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Nikon D 80

If however we use D80:

Nikon D80

DubLi Headers for Nikon D80

Dublicator Meta tags for Nikon D 80

YORGOOpublishing headers for Nikon D80

Best Price Nikon Digital Camera D80 Kit incl. DX 18-135

Best buy Nikon D80

Semantic interpretation, function of the semantic framework

The two above samples show that the same add can return different results depending on the semantic framework within which it is published. Each Semiomantics based site is defined based on user’s preferences on multiple parameters; chances that two users use the same customization features within a given topic are about 1:4,000,000,000. At least for as long as not more Semiomantics scripts are in use to promote amongst others DubLi related Auction items. An increase to 10 000 scripts in use would result in a probability of 1: over 100 000, meaning it remains highly improbable that two absolutely identical publications would be published just based on framework settings.

The above demonstrates: it does not really matter what we publish, but how we publish when we use Semiomantics semantics frameworks.

We have tested over 20 expression to distinguish identical posts and they all return top 10 rankings. An other example is: “[product name] best deal”

Nikon D80 Best Deal

Clustering and increased scattering on Louis Vuitton

The below screenshot gives an impressing picture of the clustering and scattering function described in Semantic Publishing of DubLi Auction Ads with Semiomantics I:

Louis Vuitton Clustering an Scattering

Louis Vuitton Gift Voucher

Best Price Cameras

Where are the advertisers?

Serious publishers and advertisers alike spend time and money on assessing the market (target) as well as the competition. One of the question is: where is the center of gravity aimed by competitor’s ads and what are the privileged exact search terms.

Let’s return to the Nikon example:

Remember the controversy about D80 or D 80? It’s a matter of a space and yet, that space makes a whole difference!

Here is D 80 …

D 80

D80

Results:

1. On D 80 there are about 15% more search returns on Google 467 000 compared to 407 000.

2. On D 80 I didn’t see any ads, at least not from here in Greece

3. On D80 I get advertisers

4. INTERESTING: on both search returns we find Nikon USA within the top 3 with the same content, the other top ranked sites change from one search to the other. There is an interesting lesson to be learned here and we will elaborate on this in a later article.

We can simplify the D issue by just searching for nikon d80 compared to nikon d 80. Again Google gives us some indication here:

Please note: Google treats ‘d’ as a single expression in the search Nikon D 80:

Nikon D 80

While the search Nikon D80 deals with D80 as a single expression:

Nikon D80

Finally, what should we target, D 80 or D80?

Clearly both as with Semiomantics Frameworks it will not result in more work. Remember the pair of socks and the finite matches for infinite pairs of socks? Well, it’s along those lines that the issue can be explained. When assessing a market and competitors, the devil is again in the detail. On this issue it is possible that many advertisers get it wrong:

while the exact type designation is D80, many searchers may type D 80 and what counts is what the customer types in. They will use both, depending on the source of their information: if the ads about that camera is featuring D 80, as we noticed in the ad by DubLi, then it’s normal that D 80 will be what they are looking for.

In general one can say that the end user is not functioning like a precision clock. What matters to him or her is not the exact spelling of a product name or type, what matters is, whether he or she finds what he or she is looking for.

And that is may be the best conclusion to all the science and calculations and probabilities and possibilities: what counts for the customer is the result and therefore the publisher must be visible where the customer searches for that result.

In the end the customer is only to a limited degree predictable, some times more others less. There are measurably more probable key-phrases on many items. The publisher needs to take such higher probabilities into account and scatter the adds all around such centers of gravity. And that’s exactly where Semiomantics is pursuing its work and development: to provide publishers with ever better and more predictable publishing results on a target that will never be 100% predictable.