HANA TA for Hybris Ecommerce – Why Google??
Alright, so lets pick an ecommerce site– Say Levi’s-Great Britain http://www.levi.com/GB/en_GB/category/men/collections/levi-collections-whats-new-men
On the top right we see a generic search, that may use Apache SolR. Below we see structured search.
If I wanted to search for “Levis Great Britain Mens new arrival Slim 32″ , I add “Great Britain” only to set the regional context. So let’s analyze different ways in the current system:
1. On the Levi’s site the search “Mens New Arrival Slim 32” does not provide any result
2. On the Levi’s site the search: “Slim 32” provides a lot of data of which a lot is unrelated. For example, “Boot Cut” is displayed whereas I was looking for
3. What if we use Google? Many do this for most online shopping. The top 10 searches provide a lot of context
So, the question is what can be done here? Why utilize Google, when we can implement a change that keeps the user from leaving the site and possibly getting distracted with counter offers.
Using Text Analysis in HANA:
- Create dictionaries and rules for product filter dimensions and their values
- Dictionaries will help identify the filter dimensions from the value typed in. Example: “Slim” would automatically map to “FIT”.
- Rules needs to come in action when value does not uniquely identify the filter dimension and we need to do natural language processing. Example: If we have Slim 32, “32” could stand for waist or length. So unless qualified via qualifiers 32 will be used to filter waist and length both. With a rule if we will map “waist” only for sentences like “Slim and Waist 32” or “Slim with 32 waist” etc.
- Use the XS API for runtime applying the configuration on the query to bring in the filter route
- If the filter route is achieved feed the converted routes from unstructured search to structured search
- If the filter route is not achieved as the query was not identified feed the string to free text search of underlying framework
POC Snap Shots:
Scenario 1: Searching on “Slim 32”, results in: “Slim” gets assigned to “FIT”, “32” gets assigned to both “WAIST” and “LENGTH”. Conversion from unstructured to structure search happens.
Scenario 2: Searching on “Originals waist 32″, results in: “Originals” gets normalized to “Original” the base form and maps to “FIT”, “32” gets assigned only to “WAIST”. Conversion from unstructured to structure search happens
Scenario 3: Searching on “Shirts”, results in a handover to the existing platform search environment as currently this item type is not mapped within Text Analysis in HANA.
Please see the video of POC in action: