Take a moment and to try imagine how much data mankind transmits over the internet every day. If it makes your brain start to hurt, you’re not alone.
Let me help with a few statistics.
Every day there are roughly 2 million searches on Google, 145 billion emails sent, and around 340 million tweets made on Twitter. All of this information and much more is stored on servers across the world, and some of it is available and useful to marketers.On a smaller scale that applies more to marketers, think about all of the transactional data that is available to a supermarket that uses a loyalty card. They collect all of that data and then use it to market to you in the future. Maybe the value is knowing which products you buy. Alternatively, maybe they want to track when your 30-day supply of a supplement runs out so they can remind you with an email to come back and buy more.This is just one example of how big data is being used by marketers today.
What is Big Data?
You’ve probably heard about big data in the news and wondered what exactly it is and how it applies to programmatic. Big data comes from traditional as well as digital data sources. These can be found inside your company and from external sources.Put simply, think of it as lots of data (on a monumental scale). A lot of the data was available to a lesser degree long before computers were around. Computers, databases, software, and more have allowed us to collect more data, many times faster than we used to think possible.This data can come from digital sources like behavior data collected across websites and social media networks. However, it also includes more traditional data like product transactions, loyalty programs, as well as data collected from the service side of your business like call centers and customer service reps.
What Does Big Data Look Like?
Big data can exist in the form of unstructured data like information from social media such as Facebook posts, Twitter tweets, metadata, and more. This data is usually text heavy and doesn’t fit well into a structured database.The next type of big data is multi-structured data. This is typically more of what you think would fit into tables within a database. Example of this type of data might include traditional financial information and audience demographics.
Fitting Programmatic Advertising and Big Data Together
One goal of programmatic is to take all of the relevant dispersed big data and bind it so it can be used for marketing. Once these multiple systems are bound together, it is possible to write rules that can make decisions based upon this data.This allows companies to combine this data and use it to create personalized marketing that is more meaningful to the audience. A good example would be combining demographics data with behavioral data from your actual website. Using these, you can create personalized ads that fit the age, gender, and behavioral information (what the person is searching for) to deliver ads that are relevant to that person. This type of data can also be used to retarget the person to bring them back to the website after their initial visit. This functionality is great; however, it is strictly reactionary in nature. The customer has to come to the site and make decisions before these rules can be acted upon. Big data can also be used for predictive analysis. This will allow companies to better predict what future visitors will do and give them advertising that is personalized, based upon that data.
Big data helps drive programmatic. Whether it’s analytics and behavioral data coming from your website or demographics from external sources, big data has answers. The key is for programmatic rules to improve how this data is bound and used in the future.