Leveraging Incrementality Reporting to Assess Campaign Impact
As the streaming video landscape continues to expand and evolve, advertisers are leaning into programmatic to automate campaign targeting, optimization, and measurement of ad campaigns to maximize budget.
Programmatic advertising streamlines the ad buying process but it’s the programmatic traders who manage the ad campaigns that make the magic happen. Responsible for overseeing the campaign, a programmatic trader’s ultimate objective is to help clients meet their goals.
Throughout the campaign, traders leverage tactics like incrementality testing to assess campaign impact and adjust where necessary.
The Importance of Key Performance Indicators (KPIs)
Trading teams need to be able to show the impact of the campaigns they run on behalf of their clients. While key performance indicators (KPIs) provide a grading system for campaign effectiveness, it’s vital for the traders to set realistic performance expectations with clients, outlining the right KPI parameters.
If KPIs are too conservative, campaign goals can be met but clients lose the potential for a greater return on investment. If they are too strict, meeting and/or exceeding campaign goals becomes very difficult.
When using KPIs to measure campaign performance, it can be helpful to understand the true impact of the advertising on a user’s behavior, i.e. whether the user would have converted regardless or if they converted because they saw the ad. With an understanding of the incremental lift the advertising provides, realistic performance expectations can be established for the campaign.
Understanding Incremental Lift
Traditionally, programmatic traders would do this by running an A/B test where they would set up two identical line items to serve to distinct user groups, adding the advertiser’s creative to one and a public service announcement (PSA) creative to the other (such as everyone’s favorite, a Smokey the Bear ad). If the line item with the advertiser’s creative outperformed the PSA line item, then the ad was having a positive impact.
But this approach comes at the cost of the campaign since part of the media budget is used to run the PSA ad. And the costs for these tests can add up quickly, particularly for streaming environments with premium CPMs.
Using A/B testing to measure incremental lift also requires additional work for the traders. They have to source the PSA ad, set up the budget split, and manage the budget for the flight. While these are generally simple campaign setups, traders often manage a large volume of campaigns, so these A/B test line items could fall to the wayside.
This is where ghost bidding comes in.
The Benefits of Ghost Bidding
Ghost bidding simplifies incrementality testing while giving traders the results needed to prove campaign effectiveness.
Ghost bidding separates users into distinct groups and shows a client’s ad to one group while serving a “ghost ad” to the other. A “ghost bid” is generated and machine learning models predict whether the bid would theoretically be submitted to the exchange, if it would win, and be shown to the end user.
Ghost bidding also tracks the attribution against these ghost bid impressions and then reports on these in an incrementality report. This allows traders to compare the number of conversions generated from their client’s ad vs the ghost ad and see the incremental lift generated from their campaign. All this happens without ever placing a real bid, so no additional campaign budget is spent.
Ghost bidding and incrementality reporting provide greater understanding of the impact the campaign has on user behavior. Running these tests while campaigns are in flight allow the traders to assess campaign performance and adjust campaign strategy where necessary to deliver better results for their clients.
Now, this only matters if the bids predicted by ghost bidding’s machine learning algorithm resemble a real-life ad; otherwise, the test will not be a realistic representation of the incremental lift, and the results are effectively meaningless. Ensuring your ghost bidding solution has a high level of accuracy, meaning the predicted ghost win rate is close to the real win rate, is key.
Ghost Bidding with Beeswax
At Beeswax, ghost bidding models are trained on new data daily to deliver realistic incremental lift results.
With ghost bidding, programmatic traders forgo the additional expenses and hassle of delivering PSA ads to a control group. The system handles the testing and calculates the incremental lift which helps traders better understand campaign performance benchmarks, represent the value of the ads, and showcase their campaign’s effectiveness.
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