Grapeshot turns keywords into categories every time the page is viewed

Most publishers work hard to apply categories to articles at the time the journalist writes them. This pre-production pre-occupation means each page has a rigid set of categories, defined within an editorial taxonomy, or set of sections, defined at that time. It means categories are fixed and inflexible.

The advertiser's concepts or categories hardly ever overlap with the editorial taxonomy. Advertisers have a different way of seeing their world.

Is an IBM ad around its "Smarter Planet" focus on computing solutions for the environment's benefit something that fits in side Technology, Business, or News sections of the website?

Also an advertiser trying to buy or reach across several publishers is presented with separate taxonomies, or universes of categories, presented by each publisher. Put simply: a category mess.

Grapeshot liberates editorial and sales teams as new categories can be developed that can be applied to old archive documents in real-time, here and now. No re-categorisation required.

Instead Grapeshot converts the keyword essence of the page into the best match category - in real-time as the user views the page - allowing both editorial and advertising staff to create, develop, enhance, refine and delete any categories they like.

For the ad sales team, this is liberating, as new categories can be crafted that make commercial sense - they meet the IBM "Smarter Planet" brief for innovation and climate change without being boxed into a few hard categories previously created by the pre-production editorial and journalist workflow systems.

With a real-time categorisation process that converts key words into categories, Grapeshot can categoriseboth the keywords it collects for page essence, but also the keywords it collects around each user. On the internet most advertising systems use cookie IDs to log where users go anonymously.

Grapeshot can use the keyword trail as a way to categorise users, without knowing who they are. Their reading habits are captured as clusters of keywords, which can be keyed to each unique Cookie ID, and turned into categories in real-timejust as easily as the pages they read can be categorised.