Although 94% of companies agree that online personalization is “critical to business performance,” only 4% of companies report personalizing the website experience well for their visitors.

That data, culled from an eConsultancy report written in association with Monetate, underscores an important problem: Big data presents a big opportunity, but companies are having a hard time getting the most out of their analytics.

“There are a lot of things that can get in the way of understanding data internally,” said Colton Perry, Monetate’s VP of partnerships, during the recent “Hitting a Personalization Home Run With Data” webinar. “There are IT roadblocks, legacy technologies, lack of budget, lack of staff, disparate data sources, and the inability to translate data into action.”

Perry, who presented the webinar with Tyrone Anderson, VP of solutions engineering and consulting at BlueKai, added that in order to get more bang for your analytics buck, it’s important to understand which types of data are available, where they come from, and how to use them effectively.

According to Perry, there are four main types of data your organization can leverage to create personalized experiences.

1. First-Party Data

This is explicit data that’s being collected directly from your customers by your organization. Perry noted that this data is based on customer behavior, and actions customers take on your website, as well as their interests, preferences, and affinities. This data helps a company determine which products are most popular with visitors, as well as the types of content they like and interact with.

2. Second-Party Data

While second-party data is similar to first-party data, it comes from a source outside of your organization. For instance, your company might share data with its partners, and combine it with first-party data, in order to develop a clearer picture of customers.

3. Location Data

This data is based on what your organization knows about where a visitor or customer is located, which can be indicative of a lifestyle or regional preferences. Knowing whether a visitor is on a smartphone or a home PC, in addition, can help determine the type of experience that you should deliver online.

4. Third-Party Data

Third-party data is rented or purchased from a provider in order to enhance the insight available to a company at the point of interaction with a website visitor. This data includes demographics, geographics, lifestyle and interests, in-market status for different purchase categories, and more.

“Really the power of third-party data comes when you overlay it with location data,” Perry noted. “It can be incredibly useful and interesting. You can look at a visitor’s proximity to a physical location. So let’s say a visitor on an iPhone is near your store. Why force them to use a store locator? Why not combine their location with your brick-and-mortar locations to bring up the store closest to them? Be proactive by using your data to help serve them.”

So once you have all of this data, what’s the next step?

Perry pointed to examples from the American Red Cross, which could leverage different sources of data to create segments and respond to visitors based on information that reveals visitor preferences for donations, as well as their location.

In these examples, the Red Cross delivers different homepage content for those visitors located near Army bases (left) versus those located near Tornado Alley (right). These relevant experiences more accurately reflect and respond to visitors’ anticipated interests, which is a prime way to turn data into action.