Thursday 3 June 2010

Static Lists Recommendation (Contributed by Partha)

Recommendations are assets that determine which products or content should be featured or “recommended” on a rendered page.

There are three kinds of recommendations:
• Static Lists – return a static list of recommended items (List Mode and Recommendation Mode).
• Dynamic Lists – return a list of recommended items that is generated by a dynamic list element that you create
• Related Items – return a list of recommended items based on relationships between flex assets, such as products.

In this section I shall elaborate about Static Lists Recommendations in Recommendation Mode.

To create a Static Lists recommendation in Recommendation mode:

1.Click New in the button bar.
2.In the new form, click New Recommendation.
3.Enter Name, Description, Start Date and End Date (date range in which the asset will display online), Mode and click Continue.

Wednesday 2 June 2010

Deciding which data model

How you determine which type of data model should be used for a particular content?

The basic asset model is a good choice when your data has the following characteristics:-

1)It is fixed, predictable: there will be no need to add attributes to the asset type.

2)It is homogenous: all assets of the same type have similar attributes.

3)It has a moderate number of attributes. You are limited by your database as to how many columns/attributes you can have in the asset type table for a basic asset.

4)You want to use the static publishing method predominantly.

The flex model is the right choice when your data has the following characteristics:

1)It has lots of attributes.

2)It can be represented in a hierarchy in which assets inherit attribute values from parent assets.

3)You cannot predict what attributes might be necessary in the future.

4)Asset instances of the same type can vary widely. That is, not all assets of that type should have the same attributes.

5)Visitors browse your online site by navigating through “drill-down” searches that are based on the attribute values of your data.

6)You want to use Engage.