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Newer metrics for measuring ad effectiveness
(0)Among the most popular metrics for measuring ad effectiveness have been –
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Impressions – Number of impressions delivered on a campaign
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CTR – CTR as we have discussed earlier is a percentage of impressions where a user clicks on an ad and is taken to the advertiser’s site
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Sales – Actual sales generated by a campaign.
Newer metrics are now emerging. Among these are –
Instant Reaction–This metric measures where a user saw an ad and reacted immediately. This is an important measure because it resulted in enough interest on part of the user to stop his online activities and visit the advertiser’s site
Longer term impact – This is a measure on the mental impression an ad left on the user resulting in him/her changing behaviour.
How do we measure instant reaction and the longer term impact?
First let’s look at measurement of instant reaction.
Theoretically, the click is the best measure for instant reaction. However, since users do not click on ads all that often, a new set of metrics have been evolved. These are the effective click and the direct click.
An effective click is when, having seen an ad, a user enters the URL of the advertiser and visits their site. This is an effective click because though it is a not a click thru’, it effectively a click because the ad has cause the user to visit the advertiser’s URL.
A direct click is self-explanatory. It is when a user clicks on the ad and goes thru’ directly to the website of the advertiser.
When measuring effective clicks, one needs to distinguish between natural and paid leads. A natural lead is when a user clicks on the ad and goes thru’ to the advertiser website.
On the other hand, at times when a user sees an ad for a suitcase, he doesn’t click thru’. He enters a search string ‘suitcase’ into google which gives him a number of search results. Among these search result is the link to the advertiser website. The user clicks on this link and ends up visiting the same advertiser website albeit in a convoluted way. The credit for this visit will go to the paid marketing programs not to the banner advertising program.
Measurement of ‘Sales Lift’ is slightly more complicated but provides compelling results. It requires creation of two groups – one group to whom the ad is not served and the other to which the ad is served.
Sales out of both groups are compared. And the amount by which sales from the targeted group exceeds sales from the non-targeted group is the sales lift.
Sales lift is one of most powerful metrics of mental imprint an ad leaves on the consumer. It measure both the immediate and long-term influence.
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Yield Optimization
(0)Yield optimization (YO) is a method used by Ad servers to improve performance of a particular ad creative. The way this works is that the ad server identifies publisher impressions that a performing within the campaign parameters. It distinguishes performing impressions from non-performing ones.
The end objective of YO is to ensure that all creatives run on performing impressions. YO could be take a fairly basic as keeping track of CTRs for a site and optimizing creatives based on it. It could take more sophisticated forms feeding campaign specific parameters like time of day, publisher, ad size etc into an automated system allowing the system to take the decision of where best to place the creatives.
Factors to be kept in mind regarding YO
YO Support
Not all ad servers support YO, though. Many ad servers assume that if you have bought certain inventory, it is an informed decision. The premise therefore is that if you have taken a considered decision to buy certain inventory, it has got to be performing inventory.
Ads exchange and YO
The average ad exchange supports high-level YO. This is so because you are buying inventory on the fly. It makes sense, therefore for you to know whether an impressions is going to give you the required mileage or not.
Learning Curve
Automated or machine learning based YO systems need time to learn. In such systems, in the initial stages some impressions will be lost to learning. In the initial stages of the campaign, the ad server will place creatives with a number of publishers and slowly, based on learning, weed out non-performing impressions. We would eventually get there, but there will be a period of non-performance or more likely, low performance.
To sum up YO is a wonderful tool that an advertiser has. The use an effectiveness of YO to a particular campaign is essentially about understanding an ad server – features and functionally – in depth and harness these features to get optimum results.