It’s the trifecta of digital marketing; predict who will buy, what they’ll buy and when. If it seems like an unrealistic goal, think again. Digital marketers who can collect and analyze intent data are able to make these kind of predictions.
Intent Data: Collected data that indicates intent or future action
While traditional digital marketing techniques create general brand awareness, intent marketing focuses on consumers who have already conveyed an intent to make a purchase. By analyzing intent data, marketers can target prospects with powerful, personalized messages and ads at exactly the right time.
Intent data includes web page visits, search queries, social engagement, content downloads, video views and more. Both first and third party data signals can be analyzed to understand customer intent.
First Party Intent Data: The activity a company captures on its own website or application logs. This data contains highly predictive buying signals because the content is relevant to the purchase decision, such as pages viewed by a prospect, which links they clicked on, and how long they spent on each page.
Third Party Intent Data: Data collected by publisher networks either at the IP level, or through user registration and shared cookies. These sites track the articles a user reads, content they download, and site searches.
A recent Forrester survey suggests marketers realize the impact intent data can have on the effectiveness of their ads and messaging. However, many digital marketers struggle to collect and analyze intent data for targeted value.
- 81% of survey respondents agree that analyzing customer data is a valuable way to predict consumer intent
- 78% believe using intent data improves the relevancy of ads
- 64% believe that combining site-level data and search behaviors can increase the ability to reach audiences across the customer funnel
- 49% have limited ability to integrate first and third party data
- 54% of respondents are unable to integrate intent data into targeting technology
Analyzing Intent Data for Predictive Marketing
According to ClickZ, there are several important steps to identifying customer intent using data analysis:
1. Identify where the customer journey begins
For transactions and shopping, determine if the customer path started on a search engine, email message, landing page, etc.
2. Collect the right data
Capture data from all customer touchpoints including data from websites, social channels, product views, purchases, downloads and clicks.
3. Study patterns
The use of a data analytics tool that can integrate all of your customer data touchpoints is the best way to investigate the patterns of your prospects. By doing this, you can optimize your ad spend by predicting where your customers are likely to go next and what message they would like to see. Integrating intent data in your digital marketing efforts is one way to help deliver relevant brand experiences and messages that influence potential customers. The key is cutting through the clutter of digital information with ads and content that are timely and relevant. Intent data can help get you there and ensure your brand is top of mind when a customer decides it’s time to buy.