Attribution Case Study - Ad-Tech Presentation

Post on 17-Oct-2014

2.050 views 2 download

description

This Attribution Case Study was presented at Ad-Tech SF in April 2012 by Steve Latham, ceo of Encore Media Metrics. Special thanks for Lipman Advertising for participating in this case study. Feel free to download and use as you wish. Just remember to "Attribute" credit where it's due :-)

Transcript of Attribution Case Study - Ad-Tech Presentation

Attribution Case Study: Insights You Can Use April 2012

Steve Latham CEO Encore Media Metrics @stevelatham

Background •  Agency: Lipman Advertising NYC •  Client: Hotel and Resort Operator •  Campaign objectives:

– Create awareness and consideration in a way that is measureable and insightful

– Primary goals: hotel and lodging reservations. •  Channels

– Display (150 million impressions) – Paid search – 3rd party email

Assignment •  Produce insights that matter

–  Useful –  Actionable

•  Measure and Interpret KPIs –  Conversion paths –  Engagement cycles –  Impressions required to influence a conversion –  True performance of vendors, placements and

keywords (beyond last click)

Key Takeaways •  Display was more impact than previously thought

–  Accounted for 26% of attributed conversions –  Exceeded paid search (26%) and natural search (15%) –  Influenced 30% of conversions via natural search,

referring and direct navigation •  Performance by media vendor and placement

varied significantly… –  Attributed CPAs ranging from $32 to $919 –  Mean was $107 with standard deviation of $67).

Path%Analysis IMPs Visits Display%Clicks Direct%Nav Natural%

SearchPaid%

Search Referring Display% Visits%

All Visitors 5.2 4.2 1.1 0.4 0.8 0.5 1.4 55.2% 44.8%Cluster 4 (45%) 1.5 2.8 0.8 0.0 0.1 0.0 1.8 35.2% 64.8%Cluster 6 (21%) 4.7 3.8 0.2 0.6 0.8 1.5 0.6 55.2% 44.8%Cluster 3 (15%) 6.1 4.0 1.5 0.2 1.8 0.3 0.2 60.3% 39.7%Cluster 8 (13%) 3.9 4.8 0.0 1.2 2.0 0.1 1.3 45.1% 54.9%Relative Contribution (all) 54.2% 45.8% 9.1% 6.1% 9.5% 7.6% 13.3%Includes Converters who were exposed to ads, grouped in natural clusters via machine-learning algorithm.

InterpretationThere is a broad distribution of conversion paths so we need to look beyond the averages. In aggregate, display ads accounted for 54% of interactions (range 35-60%) that led to conversions. Natural and paid search combined for 17.1% of of Interactions that influenced conversions.The "Average" Converter saw 5.2 display ads and visited 4.2 times. Most common sources: 1.1 Display, 0.8 Natural Search, 0.5 Paid search, 1.4 referring.

Key Insight #1 •  Conversion path analysis showed:

–  Converters were engaged via numerous channels –  Among Converters who were exposed to ads:

•  Average Converter saw 5.2 ads and visited 4.2 times •  1/3 visited through paid or natural search

Key Insight #2 •  Optimal frequency was 5.7 impressions overall

–  Ranged from 1.8 to 9.6 among vendors on the plan.

1.7$

6.2$

2.4$

5.4$

1.1$

3.0$

7.0$

1.3$

3.2$

6.6$

1.3$

4.7$

7.8$

1.8$

4.4$

1.8$

9.0$

2.4$

3.5$

7.0$

9.6$

1.6$

0

1

2

3

4

5

6

7

8

9

10

Publisher

8

Ad Net

1

Publisher

9

Publisher

5

Publisher

7

Publisher

2

Publisher

1

Publisher

3

Publisher

6

Ad Net

2

Publisher

4

Impressions*Required*by*Vendor*

Visit$ Conversion$

Key Insight #3 •  After attributing credit for assist impressions and

clicks… –  CPA for Display Ads fell by 60% overall

•  Range: 20% to 85% among placements

–  CPA for Paid Search fell by 15%

609$

1,026$

1,520$

1,013$

499$435$

733$

1,086$1,201$ 1,210$

0

200

400

600

800

1,000

1,200

1,400

1,600

Direct Nav Org Search Referrals Paid Search Display

Ac#ons'By'Channel'

Lst Click

Attributable

$22.38$

$319.96$

$18.89$

$131.98$

$0

$50

$100

$150

$200

$250

$300

$350

Paid Search Display

Cost'Per'Ac#on'By'Channel'

Last Click Attributable

Key Insight #4 •  Engagement cycles validate the need for a

sustainable, visible presence –  48% converted >30 days after seeing the first ad –  49% converted within 1 day of seeing the last ad. –  Average person visited 4.2 times before converting

Key Insight #5 •  Performance of media vendors varied

considerably (based on Attributed CPA). –  Four clear winners had an average CPA of $46 –  Four “on the bubble” with average CPA of $121 –  Three laggards with an average CPA of $521

Vendor Impressions Actions/(Last)

Click/Assists

Assist/Imps.

ICE/Ratio

ICE/Assists

Actions/(Attrib.) Spend CPA:/Last/

ClickCPA:/

Attributed Rating

Publisher/8 2,046,438 333 75 107 4.7 23 431 $13,971 $41.96 $32.43 WinnerAd/Net/1 3,427,418 63 45 1,672 7.8 214 322 $13,710 $217.61 $42.53 WinnerPublisher/9 1,227,090 8 5 610 1.8 339 352 $15,792 $1973.95 $44.88 WinnerPublisher/5 1,002,757 20 5 939 4.4 213 238 $15,368 $768.39 $64.46 WinnerPublisher/7 307,472 5 0 91 1.8 51 56 $5,863 $1172.56 $105.53 BubblePublisher/2 433,527 14 7 140 9.0 16 37 $3,978 $284.16 $108.83 BubblePublisher/1 1,735,227 11 1 143 2.4 60 72 $9,059 $823.58 $126.56 BubblePublisher/3 1,191,854 18 5 198 3.5 57 80 $11,329 $629.41 $142.38 BubblePublisher/6 238,828 17 6 0 7.0 0 23 $6,207 $365.12 $269.87 LaggardAd/Net/2 7,786,210 13 8 344 9.6 36 57 $21,306 $1638.95 $374.89 LaggardPublisher/4 227,348 2 0 11 1.6 7 9 $8,157 $4078.26 $919.04 LaggardTotals 19,624,169 504 157 4,255 4.2 1,014 1,675 $124,740 $247.50 $74.45

So…What’s The Point? By understanding…

–  Conversion Paths and Engagement Cycles –  Optimal Frequency –  Impact of Channel, Vendor and Keyword

…the Agency can optimize performance The economic opportunity is significant:

Group Spend % of Budget Revenue ROS Proforma

% BudgetProforma

ROS Proforma Revenue Impact

Winners $58,841 37% $1,343,423 $22.83 59% $22.83 $2,157,823 $814,401

Bubble $65,148 41% $267,262 $4.10 41% $4.51 $293,988 $26,726

Laggards $35,670 22% $88,708 $2.49 0% n/a $0 ($88,708)

Total $159,659 100% $1,699,393 $10.64 100% $15.36 $2,451,811 $752,418

Relative Improvement 44%Incremental Revenue $752,418

Takeaway: by moving budget from Laggards to Winners and improving performance of Bubbles by 10% is worth a 44% improvement in revenue

What’s Next •  More granular analysis

–  Format and creative •  Tracking offline converters

–  Via post-purchase site visits •  Excluding non-viewable impressions

–  Leveraging MediaMind visibility metrics •  Attribution for Brand Lift studies

–  Via partnership with Vizu

Criteria for Choosing a Vendor •  Consultative approach

–  Planning, implementation, production, analysis •  Transparent and programmatic approach

–  Known algorithms are preferred (vs. proprietary) •  Insightful, actionable and intuitive reports

–  Must be useful for media planners, analysts, clients •  Flexibility

–  Able to accommodate specific needs •  Level of effort to deploy and manage

–  The lower the better!

Questions?

Encore Media Metrics Steve Latham, CEO 646.919.1809 http://EncoreMetrics.com

Steve@EncoreMetrics.com

@SteveLatham @EncoreMetrics

http://Attribution101.com