Programmatic advertising has many definitions including, “automated media buying,” “tech assisted buying,” and “ai driven media buying.” To many marketers, programmatic is the holy grail of ad buying. Technology that will find their perfect audience and optimize every part of their campaign. Sounds perfect, right? To a certain extent, this is true. Adtech as an industry is building amazing things, and the future looks awesome. However, despite all of these advances, human interaction is still a key part of the programmatic ecosystem.
Here are 8 tips that you can implement when analyzing the performance of your programmatic campaign.
1) Sitelist Reports
Sitelist reports should be the first thing on your checklist when evaluating the health of your campaign. The reason being, unlike in the GDN, where you are paying for per click, you are paying per impression. You want to make sure that your ads are showing on placements that are relevant, not spam or poor quality inventory, and that the targeting you have implemented is driving the right type of engagement. Compare your KPIs against the data being presented and build a blacklist of the worst performing inventory that you have been showing on.
Sitelist reports should be the first thing on your checklist when evaluating the health of your campaign. Click To Tweet
Sitelist reports can also be a source of shaping your audience persona. Based on what the data shows you, trends will begin to emerge about what types of content your most engaged audiences are interested in. It may be different than what you had originally thought. It is important to know your audience, not your demographic. Use this collection of sites and themes to build breakout campaigns and messaging that are highly targeted and relevant to your audience’s interests.
Each device has its place in the behavior of a consumer. However, each device will only perform as well as it is targeted towards. Many programmatic campaigns are kicked off with devices all lumped together in an effort to obtain scale and data. But what do we do when we have hit scale and performance is lagging? Look into device performance. I have seen many cases where desktop has been cannibalizing much of the daily budget, when realistically, mobile has been outperforming against KPIs, and vice versa.
Use the data to create a test to break out mobile vs desktop and move budgets towards the better performing device. This strategy is extremely important in the cases of brands that do not have consistent user experience across all devices.
3) Exchange Performance Reports
Believe it or not, there are more ad networks than GDN. Much more! And it can be overwhelming. Programmatic platforms allow us to access all of these different sources of inventory, at different prices, with varying levels of quality and performance. Because programmatic auctions are carried out in milliseconds, it is impossible to control where your ad will show up if the system deems the placement to be within your target audience. This can lead to portions of your budget being pushed across exchanges that contain inventory that does not perform against your KPI’s.
Pull campaign reports, segmented by exchange and see what exchanges your ads are serving on. Highlight your worst performing exchanges and remove them from your targeting. It is worth noting that this technique can have an impact on your scale. If your largest source of inventory is the worst performing, it may be worth reevaluating your targeting.
Like any paid campaign, dayparting is just as important in programmatic. It allows you to follow user behavior and increase budget efficiency to serve ads during the times and days where your audience is most likely to click or buy. Utilize dayparting reports to analyze when your audience is most engaged and begin to test the impact that dayparting can have on your campaign performance.
Analytics is probably the most important tool that you can use when managing programmatic campaigns. Campaign metrics such as impressions, clicks, and CTR will only provide a snapshot into your overall campaign performance. It merely shows that someone saw an ad, clicked on it, and visited your site. But, what did they do when they got there? Did they bounce? Did they look around? Did they buy? Use analytics to see the full impact of your campaign. High bounce rates and low time on site may indicate a number of problems, such as:
- Landing page relevance
- Poor user experience
- Subpar targeting
- Bot traffic
Armed with data and insights, you can make adjustments to your funnel, user experience, and targeting to fine tune your campaign performance. Your analytics tell the story of your customer journey. Make sure it is not a horror story.
Your analytics tell the story of your customer journey. Click To Tweet
Another great way to improve performance is by leveraging geotargeting. Not every part of the country is going to respond to your ad or even your product in the same way. For example, an ad promoting ski boots will more than likely not perform as well in California compared to the same ad in Vermont. Geotargeting also gives insights to specific markets within certain states. Using the same ski boot analogy, I live in Spokane in eastern WA. Despite being in the same state as Seattle, where it rains pretty much every.single.day, we get a lot of snow in the winter time, and the ad for ski boots will likely resonate better here than in Seattle.
When looking at geo reports, make sure to drill down to not just state, but as deep as the major cities and markets. You will learn a lot more about your audiences and potentially save a significant portion of your budget.
Frequency cap is a common debate. It depends on the strategy, response needed, and ultimate goals of the campaign. In order to avoid ad fatigue, it is important to continually test and adjust the frequency and time between impressions that users need to see an ad to be influenced. When analyzing frequency reports, it is important to look at:
- The total amount of times a converter/visitor needs to see an ad
- The frequency range which brings in the lowest costing conversions/trafficUsing this data, begin testing different frequency caps
Here are a few that I have seen work well in the past.
- 1 impression per user every 2 hours
- 1 impression per user every 4 hours
- 5 impressions per user per day
- 25 impressions per user per week
Once you find a frequency range that works best for your campaigns, monitor it over a longer period of time and see what impact it has on your overall campaign.
Many DSPs in the Marketplace have their own proprietary algorithms that they can apply to your campaigns to reach specific CTR or CPA goals. However, algorithms and robots don’t always work to your advantage. Human analysis and interaction are constantly needed in programmatic, especially when it comes to bidding. While algorithms can be useful as more campaign data is collected and your strategy evolves, DSPs do not create them. It is important to consider using manual bidding as you ramp up your campaign. Not only does this control how you manage your spend, but it also gives insight into what is a realistic CPM bid, to maintain both scale and performance.
On the outside, programmatic is a scary beast. Marketers are hesitant to face it head on. However, by taking the time and digging through all the vast amounts of data that it can provide, you can not only optimize your programmatic campaigns, but gain a true understanding of your market and your audience.
Analyze the following:
- Sitelist reports
- Device performance
- Exchange reports
- Daypart reports
- Manual bids