The IAB UK recently revealed that over half of all brands are buying mobile inventory using programmatic media buying technologies, but less than half (45 per cent) understand how the technology actually works.
Not too long ago, search engine marketing was an “experimental” marketing channel that only a handful of companies were willing to test out. However, somewhere around 2007, search became a primary source of revenue for most online businesses and the introduction of Product Listing Ads moved search marketing to the forefront of their online marketing strategy. Today, you’d never meet an e-Commerce company who isn’t deeply invested in their search strategy.
As we enter a major turning point in the world of digital marketing, e-Commerce brands need to understand exactly the why, what and how to programmatic.
Why is “programmatic” so confusing?
Programmatic advertising is simply the automated process of buying and serving of targeted ads, using data-driven systems. The ultimate goal is for the advertiser to reach the perfect shopper, at the right place, at the right time and with the right message.
The programmatic industry is constantly growing and with it, a slew of confusing advertising tech jargon has emerged making ‘Programmatic Advertising’ a catch all phrase for a few different concepts:
- ‘Real-time bidding’: the auction-based system whereby a data-driven software systems bids on advertisements in real-time.
- ‘Retargeting’: using a pixel or cookie to “follow” someone who visited your site with ads to bring them back (very common in e-Commerce).
- ‘Programmatic direct’: when a buyer negotiates an ad buy upfront, usually for a set price, but executes the deal with programmatic technology.
In the retail world, the path to purchase is becoming increasingly complex, but marketers are now acknowledging the many touch points present in the path to purchase, each of which have their own contributing effect on the consumer’s decision to buy.
However, this process is extremely hard to measure. That is why most major retailers manage their programmatic advertising work with agencies, as they are equipped with the right software, data and experience to provide results without the overhead.
That being said, it’s still crucial that e-Commerce brands understand the data that is powering their programmatic campaigns and whilst for some, search marketing has become part of the company’s marketing DNA, many advertisers are comparatively lagging when it comes to incorporating programmatic into their marketing strategy.
The areas that retailers need to ensure they give enough attention to are:
- First-Party Data
Retailers should be proactive about aligning their marketing teams around data and programmatic initiatives. Consider creating a Data Task Force responsible for locating and consolidating your data stores—such as CRM data, browsing data, email segments, app downloads, conversion data, rewards members etc.—into a DMP so that your agencies and partners are able to utilise it in real-time.
- New or Third Party Data
Modelled audiences are great for targeting shoppers who have not considered you before, but are (hopefully) likely to do so. However, if your goal is to hit shoppers who have previously expressed interest in purchasing a product, then you may want to focus on observed audiences, who consist of people who have actually engaged with a product page or purchased a specific item before.
Another way to think about this data is by looking at shopper interest vs. intent. Interest data may reveal that John read an article about “The Best Golf Clubs of 2015,” but intent data shows that John was shopping for Irons and Drivers this morning.
These distinctions may not be immediately obvious; it’s important you ask your agency to elaborate what kind of data they are using, and ensure it’s aligned with your online marketing goals.
5 simple questions to ask your agency:
- Source: Where is this data from?
- Recency: How often the data sources are updated? Monthly? Weekly? In real-time?
- Uniqueness: How much of this data overlaps with other data sets available?
- Modelled vs. Observed: How much of this audience is modelled, and how much is based on observed shopping intent?
- Interest vs. Intent: Is this data based on consumer interest (i.e. reading relevant content) or purchase intent (i.e. browsing specific products).
By Marie Dalton, Marketing Director at Connexity