41. Thank you
Aruna Thota, Director of Product Management, Adometry
aruna.thota@adometry.com
Notes de l'éditeur
Key FindingsForrester’s study yielded six key findings:Practitioners of attribution indicate general consensus on the definitions, benefits, and expectations of attribution.Forty-four percent of interactive marketers don’t have processes in place to assign credit to their efforts, not even rudimentary attribution such as “last event,” indicating that adoption of attribution has room to grow.Few marketers, agencies, or publishers stand behind last-event attribution, but it’s still commonly used as a standard for attribution.Algorithmic attribution models are gaining acceptance, but some in the market remain skeptical.Publishers are cautiously enthusiastic about marketers using attribution to show the value of upper-funnel inventory.Attribution across devices represents a major challenge.
In additionDisplay has an average conversion lag that is 6 times larger than searchDisplay when preceding other channels shortens the conversion lagDisplay is the introducer in almost 80% of the conversions it participates inIn visitor paths towards conversion display is one of the first few media touch points and consistently lifts other lower funnel media such as paid, organic search and Affiliates
Although there are several anecdotal examples that say 90% of users exposed to display ads are not engaged, that is the danger we encounter when we use flawed metrics such as click through rates to measure impact of display. When there are formalized A/B tests and experiments structured to measure display, we see a different story emerging that shows increased search relevance, increased site visits, increase in time on page and larger order sizes which all ties back to hard revenue numbers for the advertisers.
To understand the weight or credit due to an event in a particular sequence, we first find all examples of that sequence – both converting and non-converting. From this we can calculate the conversion rate for that sequence.Next, we find a similar sequence of events that excludes one of the events from the prior sequence – for example, the first event. Again, we find both converting and non-converting examples. We then calculate the conversion rate for this (second) sequence.Now, by comparing the conversion rates of the sequences we can determine the weight or impact of the the missing event. If the rates are identical or similar then the missing event deserves little or no credit whereas if the rates are different then that missing event had an impact and deserves credit.This is an obviously simplified explanation. The complexity is in the details.Number of sequence and length of sequences will varyWe normalize the weights such that they add up to one (1)Tons of events - "big data problem"If there is only one event in the sequence it will get 100% of the creditAn event is actually a complicated thing – has lots of attributes – site, campaign, placement, creative concept, tactic, etc. we calculate at the lowest level and roll the results upAlso frequency and recency.But this is the stuff that the engineers have all worked out in a principled manner. Machine learning, etc.
Moving from interesting to ACTIONABLE!
Attribution is sync’ed with the lifecycle of a campaign- Monitor Campaigns to mitigate waste – ad and audience verification to ensure viewability and target the right audience; Impact: recognize an immediate 10-20% waste reduction through elimination of out-of-compliance and non-viewed display ads - Improve Performance and predict success – automate the numerous adjustments that can drive significant improvement in ROAS and optimize in-flight campaigns. The complexity of cross-media interactions is too challenging to be analyzed and managed manually; it requires sophisticated technology to automate the process and make recommendations for media buyers and planners - an "Easy Button" to optimize campaign performance based on constraints and key performance indicators. Impact: Immediate 20–40% aggregate ROAS lift through optimization - Glean Insights to build better campaigns – looks at the entire stream of media to evaluate and measure campaigns to determine what is and isn't working. Impact: Longer term 25-75% aggregate ROAS lift through better campaign development and strategies through attribution
- Monitor Campaigns to mitigate waste – ad and audience verification to ensure viewability and target the right audience; Impact: recognize an immediate 10-20% waste reduction through elimination of out-of-compliance and non-viewed display ads - Improve Performance and predict success – automate the numerous adjustments that can drive significant improvement in ROAS and optimize in-flight campaigns. The complexity of cross-media interactions is too challenging to be analyzed and managed manually; it requires sophisticated technology to automate the process and make recommendations for media buyers and planners - an "Easy Button" to optimize campaign performance based on constraints and key performance indicators. Impact: Immediate 20–40% aggregate ROAS lift through optimization - Glean Insights to build better campaigns – looks at the entire stream of media to evaluate and measure campaigns to determine what is and isn't working. Impact: Longer term 25-75% aggregate ROAS lift through better campaign development and strategies through attribution