Research: behavioral KPI VS branding KPI correlation

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  • 1. Can Rich Media MetricsPredict Brand Impact?Ken Mallon Rick BrunerSVP, Custom Solutions Head of Research, NA SalesDynamic Logic Google
  • 2. Situation OverviewAd serving metrics (click rate, rich mediainteractions) are standard direct-response measuresof campaign performanceSome advertisers care more about brand objectivesthan direct response onlineThird-party survey-based test/control experimentshave become the norm for measuring lift in brandattitudes
  • 3. Key Research Question Could ad server metrics (click rate, rich media interactions, expansions) be proxies for assessing brand performance of campaigns?
  • 4. Methods (Database Construction)Rich media ads served by DoubleClick that were alsomeasured by Dynamic LogicFinal analysis dataset– blinded to advertiser– 4,299 records (creative units)– Contained both ad interaction data and brand impact metricsMerging was performing by independent 3rd party tomaintain the blind
  • 5. Methods (Metric Definitions)Behavioral metrics– Interaction A person is said to interact with a rich media ad if they hover over it for at least one second– Click-through-rate– Expansion rate Percent of impressions in expandable format that generate an expansionBrand metrics– Aided brand awareness– online ad awareness– message association– brand favorability– purchase intent
  • 6. Methods (Statistical Analyses)Correlation– Each brand metric was correlated with each behavioral metric– This was done both on the original scale as well as log- transformed scale for behavioral metricsLinear regression– Models were developed to predict the brand impact metrics as a function of each of the log-transformed behavioral metrics– Adjustment variables included baseline brand levels (brand levels within each ad campaign among those not exposed to the ads), the category of the advertised brand and other factors
  • 7. Results Relationship between CTR and Brand Metrics Very weak positive relationship between CTR and both ad awareness and message association Using linear regression, only ad awareness remains statistically significant with a model r-square of 2% Linear Regression    0.40   0.14   0.120      0.12               0.10                                       0.20                             adaw are = 0.10 + 0.02 * CLICKLOG 0.08 0.067     adaware                               R-Sq uare = 0.02                              0.06                                                                                                                        0.04                                                                                  0.022                                                                        0.02                                  0.00                                                                                                   0.00                     Ad Awareness Message Brand Opinion Intent                    -0.02 Association         -0.022       -0.04   -0.20 -6.000 000 0000 -4.000 000 0000 -2.000 000 0000 0.00 000 0000 0 CLICKLOG
  • 8. Results Relationship between Interaction Rates and Brand MetricsWeak positive relationship between ad interaction rates and both ad awarenessand brand favorabilityNegative relationship with message associationRegression analyses revealed statistically significant but practically unimportantrelationships (r-squares in the range of 1-3% for the 4 models) 0.15 0.132  0.120  0.10 0.05 0.00 Ad Awareness Message Brand Opinion Intent Association -0.05 -0.048 -0.10 -0.15 -0.162  -0.20
  • 9. Results Relationship between Expansion Rates and Brand MetricsWeak positive relationship between ad interaction rates and ad awarenessNegative relationship with purchase intentRegression analyses revealed statistically significant but practically unimportantrelationships (r-squares in the range of 2-4% for the 4 models) 0.25 0.20 0.188  0.15 0.10 0.071 0.05 0.00 Ad Awareness Message Brand Opinion Intent -0.05 Association -0.053 -0.10 -0.15 -0.20 -0.190  -0.25
  • 10. Conclusions Ad behaviors not good predictors of brand impactThese results show that rich media ad behaviors suchas clicking, interaction and expanding are not goodpredictors of the branding impact of adsIt may be that people interact with ads that are eye-catching or have an interest game, etc. but that thisactivities may actual distract from delivering brandmessages and other brand attributesSuggest using copy-testing as a better predictor of in-market branding success