4 Ways Big Data is Changing the Practice of Advertising in 2016 & Beyond
Are you worried that you haven’t yet mastered all of the ins and outs, ups and downs, and quirky oddities of big data? Don’t fret. Nobody has it mastered 100 percent just yet. But you will need to get on board and begin a data initiative pretty soon so you won’t be left behind. Here are all the ways that big data is changing advertising, so you can be sure your data plans are on the right track.
1. Understanding the Difference in the Right Data, Not Just Big Data
The first thing to know is that not all data is even worth your while. You’ll need to assess what data is useful to collect and analyze, and what data can safely fall by the wayside. For example, is your marketing department stuffing your landing pages with umpteen form fields? If so, you’re merely upping your form abandonment rate unnecessarily. Similarly, there are many data points you can collect via social media, internal systems, from email, etc. that just don’t do you any good. Be selective. There are plenty of data streams available, but not all of them will up your game. They’ll just cause unnecessary complexity in your data analytics efforts.
2. Learning to Split Advertising Among the Various Available Channels
Similarly, the number of advertising channels available to you have increased exponentially, and more are bound to be on the way. Not only will you need metrics to assess the effectiveness of your traditional advertising venues (TV, radio, print), you’ll also be faced with assessing your performance with various online channels across platforms, devices, and venues. Over time, you’ll need to drop the ones that aren’t producing an ROI and hone the ones that are showing the most promise. Don’t let big data send you down so many pig trails that you never get anywhere.
3. Taking on Unstructured Data Streams & Marrying Those to Structured Data
Before big data, your advertising data fit nicely into a relational database like SQL. Now, you’ve got scads of unstructured data sets from email, videos, image collections, email, text documents, and much more. That means you’ll need a new type of data store, as well as new tools for analyzing your data. You’ll need to do your research on Data Lakes, NoSQL databases, Hadoop, and other alternatives for storing and analyzing your big data.
4. Leveraging Real-Time Analytics
The snail’s pace of traditional analytics also won’t cut it with big data. In order to make use of the potential of highly-targeted and personalized online advertising, you will need to be able to conduct real-time analytics on your incoming data. That means taking on tools like Spark, Kafka, etc. Some of these tools have a significant learning curve, but almost all of the most popular and potent big data analytics tools are available for free via open source software. This is creating somewhat of a talent shortage for workers capable of using these tools, so you’ll need to beef up your hiring practices and retention programs, as well.
Are you ready to learn more about how to get into big data and what it will mean for your future success in advertising? Big Data Week is your ticket. See the full lineup of speakers here.