53%
58%
57%
57%
53%
57%
50%

61%
52%
52%

50

53%

60

64%

70

65%
61%
59%
61%
63%
59%
60%

80

72%

Current data capabilities split by industry

30
20
10
0

Tech

eCommerceMedia

Telecom

Our marketing team has self-serve access toreal-time reporting

Our reports show end-to-end performanceof marketing campaigns

We combine our marketing data with otherdepartmental data to make company-wide decisions

The majority of our marketing reporting isprovided through a dedicated analytics / BI tool

We use a Business Intelligence tool to visualize ourmarketing data (i.e. Tableau, Qlik, Power BI, etc.)

Our marketing data is accessible froma centralized data warehouse / lake

We leverage predictive modeling in our analytics

State of Play 2022: Data Capabilities & Aspirations

30

Data strategies for 2022
The cross-industry average tells us that creating a single unified view of marketing performance, and predictive analytics
are the most common plans for 2022. Tech, eCommerce, finance, and marketing agencies all conform to this. However,media and telecom organizations have a different game plan.
After developing a single view, media companies’ next most common plan for 2022 is to implement marketing mix
modeling. Telecom companies are more likely to work on their multi-touch attribution capabilities in 2022.

Data aspirations for 2022 by industry

57%
47%

43%

43%

43%

41%

40

49%

57%

62%
54%

56%

66%

61%

56%

56%

46%

50

54%

58%
50%

57%

62%

59%

69%
59%

65%

67%

61%

56%

60

63%

70

67%

80

30
20
10
0

Tech

eCommerce

Finance

AgencyMedia

Telecom

Developing a single, unified view of marketing performance

Incorporating Artificial Intelligence and/or Machine Learning
into our analytics

Predictive analytics to develop forward-looking optimization

Multi-touch attribution modelingMarket Mix Modeling

My biggest pain point is that different data sources andmodels make it difficult to bring marketing data together
for analysis.
Data Analyst, Germany, Director, Automotive

State of Play 2022: Data Capabilities & Aspirations

31

About the research
In August 2021, Sirkin Research, commissioned by Adverity, surveyed 964 Marketers and Data / Business Intelligence Analysts
across the United States, United Kingdom, and Germany about Marketing Analytics. The survey covered topics ranging fromcurrent capabilities, key challenges, and strategic priorities of organizations’ use of marketing data and analytical maturity.
Respondents represented a large range of industries, including Technology, Marketing Agencies, and eCommerce.

Demographics
7%
27%

3%
Telecom

8%

37%

35%

Country
breakdown

Germany

9%

UK
USA

Industrybreakdown

Financial Services
Media /
Entertainment
eCommerce
Other

13%

Agency36%

Technology

25%

15%
C-Level / Vice
President
16%

Job levels

50%

Independent
Contributor

48%

Director

9%

7.3%

22%

16%

52%

Marketer
Data Analyst

Manager /Supervisor

19%

16%

Role
breakdownSize ofmarketingdepartment

101 to 150
Less than 10
10 to 25
More than 150

21%

16%

5.4%

42.2%

12.3%

55+

Age group

Under 25
45 - 54
35 - 44

51 to 100

25 - 34

26 to 50
32.8%

About Sirkin Research
Sirkin Research is the leading custom research service for B2B marketers. They have spent the last 15 years working withsome of the fastest-growing marketing, technology and financial brands in the world, from Copenhagen to London to New
York City, helping them understand and generate demand from their audience, based on hyper-relevant, data-driven insight.

State of Play 2022: Data Capabilities & Aspirations

Marketing Analytics
State of Play 2022

Data Capabilities& Aspirations

info@adverity.com
www.adverity.com