Real-time bidding,
data segmentation, and new buying methodologies have made a dinosaur out of the
traditional agency request-for-proposal.

A programmatic approach to budget
allocation and audience discovery is coming soon that will forever transform
the RFP from a static document to an effective attribute matching engine that
can effectively connect the demand and supply sides in media.

The programmatic approach to media allocation is coming soon to a platform near you

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 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 to 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 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.