It has become the cheap word that every ad network, rich media company, technology provider, publisher, and agency drops when they attempt to sound sophisticated.
It makes its way into
every media plan, and sneaks onto every vendor Web site. So what's wrong with optimization?
Optimization is like love. It is an easy thing to say, and
much harder to put into practice.
Worse, everyone means something different when they say it, and most mean very little at all.
This is a shame, because if the first generation of
online display advertising was about delivering reach, and the second generation was about delivering audience, the third generation will most certainly be about delivering ROI through
optimization.
Defining Optimization
In order to have an effective debate, we should first agree on what we mean by optimization as it relates to online
display advertising. I will offer up a simple definition: Optimization is the process of maximizing ROI by evaluating all of the relevant data points.
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The goal in all cases should
be really simple: profit. While advertisers have varying objectives short-term, every single advertiser hopes to earn more money on their investment long-term than they spend. The only variable is
timeline. Direct-response or transactional advertisers seeks to capture the purchase instantly or near-instantly. The rest of the advertisers hope to advance the sale now, and capture the purchase
eventually.
Rocks, Pebbles, Sand, and Water
The first step toward helping advertisers achieve ROI goals is to connect them with buyers, not demographic groups.
Relying solely on demographic data is a recipe for massive inefficiency. Individuals are only willing to buy a certain number of products at a given moment, so advertising to an entire wide
demographic like 18- to 34-year-old males, rather than the 5% of Web site visitors willing to buy a pair of shoes in the next 10 days, is a mistake.
Add in their shopping habits,
behavioral data, context of the sites they visit, spending history, and other data points and you will get closer, but you then need to know what order to use the data in.
In fifth grade
science class, we all watched a teacher fill a jar with rocks until the jar was full, then add pebbles, then sand, and finally water until nothing more could be added. Each time it looked full
until a smaller-sized item was added.
The same logic applies to optimization. If you want to maximize the effectiveness of your data, you need to work in order of granularity from largest to
smallest.
Knowing What to Ignore
Social networks routinely tout their vast mountains of data, yet they earn a small fraction of the average CPM rate Online
Publishers Association members get. One reason for this disparity: advertisers do not know how to leverage the social network data to improve their ROI.
There are more than 100 discrete
types of user data, and thousands of companies that own slices of data. These data sources are far from equal.
Over the next five years, our industry will face the same challenge every Wall
Street analyst has: figuring out which 90 data points to ignore, and which 10 really matter.
Targeted Delivery Without Being Creepy
Once you have the right data
points, the next challenge in optimization is selecting the delivery vehicle for the message.
Data-driven ads use programming hooks (typically an API) to enable you to query a back-end
database and retrieve the right ad unit for a given set of data points.
Early implementations of data-driven ads have been primarily focused on trivial elements such as swapping out buttons,
photos, and color schemes. While this can have some impact on take rate, there is a much larger future for data-driven advertising.
The real value is to enable you to create a one-to-one
message in real-time that offers a product to a customer who is "in-market" for that category of product at any given moment.
Get Real About Performance
Performance-based advertising is the future of our business, and if done right, everybody wins. If you can understand a user's intent, you can deliver advertising that feels like
a feature. A better user experience will lead to higher clicks, and thereby increased advertiser ROI. As ROI increases, publishers have the ability to increase rates without a negative advertiser
reaction. This creates a vicious cycle in the right direction.
Choosing to use optimization technology is an IQ test for advertisers. For publishers, it will rapidly become de rigueur.
Advertising execs often refer to the last mile problem: how to deliver the right creative to the right audience. There is in fact a last mile problem in advertising, but these execs got it
wrong.
The last mile is optimization to help advertisers maximize ROI and does not end with marketing at all.
It ends in the CFO's office.