Despite the name, lead scoring can be applied to leads, customers, clients, visitors, users, subscribers…in fact, anyone who interacts with your brand.
In its most basic form, contacts in your database are allocated a single score. As these contacts interact with your digital channels you can choose to add to or subtract from their score based on the actions they take. For example, you may choose to add 5 points to a contact’s score if they watch your latest video for more than 30 seconds, but if they only watch for 10 seconds, you may choose to add only 2 points. Higher scores tend to indicate greater interest in your brand, lower scores indicate lesser interest.
Scores can be used to segment customers into different audiences. For example, using the basic scoring system outlined above, you may create three segments and use these to target contacts with different messaging:
0-10 points Low interest Messaging that introduces your product
10-20 points Mid interest Messaging that helps convince contacts to purchase
20+ points High interest Messaging that focuses on conversion
This example uses a single score, but the real power of lead scoring comes from applying multiple scores to each contact. Scores can be used to measure things like interest in a particular product or product category, preferences for particular colours or sizes and even how closely a contact matches the profile of your ideal customer. This information is invaluable.
Scores are usually used in two ways:
- To trigger messages when a score rises above a threshold
- To segment contacts and personalise content based on scores
This is exciting stuff: you can use scores to make your content incredibly relevant for very little cost. However, there are a few things you need to bear in mind before you get too carried away:
What to score
One of the difficulties is working out how many points to allocate to each contact interaction. Do you add 10 points, 5, 3, 4? The truth is that it depends on a few things: how important the interaction is, how many points are allocated to a contact when they first enter your database, score decay and how you’re going to use the score.
Data set size
Using multiple scores to capture more granular insights causes another problem. Say you’re using three scores to measure interest in three different products. You want to use these scores to send contacts different messages based on which product they look most interested in. When a contact visits the product page on your website, you increment the score for that product by 3 points.
In principle this will work, but if it’s unusual for contacts to view product pages more than once it may be difficult to measure any difference between each score. This problem is made worse if you typically have low traffic. Look at your analytics to work out whether this is likely to be a problem and if it is, consider using scores to measure something else, for example interest in an entire product category rather than individual products.
Of all the things most likely to cause you headaches, campaign clash is the one. It happens when multiple scores increase enough to trigger messages at the same time. The result is that a contact receives multiple, mixed messages in a short space of time.
To avoid this, you need to introduce exclusions to your campaigns, but because contacts can increase their scores at random, planning for every eventuality can be a challenge.
Lead scores are incredibly powerful. They provide granular insights at low cost, but they do have their quirks. It’s easy to get into a pickle without giving some thought to them beforehand.