How to Avoid Data Overload in Web Personalization

How to Avoid Data Overload in Web Personalization
How to Avoid Data Overload in Web Personalization

The internet of things (IoT) and Big Data have added a whole new dimension to digital marketing and web personalization. The more people use their devices for check ins, tracking their activity and data, and surfing the web, a larger set of data is created.

The issue then becomes not about the amount of data created, because we have more than enough available to personalize any website, but how to not become overwhelmed by the sheer volume of the data, and analyze and categorize it into usable data.

So how do we avoid this data overload, and make big data useful for web personalization.

Analyze Your Current Website

Before you embark on any web personalization campaign, it is important to take a look at your current website and the data you are already gathering, even if you are doing so passively at the moment.

Your domain and where it is located and how the analytics are structured can tell you a great deal about how far you have to go to achieve optimal personalization. Are you running on a WordPress platform? What plugins or tools are you currently using to gather data about your customers? Are you using Google analytics or a more robust program?

The ability of your users to create an account they can sign into every time they return to the site not only makes things more convenient and easier for them, but it makes data gathering and the amount of data you receive greater as well.

Allowing a user to register or log in with a social media account enables you to gather their public information from their profile as well. This can provide you with a great deal of data: age, location, marital status, likes and dislikes, and interactions they may have with your competition.

Of course, this adds data to the already large pile you have gathered. This means you must decide what data is relevant to your website personalization efforts, and what data you can ignore.

Analyze Social Media

Who are your followers on social media? These are questions that go beyond simply what their names are or where they are from. What income bracket are they from? Do they own or rent? What is the gender mix, and age range you are reaching?

The most important of these questions is if you are reaching the target audience you were aiming for. Does the follower you are reaching on social media match your marketing persona?

You can find all of this information through the analytics of the social media network yourself, including Twitter, Facebook, and others. You can also use programs like Tweepsmap for Twitter and Hootsuite and others for Facebook and other networks to gather and categorize this data.

Much like the data you have gathered from your website, you need to combine and categorize that data to make it usable. What do you really need to know about your customers, and what information is not nearly as relevant?

Analyze Your Goals

What are you trying to accomplish with personalization? Generally speaking, the goal is to meet the user where they are, and shorten the buyer’s journey by directing them to what they want or need without a lot of needless searching and discovery.

However, there are two things you need to target as precisely as possible. First, what is the marketing persona you have created, and do the customers you are attracting the same? If they are not, either your targeting and messaging are wrong, or perhaps you have not chosen the correct target. Either way, you need to shift these efforts before you work too hard on personalization.

The second question is what information you need to reach that persona. If you are selling shoes, directing the person to the appropriate landing page may involve knowing their gender, so you can direct them to men’s or women’s shoes initially, and let them search from there.

At the same time, in the same scenario knowing the web visitor’s location will help you direct them to the shoes popular in their region. While socks and sandals may be popular in the Northwestern United States, the same shoes will not be popular in New York City or Atlanta. Winter boots will not sell as well in Phoenix as they do in Colorado.

No matter what your product or who you’re target audience is, certain information will help you personalize their journey to buying your product, while other information will not. Only collect and analyze the date you need to prevent overload.

Web personalization is one of the keys to successful marketing, but the data available from the Internet of Things and other sources can be staggering. Gathering only what you need and analyzing it properly can help prevent data overload, and make your web personalization efforts more successful.