Adobe Summit - Advanced Advertising Analytics

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.© 2015 Adobe Systems Incorporated. All Rights Reserved. Adobe Confidential.

Advanced Advertising AnalyticsMarketing Insights through Adobe Analytics & Media Optimizer


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Dan CardamoneManager - Search

[email protected]

Chris HaleuaProduct Marketing Manager

[email protected]


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1 | Foster curiosity with people, process, & technology

2 | Break the habits of basic monitoring

3 | Balance the load between man & machine

4 | Mitigate the risk of advanced analytics

5 | Expand your perception of attribution & allocation

Summary


MyAnalyticsScore.com


myanalyticsscore.com

adobemarketingpro.com

adobemediaoptimizerpro.com

Surveys



Takeaways

8

PeopleAlign structure to break down silos

ProcessFoster curiosity &

reduce chores

TechBuild trust in single

source of truth


People

9

Advertising-analyst hybrids automate basic reporting to focus on advanced insights


Process

Targeting

Analysis

Testing

BiddingCoverage

Structure

Life

IDEAL COMMON

Meetings

Training

Email

Bugs

Planning

Calls


Technology

11

Media Optimizer

Conversion Metrics

Campaign Classifications

Engine Data

Adobe Analytics

Site Traffic Metrics


2 eVars

EFID = serialize clicks

SKWCID = unique ad/keyword combination

5 events

Impressions

Clicks

Cost

Position

Quality Score

Nuts and Bolts of the Integration


Raw Tracking Codes

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http://www.carnival.com/

?CID=Psearch_A_B_HONEY_1241236

&SE=Bing&KW=all_inclusive_honeymoon_cruise

&CM=General_Non_Brand Life_Style_Cruise

&AG=Honeymoon_Cruise

&_vsrefdom=nonbrand

&gclid=CICe6NDYusMCFYuafgodxC0AOw

&gclsrc=ds


SAINT Classifications

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SAINT Classifications

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1 | Foster curiosity with the right people, process, & technology






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What does basic really mean?


Getting Started


Volume vs. Efficiency


Pathing & Fallout Bottlenecks


Funnel Averages


FILTERS

Volume Leaders

Efficiency Threats

SORTS

ConversionSuccess

Non-Converting Spend

Conversions > 0

Conversions = 0Cost > 0

Revenue ROAS Pos.

Pos.CPCCost

Performance Segmentation

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FILTERS


FILTERS

Volume Leaders

Efficiency Threats

SORTS

Non-Converting Spend

Ignored Impressions

Conversions = 0Cost > 0

Cost = 0Impressions > 0

Pos.

Pos.

CPCCost

Impressions Quality Score


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FILTERS






You might know your total conversions

...but do you know the minority driving the majority?

You might know your efficiency threats...

...but do you know your deadends in the step before?

You might know your loss leaders...

...but do you know the segments & pivots that caused them?



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Advertising Insights


Day of Week

Spend Distributions at weekly spend of 17500

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

Flat 2500 2500 2500 2500 2500 2500 2500

Current 2500 2500 2500 2500 2500 2500 2500

Optimal 2564 2408 2564 2720 3032 2096 2252

Uplift from current to

optimal allocation+ 0.4%


Budget CapsRelevant portfolio settings

Spend Multiple: Predicted campaign spend variance allowed to give head room for cost

Multiple 1.5Status too low


Quality Score Counts

Quality Score Tiers

Keyword Count

Good 731

Average 1489

Poor 61

In the last 30 days, 32.0% of keywords had a Quality score in the 7 to 10 range

adobe_systems | ACRO : NA : GG : PURCH : UNITS | 2016-02-20 to 2016-03-20

Impression weighted Quality Scores rounded up to nearest integer


Portfolio Objective Weights

Sale Closed1

Lead Completed0.6

Lead Started0.4

Whitepaper Download0.2


Prediction Accuracy


Correlation between Predictors

Properties considered 25

Properties removed 21

No early signal 0

Do conversion data 11

Redundant data 10

Low correlation 0

Included in final model 4


amosummit.gamification.ws


Audit Summary

2 of 30number of days with atleast one bid change

6.8%impressions forfeited due to

inadequate campaign budgets

2%of bids were changed in

increments of 5%

65%of all keywords havethe same Five bids

99%of all adgroups have the same

mobile bid adjustment

35%of total investment is

flowing through mobile


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How does advanced really differ from basic?


Averages LIE!


PIVOTS


Cart vs Partner

47


Cart vs Partner

48

Adobe revenue driven by Adobe

Adobe revenue driven by Other


49


Portfolio

Time Product

Pivots


PREDICTIVE


52


Anomaly deep-dive in Analytics Workspace

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unusually high revenue for the contributing products as a whole

Customer A

Customer B

Customer C

Customer D

Customer E

Customer F


AnomalyCustome

rProduct

Predictive


Customer Segments to RLSA

55


Visitors of Page

Advanced Definition

Alignedtargeting &

analysis

RLSA


SEGMENTS


Solving for the (not provided) conundrum

58


Solving for the (not provided) conundrum

59


Entry Page Site Section % New

Segments


Customer loyalty by Marketing Channel

61


Using visit numbers to create new/returning visit %

new visits segment

return visits segment

new visits % metric

return visits % metric


Using visit numbers to create new/returning visit % (cont.)

63


Loyalty Channel % Return

Loyalty


OFFLINE


Engagement Metrics


Call Tracking in AMO

67


Call Tracking in Analytics

68

page views = calls

create a segment based on those page views

and then a calculated metric that counts those page views

then bring more dimensions in through an eVar


Page Views = Calls

Segment = Page Views

Dimension = Caller ID

Call Tracking


Customer Attributes in the People Core Service

Solutions

Core services

Places

PlatformPeople

AssetsMobile

Activation

Data science

Data Content

MediaOptimizer

Social

AudienceManager

Target PrimetimeExperience

Manager

Campaign

Analytics


Customer Attributes

Age & Gender Job Function PropensityMember Level Proximity

Adobe Marketing Cloud:People Core Service

Customer records

ID aliases

User login

Marketing Cloud Visitor ID Service

Customer ID = A383278

Customer ID = A383278

Age=30Gender=FemaleMembership=Gold


Customer Attributes

VALIDATE schema and subscribe to 3 attributes in Analytics2UPLOAD area of the Marketing Cloud1


Customer Attributes

CREATE custom reports, segments, and metrics3 ANALYZE behavioral patterns and share segments4


Similarities Applies forward & back

Differences Attached to the visitor

Entire life of the cookie

uniques

Available to all solutions

Are These Classifications?


Export from CRM

Upload to People

Core Service

Segment byAttributes

Customer Attributes


ALLOCATION


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What do these pictures have in common?

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Comparisons of Different Models

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Model Pros Cons

Participation Fair to all Doesn t distinguish touch roles

First Focuses on triggers Overvalues awareness

Last Focuses on closure Overvalues low funnel & brand

Linear Fair to all Doesn t distinguish values

SPC / U Shaped Weights both ends Requires expertise and can run into user bias

Adjacency / Decaying Weights the latest Less specific in how values are assigned

Latency Weights for recency Time may not be a factor based on business

Algorithmic Statistics eliminate bias No control over assignment of values


Reporting Flexibility

80


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Going Beyond Attribution with Adobe Analytics

AttributionRules, Fractional,

Marginal, Algorithmic

AnomaliesDetection & Contribution

CorrelationsCauses & Statistics

ClusteringSequential Segments & Propensity Scoring

AllocationBudget, Time, Focus

Mat

uri

ty L

eve

l


Prioritize perspectives

Double-check Deltas

Expand beyond

budgeting

Attribution


Key Takeaways

PeopleTrade easy for

important

Keep learning to become a hybrid

ProcessDrag & drop workspaces

Pivot advertising by analytics

TechMachines essential

for AI audits

Humans essential for exploration



4 minutes

Winner: $1000

3 Runners Up: $100

Passing Grade gets a

Adobe Summit Programmatic Quiz #AdobeAdGenius

Test your knowledge here


Q&A

87

Dan [email protected]

Chris [email protected]


Adobe Summit - Advanced Advertising Analytics

Data & Analytics