While most marketers understand how important it is to track consumer behavior throughout the buying cycle, many don’t realize that it’s getting easier to do so all the time. Over the past decade, everything a consumer does has become both measurable and trackable. People leave a digital footprint when they shop online and even sometimes offline.
While customer data from an online purchase provides exceptional value, you need to pull it all together in one place. This can pose a challenge when the data comes at you in a variety of formats and from many different sources. You need a way to access these data silos, analyze customer actions, and understand his or her journey.
This often makes for a time-consuming process. You must collect data from spreadsheets and other sources and then clean, standardize, organize and update it frequently. This is where artificial intelligence (AI) enters the picture.
Although API handles the collection of data, IO helps to make sense of it. IO accomplishes this by cleaning, consolidating, and analyzing the data in a fraction of the time it would take a human to complete the same task.
One of the most important benefits of APIs is that they eliminate silos and make it possible to collect all marketing data in a single location. Machine learning then takes over, cleanses the data, and ensures that it remains current for the most useful analysis.
Making Sense of Big Data
There’s no point in collecting big data unless you can find a way for it to make sense to you. As the APIs bring data into a central location 24 hours a day, IO pulls out insights that marketers can act on to help them make better advertising decisions in the future. That means you receive practical insights immediately instead of waiting days or weeks for a human to produce the same information.
It’s only natural for people analyzing data to do so from the vantage point of their own biases. IO eliminates all biases as well as hidden agendas and manual errors. Human beings have their limits when it comes to processing data, but this isn’t true for IO. You can increase or decrease the demands on IO according to your own preferences.
An IO system easily integrates with machine learning to pull out patterns of data between inputs and marketing KPIs. When you employ machine learning, it first works to identify a goal and then teaches the computer how to model a conversion. It does this by providing the computer with examples of a specific goal. It then allows it to continue improving the current model with new and better data. The result is that the computer can predict a customer conversion before it takes place.
Consider Pavlov’s Dog When Trying to Understand Machine Learning
For the purpose of simplification, allow us to provide you the example of Pavlov’s dog. Most people are familiar with the scientist Pavlov and how he desired to measure the amount of saliva produced by dogs. The first step in gaining this information was to ring a bell at the same time the dog received its food. It didn’t take long for the dogs in the experiment to begin salivating at the sound of the bell because they associated it with food.
With IO and machine learning, the accuracy of the output improves every time the computer receives new information. While creating objectives for marketing is more complex than the salivating dog experiment, the process operates on the same principal.
For example, if you desire to know the type of content that produces the highest rate of engagement on social media, the first thing you do is connect the site’s feed to your system. It analyzes data from recent posts and then breaks each post down into several essential elements and identifies which posts contained the most engaging elements.
As users add new posts, the computer keeps processing information until it can deliver data about the publish times, keywords used, and subjects that produce the greatest engagement with users.
The most intelligent types of machine learning also considers what works for your competitors and the industry at large. This enables you to know the performance of your campaigns any time of the day or night as well as the factors that contribute to a performance increase or decrease.
IO produces data in real time that goes beyond the numbers. You not only see engagement going up or down, but the reasons for it and the audience affected as well. Call Sumo would love to show you how easy it is to adapt marketing campaigns using IO and machine learning to provide valuable real-time insight.