By Ted Brauneck on June 3rd, 2020
How to Pre-Optimize a Programmatic Ad Campaign
The process of optimizing a programmatic advertising campaign allows you to make the campaign more efficient and effective in real time as you work toward reaching your marketing goals, but there is no reason to wait until after the campaign has been launched to start optimizing. There are several ways to pre-optimize a programmatic campaign before it ever begins.
In order to pre-optimize a campaign, you first need a good sample size of data to work from. This can come from your existing site data (most companies use Google Analytics); data you’ve begun gathering in advance of the campaign for retargeting purposes (e.g. through a tracking pixel installed on your website); or any data available from your past digital advertising campaigns.
The following list provides details on what to look for in your data. Trends that emerge will help your programmatic campaign manager adjust the “bid factors” they use to purchase the best ad impressions for your campaign goals during real-time bidding.
Pre-Optimizing Based on Past Site Traffic & Conversion Data
No matter how you gather and monitor your data, every user to your site leaves a digital trail of information which can be used to make informed decisions that help pre-optimize a campaign. Good data points to look at before you launch a new campaign include geography, time and day, device type, and purchase cycle data for your past website visitors and conversions.
By reviewing this existing data, you can identify trends and begin your digital ad campaign with a narrower scope than you would otherwise have at the start. This eliminates time and budget spent gathering data from scratch on the best places, days, and ways to reach your brand’s most likely customers.
A great way to pre-optimize an ad campaign is to see where your previous conversions or purchases have come from. In a national campaign leveraging previous data on conversions, for instance, I would bid up on the top ten percent of states in which conversions came from in the past and bid down on the bottom ten percent.
When targeting at the city level, the same can be done for specific cities or Designated Market Area (DMA) regions.
Technology (Browser, Operating System, & Device)
There is a wealth of data on the technologies associated with your site’s past conversions, which helps indicate where best to make bid adjustments. Your site statistics will indicate which devices (PC, mobile, or tablet), browsers, and operating systems your past conversions have been most frequently associated with.
Bid adjustments based on technology can have multiplicative effects on each other (for instance, bidding twice as much on iOS ad impression and also twice as much on a Safari ad impression may result in a single bid of four times as much), so I always start with one adjustment at a time. I like to go in order of browser first, operating system second, and device type third, keeping the latter bid adjustments more conservative than each former one.
Time & Day
Pre-optimizing an ad campaign for time of day can be difficult: You’ll want to note which time zone the ad campaign is set to serve ads from and which time zone your existing data is coming from. This will avoid your programmatic campaign manager incorrectly modifying bids for ad impressions at the wrong times of day.
By looking at the data on time of conversion and cross-referencing it with site traffic by time of day, you’ll get a good idea of when is best to make adjustments to bids based on the highest-traffic hours for both website visitors and sales.
Pre-Optimizing for Ad Retargeting
When you sign on with a new programmatic agency, one of the first things they may do is ask that you install a tracking pixel on your homepage and any sales or landing pages relevant to the ad campaign. This way, you can begin building a pool of recent website visitors for ad retargeting.
If you have access to recency data associated with your past conversions, it allows you to pre-optimize the bids of your retargeting ad groups to fit the average length of your sales cycle. If your data show that most conversions occur within a lower amount of days of the first impression and with less impressions overall, I would bid up on recency from the start and lower bids as days from the first impression increase, setting the bid to zero at the point at which conversions typically stop coming in.
Should the data show that you have a longer conversion cycle, with a longer amount of time between a conversion and the initial impression, you can bid down from the start and increase the bids on the recency schedule later in the timeline as you near the point of conversion seen in your data.
Pre-Optimizing Based on Past Campaign Data
A great way to pre-optimize a campaign is to see which sites your previous ads have run on, and which ones the most conversions have come from. Compile a list of sites that have performed well for you in the past so your campaign manager can bid up on those sites accordingly.
With all of the data available to us there is no reason any campaign should launch and have to wait to acquire performance data before beginning the optimization process. Use what data you have available in order to make smart adjustments to your initial bid modifications and launch your digital ad campaign with a head start.
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