Eloqua users are ahead of the game with co-dyanmic lead scoring. Why is this important?

Behaviour changes and a scoring model that does not automatically adjust to behavioural changes limits your ability to take full advantage of lead scoring in your lead generation campaigns.

Smart lead or engagement scoring models are c0-dynamic. This means they take into account both implicit and explicit data in order to arrive at a score.

Your lead scoring must be more than just profile data

What is a co-dynamic score?

Long before Marketing Automation platforms provided automated scoring model, sales people scored their prospects either in their head or perhaps in an excel spreadsheet.

These scores are generally based on basic profile data e.g. job title, industry, annual revenue etc. This is then usually balanced with a percentage based on the gut feel of the salesperson.

But what about a person’s behaviour?

This is the missing link in a manual lead scoring model. In today’s digital world we know that far more of the buyer’s journey takes place online long before they engage with a salesperson. 

We call this a person’s Digital Body Language. If you’re using a marketing automation platform like Oracle Marketing Cloud – Eloqua, the tracking of people’s digital behaviour is automated and stored against their profile.

Implicit & explicit data enriches your score

Scoring on explicit data is easy. e.g. you may score someone higher if their job title includes “CXO” and lower if their job title contains the word “manager”. However this can be a little risky, job title vary a great deal. 

Scoring on implicit data is a different story. Through a person’s implicit data you’re able to imply certain things about them. First of all, you need to be in a position to capture implicit data before you can score on it. 

Implicit data is incredibly valuable because it enables to add layers to your scoring model i.e. their actual online behaviour mixed with recency. By that I mean behaviour they’ve done within the past 30 days can be weighted higher than behaviour completed in the past 13 months. 

For example, a white paper download will add profile or explicit data to a person’s profile, regardless of it being last week or last year. Recency is a data point you want to weight and score as well, a person submitting a form last week should be weighted higher than someone who submitted the form 13 months ago.

In addition, their behaviour around your website before and after the form submission adds implicit data to the score. 

Hopefully this helps explain why we call this process both a Lead Score as well as an Engagement Score.

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