WebRF is a PC-only program that can be used in a variety of ways. Ad buyers can type in their proposed site lists and budget weight levels to determine what type of overlap they’ll experience from the sites. They will get back charts of how many people will see the ads, and how frequently, all based on syndicated data from online panels. In the non-customized version of the program, the budget weights are distributed among the sites based on rate card information, but agencies can tailor their data based on their own negotiated rates. This makes the figures much more accurate than those seen with some other reach/frequency products.
A common problem with this type of data, however, is the fact that certain targeting mechanisms interfere with the rates at which different sites overlap one another. In other words, a company buying the automotive section of one site and the automotive section of another will likely find a much higher overlap than is indicated by the syndicated data. The syndicated panel data averages all pages across both sites to determine an overlap factor, often severely underestimating frequency.
Nielsen partially solves this problem by allowing users to enter in only what pages are being bought. Their data is broken down into units fine enough to get the more accurate frequency figure. But all types of targeting aren’t taken into account. Keywords, for instance, can’t be factored in among search engine sites, at least not yet.
Companies that sell products online, targeting Web visitors based on their online behavior, may not find reach and frequency numbers a very high priority. But the tool looks to be a must-have for buyers involved in brands that concentrate on broad demographic groups. It is particularly strong in its ability to separate out the very different reach and frequency figures among different audience groups within the same buys. Sites, too, will likely find this tool necessary.
Manish Bhatia, SVP of Product Marketing at NetRatings, showed an example where a $23 cost-per-transaction turned out to be misleading when broken out into desired demographic groupings. The intended target, women 25 to 34, had a $404 cost-per-transaction. This is the type of data that should make sales reps quake — especially if they don’t have the same opportunity to peruse the information.
The back-end performance data does not automatically come with the product. Information such as cost-per-transactions and like performance measures must be integrated with a special implementation called WebRF Plus, which is still a work in progress.
However, the version launching now comes with an impressive campaign optimization feature. Buyers can put in their budget levels and desired targets, and the application will show which sites and which portions of sites will optimize the campaign to a specified reach or frequency.
These reports can all be exported from the application into Microsoft Excel documents for importation into campaign management systems.