Understanding and Predicting Online Behavior
Jun 12, 2017, 7:21:00 AM
As a Digital Marketer in the CPM space, it’s important to understand the online behavior and content engagement of this very specific and finance oriented audience. This allows us to get the right message in front of the right audience at just the right time. Some of the questions we ask to help understand this behavior include:
- Do they search for CPM solutions on Google?· Are they using any form of Social Media?
- Which websites do they visit regularly?
- What type of content or messaging engages them the most?
Simple questions but gathering the data requires a series of tools and analytics
to provide the best predictive behavioral analysis.
Typical Behavioral Pattern
Many professionals spend most of their work day, well, working. Occasionally they will find time to check Facebook or other Social Media platforms, Google something related to a work item, receive a mobile notification on their smartphone and then at night browse news and catch up on anything missed during the day. So where in this general pattern of behavior is it okay to disrupt? If the markets’ digital behavior is based on self-knowledge and personal activities can we say hello?
It’s usually during the self-knowledge and research behavior (SKRB) we can communicate. There is an opportunity to connect with the target market during their personal time, but the messaging needs to be specifically tailored to the environment and source. Varying factors contribute to a user’s level of SKRB such as; email marketing, professional events, and conferences
, referrals, conversations and cold calls. The average person will research a topic before engaging in a conversation or committing to an outcome. These drive actions of research through search engines or professional websites. Where it gets interesting is in the search behaviors.
Predicting behaviors using Artificial Intelligence
Have you ever tried searching something on Google where you weren’t quite sure what your question should be? Have you noticed that your second search attempt Google helps to close that gap of uncertainty? Furthermore, if you have a Google account with stored bookmarks and history, you may see Google suggesting information or search results related to a collective group of searches conducted in the past. Similarly, iPhone users may notice Siri is getting much better at answering their questions and communicating the information desired. The ability of these programs to predict a result is based on a series of previous behaviors. This growth and development of machine intelligence or machine-learning artificial intelligence allow marketers to apply intent based marketing.
The relationship between search terms from an organic website visitor and the pages with which they engage tells us a great story of their intent. How they engage with the site also determines if the search they used was correct to find the information they were seeking. The pattern of behavior regarding search terms and pages visited allows us, Marketers, to target similar search behavior with the desired content. This ability to predict the users’ behavior using data and analytics has given Marketers insight that we didn’t have years ago. Google along with other tools provides the list of related searches that allows us to map the buyer's journey or interest path of web visitors. This ability to target users with the information they are truly seeking improves the digital User Experience (UX). Although the ability to capture this type of information can be deemed a lack of privacy, the Marketers intent with this technology is to get the right message to the right audience at the right time. This helps the audience find what they’re looking for faster and reduces the frustration of unnecessary ads and content that clutters the digital skyline.