Making The Case For Spending Levels

OK. We've gotten to the point where many advertisers accept that the Internet has to be a part of their mix. They also realize that they need to be aggressive in advertising levels overall (see MPA and ARF literature on spending in a down market). But how much should they allocate? We had a meeting this week that was going wonderfully. We had the target nailed, as we did the other objectives. We showed the client from a broad stroke what priorities they could afford within their budget and what it would cost to get downtown with their aggressive targets. We reviewed the A/S ratios for their competitors. Problem was, there was a gap. Since it was a BTB client, most of their competitors spent money in print and Web. We could wax poetically about the level of spending, even estimate R/F within print and list the vehicles they advertised on. Then they asked the killer question. What about Interactive competitive spending? We really did not want to go there for a number of reasons.



First, the current tools are no good for estimating how much each competitor spends. Sure, they can chronicle the creative units, telling us in detail how fast the move is to new IMUs and what the relative expenditure is for each unit. They can, for the most part, pick up when a new competitor starts to advertise. But the representation of dollars spent is not even close. Many campaigns are off by 50%. And there are still cases where spending levels are overestimated by hundreds of percentage points or not shown at all, even though we can identify by simple browsing that the competitor is advertising on the Web.

The reality is that, after years of investment, the process for measuring competitive may just be wrong. Think about it. In order to identify an advertiser, the competitive metric company must send bots out to tell which ads are running. Besides the fact that some sites try to defeat these bots, there is no way that the technology can pick up all of the advertising. If they could, there would be no advertising served to consumers, it would all be served to the bots. In print advertising, all ads are identified for the most part. In national TV, the case is the same. The only issue is predicting the price and the vendors have gotten pretty good at that.

Spot radio is hard to measure with external technology. That's why the industry went to station reporting some time ago. Took some arm twisting to show the benefit but the cooperation is now fairly global.

Oh, and by the way, as covered in my Spin article from last August "Making Internet Advertising Affordable", the costs for the inaccurate Internet metrics are way out of whack. It costs almost as much to subscribe to one of the Internet competitive ad spending services as it does for all traditional media competitive spending combined. And, it is pretty much unit pricing, with little understanding that smaller clients and agencies cannot afford the same as a multimillion dollar conglomerate, based on the commissions earned on the medium.

So we were forced to tell our client that the data was insufficient for an intelligent decision and was inordinately expensive for the quality.

We need a new model. Yahoo!, MSN, AOL, CNET and other top sites, are you listening? Clients want to know the level that others are spending. Then, they want to up the ante and spend more. How hard is this to figure out? Commission a new third party to collect all spending information that has already happened. Most media regard history as an open book. If you share the spending levels by client (not the cpm or impressions), major companies will be able to justify greater spending!

Who could take on this project? It could be somebody like SQAD that is collecting aggregate CPMs for planning purposes. Or, it could easily fit into the data collection done on sites by Atlas DMT, DoubleClick or other agency site selector interfaces yet to come.

We need a new model. The current one has had over five years to prove itself and does not seem to be getting better. They keep adding features to justify even higher prices for data that is not good enough for decisions. If they won't change, someone else should introduce a new methodology, based largely on the process that has worked well for radio. It is not perfect, but it makes for better decisions. Better information results in more spending. The major sites can push to make this happen and benefit as a result. We only hope that they will do something.

David L. Smith is President and CEO of Mediasmith, Inc.

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