How to Troubleshoot Issues in your Programmatic Advertising
Did you know that more than two thirds of US digital display ad-spending is programmatic?
In 2016, US programmatic digital display ad spending will reach $22.10 billion. That’s a jump of 39.7% over last year, and represents 67.0% of total digital display ad spending in the US. An interesting article at the Emarketer also states the categorical division in programmatic ad-spendings.
In this article, we’ll identify and solve issues, such as a sudden change in the advertiser’s budget.
As you review your in-house reporting – you may notice several issues that SigView can help you troubleshoot, such as if one ad-placement in an app isn’t delivering any conversions, you see a spike in demand in certain categories or your advertising spend has dropped off.
To identify the root causes of any issue – you can use the metric selections, filters & time comparisons. The example we’re using to demonstrate the use case, is ad-spend drop offs.
Step 1: Select the dimension of the chosen advertiser, in question to understand the issue of ad-spend drop offs.
Fig 1.0: In this image, we’ve selected a single advertiser and now we’ll be filtering on his campaigns and drawing the correlation between his spends.
Step 2: In this step, we’ll expand the campaign_name dimension and take a look at each of the distinct campaigns in multi-select view, run by the advertiser. We’ll filtered down to a particular advertiser. Now, we’re selecting the metrics advertiser_spend, CTR, Clicks and impressions to understand the sudden drop or spike in the spend metric.
Fig 1.1: In this image, we can see the various campaigns that the selected advertiser is currently running and we can also view the advertiser_spend, CTR, Impressions and clicks.
Step 3: In this step we’ll see how this metric has fluctuated over time, by comparing the current time period over the previous period. This will help you understand which campaigns have had relatively stable spend, which has spiked up and which are tapering off. Sort this metric to see the campaigns which have the largest change in spends, over the previous period.
Fig 1.2: In this image, we’ve drawn a comparison for in the time range, to understand the difference and also sort the advertiser_Spend in descending order to understand the performance of each campaign.
By taking a look at this view, you can understand if the advertiser is spending less on the whole, or if the changes are limited to individual campaigns. Now that you get an idea of how your advertiser’s campaign activity is changing – you can initiate conversations, around campaigns which are put on hold or resume, slowing campaigns will ramp back up, or if there are any other opportunities to provide them with the inventory they’re looking for.
If you’re struggling with a different dimension and need personal assistance, you can directly reach us at [email protected]