monetize website, best monetization, best website monetization, monetize, ads, viewable impression, ad revenue, moneymaker, ads, wallpaper, publisher, direct sales, media kit, revenue manager, campaign manager, ad server, programmatic, cmp, ssp, exchange, monetization platform, ad monetization platform, wallpaper skins, wallpaper ads, skins wallpaper, adaptive ads, responsive ads, injected ads, ncremental revenue, viewable inventory, premium inventory

CONTACT US
NEWS
ABOUT US
INQUIRY
SIGN IN
making something from nothing ®
MORE SAMPLES
ADAPTIVE AD
Fold-less Campaign Analytics
Reporting based on TV-like Reach & Frequency distribution model allowing for GRP and Direct Response analysis.
Because of the fold-less nature of the ads delivered using LIQWID Ad Technology®, many traditional, including print and TV, analysis concepts can be applied not just as a historical data but also as upfront delivery parameters. For example, Reach and Frequency, Direct Response, GRP and Dayparting are more increasingly utilized but have a different meaning when it comes to online advertising because of a number of reasons, since viewability and scheduling issues based on the audience local time cause some deviations.

The ability to use LIQWID ad technology to properly Daypart plays a critical and essential role in managing the audience structure by time and day to achieve effective advertising scheduling and delivery. Because all ads delivered are viewable, the reach and frequency can be applied for the campaign delivery pace and control, and even geo targeting is now possible across different websites based on a specific GRP goal.

LIQWID's Viewer-Directed Placement Method uses the viewer's computer or mobile device as part of the ad serving process. This approach allows for a Viewer-directed queue of ads to be set for each individual viewer and managed similarly to a television advertising break queue of ads — that is, to show ads in a specified order and for a specified number of times (controlled frequency) with a specified iteration of each individual ad to each individual viewer based on the viewer system's local time, irrespective to the order of web pages visited by the viewer.

Even if all ads were viewable today, it would not change the fact that one thousand [viewable] impressions can represent one thousand people viewing the ad once or one person viewing the ad one thousand times. Ironically, this complicates the concept of click-through rate as a ratio between impressions and clicks. The key question is, how many users clicked after how many times of viewing the ad? LIQWID Ad Technology overcomes this limitation and enables for straightforward Direct Response (unique viewers clicked) models.

Here are some custom reporting data examples:

Minimum Exposure Time criteria

Because LIQWID saves the log data for each impression, it allows for a custom report rendering based on any specific minimum time criteria. For example, all data analysis can be easily rendered for any specific placement or campaign based on users that viewed the ad for at least 3 or 5 seconds, etc.

Average Ad Exposure Time

The average length of time the ads were exposed to a viewer on a screen, when rendered. We measure maximum Exposure Time for ads that are rendered on a screen up to 3 minutes. However, the Click time is always registered regardless of the Ad Exposure Time on the viewer's screen, so the Ad Exposure Time is always registered at the moment of Click. This methodology allows for determination of Click Density and Click Rate in relation to Ad Exposure Time and Impression Density (degree of the audience activity.)

Clicks Distribution by Exposure Time

An important factor is the density of clicks relative to the exposure time length of each impression. For example, one the campaign data suggested that only 35.2% out of all clicks occurred during the initial 30-second in-view time.

Clicks Distribution by a specific In-View Time Interval

For example, some Click distributions (each 10-second interval with an aggregate interval from 30 seconds to 5 minutes for all Clicks registered) demonstrate that the curve of density of the Clicks is smoothly sliding down after the initial 30-second in-exposure time. However, a meaningful number of clicks are still commonly happening even after a few minutes of the ad being in view.

Click rate in relation to exposure time length

Our data analysis shows that the Click Rate taken as an average irrespective to Exposure Time intervals is significantly skewed by a number of impressions that remained on the viewer's screens for a longer time period. Comparing data of absolute number of Clicks and Click Rate relative to Exposure Time helps to understand how Click Rate relate to an increase or decrease of absolute number of Clicks.

As an example, if you have two Impressions and one Click then your Click Rate is 50%. If you have 1,000 impressions and 10 Clicks then your Click Rate is 50 times smaller (just 1%), but you have collected 10 times more Clicks. Sometimes we see that less and less people clicked during Exposure Time intervals after 30 sec as less ads were staying that long in view, but the ratio between impressions and clicks kept getting higher.

Clicks Distribution by Time of Day

Over the years collected data tells us that Click Rate is not a constant and its value changes according to time of day. In fact, the campaign data collected during many campaigns shows that Click Rate is a floating number and increases and decreases according to time of day with up to a 50% deviation from the average.

Click Rate Distribution by Day of Week

Some campaigns data demonstrate that click rate deviated more than 50% (for example, from 0.45% on Saturday to 0.20 on Wednesday) for some campaigns. Data analysis for numerous campaigns suggest that Click-through rate can be different during different Days of Week and can be taken into consideration for scheduling if needed to achieve campaign goals.

Frequency Distribution based on specific percent of Unique Viewers

For example, the ad could be delivered once for 70% of all Unique Viewers, twice for 20% of all users and fifty times for 10% of all users. With 100 unique viewers this would create 610 impressions with an average Frequency of six, even though only 10% of viewers in fact saw the ad six times. Clearly, without the frequency distribution data, Frequency taken as a single average number can lead to a misleading conclusion of the campaign effectiveness.

Frequency in Relation to Clicks

Sometimes we see that 50% of all Unique Viewers exposed to the ads three times have contributed 10% of all Clicks. Sometimes only 4% of viewers were exposed to the ads three times contributed 10% of total clicks. The data demonstrates that frequency relates to clicks, sometimes not in intuitive ways.