Why behavioural marketing is important to differentiate online visitors to help and those to add to your newsletter.

A common practice on e-commerce websites is to try and get visitors' details such as their names, emails or phone numbers for further communication. Once stored in the company's CRM, they can be reached anytime through email marketing campaigns for example, and a conversion rate is expected at the end of the campaign. While this has a proven efficiency, let’s say between 1% and 5% when the campaign is successful, is this the only way to target your prospects and clinch sales on your website?

Among the information you can get from your online visitors, we can differentiate 2 categories:

• Explicit context is usually defined as data voluntarily given by prospects. It can be their name, address, email or anything you’ve asked them, in a web form for example. For e-commerce though, and with the usage of real time web analytics tools, we could extend the scope to data supposedly stable for a given prospect. The operating system of visitors’ computers or their country of connexion can change, but chances are it will be marginal or temporary for a given visitor.
• On the opposite, implicit context is more likely to change depending on the situation. Search terms or a session’s navigation history is expected to be different for visitors at every visit.

This implicit context is very important when dealing with e-commerce, because it lets us infer a lot about visitors’ state of mind at the very moment. Let’s look at these 2 examples:
Example 1: Car rental website
Real time analytics data:

• Visitor language: US English (Explicit data)
• Country of connexion: Italy (Explicit data)
• Search terms: “car rental roma” (Implicit data)
• Number of pages visited since session start: 6 (Implicit data)
• Pages viewed: Home Page, SUVs page, SUV #1 page, Compact cars page, compact car #3 page, compact car #2 page, Home Page (Implicit data).

What we can infer from the data:

• US English + Italy + “car rental roma”: it is probably the case of an American tourist visiting Italy.
• Then, having 6 visited pages during the session is a good indicator that the website has been acknowledged as a possible answer to the initial request. Yet, the good product has not been found so far.

Conclusion: high chances of immediate needs and no success finding the right choice. Contacting this person could be a good idea to help him find the product they need.

Example 2: General online shop
Real time analytics data:

• Visitor language: US English (Explicit data)
• Country of connexion: US (Explicit data)
• Search terms: [shop’s brand] (Implicit data)
• Number of pages visited since session start: 20+ (Implicit data)
• Pages viewed: Home Page, diverse categories, sales page.

What we can infer from the data:

• No predetermined needs
• Shop was known before the session, reputation visit

Conclusion: low chances of purchase, except maybe good value detected. But this person came from the brand’s reputation and browsed a lot of page. It would be very interesting to suggest a newsletter inscription to get notified of special offers.

Getting prospects’ explicit data can be very interesting when they’re not ready to purchase during the current visit. They can be added to your lead nurturing program, like your newsletters or white papers, to facilitate later possible purchases. But if you’re dealing with visitors with a determined choice, it is more important to facilitate the buying process than to ask for their information: a need has to be answered quickly, and moreover, if the purchase is done, you will have their explicit data anyway.

Learn how Butterflive can help you detect the interesting prospects on your website.