digital identity: how marketing is failing at its top priority (customer recognition)

1 May 2023 Copyright © Econsultancy

Marketing is failing at its top priorityStudy findings and research-driven recommendations

In partnership

1 May 2023

Your presenters…

2

Stefan TornquistVP, ResearchEconsultancy@sktornquist

Ben Eason SVP, Client

DevelopmentConversant

Warren StoreySVP, Product

Marketing & InsightEpsilon

1 May 2023 3

About the study…

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prioritize providing an integrated experience across devices and media86%

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agree that their growth depends on communication with their customers and prospects as individuals75%

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believe their competitors are focused on this capability70%

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Our goal is recognition

7

0%

20%

40%

60%

80%

100%

74% 75% 76%84%

“Very important to growth”

Matching customers across multiple devices

Understanding customer behavior

over time

Tailoring message by

channel

Associating conversion events

with marketing

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We’re failing

8

0%

20%

40%

60%

80%

100%

74% 75% 76%84%

14% 12% 13% 10%

Matching customers across multiple devices

Understanding customer behavior

over time

Tailoring message by

channel

Associating conversion events

with marketing

Very important to growth Strong Capability

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Issue #1…knowing what we don’t know

9

report that their organizations have a “single customer view”43%

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10

Actually have a “single customer view”12%

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11

34%

37%

35%

45%

27%

38%

52%

42%

56%

62%

71%

79%

77%

100%

100%

100%

100%

100%

= 12%

Personally identifiable CRM data such as address, name and phone

Digital marketing channel data such as site, social, search and email activity

External data appended to consumer profiles (such as demographics)

Historical Purchases

Non personally identifiable data such as device IDs, cookies and IP addresses

Offline marketing channel data such as catalog responses, store visits and loyalty

program activity

Tier 1 Tier 2 Tier 3

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Issue #2…knowing what the left brain is doing

12

9%

11%

32%

34%

14%

2%

0%

19%

51%

28%

0%

0%

14%

36%

46%

We can tie actual online and offline sales back to online marketing programs

We can tie actual online sales back to online marketing programs

We use models to associate results across channels with sales

We do not have mechanism for measuring marketing success

We look at the impact of channels independently, mainly based on click data

Tier 1 Tier 2 Tier 3

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Issue #3…truth and tools

13

The reality of our data management platform does not align with the promises we were sold

38% 52%

6%4%

Strongly agree Agree Disagree Strongly Disagree

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Issue #3…truth and tools

14

Vendors lack the ability to apply test and control measurement consistently across devices and channels

19% 52%

21%8%

Very significant Significant Neutral Somewhat insignificant

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Issue #4…clicks?!

15

Clicks are our primary source of information about all channels, not just search

28% 54%

10%8%

Strongly agree Agree Disagree Strongly Disagree

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Issue #4…clicks?!

16

Internal reluctance to moving away from using proxies such as clicks or predetermined percentages

40% 40%

8%

2%

10%

Very significant Significant Neutral Somewhat insignificant Totally insignificant

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Issue #5…trust

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Cookie deletion

Ad fraud

Ad blocking

Inability to unify cookies, device ids and IP addresses for a single individual

Limited resources to produce a high volume of personalized creative ads

Limited mobile-user data

Rising privacy concerns

10%

10%

12%

13%

14%

14%

26%

27%

31%

32%

39%

36%

33%

40%

Very significant Somewhat significant

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WHERE DO YOU FALL?CAN YOUR DIGITAL SOLUTION

Recognize consumers across devices, even before they log in?

Match offline transactions to online marketing?

Build and maintain one view of each consumer—including purchases (on & offline) and cross-screen engagement?

Ensure consumer privacy without compromising meaningful experience?

Measure digital marketing’s impact on online & offline?

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CONSEQUENCES OF DISJOINTED CONSUMER RELATIONSHIPS

Media inefficiency and wasted spend on broken connections

Limited understanding of the consumer

Poor consumer experience

Incomplete and inaccurate measurement

2020

Speak to people as individuals, instead of devices, cookies or segments.

Have proactive, ongoing conversations, instead of just reacting to a single action they take.

Measure every ad dollar spent, and see an incremental return on each one.

21

Case Study #1Cookies vs. Individuals

2222

Over a 90 day period

44M Cookies & Device Visit BrandCo.com

2323


12.7M Actual BrandCo Customers


2424




791M Total Associated Cookies & Devices

25




791M Total Associated Cookies & Devices

62 cookies & devices per person on average25

26

Case Study #2The Ongoing Handshake

27PID# 4567

PID# 1111 PID# 3333+

+

+

COOKIES VS. THE INDIVIDUAL

Recent browsingbrandco/categoryc.com

Recent browsingbrandco/categoryb.com

Recent browsingbrandco/categorya.com

27

28PID# 4567

PID# 4567 PID# 4567

+


28

Recent browsingbrandco/categorya.com

brandco/categoryb.com

brandco/categoryc.com

+ +

29


• Multiple reintroductions to customer• Multiple offers targeting same unidentified customer29

• No “on/off” switch• Mismatched cadence

Current state:

3030

DEVICE IDENTIFICATION AT THE INDIVIDUAL LEVELONE CONVERSATION ACROSS DEVICES

+

PROFILE ID: 4567

Building consumer understanding and relevant conversations over time

3131

How you match matters

3232

PROBABILISTIC MATCH

Third-party standard household-level match

• Jim Pennell • Trish Pennell (wife)• Mark Pennell (son)• Susan Pennell (sister)

3 cookies avg. for each individual = 12 cookies now associated to Jim Pennell

3 cookies actually relate to Jim Pennell's browser

3333

TRANSACTION-BASED DETERMINISTIC MATCH

Conversant Customer Identification Rate = 92%

Matches Jim to 3 devices: desktop, tablet & mobile

5 unique ID’s associated to Jim across his various devices and browsers

34

MORE SERVICESLESS SCALE & PRECISION

DATAONBOARDER

DSPPROFILES

DMP PROFILES

INTEGRATED PROFILE

POOL

More: Accuracy, Scale, Persistence

& Enriched Profiles

VS

No control of the chain of custody.

FRAGMENTEDSOLUTION

COMMON PROFILE

POOL

35

MAINTAINING CUSTOMER RECOGNITIONINCREASES RETURN & EFFICIENCY

IDENTIFICATION12 Month Buyers 60% Matched = 19.8M

30% = 5.9M

60% = 3.5M

10% = 356K

REACHPast 90 Days

ACCURACYVerified Individual

PERSISTENCE365 Day Retention

70% Matched = 23.1M

40% = 9.2M

95% = 8.8M

76% = 6.7M

IntegratedSolution

FragmentedSolution

33M

18xAudience

36

Comprehensive view of online & offline outcomes

1

Continuous learning & ROAS optimization

3

Actionable insights reflect changing cross-device consumer actions

2

VERIFIED INDIVIDUALS

CONSUMER IMPACT MEASURING CAMPAIGN IMPACTON CONSUMERS, NOT DEVICES

36

FULL VISIBILITY INTO PERFORMANCE

3737

People-centric drives integrated relevant experience

Display

Mobile

Catalog

Search

SocialVideo

Retail

Site

38

THANK YOU

38