A Brief History of Programmatic
December 27, 2017
The programmatic advertising industry is growing at unprecedented rates – according to eMarketer year over year spending has increased approximately 30% and it is set to top $39.10 billion in 2018 in the US alone!
Automating the media buying process via programmatic advertising has become the ultimate solution to improve digital campaign ROI and ensure strategic business goals are met.
How Did Programmatic Come About?
Programmatic advertising uses technology to buy and sell ad inventory via an automated and data-driven process, across channels and formats including display, video,native, audio, CTV and digital outdoor ads.
In the early stages of the internet, buying an online ad was a simpler process, starting with a relationship between publishers (sellers) and advertisers (buyers).
Advertisers wanted to reach their target audience to influence users, such as to purchase, build brand awareness and affinity or promote an event. Publishers provided a web property made up of intriguing and useful content to attract an audience the advertiser might want to reach with their campaigns. Agencies helped advertisers achieve their marketing goals and connect with their target audiences. It was up to media buyers to create media plans that targeted the right people and communicate with publishers that had access to those audiences.
As the internet grew, it caused a massive ad oversupply that resulted in a significant amount of inventory being left unsold and unmonetized. Publishers grew faster than advertisers, making it hard for buyers to consume available ad supply.
Then came ad networks, which categorized a publisher’s unsold ad inventory so it was easier for buyers to access and include it in media campaigns. Ad networks split ad inventories into two categories: premium and remnant. Premium ads were sold via direct relationships between buyers and sellers, while remnant ads were those left unsold or leftover, which publishers sold via ad networks.
Multiple Technologies, Single Infrastructure
Ad networks created an environment where agencies had more than a single channel to source ad inventories, but made the ad buying process more complicated for publishers. The solution? Supply side platforms (SSP), which provided publishers with a way to manage who gained access to ad inventory for resale to agencies and advertisers. SSPs help publishers maximize revenue earned via ad networks because they act as a middleman between the seller and the advertising networks. They give publishers more control over ad inventory and dictate how it’s sold and delivered to the ad network. SSPs create a bidding environment wherein publishers extract the most revenue possible from their ad inventories.
On the other hand, Demand Side Platforms (DSP) have emerged to help agencies and advertisers scoop up ad inventories, enabling them to manage media buying via a single platform. DSP and SSP technology evolved to create an infrastructure that integrated both platforms, allowing buyers and sellers to perform programmatic advertising with Real-Time Bidding (RTB).
RTB Captures the Right Audiences in Real-Time
Before RTB, advertisers purchased impressions in bulk, making it hard to differentiate audiences from each other. For example, if an advertiser wanted to sell a product to a market of people aged 50 and over, they could only tap an impression range that included audiences in the 20 to 30 year old range (not exactly efficient, right?)
RTB created an environment in which advertisers can display ads to a particular audience based on data points related to that audience. Using the example above, a RTB would help the advertiser programmatically display the ad only to its target audience of those 50 years and older, instead of losing impressions on uninterested audiences within the impression range. RTB uses data and machine learning to ensure ads are delivered to the right people at the right time.
Programmatic advertising and real-time bidding helps advertisers effectively create campaigns and respond accordingly to real-time behavior analysis based on parameters and filters that administrators can adjust as needed. This helps advertisers craft campaigns that respond quickly to shifts in customer behavior, demographics, traffic and costs.
A Programmatic Advertising Case Study
How Programmatic Maximizes Digital Campaign Effectiveness
Programmatic advertising helps advertisers consolidate the media buying process to funnel ads across a number of relevant content channels to maximize a campaign’s effectiveness. Doing so requires identifying the right data and using it effectively. Machine learning provides advertisers with the ability to work at a much larger scale and much more efficiently, allowing them to focus more on developing effective campaign strategies and reviewing reports. Effective marketers are making use of the data available to them via technological advancements to reach their target audiences.
Acuity platform is powered by a proprietary machine learning algorithm and employs strategic digital advertising solutions that cater to advertiser needs and help them connect with their most meaningful audiences intelligently.
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