April 2, 2019
New capping types, Bidding Multiplier, and insightful reports — The Epom White-Label DSP introduces new updates to make your media buying even more accurate and cost-effective.
Programmatic media buying isn't easy. Tons of details should be considered on your way to the positive ROAS. So having the right tools at hand is the key to outstripping expected KPIs and being profitable.
The fact is that sometimes a few setup improvements towards your ad campaigns may significantly reduce the cost for conversion. In addition, the analytics already have answers to all your questions when you ask them in right way. With this in mind, we have started working on the next release of the Epom White-Label DSP.
As a result, the 3.3 release brings new types of frequency capping, offers a unique solution for your bidding strategy and helps you to get the most of your real-time reports.
With our new secondary 30-day frequency capping, you set the time periods between ad impressions to one user. For example, if you need to hit the user with different messages once per every 7 days, you would need to put 7 in front of the 30 days cap in your ad campaign settings.
Use the secondary 30-day capping as an additional capping to the standard 1/24 or 3/24. It will help you to better shape your communication strategy and not exhaust your audience with ads.
With the Recency capping, you define how much time should pass until the user who has already seen your ad will see it another time. 15 or 45 minutes? You're the one who decides.
Let's assume that users saw your creative, but didn't click on it. Even though they left the website, they may still be online. This is why you still have a high chance to bring them to conversion. Delivering your banner the second after the first impression happened isn't necessary. However, you can switch on the recency capping and continue your communication when you are hot on your heels.
Whether you like it or not, a part of your marketing budget is always wasted. Tons of dollars spent on users that will never become your customers raise the gap between you and your positive ROAS. The Exposure Time Multiplier helps cut down the costs spent on impressions delivered to the same user.
For example, the user has already seen your ad but hasn't made the next step towards your product. Then you decide to hit him/her with the next impression. The Exposure Time Multiplier exponentially lowers the bid for non-unique users (exponential decrease of a bidding price) so that the following impression will cost cheaper than the previous one. The more often the user sees your creative, the less you pay for the next impressions.
To avoid investing in users that have low purchase intent. The exponential lowering of a bid makes your frequency capping more accurate and will also take care of your budget.
The Bidding Multiplier feature helps media buyers win impressions from the best-performing traffic sources without overpaying for them. How does it work?
After analyzing your numbers in the analytics tab, you pick traffic sources with the highest performance. For winning more of their impressions, you switch on the Bidding Multiplier that automatically increases your bid for the specific publisher by two, three or more times (you decide) to ensure that you get the impression. When you win the impression, you only pay the second price + 0.01 cent and not a high bid that you've offered.
For winning relevant impressions without overpaying.
Release 3.3 added more tracking filters to the analytics tab. Along with standard metrics like impressions, clicks or countries, reports now display columns with the bid price, bid floor, win rate, and more precise data, all in real time.
You're not limited in how many columns you can display on the screen. The more numbers you compare, the more insightful your reports are.
Additional columns help generate reports that display performance to the smallest details. The new columns shown reveal the improvements that should be taken towards specific ad campaigns or creatives.
These two new dimensions in analytics uncover performance per the OS versions and devices. When applied along with other filters like conversions or I2C (impression to conversion), dimensions of the OS version and Device reveal points for future optimization.
To define the best and the worst performing OS and types of devices, before putting your hands on optimization.
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