‘Real-Time’ Marketing: Still Not Quite A Reality

chris-ohara-updatedData-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Chris O’Hara, vice president of global data strategy and agency lead at Krux.

The term “real time” is bandied about in the ad technology space almost as heavily as the word “programmatic.”

Years later, the meaning of programmatic is finally starting to be realized, but we are still a few years away from delivering truly real-time experiences. Let me explain.

Real-Time Programmatic

The real-time delivery of targeted ads basically comes down to user matching. Here is a common use case: A consumer visits an auto site, browses a particular type of minivan, leaves the site and automatically sees an ad on the very next site he or she visits. That’s about as “real-time” as it gets.

How did that happen? The site updated the user segment to include “minivan intender,” processed the segment immediately and sent that data into a demand-side platform (DSP) where the marketer’s ID was matched with the DSP’s ID and delivered with instructions to bid on that user. That is a dramatic oversimplification of the process but clearly many things must happen very quickly – within milliseconds – and perfectly for this scenario to occur.

Rocket Fuel, Turn and other big combo platforms have an advantage here because they don’t need to match users across an integrated data-management platform (DMP) and DSP. As long as marketers put their tags on their pages and stay within the confines of a single execution system, this type of retargeting gets close to real time.

However, as soon as the marketer wants to target that user through another DSP or in another channel, user matching comes back into play. That means pushing the “minivan intender” ID into a separate system, but the “real-time” nature of marketing starts to break down. That’s a big problem because today’s users move quickly between channels and devices and are not constrained by the desktop-dominated world of 10 years ago.

User matching has its own set of challenges, from a marketer’s ability to match users across their devices to how platforms like DMPs match their unique IDs to those of execution platforms like DSPs. Assuming the marketer has mapped the user to all of his or her device IDs, which is a daunting challenge, the marketer’s DMP has to match that user as quickly as possible to the execution platform where the ads are going to be targeted and run.

Let’s think about how that works for a second. Let’s say the marketer has DMP architecture in the header of the website, which enables a mom to be placed in the “minivan” segment as soon as the page loads. After processing the segment, it must be immediately sent to the DSP. Now the DSP has to add that user (or bunch of users) to their “minivan moms” segment. If you picture the internet ID space as a big spreadsheet, what is happening is that all the new minivan moms are added to the DSP’s big existing table of minivan moms so they are part of the new targeting list.

Some DSPs, such as The Trade Desk, TubeMogul and Google’s DBM, do this within hours or minutes. Others manage this updating process nightly by opening up a “window” where they accept new data and process it in “batches.” Doesn’t sound very “real-time” at all, does it?

While many DMPs can push segments in real time, the practical issue remains the ability of all the addressable channels a marketer wants to target to “catch” that data and make it available. The good news is that the speed at which execution channels are starting to process data is increasing every day as older ad stacks are re-engineered with real-time back-end infrastructure. The bad news is that until that happens, things like global delivery management and message sequencing across channels will remain overly dependent upon how marketers choose to provision their “stacks.”

The Future Is Dynamic

Despite the challenges in the real-life execution of real-time marketing, there are things happening that will put the simple notion of retargeting to shame. Everything we just discussed depends on a user being part of a segment. I probably exist as a “suburban middle-aged male sports lover with three kids” in a variety of different systems. Sometimes I’m an auto intender and sometimes I’m a unicorn lover, depending on who is using the family desktop, but my identity largely remains static. I’m going to be middle aged for a long time, and I’m always going to be a dad.

But marketers care about a lot more than that. The beer company wants to understand why sometimes I buy an ice-cold case of light beer (I’m about to watch a football game, and I might drink three or four of them with friends) and when I buy a six-pack of their craft-style ale (I’m going to have one or two at the family dinner table).

The soda company is competing for my “share of thirst” with everything from coffee to the water fountain. They want to know what my entry points are for a particular brand they sell. Is it their sports drink because I’m heading to the basketball court on a hot day, or is it a diet cola because I’m at the baseball game? The coffee chain wants to know whether I want a large hot coffee (before work) or an iced latte macchiato (my afternoon break).

This brings up the idea of dynamic segmentation: Although I am always part of a static segment, the world changes around me in real time. The weather changes, my location changes, the time changes and the people around me change constantly. What if all of that dynamic data could be constantly processed in the background and appended to static segments at the moment of truth?

In a perfect world, where the machines all talked to each other in real time and spoke the same language, this might be called real-time dynamic segmentation.

This is the future of “programmatic,” whatever that means.

Follow Chris O’Hara (@chrisohara) and AdExchanger (@adexchanger) on Twitter. 

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  1. Another great post, Chris – and now I know what to send you at Xmas (beer not wine:-))

    On the issue of realtime: for many, many products – realtime is not the key. The key is the base intelligence. Getting a MiniVan ad to a Mom as she hits her next digital destinaton is of less import (not to mention the creepy, primitive retargeting-like reaction this tends to get) and more about how to map to a logical, non-linear buying journey for a car/van – which means we can breathe a little and do our processing and analysis to understand HISTORICAL behavior. The biggest problem within the eco-system is the definition of intent and the ability to understand this Mom is mid-funnel because we have the ability to understand when she started the process. Then again, the cookie-based architecture limits history – which is why device-based is a much better way to go when a client is interested in the journey of considered purchase products. I like to think we are getting smarter and more realtime in our analysis and more effective at our executional deployment. Keep it coming, Chris!

  2. I really appreciate how well you’ve used regular language to explain seriously technical processes. It seems to me that of all many acronyms, the DMP blurs the line between adtech and martech the most right now. I mean that as a positive.

    I’m curious if you’ve seen or conducted a test that demonstrates how incorporating local weather or location has improved a campaign’s outcome. I’ve been trying to find data on that but so far have not beed successful.

  3. This is correct, and this is why it only makes sense for DMP’s to pivot, and have a buying arm and element (competing directly with their DSP partners), and have both a DMP and DSP, similar to what Turn, Quantcast, and many others have done for a long time? You can only do real time segmentation if you can control/understand/manipulate/model the data and the media.

  4. Great piece. Among the things that need to happen: the DSPs need to expand their creative macros beyond ${WIDTH} and ${HEIGHT}. There are currently very limited capabilities to pass rich segment and viewer ID information to the ad creative, which is the final execution step in the real-time stack you illustrate. Because after all, even if a person can be ADDED to a segment in real time, it does little good if no other system can RETRIEVE that segment (via macros) in real time as well. So you end up with perhaps several siloed systems, some with their own real-time CRUD capability, but limited to no ability to talk to one another.

    Of course, many DSPs are reluctant and/or outright refuse to add the means to pass richer data to other systems, as it pokes holes in their walled gardens. C’est la vie…

  5. Excellent article, Chris.

    From what we see here at Simpli.fi , data recency definitely drives performance across site retargeting, search retargeting, and geo-fencing campaigns. We typically serve between 23% and 25% of our impressions with data that is less than 1 hour old, and see that the KPIs for that data are the best. We serve approx. 50% of impressions with data that is less than 1 day old…and that also outperforms older data.

    • Frost –

      are you breaking those numbers down by type of product? Interested in knowing the composition of the product set – considered purchase v CPG v…


      • Hi Charlie- We haven’t broken the numbers out by type of product, but easily could. Typically our algorithms optimize to data recency on a campaign by campaign basis as opposed to type of product. Later this week we’ll be posting some additional info on our blog about how data recency impacts performance. Thanks!