Occasionally, some metrics might not fall within an acceptable difference when comparing Adobe Analytics metrics to DFA metrics. Below is a list of metric definitions and possible reasons for variances.
This section includes the following topics:
Adobe uses the following terms when talking about metrics related to the DFA integration:
Impressions: Impressions refer to the number of times an ad was viewed. Impressions are reported on an ad-by-ad basis, but can also be aggregated into ad groups or other multi-ad groupings. The impressions metric in Analytics is imported from DFA via a nightly data sources import.
Clicks: Clicks refer to the number of times an ad was clicked, as report by DFA. Clicks are registered on the DFA redirect page prior to the visitor landing on the customer’s website. Like impressions, the clicks metric in Analytics is imported from DFA via a nightly data sources import.
Click-Throughs: Click-Throughs refer to the number of times the user arrived to the landing page, after clicking on an ad. This metric can be subtly different from Clicks.
View-Throughs: View-Throughs refer to the number of times a visitor came to the customer’s Web site after viewing an ad, but having NOT clicked the ad. The visitor must come to the site within the view-through window, which by default, is set to 30 days. The impression must have happened more recently than the last click. View-throughs are registered once per campaign, per visit and are counted when the integration populates the view-through eVar with the DFA campaign ID, and the view-through event is set.
Lists a number of reasons why data discrepancies can occur between Adobe Analytics and DFA reports.
3rd party cookie acceptance is typically the largest cause of discrepancy between Adobe Analytics and DFA. Safari and some other browsers block third-party cookies by default. This means that by default, Safari accepts the first-party cookie used by most Analytics implementations, but rejects the third-party cookie used by DFA.
A sample of data from our Analytics 15 beta customers showed less than 0.5% of users typically reject first-party cookies, while 5-12% reject third-party cookies (many of these rejections are likely due to default browser settings).
This discrepancy can result in large difference in the data collected by Analytics and DFA.
DFA sends data to Adobe data collection servers in a nightly batch, so impression data in Analytics can be up to 2 days behind the DFA reports.
Adobe uses SAINT classifications to classify imported DFA tracking codes into various levels of aggregations (campaign name, placement name, ad name, etc.) If the discrepancy appears when running a classification report, perform a simple test to see if the classifications have not yet caught up with imported metrics:
DFA:XXXXX:XXXXX
.s.maxDelay
timer is being hit.?CID=1
”). Failing to set this parameter will cause the Adobe Analytics JavaScript to miss any click-throughs which happen after the first hit of the visit.clickThroughParam
included in the query string. Failure to redirect the browser will not cause a click-through to be recorded.s.maxDelay
parameter determines how long the JavaScript waits for the Floodlight Service (FLS) data. If s.maxDelay
is too high, visitors can leave the site before Adobe collects the hit data; meaning that no click data is recorded. If s.maxDelay
is set too low, the visitor’s Internet connection cannot retrieve the FLS data in time; meaning that the hit is sent to Adobe without DFA click information.s.maxDelay
expiring, and DFA data returning, will be lost; no DFA or visitor data will be collected for them.Consult your Integration Consultant, or Adobe Client Care, to document the discrepancies and report them to the Data Connectors engineering team. To expedite your request, have 2 - 3 days of data comparing the metrics in question (at a campaign code level). In your request, identify all actions you have already taken to reconcile the discrepancy.