"Today, brands, agencies and publishers are making decisions based on pricing data that is inaccurate and may be only vaguely directional. Some of this stems from the thinking that faster is better and that best-guess projections are often good enough." -James Fennessy, SMI
When it comes to staying agile in today’s crowded media landscape, increasingly companies know that competitive market intelligence is crucial to making better decisions. The ability to monetize inventory is contingent on pricing that is fair and reasonable for both buyer and seller and changes dynamically based on supply and demand.
Unfortunately, the reality of most projections-based data sources in the market today results in massive gaps in understanding when it comes to the actual price of inventory across publishers and TV networks. It’s essential for today’s media companies, agencies and brands to be able to understand pricing and volume in this fast-moving environment and this does present real challenges.
Where gaps exist today
Historically, media buying relied on intelligence in the form of TV ratings and print circulation, and advertising rates were based on historical rates paid by the brand or the sector they were in as well as demand. In search of efficiencies markets began to revolve around forward-looking projections, which became an enduring feature of the ad pricing landscape through the Upfront buying season which typically happens three months before the next TV season begins. The benefits of this projection-based approach were that media sellers were able to lock in 80% of their revenue in exchange for guaranteed and preferential pricing for brands, but this approach is not giving marketers the flexibility they are looking for.
Today, brands, agencies and publishers are making decisions based on pricing data that is inaccurate and may be only vaguely directional. Some of this stems from the thinking that faster is better and that best-guess projections are often good enough. The problem with making projections off data sets generated through rate cards or small samples are many. Dated rate cards and non-representative samples can lead to estimates that are anywhere from 30-60% off the actual pricing being paid for media. And with margins as tight as they are, 30% could ultimately be disastrous for a performance-based advertisers. When it comes to understanding the overall ad market, accuracy and detail are vital.
As it stands, most media companies currently have a good handle on their P&Ls and internal measures around viewership. However, many struggle to attain a similar level of information on their competitors’ revenues, which is necessary to understand market share and competitive positioning. The reason is not a lack of trying, but a lack of accurate data as measured by a third party, particularly for digital media (it’s much easier to create metrics for traditional media, where the same ad is delivered to all users). This fundamental blind spot makes it incredibly hard for companies to gauge their true performance in relation to their competitors.
Another knowledge gap that media companies must contend with is a lack of accurate information regarding their yield versus that of their competitors. It’s easy enough to see how many ads are running across publishers and networks, and to understand how many people see these. But with projection-based data it’s impossible to know which spots represent unpaid or make-good placements, as well as the true cost being paid by advertisers. This willingness to rely on projection-based data misses a key component in understanding the health of the market.
The above two issues combined make it incredibly hard for media executives to understand the performance of their sales teams. Sure, they know that sales are up 5 percent. But is that good? Is it bad? Is it on par with the rest of the market? Without an accurate, real-world understanding of competitor revenue performance and good fair share analysis, it’s impossible to know whether a sales organization’s performance is outperforming the market, or falling behind.
Tracking ROI for brands across network TV:
For TV networks, a lot of investment goes into programming, both for sports and original scripted series. We know these programming genres attract very high CPMs, but is the return on investment where it needs to be? Again, without accurate cost and revenue data that looks across other networks and programs, it’s hard to know whether enough value is being generated by these properties, or which properties we should acquire next. Also, between national and local, what is the lifetime value of the content with pricing estimates based on real market data?
Brands have a good idea of the ROI for their campaigns and the corresponding media. The question is: What’s the trade-off for unused elements of each media form and the competitive (brand) effects on ROI? It’s tempting for brands to ignore this line of inquiry due to their inability to acquire campaign data for competitive brands (e.g. Coke vs. Pepsi). Additionally, sales teams at media companies can only understand the impact.
But brands have considerable activity across the advertising industry. Nowhere is this more apparent than in ROI measures of branded integrations. Usually those services assume all impact from on-network activity with line-of-sight from that network. But remember that brands have activity everywhere, and no one media company has enough information to create a true analysis (barring brand involvement, which is happening less and less).
The bottom line
When it comes to the competitive lay of the land, it’s vital for ad sales teams to have accurate, up-to-date data on which advertiser categories are investing most heavily across the marketplace. If sales teams are working off inaccurate or incomplete data in this regard, they could be chasing the wrong opportunities—or missing out on the most lucrative ones.
Consider overall pricing strategies: Today’s media companies must be able to ensure that their pricing compares favorably—or at least fairly—with that of their competitors. If the data they’re working from is inaccurate, it’s highly likely that media companies are either underpricing their inventory (and leaving revenue on the table) or overpricing it (and alienating advertisers that would otherwise buy in). Proper pricing—and thus, maximum yield—requires accurate data based on actual (not projected) spend.
It’s challenging enough to be in the media business today, facing pressure from many sides. Company executives that are making key business decisions based on inaccurate or incomplete data are doing themselves no favors in their pursuit of speed and efficiency. Staying competitive in the market requires reliably accurate ad spend intelligence. Smart players in the market would do well to consider actual pricing data along with forward looking projections. The extra time required is worth the cost.
Standard Media Index accesses actual invoices from the world's largest media buying groups, as well as leading independents and offers detailed ad intelligence across all media types, including television, digital, out-of-home, print, and radio.