Campaign Details Dashboard
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In the first part of the campaign details dashboard, you can see an overview about the campaigns running in the selected time range: the campaign name, the number of non bounces, the number of offers presented, collected and redeemed, the redemption rate, the AOV and the net revenue of Fanplayr’s orders.
In detail:
Presented offers: offers shown to a users.
Collected offers: offers collected by users; if the auto-collect options is set for a given campaign this number will be the same as the number of presented offers
Redeemed offers: offers redeemed by users
This table drills down information contained in the previous campaign overview, showing the performance achieved by each users in a given segment.
Please note that users may fall in more than one segment during their session creating overlaps. In case the number of rows is more than 100, you can click on “show all” to display them all.
Similarly to the segments table, this one shows the detail of each single offer presented to users in a given campaign
In case the number of rows is more than 100, you can click on “show all” to display them all.
Fanplayr allows for optimizing offers performance by A/B testing offers for each segment, to evaluate which one achieves the best performance (different discounts, creatives, copies, etc.).
The offer testing table shows for each segment the attached offers, the number of presented and redeemed offers, the net revenue, the discount total amount, the AOV and the percentage of redeemed offers over the presented ones. In the last column the net revenue per visit.
This table is related to the collected data throughout a campaign A/B test period. Differently from the offer testing, which is based on showing different offer types or creatives to users that are in a campaign, the A/B test is useful to evaluate the site performance with and without Fanplayr’s strategies.
In order to do that, users falling into a campaign targeting segments are divided in two groups: control group (which keeps the standard user experience) and target group (which receives the Fanplayr’s offers). Then the KPIs of the groups are compared to evaluate the impact of a Fanplayr’s campaign.
In the last two columns the values are compared by showing the percentage change, which is calculated by normalizing for homogeneous number of non-bounces.
