With the rise of big data and rapid adoption of programmatic advertising, it is no surprise that Forbes declared 2014 as the year of digital marketing analytics.
If 2014 was the year of digital marketing analytics, than 2015 and beyond would see a focus on machine driven prediction and decisioning tools. Early adopters of this approach automatically have a strategic advantage over competitors. Why? You ask. Here's why.
Programmatic is Here to Stay
What was once relegated to the fringes of digital ad buying and left-over low-quality ad space inventory, programmatic (automated digital ad buying) now accounts for about 50% of digital display ad spending in the US and it is expected to account for 63% of spending or $20.41 billion by 2016. Programmatic is growing so rapidly that it might soon take over TV ad buying as well.
Most digital ad programmatic activities take place through Real Time Bidding (RTB) on open exchanges. The ever growing access to data (everything from billions of social media interactions to millions of e-commerce transactions) means that brands and agencies with the right data modeling tools can identify and target ads and offerings to ideal customers, thereby optimizing ad efficiency and improving conversion rates.
Programmatic is not a fad, it is here to stay because it makes sense and generates serious revenue. It is the fastest growing segment of digital marketing because automating digital transactions creates opportunities for display ads to be shown at the right time to the most interested audience or individuals.
While digital marketing analytics is the measurement of digital marketing activities, machine driven predictions take it a step further by employing machine learning technology to determine the optimal course of action in a given situation.
In programmatic activities, decisioning in real time is crucial. Whoever makes the right decisions in split seconds, wins the game.
The next phase of programmatic domination will be the expanding use of real-time machine driven prediction to more accurately predicts audience segments most likely to act on any given intent.
Look-Alike Modeling Drives Conversions
According to the Digiday “State of the Industry Report” on audience targeting; a survey of leading digital advertisers revealed that less than half employed lookalike modeling; despite the fact that 40% of respondents in the same survey claimed to see 2 to 3 times improvement in performance from look-alike modeling. Even more surprisingly, 25% of digital advertisers have no idea what look-alike modeling is.
An Oracle BlueKai/Datacratic case study saw up to 1,000% lift increase in conversion with lookalike modeling. With such high performance rates, why are many digital marketers still out of the loop on this?
Quite simply, many are not yet aware of the power of machine driven behavior data modeling, in this case predictive and lookalike modeling. And of those that are aware, many have a misconception of lookalike modeling as too complex or too capital intensive. However, lookalike modeling is increasingly accessible to brands and agencies of all types, sizes and industry verticals; thanks to data modeling solutions bolstered by infinite supply of big data and advances in adaptive machine learning technologies.
If you are ready to harness the power of lookalike modeling, the behavior data modeling solution you employ will go a long way in determining your success. Here are five things to look for in a winning data modeling solution:
(1) Access to Trusted 1st & 3rd party data sources
A solid look-alike modeling solution should have compatibility with a Robust DMP (Data Management Platform) with access to sufficient data sources.
Datacratic's lookalike modeling solution is completely embedded within leading DMP platforms and the worlds largest 3rd party marketplace. The Datacratic Behavior Prediction API allows brands to work with trusted and ethically sourced 1st & 3rd party data sources.
With privacy concerns at their highest it’s important to verify the lineage of the data you use.
(2) Leverages Time Series & Behavior Sequencing
It is one thing to know what a person has done leading up to a conversion or click but it’s not quite enough. You need to know what they did, in what sequence and within what period of time, in order to target your audience with high accuracy and be able to focus on the audience members that are highly likely to convert based on their behavior.
Datacratic Behavior Prediction API offers information on your customer's sequence of action and activities leading up to conversion. This is vital information to aid in continually optimizing and improving targeted campaigns and messages.
(3) Provides Visibility into the “Black Box”
Don’t trust mysterious algorithms. Make sure you can see into the “black box”. Datacratic solutions deliver visualizations and reports to showcase how your models are performing. It is not only important to know what works, its equally essential to have transparency and knowledge of how the modeling solution is working.
(4) Applies Adaptive Machine Learning
Machine learning is a branch of artificial intelligence and is much more than using simple decision tree logic. Datacratic’s Machine Learning Database’s (MLDB) process of learning, adapting and decisioning discovers data points that may be missed by the human eye or even ignored through decision tree logic. MLDB separates signal from noise and uses adaptive learning of past and present actions from an audience to predict the future and produce more accurate decisions which are free from bias.
(5) Domain Expertise in Marketing Technology
The Datacratic team (from software developers to the management board) have a well rooted domain expertise in the digital advertising industry. It is not enough to just know and understand data modeling and technology but a lookalike modeling solution must be backed by team members with in-depth knowledge of the marketing and advertising industries.
Datacratic’s team of business experts and data scientist have a strong pedigree in both advertising and machine learning technology and understand the needs of brands and agencies in implementing technology to improve advertising performance. Datacratic behavior modeling solutions come with extensive team support.
In conclusion, results from behavior modeling would only be as good as the sources of data and power of the modeling solutions used to understand this data. These five aforementioned points are key to success on a machine driven modeling solution.