Since its inception, advertising has always been about putting the right message in front of the right audience. Back when televisions were really expensive, and people used to gather around them in bars to watch baseball, beer companies started to do a lot of television advertising. While it’s still pretty easy for marketers to find the right beer demographic on sports programming in broadcast, the new world of multiple screens makes finding that audience at scale tougher every day.
The guy who was likely in the pub watching the game back in the 1940s and 1950s is now watching the game at home, but maybe on his iPad. Or perhaps he’s sneaking it in at work on his computer via Slingbox, or following along on his Android phone on the MLB Mobile app. The point is, there’s no easy way to find him, it’s almost impossible to find him at cheaply at scale, and we may have the wrong way of discovering him online.
The traditional method of finding your audience in the digital space is to put together a campaign request for proposal (RFP) that details the nature of your ad campaign, the audience you are looking for, where you want to find them, and the most you expect to pay to reach them. An agency’s trusted inventory suppliers receive and evaluate the RFP, and put together (hopefully) creative strategies that deliver a way to find that audience, and put the agency’s message in front of the user at the right time, in the right place. This approach makes complete sense. Except when it doesn’t.
Here are some ways in which the traditional, single RFP fails:
Multiple Pricing Methodologies: One of the problems in the traditional RFP process is that the agency is often limited to suggesting a single price range they are willing to pay for the media. For example, a typical RFP for a branding campaign looking for contextually relevant, above-the-fold inventory may suggest a price range to publishers of between $8-$12 CPM. This is fine if the proposal is only going to premium publishers with guaranteed inventory. But what if the advertiser is also interested in finding his audience on a cost-per-click basis? Knowing the historical performance of similar past campaigns, he might suggest a range of $1.50 -$3.50 per click. While the agency is comfortable buying using both methodologies (and certainly prefers the latter), the publisher is left wondering how to respond in a way that gives him the best overall price, and best revenue predictability. After evaluating the campaign, he may well decide that he will fare better on the CPC model, but in the absence of the granular past performance data of the demand side client, he will probably opt for the revenue visibility afforded by a CPM campaign.
Markets tend to work most best when both sides of the transaction have access to similar information. That leads to pricing efficiency, which in turn creates long-term sustainable performance results. Unfortunately, the traditional RFP process tends to strongly favor the demand side customer rather than the inventory purveyor. Add in the possibilities of buying on cost-per-lead (CPL) and cost-per-action (CPA), and you have a situation in which the demand side customer has the benefit of greater data visibility, and the supply side opportunity becomes purely speculative, leading to even more pronounced market inequities. These dynamics have largely occurred due to the seemingly unlimited supply of banner inventory (a supply side problem that will be debated in another article), but the fact remains that today’s standard agency RFP process falls far short of accounting for the multiple ways in which digital media can be bought and sold today.
Multiple Buying Methodologies: Along with a new multitude of pricing choices available to both sides, the emergence of real-time-bidding (RTB) makes the traditional RFP process even less relevant in for today’s progressive digital marketer. Say a marketer wants to reach “Upper income men in Connecticut that are in-market for a BMW 5-Series sedan.” That’s a pretty specific target, and I’ll bet that if a marketer could actually identify and find the several dozen guys in Darien, Stamford, and Greenwich that are looking for that specific make and model of car within the time period of the campaign, they might be willing to bid upwards of $500 CPM to reach him. Unfortunately, if you were to restrict the RFP variable to that exact target, you would end up serving a few hundred impressions, and probably fail to even spend $500 altogether. Naturally, the marketer is willing to bid a lot less find all men and women in Connecticut that are in market for a BMW; or just men in Connecticut in market for a car in general; or even just men in Connecticut, whether they need a car or not. Naturally, bids for each segment will vary widely, and can span from single to triple digits. Without a CPM-based pricing cap, it is not uncommon to see bids above $1,000 for certain impressions, although very few of them are won.
Well executed RTB campaigns have multiple segments that bid at different levels, and impressions are won at widely differing prices. While the marketer expects some visibility around what the effective CPM may be for such a campaign, RTB systems work best when agnostic to media cost, and should depend purely on the advertiser’s CPC or CPA goals. While a marketer can be very specific about his ultimate CPA, CPC, or CPL pricing cap, the traditional RFP does not address his tolerance for certain types of risk, his willingness to deploy a large percentage of media budget for data costs, and his willingness to forgo placement and context in exchange for reaching his ultimate demographic targets. This is just one of the reasons that agencies are having difficulty transitioning to the new world of demand side platforms in general.
New Discovery Mechanisms: Finding your audience by creating a well-crafted RFP and working with inventory suppliers to cobble together an effective buying program is still a great way to reach your ultimate goal, mostly because publishers know their audiences really well and have been able to offer new and creative ways to engage them on webpages (and, now, multiple screens). But what if the publisher isn’t really in control of his audience? What if the content an advertiser wants to be associated with migrates and changes constantly, based on user behavior and activity? I am talking, of course, about user generated content. Companies like Buzz Logic measure the “conversational density” around a topic and find where people are talking about, say, “organic food.” You can’t find that audience with a traditional RFP. The prevalence (or downright dominance) of social media outlets has created an explosion of UGC that is creating content almost faster than marketers can discover it. And that those new content areas are highly desirable to advertisers looking to engage consumers in contextually relevant activities. Those audiences are found via technology. How about finding people through the products they own (OwnerIQ) or even based on their occupation (Bizo)?
RTB and data make finding very granular audiences an intriguing option for marketers, but the traditional RFP process makes it hard to describe a marketers willingness to mix traditional, contextual audience buying (finding fantasy football fans on ESPN, for example) from some of the new audience discovery options (finding college students online based on their ownership of mini refrigerators, for example). Both are possible, and probably great to deploy over the course of a single campaign, but the traditional RFP process doesn’t really address this well.
Allocation: In my mind, the most important aspect missing from the traditional RFP process is that it doesn’t bring the demand and supply sides together effectively to suggest proper budget allocation for a campaign. If you have a $100,000 budget, and suggest $10,000 per publisher, every publisher is going to suggest $10,000 in media—regardless of whether or not they have it available. Moreover, you are going to alienate some publishers that may have larger minimums. The real problem is that the traditional RFP process doesn’t easily allow budget allocation across multiple media types (guaranteed display, real-time bidded display, mobile, video, search, and social) or take into account historical performance data. Essentially, the RFP makes a crude guess at budget allocation, with the marketer using his gut and some past performance data (“well, the $40,000 I spent with Pandora last time performed pretty well, so I’ll do that again”). Although the amount of choices today’s digital marketer has have expanded greatly, his form of communicating specific campaign needs is still an essay-length Word document or form-based technology with limited fields that do not capture the breadth of choices available.
So, what is the answer? New platform technologies are helping marketers expand the way they describe their campaign needs-and their willingness to deploy differing pricing and buying methodologies to reach their intended audience. Real time bidding systems are also giving end users hundreds of different levers to control the types of bids they are willing to make, based on the granularity of the audience, and performance of the inventory they purchased. In coming months, technology will not only expand a digital marketer’s ability to better describe his goals, but also use past performance data to suggest more effective media allocations in the beginning—and during—a campaign. Based on granular campaign attributes, knowledge of price points where certain real-time bids are won, and historical campaign performance, systems will be able to tell the marketer: “Allocate this percentage to SEM, this percentage to guaranteed display, and this much to real-time display” while suggesting the most effective bids to place. This three-dimensional discovery technique is where we are headed. While we are getting ready for its arrival, marketers should start thinking outside the traditional RFP box, and begin configuring new ways to ask inventory partners to find their desired audiences.
[This post originally appeared in eConsultancy on 8/19/11]