3 Real-Life ‘Programmatic’ Executions & What They Mean To You

Firstly, as a quick refresher, the terms ‘big data’ and ‘programmatic’ sound more complex than they are! In my last article, Why Do Big Data & Programmatic Marketing Actually Matter?, I described how big data can simply be thought of as ‘more data,’ and that having more data makes us smarter marketers.

Using more data can be difficult to do, and so, the way to use more data is with an approach called ‘programmatic.’ Removing all the complexity and BS from the term, at its highest level, ‘programmatic’ just means that you are writing some logical rules that combine bits of that data together.

Simple, right?

It Means You Don’t Have To Guess Anymore

The rise of media exchanges and RTB (real-time bidding) means that as marketers we no longer need to simply shout at crowds, but instead can talk directly to individuals.

emarketer RTB spending in US

It used to be common for a marketer to brief an agency or publisher about their audience by describing them with attributes such as age, gender, household income (HHI), whether they have kids, etc., and then go find sites that felt they had a similar audience.

If you wanted males between the ages of 18 and 25, you would probably call GQ or ESPN; if your need is moms with new babies, then probably iVilliage or Parenting.com; or if you wanted financial types, then Motley Fool or Yahoo Finance. Each of these would be perfectly reasonable sites to include on a media plan, but each one inherently includes wastage that drives down the efficiency of your plan. GQ, for instance, will also have some female visitors; iVillage, some dads, and so on.

With a site buy, marketers are guessing that they will be getting their ad in front of the right person.

But then, the guessing was reduced significantly. The site became less of a focus, and the individual became what mattered. Instead of hoping to find males between the ages of 18 and 25 on your selected publishers, marketers can now cherry pick who matches the criteria by using their own data, or 3rd-party data.

Not Getting Carried Away

This is a great shift, and RTB has changed marketing forever. I accept, though ,that marketers are on somewhat of a data high; they feel cookies and algorithms are all that matters today.

That is actually very wrong, and thankfully for the sake of us all, it turns out the context of the placement remains important, as does the creative message you choose to show (webinar recording: ‘Why The Creative Still Matters in Programmatic Marketing‘).

Real Executions With Programmatic

There are many cases where the use of big data and a programmatic approach are making a real difference already.

A.  Programmatic Site Retargeting

Know it or not, the most dollars being spent today using data are with site retargeting – in this case, the data is that of an individual visiting a site. As we also reviewed in the last article, though, most marketers don’t understand all the data they have, and are not using it in their decisioning, meaning they are not being smart.

Dedicated site retargeting companies are incentivized to make you spend more, not to ‘spend the right amount.’ They are not interested in encouraging the use of big data because it will tell you that many people shouldn’t be in your cookie pool.

As an example, if an individual is visiting a luxury car brand, but is also searching for ‘bad debt loans’ on Google, why retarget them?

If an individual is looking at the careers page of a retailer, they want a job, not your products, and so why retarget them, given they aren’t looking to buy?

If they are your fan on Facebook, why use retargeting impressions to talk to them, too – or, given they are a fan, they must be super-engaged, so perhaps double your investment in them.

Facebook Targeting Options

This is big data, or more data, in action.

B. Search Retargeting

Another great example is search retargeting. In order to process billions of keywords every month, we construct rules that help determine which individuals are relevant and what value they have to an advertiser.

Programmatic rules might help us determine that someone searching for ‘vacation,’ ‘champagne delivery’ and ‘burberry’ are likely to spend more on a travel site than someone searching for ‘vacation’ and then browsing sites for credit cards for people with bad debt.

Hopefully you are seeing the trend here, more data makes you smarter, and means you can cut out the wastage from what you are doing.

C. Programmatic Look-A-Like Targeting

The same applies for common techniques such as look-a-like modeling. To understand the difference, think of search retargeting and programmatic site retargeting as ‘reactionary’ – someone does something, you respond – whereas look-a-like is predictive, you are using lots of data to decide who else will respond well to the message a marketer wants to show.

As an example, you could take a site like Bed Bath & Beyond. If an individual buys a lot of basics in one go and uses a ‘new mover’ voucher, then we know they just moved into a house and are a desirable target customer.

We could then look at everything else we know about that person (gender, search terms, location, age etc.) and find more people who share those attributes. Those people who overlap are very likely to respond well to the Bed Bath & Beyond messaging.

There is so much data that can be collected about individuals that a programmatic approach is being used to crunch it all and work out what makes the most sense.

And So…

Programmatic and Big Data might be new buzz terms within this industry, but many smart tactics are using them already. If you are buying display today, chances are some of the tactics you have live use this way of thinking.

But importantly, know that they highlight smarter spending, not just more ways to spend more. And so, be sure your partners are incentivized to work with you in that way.

Opinions expressed in the article are those of the guest author and not necessarily Search Engine Land.

Related Topics: Channel: Display | Search & Display


About The Author: is the Chief Strategy Officer at Chango, the solution to programmatic marketing and "big data", and is based in San Francisco and London. You can follow him on Twitter @DaxHamman.

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