DATA ANALYSIS & RECOMMENDATIONS

Raj, Director of Marketing

Product Catalog Management (PCM)

Scope: Catalog - To enrich the product information or optimize the online catalog

Attribute set creation/enrichment Aggregate attribute values Cleanse and Standardize values

Product with key and exhaustive information will make buyers to take a quick buying decision, to improve sales and User Experience

(UX)

Product with key and exhaustive information will make buyers to take a quick buying decision, to improve sales and (UX) User

Experience

•Aggregate data from manufacturers and Arnotts product data repositories

•Cleanse and normalize product data as per industry and client standards

•Analyze category, create attribute set based on industry best practices and competitor benchmarking

•Map products into right categories/taxonomy

Product Categorizatio

n

Attribute set creation

Data Aggregation

Data Cleansing & Standardizati

on

Item Setup/Catalog Creation - Methodology

Data Accuracy

Data Consistency

Data Completeness

Data Standardizatio

n

Faceted Navigation – Data Cleansing & Standardization

Scope: To validate the values under all facets, cleanse the junk values, maintain data uniformity and also recommend the facets to have a better competitive edge

Faceted Navigation or Refine Results or Filter Attributes always drive consumers to land their required products easily which will

improve the shopping experience and conversions

Faceted Navigation & Recommendations

Analyze Facets and values for category

Cleanse facets and values

Recommend new facets based on best practices, client goals and competitor benchmarking

Faceted Navigation & Recommendations – Specific Tasks

Brand verification, removal & standardization

Material, Color, Size and other facets - data uniformity

Remove spell mistakes, duplicate data, etc.

Product de-duplication

To cleanse and normalize data; identify and remove “junk data” for data integrity and usability purposes

Facet Recommendations – Mobiles (Link)

Existing Facets Recommended Facets

Data Cleansing/Standardization – Mobiles (Link)

 Bada Blackberry

 iOS  Symbian WebOS

Recommended New Values

Existing Values

Existing Values

Value range should not be overlapped

– For example: products with 3.5 inch displayed in

both search

Data Cleansing/Standardization – Laptops (Link)

Duplicate of same

facet/attribute – needs to

be normalized

Data Cleansing/Standardization – Laptops (Link)

For Dimensions, height/depth/width to be displayed to

make consumers for better

understanding

Data Cleansing/Standardization – Cameras (Link)

Duplicate of same

facet/attribute – needs to

be normalized

Value range should not be overlapped

– For example: products with 3.5 inch displayed in

both search

Data Cleansing/Standardization – Men’s Clothing (Link)

Duplicate of same

facet/attribute – needs to be normalized

Data Cleansing/Standardization – Induction Cooker (Link)

Duplicate of same

facet/attribute – needs to

be normalized

Taxonomy Mapping - Categorization

Scope: To validate the existing products whether it has been mapped under appropriate category and also to map new vendor items under correct category

Mis-Categorization – Snapshot – Shirts (Link)

2 issues we identified:

Case 1: Casual shirts has been mapped under Format Shirts

Case 2 : Product name has been updated with wrong keywords

Example for case 2

Mis-Categorization – Snapshot – Shirts (Link) Casual Shirt

Formal Shirt

Digital Asset – ImagesScope: To source images for products and optimize the images as per standards

Source images for products w/o images

Optimize or enhance images – resizing, white background, etc.

Product with consistent images will provide insights about the product to consumers, which will improve buying decision and

shopping experience

Images – Optimization - SnapshotBackground

to be cleansed

Image shade to be

removed

Consulting Services

Images – Optimization - SnapshotBackground

to be cleansed

Image shade to be

removed

Taxonomy Building & Assessment

Scope: To validate the existing taxonomy or category structure, provide recommendations to meet the competitive intelligence and also par with customer expectations

A perfect taxonomy or category structure will always provide better shopping experience (UX) and conversions (also effective

utilization of search keywords from the ecommerce platform)

Consulting Services

Taxonomy Building & Assessment

Provide recommendations and

justifications for taxonomy optimization

Apply taxonomy building

methodology

Analyze existing taxonomy

Taxonomy Building & Assessment – Quick Reco

Computers, Home

appliances, Kitchen

appliances – should be

maintained separately to improve the

user experience, to

meet the competitive intelligence and industry

standards

Taxonomy Building & Assessment – Competitors snapshot

Taxonomy Building & Assessment – Case Study

Problem: One of the leading online retailers from Europe wanted us to assess their taxonomy whether the current structure par with competitors.

Our Solution: GS1 taxonomy consultants provides the solutions for client problem and also recommended best practices and also added more value proposition to problem statement

Best Taxonomy Recommendation

Folksonomy

Competitive

Intelligence

Industry Practices

Value Propositions we added:

1. Provided recommendations of taxonomy based on competitive intelligence

In addition, we ensured that the taxonomy structure to par with

2. Industry practices

3. Consumer expectations (User Experience)