Category management is a retailing concept that breaks products into discrete groups ("categories") to be managed strategically. It aims to improve sales and profits by treating each category as a business unit. Spencer's Retail uses category management by collecting data at the store and strategic level to gain insights. Data is analyzed at the SKU, category, and store level to inform category visions, personalized experiences, and promotion optimization. This helps improve performance across the business.

1. PROJECT ON
Submitted By: Shamik Chakraborty

2. TOPIC PAGE NO
Definition of Category Management 01
Significance of Category Management 02
Process of Classification of Category 03
Data Collection (Store Level) 05
Collection of Data at Strategic Level 07
Conclusion 08
References 08

3. Category management is a retailing and purchasing concept in which the range of products purchased
by a business organization or sold by a retailer is broken down into discrete groups of similar or related
products; these groups are known as product categories (examples of grocery categories might be:
tinned fish, washing detergent, toothpastes). It is a systematic, disciplined approach to managing a
product category as a strategic business unit.
Category management in a retail context
Each category is run as a "mini business" (business unit) in its own right, with its own set of turnover
and/or profitability targets and strategies. Introduction of Category Management in a business tends to
alter the relationship between retailer and supplier: instead of the traditional adversarial relationship,
the relationship moves to one of collaboration, with exchange of information, sharing of data and joint
business building.
The focus of all supplier negotiations is the effect on turnover of the category as whole, not just the
sales of individual products. Suppliers are expected, indeed in many cases mandated, to only suggest
new product introductions, a new planogram or promotional activity if it is expected to have a
beneficial effect on the turnover or profit of the total category and be beneficial to the shoppers of that
category.
The concept originated in grocery (mass merchandising) retailing, and has since expanded to other
retail sectors such as DIY, cash and carry, pharmacy, and book retailing.
The Methodology of Category Management (By Partnering Group)
The industry standard model for category management in retail is the 8-step process. These includes:
i. Define the category (i.e. what products are included/excluded).
ii. Define the role of the category within the retailer.
iii. Assess the current performance.
iv. Set objectives and targets for the category.
v. Devise an overall Strategy.
vi. Devise specific tactics.
vii. Implementation.
viii. The eighth step is one of review which takes us back to step 1.
Market research company Nielsen has a similar process based on only 5 steps:
Reviewing the category, Targeting consumers, Planning merchandising, Implementing strategy,
Evaluating results.

4. Significance of Category Management
 Increased sales, goodwill and market share
 Proper care and devotion to each item of merchandise
 Increased sales further lead to increased turnover
 Maximize shelf efficiencies
 Less inventory shrinkage
 Recognizes procurement opportunities
 Enhances customer knowledge level
 Improves return on investment (ROI)
 Decreases chances of out-of-stock positions
 Enhances return on money invested in marketing efforts
 Classifies the performance of brands as doing well, not doing well, problem brands, etc.
 Purchasing merchandise exercise becomes easy and cost effective.

5. Process of Classifying Category Management in Spencer’s Retail
The best practices in category management report suggests a set of four consumer centric categories
roles as follows:
Destination Category:
It is used by retailers to position themselves as the most favorite stores of customers through combining
the attributes of several categories of stores.
{Special trip to the stores with the specific intention of making a purchase that concentrates on one
product category and that combines a huge multivariate selection with low prices}
E.g.: Fresh vegetables and fruits at super bazaars, apparel at departmental stores, fresh bakery produce
and food.

6. Routine Category (Preferred category):
These are the products and services that customers use in their day to day life on regular basis as a
matter of routine or habit.
E.g.: Shaving cream, body wash, hair oil, shampoo, toothpastes, soap, etc.
Seasonal Category (Occasional category):
These are the products and services which are not purchased on regular basis but occasionally.
E.g.: Umbrellas, colors and water balloons before Holi, flying kites before Independence Day in Delhi
and Northern part of India.
Convenience Category:
These are the products that a customer always prefers to buy from neighbourhood spencer’s retail
stores. Usually these goods carry a wide range of products but of low prices.
E.g.: Bread, butter, eggs, routine stationery, and routine toiletries and so on.
Strategies for Implementations:

7. Collection of Data (At Store Level)
Creating the analytical ecosystem for category management is incredibly important in today’s shifting
consumer landscape. Companies who fail to invest in this area run the risk of missing out on
incremental revenue opportunities or falling behind on product development. Other risks include:
 Lack of insight about products, stores, and customers
 Poor customer experience
 Lack of a clear category growth roadmap
 Unproductive planograms
 Uncompetitive pricing and promotion
 Inability to change shopper behavior to drive growth
Utilizing big data at the category level for new insights contains unprecedented opportunity for
company to grow. By invested in taking advantage of this opportunity Spencer’s uses few best practices
in mind as they develop their businesses.
Data Unification for Category Management
Cleaning and centralizing the company’s existing data, in addition, enabling users to blend relevant
external data, which can help to develop an insight at the category level. By combining internal and
external datasets, Spencer’s Retail can get much more granular feedback on promotional effectiveness,
pricing decisions, and assortment.
Clear Category Vision and Story
To develop a clear category vision and story, Spencer’s Retail has invest in analytical tools that
promote visibility into category performance in-store, online and across multiple geographies, since
categories perform differently based on local.

8. The ability to conduct analyses at the SKU, category and store level is crucial in helping category
management teams develop long term roadmaps and gain organizational buy-in for their vision.
Personalized Customer Experiences Through Enhanced Analytical Flexibility
The ability for the internet to customize and recommend products to shoppers based on their personal
preferences must be mirrored by stores and brands.
Category managers who are able to develop assortment and pricing strategies specific to individuals
and stores will find a greater chance of capturing a larger share of customer wallet.
WEEKLY WORKOUTS IN ALL THE STORES

9. Collecting Data and Showing it at Strategic Level
End-to-End Data & Analytics Solution
With IT support the entire data infrastructure has served as a provider of becoming the leading retailers
and brands in the Eastern India. The IT team enables category managers to:
 Unify data from any data source including third-party, retailer, or brand data to provide a
centralized and single analytical access point;
 Consolidate product and business performance data across ERP systems;
 Give teams the ability to blend their own external data through a self-service platform complete
with advanced analytics and visualization;
 Provide a flexible interface to every other part of the business including application
development for IT, interactive analysis tools for category managers and dashboards for
executives.
Category Visibility
Category management teams to gain line-of-sight visibility into performance through a platform for ad-
hoc analysis and set of pre-built reports that help:
 Determine which products drive aisle traffic and shopper baskets
 Develop online and in-store category management strategies
 See how product loyalty changes over time
 Identify shifting category trends and the entrance of new competitors
Promotion & Assortment Optimization
Specializes in answering the hardest promotions questions through drillable reports and applications
that reveal:
 Optimal promotions pricing and space allocation for each store and category
 Trade spend effectiveness
 Planogram performance to identify space reduction opportunities
 Assortment effectiveness with new and discontinued items

10.  Product substitutability and how different shelving strategies and assortments drive shopper
trips
Competitive Market Insight
It is the only multi-source data platform that contains pre-cleaned and blendable datasets to help
category managers develop greater market insight around shifting macro and consumer trends. Such
data includes:
 Transactions data which provides a total wallet view of consumer spending
 Digital e-receipts data which analyzes online shopper baskets and spending
 Clickstream data which tracks online shopper behavior
 Pre-cleaned CA datasets on economic conditions, demographics, housing, and more.
CONCLUSION
Category management can be taken to a whole new level by following a more structured, analytical and
data-driven approach. The category management workflow proposed in this white paper is intended to
facilitate such an approach.
Implementing this workflow requires both a thorough understanding of category management as well
as experience and expertise in establishing effective structures and an understanding of the people side
of change to ensure successful execution.
At Spencer’s Retail, we aim to tailor our approach to the specific needs of our clients. To get there,
together.
REFERENCES
en.wikipedia.org/wiki/Category_management
Spencer’s Retail Store (Springdale Apartment, Netaji Nagar & Usha Bus Stop)