How to analyze floating Business KPIs?
Programmatic Advertising and Real Time Bidding are rapidly gaining advantage over the digital advertising industry. From efficiency to cost effectiveness, Programmatic buying and selling has proved its mettle numerous times and appeared victorious. With the rise in demand of rich and interactive Ad Analytics solutions, Programmatic Advertisers and DSPs are also catching up to maximise their value using the right analytics tools such as SigView.
In this article, we will discuss as an example on how you can identify a root cause of a dip in advertiser spend** for one or more advertisers and how you can turn your key metrics around to maximize your potential revenue.
[**Advertiser Spend is the amount a DSP spends once it has won the bid.]
As a country manager, to check how different advertisers are performing across your country, you need to look for reduction in advertiser spend and focus on the publisher where they usually bid. Then compare their metrics over time against the usual suspects like CTR%, bid count, win rate, average spend and Bid Prices to pinpoint the bottlenecks. Thorough analysis with SigView can help you identify the root cause for a dip in ad performance and total spend.
Let us take a look at the below use case as it takes us step by step to understand how a country manager analyzes the performance of advertisers in their region.
Step 1: First let us select the country for which we wish to analyze the data over the selected time period and compare it against previous week.
The country selected here is USA.
Fig 1.0: In the above image you can see the Advertiser_Name data for the selection of USA Device_Country for 29th Nov 2016, compared with 28th Nov, 2016.
As you can see USA has a 69.32% drop in its ad spend but its auctions have increased by 5.24%. It means the incoming traffic for this country has increased but the number of conversions has reduced drastically.
Now examine the advertiser name table and find out the advertiser with the maximum decrease in Ad spend and select it to filter data for this advertiser to drill deep into the reason behind the sudden drop in ad spend.
Step 2: Let us now examine the App/Site Domain matrix to identify where did our advertiser spend the most in ads.
Fig 1.1: In the above image you can see the App/Site Domain table for low spending advertiser and their metrics.
As you can see Pinger.com is the biggest spend domain and the ad spend there has gone down by 42.90%
Step 3: Click on pinger.com to filter all data for that domain and then expand the Campaign ID table for a detailed look of various campaigns that are being run on Pinger.com.
Fig 1.2: In the above image you can see the campaigns being run on Pinger.com on 29th Nov, 2016 and compared with 28th Nov, 2016
As you can see, only 2 campaigns have a drastic decrease in ad spend and the rest have increased their ad spend considerably.
Step 4: Let us now check the campaigns which were being run on the previous day and compare it with 29th Nov, 2016
Fig 1.3: In the image above, you can see the high CTR% campaigns from previous day selected and marked in blue.
As you can see, the selected advertiser was running 94 campaigns on 28th November, out of which the campaigns with highest CTR% and delta CTR% are selected in the image above ~ Campaigns 58797 and 58798 respectively. You will notice that a few high performing campaigns with high click through rates performed well even despite reducing the Ad Spend and their wins increased drastically. Hence, it is evident that they were restructuring the campaigns and running the most efficient ones. Thereby resulting in a decrease in Ad Spend.
You can perform similar analysis for more advertisers with decreasing ad spend and share beneficial information with advertisers to help them maximise their value and returns from their ad campaigns
If you enjoyed this article and would like to know more about our Programmatic Ad analytics tool, reach out to us for a demo .