Stephen Jeong
I think the approach will depend on the nature of your product lines and how many there are.
Scenario 1 - less than ~12 product lines, product lines don't change often, different target personas for each product + high complexity in scoring requirements for each product
In this case creating completely separate models for each product line is likely the way to go. Yes you need a relatively large number of scoring fields and and smart campaigns to track it, but I would just consider that the overhead needed to achieve your goal.
I have implemented something like this for a company with about 14 product lines and a huge number of website pages to track and it was a significant project, but quite achievable. However, with a larger number of products than this, it won't scale.
Scenario 2 - dozens or hundreds of products, each product interest needs to be tracked separately, products change frequently and have a fixed lifespan, similar personas for each and lower complexity
In this case it would obviously be completely impractical to create scoring fields and separate models for each of these.
We used an interesting approach to solve for this scenario in a recent project. We developed a product scoring program template that could be cloned to create an individual Product Interest Scoring Program to track interest in each product. Rather than use an incrementing scoring field, the various stages of the program channel were used to track the incremental level of interest. At a certain stage they would be considered a "success" which would trigger the MQL flow and stamp their product interest.
This provided a scalable way to track any number of products without maintaining separate models for each, and programs could be deployed or retired in minutes as products changed.
If this sounds relevant to you shoot me an email and I am happy to give you a quick screenshare of how it was done. justin@perkuto.com
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Justin Norris | Perkuto
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