Ad campaigns are very crucial to the business and success of a product or the company. The
difference in the customer impact created by the advertisements can decide whether a product
skyrockets or fails in the market. These high stakes makes it critical to measure the performance of
an ad campaign and take instant measures to improve the performance and make the campaign successful.One of the important factor here is identifying the issues as early as possible as every aspect is time sensitive and losses are exponential with respect to time. Minimizing the damage by identifying and investigating the issue in real time is where ThirdEye comes into picture. In this recipe, we’ll use Startree ThirdEye to monitor ad campaign data and investigate the anomalies generated by ThirdEye for the anomalous behaviors.
Use the following alert configuration for “Startree-ets multidimensional alert creation”Exponential smoothing (ETS) is a technique for smoothing time series data that uses a window or tapering function. This is an advanced detection model based on metrics pattern and seasonality plus dimension exploration (multiple-timeseries). Learn more about dimension exploration concepts.
{ "name": "AdCampaignData-seasonal-dx-sample-alert", "description": "Monitor number of clicks across multiple dimensions such as Country and Ad Campaign Size", "template": { "name": "startree-ets-dx" }, "templateProperties": { "dataSource": "pinot", "dataset": "AdCampaignData", "aggregationFunction": "sum", "seasonalityPeriod": "P7D", "lookback": "P20D", "monitoringGranularity": "P1D", "sensitivity": "1", "aggregationColumn": "Clicks", "queryFilters": "${queryFilters}", "enumerationItems": [ { "name": "Overall", "params": { "queryFilters": "" } }, { "name": "DoubleClick-Canada", "params": { "queryFilters": " AND Country='Canada'" } }, { "name": "DoubleClick-US", "params": { "queryFilters": " AND Country='USA'" } } ] }, "cron": "0 0 5 ? * * *"}
Follow this guide to perform root cause analysis with heatmaps, custom events, and other signals. From this analysis you will see that out of the few anomalies that are detected by ThirdEye, the one detected from March 28, 2018 to March 29, 2018 shows a dip of around 120k clicks fewer than predicted.In the heatmap, you’ll see no prominent dimension contributing to the dip.
But if you observe the list of events around that time, you’ll see why the dip happened. Around the same time, two events took place:
ProductCatalogChange
API Failures
After noting the correlation between the dip and the two events, we can narrow our focus to these two events and validate our findings because we now see it is unlikely that the API failures were related to the ad campaign section, so we will assume there is nothing wrong with the ad campaign strategy.But it’s also interesting to see if the change in the catalog was not well received at first by the users, and it eventually worked (as the following trend looks normal). This can be an input to the catalog designers that users experienced some initial friction upon the catalog changes.
To learn more, join the StarTree Slack community.StarTree ThirdEye comes with a lot of API calls link you can use to build your own custom portals/web wrappers over StarTree ThirdEye. As a user, you have more control over using and customizing StarTree ThirdEye in creating great user experiences.
