I'm using a Viewed This Viewed That criteria and finding that with no attribute weighting, a certain type of product is dominant and shows up about 65% of the time. I'm trying to use attribute weighting to "boost" the other product types. When I set those product types to 50% weights (and no weight for the dominant type), it does not seem to change the proportion of product types that I see in the resulting recommendations data. When I set the alternative product types to a 75% weight, they become too dominant, and my previously dominant type goes down too much (to about 3%). There's no option to set a weight in between 50% and 75%, so I'm wondering if there is something else I can do to achieve an intermediate result.
More broadly, I don't fully understand how to interpret the 0/25/50/100 attribute weights. If something is set to a 50% weight, does that mean that products with that attribute will be recommended 50% of the time? This doesn't seem to be the case since you can set the rules to sum to more than 100% (e.g. 3 product types with 75% weight each). Does 50% mean 2x as likely to recommend as another type?
Any help is much appreciated!
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Hi @abid63370229,
The attribute weightings only allow the 25% increment options. In stead of boosting up that single attribute to 75% you could keep it to 50% and then boost another attribute (that addresses a similar set of products/entities) up (maybe 25%) to nudge the results a little more. That way you might be able to achieve the mix you are looking for.
To your later question, boosting 25% doesn't mean it will achieve 25% of recommendations. It's just an increase or decrease of weighting on that set of products. A "nudge" or "boost" are pretty accurately descriptive terms for it's impact. Here's a link to the attribute weighting help docs which describe it and may be helpful.
Hi @abid63370229,
The attribute weightings only allow the 25% increment options. In stead of boosting up that single attribute to 75% you could keep it to 50% and then boost another attribute (that addresses a similar set of products/entities) up (maybe 25%) to nudge the results a little more. That way you might be able to achieve the mix you are looking for.
To your later question, boosting 25% doesn't mean it will achieve 25% of recommendations. It's just an increase or decrease of weighting on that set of products. A "nudge" or "boost" are pretty accurately descriptive terms for it's impact. Here's a link to the attribute weighting help docs which describe it and may be helpful.
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No, 25% isn't a negative weight. My point was you could create multiple weighting rules to overlapping definitions of products/entities and possibly get the mix you are hoping for over a single rule boosted really high. For example, suppose I know that a particular brand and category overlap a lot. I could create 2 separate rules one on the brand value and another on the category value to potentially add fine tuning to your weighting. It is something you'll have to test out but could give you the results you are hoping for.
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