We live in a time when data has emerged as one of the most valuable resources available to businesses. Companies with good data are able to fuel their machine learning models, make critical predictions, and ultimately deliver greater value to customers. In the process, they can also optimize their operations, lower costs, and differentiate their business.
But to realize these benefits and compete with the likes of Amazon, Facebook, and Google, companies need access to huge datasets. And while there’s certainly no shortage of data available, the problem most companies face is that they only have access to data from their own customers. As a result, they often turn to third-party data to fill in the gaps. In 2018, for example, companies spent an estimated $19 billion on third-party data in the United States alone. Unfortunately, as we’ll see, using third-party data isn’t always a great approach.
When you purchase third-party data, you’re buying data from providers with no direct connection to your customers. Instead, data providers simply collect demographic data from a variety of sources, such as websites and social media channels, among others, and aggregate it into the types of audience profiles they think you’re looking for. And while there’s nothing wrong with purchasing third-party data in theory, in practice doing so can be problematic for a number of reasons. These include:
Practically speaking, while using third-party data has long been viewed as a necessary way to get ahead, doing so is fraught with considerable challenges.
If you want your business to compete with the tech giants of the world, you’re going to need data. The trick, of course, is finding a more responsible way to source that data so that you know that it’s of the highest quality without raising security or privacy concerns, or putting you at risk of running afoul of regulatory requirements.