ClearSaleing Confidential . www. clear sale ing .com
OUR   DEFINITION ClearSaleing Confidential <ul><li>Clear’-Sale’ing (klir sāl ing) </li></ul><ul><li>1.  an advertising ana...
FORESTER RESEARCH  -  FEBRUARY 2009 ClearSaleing Confidential
THE LAST   CLICK FALLACY ClearSaleing Confidential
ClearSaleing Confidential ATTRIBUTION  MANAGEMENT HIERARCHY
<ul><li>Attribution Management </li></ul><ul><li>Engagement Mapping </li></ul><ul><li>Attribution Conversion </li></ul><ul...
PURCHASE  PATH™ ClearSaleing Confidential <ul><li>Multiple ad sources will often contribute to a single conversion </li></...
PURCHASE PATH™   DETAIL ClearSaleing Confidential In this example we drilled into the AdWords > AdWords path to see the sp...
INTRODUCERS ,  INFLUENCERS, AND CLOSERS ClearSaleing Confidential Ads are classified into 3 categories.  Introducers - the...
PURCHASE PATH™  ATTRIBUTION MODELS ClearSaleing Confidential Several methods for setting attribution management models are...
PURCHASE PATH™  TIMING ClearSaleing Confidential To further increase the accuracy of attribution, an advertiser is able to...
PURCHASE PATH™  EXCLUSIONS ClearSaleing Confidential Another method created to help with attribution is create a method fo...
ClearSaleing Confidential
<ul><li>There are simple prove am rule </li></ul>ClearSaleing Confidential
BRAND  KEYWORDS ClearSaleing Confidential
BRAND SEARCH  THE CLOSER ClearSaleing Confidential Step2 = Branded Term
BANNERS INTRODUCE …SEARCH CLOSES ClearSaleing Confidential 11 of 18 keyword queries following a display impression were br...
<ul><li>287,000 orders in 2008 </li></ul><ul><li>35% of all orders in a Purchase Path </li></ul><ul><li>100,450 orders in ...
Disclaimer <ul><li>Due to time constraints we will not be able to explain every aspect of the model nor will we be able to...
DR. PURUSH  PAPATLA   <ul><ul><ul><li>President and Founder; Vetra Analytics </li></ul></ul></ul><ul><ul><ul><ul><li>Staff...
<ul><li>Verticals Served </li></ul><ul><li>Financial services </li></ul><ul><li>Insurance </li></ul><ul><li>Travel </li></...
CONSUMER  DECISIONS
DECISION   INFLUENCER <ul><li>What we know </li></ul><ul><li>Our Communications </li></ul><ul><li>Paid Search </li></ul><u...
MODELING   CONSUMER DECISIONS <ul><li>Build a mathematical model to predict consumer decisions </li></ul><ul><ul><li>Using...
CONSUMER  DECISION MODEL Consumer’s Decision = f( Our Communications ,  Consumer Search ,   Competitor Communications, Oth...
MEASURING  THE EFFECTS OF KNOWN FACTORS We assume that each of the known  influencers   has an  influence potential
MATHEMATICAL  MODEL FOR CONSUMERS DECISION ClearSaleing Confidential <ul><li>* The  β ’s  are the attribution weights </li...
GETTING  THE ATTRIBUTIONS <ul><li>We calibrate the model on data from the ClearSaleing platform  </li></ul><ul><li>The dat...
GETTING  THE ATTRIBUTIONS <ul><li>Calibrate the model on the ClearSaleing data </li></ul><ul><ul><li>Find the values of  β...
MODELING   THE INFLUENCE POTENTIAL  Influence potential   of an influencer = f (# of exposures,    when each of the exposu...
EXAMPLE  WITH SIMULATED DATA Simulated data example
EXAMPLE   PATH DATA ClearSaleing Confidential
MEANING  OF CALIBRATION ClearSaleing Confidential
INFLUENCIAL POTENTIAL  (PAID SEARCH) ClearSaleing Confidential
Do models work?
EXAMPLE:  WORD OF MOUTH TRACKING MODEL
OTHER  INSIGHTS PATH DATA CAN PROVIDE <ul><li>Measures of the rate of decay of the influence of  </li></ul><ul><ul><li>Pai...
<ul><li>Does a consumer’s choice of an ad source influence his choice of whether or not to use another source? </li></ul><...
KEY  TAKEAWAYS  <ul><li>Get the data </li></ul><ul><ul><li>Purchase Paths™ </li></ul></ul><ul><ul><li>Time </li></ul></ul>...
BOTTOM  LINE <ul><li>We are barely scratching the surface of the potential of path data with the attribution models!!! </l...
CLEARSALEING   AND VETRA <ul><li>Today:  Our technology with Vetra’s team can build custom attribution models </li></ul><u...
 
ClearSaleing Confidential Become a fan:  ClearSaleing Read blog:  www . blog . ClearSaleing.com Follow the tweets:  ClearS...
ClearSaleing Confidential . www. clear sale ing .com
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Measuring The Immeasurable: How to Properly Measure Your Online Marketing Mix

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To view a video version of the webinar in its entirety, please visit: http://www.clearsaleing.com/V9webcastRegister.aspx.

The Webinar will present some of the challenges online marketers face in accurately valuing the team of online and offline ads that lead to a purchase. In order to realize the true promise of attribution management, you need to:

• Implement a technology that will allow you to properly capture, assemble and sequence the team of ads that lead to a conversion, and
• Be able to develop appropriate attribution methods to accurately allocate credit to the participating ads and sources.

Learn from ex-Google insider and co-founder of one of the leading advertising analytics companies, Adam Goldberg, along leading quantitative marketing expert, Dr. Purush Papalta, about how to track, assemble, sequence, and allocate conversion credit across your online marketing mix.

The webinar will examine several online marketing best practices and common online buying patterns as revealed through ClearSaleing’s advertising analytics technology, including:

• Frequent Purchase Paths scenarios
• Attributing Profit to each participating ad
• Why the “Last Click” Method Leads to Wrong Decisions
• Why Branded Terms Are Not as Valuable as Once Thought
• How to Go Beyond PPC and Evaluate Offline Marketing Efforts

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  • Measuring The Immeasurable: How to Properly Measure Your Online Marketing Mix

    1. 1. ClearSaleing Confidential . www. clear sale ing .com
    2. 2. OUR DEFINITION ClearSaleing Confidential <ul><li>Clear’-Sale’ing (klir sāl ing) </li></ul><ul><li>1. an advertising analytics company </li></ul><ul><li>2. the only effective way to manage an online advertising portfolio and increase profit (ROI) for online advertisers </li></ul><ul><li>v. 1. continually improving the ROI of online advertising campaigns </li></ul><ul><li>2. easily and transparently increasing sales and profits </li></ul>
    3. 3. FORESTER RESEARCH - FEBRUARY 2009 ClearSaleing Confidential
    4. 4. THE LAST CLICK FALLACY ClearSaleing Confidential
    5. 5. ClearSaleing Confidential ATTRIBUTION MANAGEMENT HIERARCHY
    6. 6. <ul><li>Attribution Management </li></ul><ul><li>Engagement Mapping </li></ul><ul><li>Attribution Conversion </li></ul><ul><li>Mixed Media Management </li></ul><ul><li>Marketing Mix Analysis </li></ul><ul><li>Multi-Campaign Attribution </li></ul>IT’S EVERYWHERE
    7. 7. PURCHASE PATH™ ClearSaleing Confidential <ul><li>Multiple ad sources will often contribute to a single conversion </li></ul><ul><li>This view displays the relationships between the ad sources that contribute to sales </li></ul><ul><li>You can then drill into any path by clicking on the (+) to the left of the path. This displays line item detail of the specific ads consumers clicked along the purchase path </li></ul>
    8. 8. PURCHASE PATH™ DETAIL ClearSaleing Confidential In this example we drilled into the AdWords > AdWords path to see the specific ads that were clicked on en route to purchase.
    9. 9. INTRODUCERS , INFLUENCERS, AND CLOSERS ClearSaleing Confidential Ads are classified into 3 categories. Introducers - the very first ad someone clicks or sees to find your site; Influencers- are ads that are clicked on after the Introducing ad but before the Closer; Closers- are ads that get clicked or seen at the very end of the Purchase Path™. This classification system makes it easy for an advertiser to measure an ads value even if it is not the last ad clicked or seen prior to purchase.
    10. 10. PURCHASE PATH™ ATTRIBUTION MODELS ClearSaleing Confidential Several methods for setting attribution management models are baked into the application. You can choose to attribute Profit and Revenue evenly across the team of ads that generated a conversion or you can customize the attribution model yourself.
    11. 11. PURCHASE PATH™ TIMING ClearSaleing Confidential To further increase the accuracy of attribution, an advertiser is able to choose the maximum number of ads they are willing to attribute credit to, the maximum days between ad clicks/impressions that are acceptable, and lastly the attribution time window which is the amount of time from first click/impression to purchase that is acceptable for an ad click/impression to occur within to get credit.
    12. 12. PURCHASE PATH™ EXCLUSIONS ClearSaleing Confidential Another method created to help with attribution is create a method for excluding certain types of ads from receiving credit even if they occur in a Purchase Path in the allowable window. For example, many of our clients exclude giving credit to branded ads that happen at the end of a path because those ads are used to navigate back to their site.
    13. 13. ClearSaleing Confidential
    14. 14. <ul><li>There are simple prove am rule </li></ul>ClearSaleing Confidential
    15. 15. BRAND KEYWORDS ClearSaleing Confidential
    16. 16. BRAND SEARCH THE CLOSER ClearSaleing Confidential Step2 = Branded Term
    17. 17. BANNERS INTRODUCE …SEARCH CLOSES ClearSaleing Confidential 11 of 18 keyword queries following a display impression were branded-focused Vision into the role of “Introducer” and “Influencer” are critical to understanding the value of the display advertisement.
    18. 18. <ul><li>287,000 orders in 2008 </li></ul><ul><li>35% of all orders in a Purchase Path </li></ul><ul><li>100,450 orders in a Purchase Path </li></ul><ul><li>45% ended in Brand Terms </li></ul><ul><li>45,202 orders ended in Brand Terms </li></ul><ul><li>Avg. order was $17 </li></ul><ul><li>$768,000 re-attributed </li></ul><ul><li>Total profit increased by 28% </li></ul>PURCHASE PATHS – CLIENT XYZ ClearSaleing Confidential
    19. 19. Disclaimer <ul><li>Due to time constraints we will not be able to explain every aspect of the model nor will we be able to speak to every input, scenario, and output. </li></ul>ClearSaleing Confidential
    20. 20. DR. PURUSH PAPATLA <ul><ul><ul><li>President and Founder; Vetra Analytics </li></ul></ul></ul><ul><ul><ul><ul><li>Staff – At least a Master’s in Statistics with a background in Engineer or Mathematics or a Ph.D. in Statistics </li></ul></ul></ul></ul><ul><ul><ul><li>Ph.D. from Kellogg School of Management at Northwestern University </li></ul></ul></ul><ul><ul><ul><li>Published in top-tier marketing journals </li></ul></ul></ul><ul><ul><ul><ul><li>Marketing Science </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Journal of Marketing Research </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Journal of Business Research </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Journal of Retailing </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Journal of Interactive Marketing </li></ul></ul></ul></ul>ClearSaleing Confidential
    21. 21. <ul><li>Verticals Served </li></ul><ul><li>Financial services </li></ul><ul><li>Insurance </li></ul><ul><li>Travel </li></ul><ul><li>Media </li></ul><ul><li>CPG </li></ul><ul><li>Auto </li></ul><ul><li>Retail </li></ul><ul><li>Catalog </li></ul><ul><li>High Technology </li></ul><ul><li>Non-profit </li></ul><ul><li>Online </li></ul>
    22. 22. CONSUMER DECISIONS
    23. 23. DECISION INFLUENCER <ul><li>What we know </li></ul><ul><li>Our Communications </li></ul><ul><li>Paid Search </li></ul><ul><li>Banner Ads </li></ul><ul><li>e-mail </li></ul><ul><li>Onsite Promotions </li></ul><ul><li>Comparison Shopping </li></ul><ul><li>Affiliate ad </li></ul><ul><li>Consumer Search </li></ul><ul><li>Organic search </li></ul><ul><li>Site visits to us </li></ul><ul><li>What we don’t know yet </li></ul><ul><li>Competitor Communications </li></ul><ul><li>Consumer search </li></ul><ul><ul><li>Site visits to competitors </li></ul></ul><ul><ul><li>Product trials </li></ul></ul><ul><ul><li>…… . </li></ul></ul><ul><li>Other sources </li></ul><ul><ul><li>Social Media </li></ul></ul><ul><ul><li>Word of mouth </li></ul></ul><ul><ul><li>Opinion sites </li></ul></ul><ul><ul><li>Expert opinions </li></ul></ul><ul><ul><li>Traditional Mass Media </li></ul></ul>
    24. 24. MODELING CONSUMER DECISIONS <ul><li>Build a mathematical model to predict consumer decisions </li></ul><ul><ul><li>Using data on influencers that we are able to track and measure </li></ul></ul><ul><ul><li>Representing data on influencers that we can’t yet track and measure - our uncertainty - through a statistical distribution </li></ul></ul><ul><li>Calibrate the model on observed consumer decisions </li></ul><ul><ul><li>Purchase - yes/no </li></ul></ul><ul><ul><li>Purchase size - dollar volume, # of units ….. </li></ul></ul><ul><ul><li>Repeat purchases </li></ul></ul><ul><ul><li>Word of mouth </li></ul></ul><ul><ul><li>……… . </li></ul></ul><ul><li>Test the model’s quality by comparing predicted and actual behavior </li></ul>
    25. 25. CONSUMER DECISION MODEL Consumer’s Decision = f( Our Communications , Consumer Search , Competitor Communications, Other Sources ) = f( [ Paid Search, Banner Ads, e-mail, Onsite Promotions, Comparison Shopping, Affiliate ads ], [ Organic search, Site visits to us ], [ uncertainty ])
    26. 26. MEASURING THE EFFECTS OF KNOWN FACTORS We assume that each of the known influencers has an influence potential
    27. 27. MATHEMATICAL MODEL FOR CONSUMERS DECISION ClearSaleing Confidential <ul><li>* The β ’s are the attribution weights </li></ul>
    28. 28. GETTING THE ATTRIBUTIONS <ul><li>We calibrate the model on data from the ClearSaleing platform </li></ul><ul><li>The data includes but is not limited to: </li></ul><ul><ul><li>Purchase Path ™ data </li></ul></ul><ul><ul><li>Record of consumer’s decisions </li></ul></ul><ul><ul><ul><li>Purchase/non-purchase </li></ul></ul></ul><ul><ul><ul><ul><li>Product(s) purchased </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Amount spent </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Repeat visits and purchases </li></ul></ul></ul></ul>
    29. 29. GETTING THE ATTRIBUTIONS <ul><li>Calibrate the model on the ClearSaleing data </li></ul><ul><ul><li>Find the values of β ’s which will help us predict consumer decisions as </li></ul></ul><ul><ul><li>accurately as possible </li></ul></ul><ul><ul><li>Model is calibrated using </li></ul></ul><ul><ul><ul><li>Maximum Likelihood or </li></ul></ul></ul><ul><ul><ul><li>Bayesian methods </li></ul></ul></ul><ul><li>The β ’s are the attribution weights! </li></ul>
    30. 30. MODELING THE INFLUENCE POTENTIAL Influence potential of an influencer = f (# of exposures, when each of the exposures occurred, decay rate of the effect of exposures)
    31. 31. EXAMPLE WITH SIMULATED DATA Simulated data example
    32. 32. EXAMPLE PATH DATA ClearSaleing Confidential
    33. 33. MEANING OF CALIBRATION ClearSaleing Confidential
    34. 34. INFLUENCIAL POTENTIAL (PAID SEARCH) ClearSaleing Confidential
    35. 35. Do models work?
    36. 36. EXAMPLE: WORD OF MOUTH TRACKING MODEL
    37. 37. OTHER INSIGHTS PATH DATA CAN PROVIDE <ul><li>Measures of the rate of decay of the influence of </li></ul><ul><ul><li>Paid search </li></ul></ul><ul><ul><li>e-mail </li></ul></ul><ul><ul><li>Banner ads </li></ul></ul><ul><ul><li>Comparison shopping </li></ul></ul><ul><ul><li>Site visits </li></ul></ul><ul><ul><li>Past purchases </li></ul></ul><ul><ul><li>… . </li></ul></ul><ul><li>Can be useful in deciding on frequency and recency of different types of ads. </li></ul>ClearSaleing Confidential
    38. 38. <ul><li>Does a consumer’s choice of an ad source influence his choice of whether or not to use another source? </li></ul><ul><ul><ul><li>E.g., Does exposure to a banner ad lead to greater interest in search? Branded search? </li></ul></ul></ul><ul><ul><ul><li>E.g., Does exposure to comparison shopping lead to greater interest in search? Branded search? </li></ul></ul></ul>OTHER INSIGHTS PATH DATA CAN PROVIDE ClearSaleing Confidential
    39. 39. KEY TAKEAWAYS <ul><li>Get the data </li></ul><ul><ul><li>Purchase Paths™ </li></ul></ul><ul><ul><li>Time </li></ul></ul><ul><ul><li>All advertising sources </li></ul></ul><ul><ul><li>Online and offline conversions </li></ul></ul><ul><ul><li>Etc </li></ul></ul><ul><li>Applying simple proven attribution models (e.g. Brand exclusion at end of path) can be easily applied and can improve campaign performance </li></ul><ul><li>Advanced attribution is possible to solve with sound mathematics </li></ul><ul><li>Accuracy in ad valuation leads to more profit earned from your ad dollars </li></ul>ClearSaleing Confidential
    40. 40. BOTTOM LINE <ul><li>We are barely scratching the surface of the potential of path data with the attribution models!!! </li></ul>ClearSaleing Confidential
    41. 41. CLEARSALEING AND VETRA <ul><li>Today: Our technology with Vetra’s team can build custom attribution models </li></ul><ul><li>Q3/4 2009: Vetra’s attribution models will be baked into ClearSaleing’s technology </li></ul>ClearSaleing Confidential
    42. 43. ClearSaleing Confidential Become a fan: ClearSaleing Read blog: www . blog . ClearSaleing.com Follow the tweets: ClearSaleing www.AttributionManagement.com
    43. 44. ClearSaleing Confidential . www. clear sale ing .com
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