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Use “Interest Scoring” to target like a bull

A big part of having an Engagement Platform is that you can target leads very precisely and dynamically based on a host of data coming into the platform. Despite this many clients still have not utilized the full potential this targeting can offer. Nurture Programs are a great place to take advantage of this targeting (Nurture is automated communication streams).

 

The challenge is how to know the interest for leads in their Engagement Platform. Most often clients do not know the interest of most leads in their database because the client does not have a good mechanism to gather this interest information.

“Web Interest Scoring” (Interest scoring based on Web page visits) provides a solution to this challenge.

The general idea with Web Interest Scoring is to create a scoring model that scores interest for the purpose of identifying the leading interest for a lead (no pun intended). As an example say the company is Apple (completely made-up example). I may visit various web pages but I visit the Apple Watch pages far more than the other pages. If Apple was scoring interest by product interest my Apple Watch score would be very high – higher than the scores for all the other Apple products. So Apple might decide to focus communications with me more on the Apple Watch.

How to setup interest based scoring

Here is the 1-2-3-4-5 on how to create interest scoring:

  1. Select interests
  2. Organize pages by visits
  3. Assign points
  4. Build interest scoring model
  5. Reap the results

Let’s explore each of these steps in a bit of detail.

1. Select Interests

How you might organize interest usually varies by company. In the Apple example  above interest was organized by product. So in this example interest could be Mac, iPad, Apple Watch, etc. Another example could be a business-to-business Healthcare company that organizes interest by types of customer such as Hospital, Clinic, Individual Doctor. How you categorize interest will vary by client and much thought needs to go into how this should be for your company.

2. Organize pages by visits

Once you have selected your categories of interest, you will want to organize your web pages into these categories. Back to the Apple example all the Apple Watch web pages would indicate interest in the Apple Watch. If I look at the Apple website all the Apple Watch pages seem to contain the word “watch” so in this example it would be as simple as saying any visit to a web page that contains “watch” means we should score for Apple Watch. By the same token all the iPad page visits would be score for iPad interest. Etc. If the web pages are not named like this you can still collect all the web pages for each interest – page-by-page.

3. Assign Points

Then you will need to assign points for visiting the various interest pages. You can keep it simple and assign the same point value for all the web pages or you can get more granular if you want.

4. Build interest scoring model

Finally you will need to build your interest scoring model in your Engagement Platform. Once it is built and activated you will start to see leads in your database scoring up for various interests.

5. Reap the results

There are many ways to reap the results. Targeting is the use case we have already focused on. But you can use this interest information in many ways:

  • To target your nurture or other communications
  • To help assign to the correct team if you have a sales process
  • To give sales better visibility into interest for a lead
  • To get a better idea of relative interest in your current database and over time to spot trends

Interest changes

The point I want to make here is that interest can change rapidly. So say we follow the Apple example and three months later John visits several Macbook pages, Macbook interest might score up to the top and I would move John from the Apple Watch nurture to the Macbook nurture. You don’t have to do it exactly that way. It is a business decision for each client to decide how to act on this powerful information.

Expand beyond Web visits

This example focused on looking at web activity. I also want to point out that you can look at any activity and expand your interest scoring model accordingly. You can look at email activity, event attendance or anything else you want to add to your interest scoring model.

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