Data warehousing in retail

What is Data Warehousing?

Data warehousing is a collection of decision-making and support technologies aimed at enabling, helping, and guiding the knowledge worker (executive, manager, HR analyst) to make better, faster, and proportionally more accurate decisions. Data warehousing and online analytical processing (OLAP) are building blocks and, therefore, of utmost importance for decision support technology, which has recently become a prime focus in the database industry. Many retail products and services are currently available, and the principal database management system vendors have invested stakes in these areas.

The dynamic, rapidly growing, and highly competitive nature of the present consumer retail industry means that businesses in this industry are constantly experiencing different decision-making challenges concerning pricing, inventory control, and access, target marketing, consumer satisfaction, and product optimization according to market requirements. To overcome these challenges and simultaneously create opportunities, retailers are adopting data warehousing as an absolute be applied to a wide range of consumer retailers with a minimum configuration.

THE IMPACT OF DATA WAREHOUSING ON RETAIL

The benefits of data warehousing in retailing include:

(1) more efficient promotional efforts

(2) increased sales volume

(3) increased profitability

(4) improved customer  relationships

(5) improved vendor negotiations, and

(6) improved inventory availability.

Data warehousing in the retailing industry is used in three primary analyses: promotions, vendors, and consumers. Recently, retailers have begun to be concerned with macro-market and micro-market analysis to achieve better, more refined customer service. This is one of the primary reasons for adopting and implementing data warehousing.

● Promotional performance analysis:

Promotional tools include coupons, value packs, rebates, sweepstakes, and others. By using data warehousing, retailers can derive detailed knowledge of the promotion and its effectiveness through fact-based data. With data warehousing, retailers could obtain information such as which items or brands drew the most significant sales increases and were most profitable relative to each promotion.

● Vendor analysis:

Data warehousing allows retailers to facilitate effective negotiations and sign better deals with vendors. The main reason for vendor analysis is for retailers to calculate markup and the cost of goods. Vendor analysis permits retailers to calculate the profitability of by-products and suppliers, which helps increase sales and reduce the cost of products sold. Some leading retailers employ supplier scorecards that track item-level profitability and delivery records for vendor analysis. The anticipated outcomes are lower or discounted purchasing costs for the retailers while maintaining a mutually beneficial relationship with suppliers.

● Increase sales and profitability:

The use of data warehousing permits retailers to improve inventory availability and decrease operational costs, directly impacting corporate sales and profitability.

● Market segmentation analysis:

Retailers can look into detailed market segments by implementing data ware-
housing. Market segmentation is “the process of partitioning markets into
groups of potential customers with similar needs and characteristics
likely to generate similar purchase behavior”. There are three common segmentation strategies, geographic, demographic, and socioeconomic market segmentation.

After a geographic market area is defined, demographic analysis
(e.g. age distribution, gender, family life cycle, race, and religion) and socioeconomic analysis (e.g. education, occupation, income level, social class, and stability) are performed. Data warehousing allows retailers to segment and analyzes such market areas and consumers for successful marketing alternatives.

● Customer analysis:

Data warehousing permits retailers to implement “one-to-one” marketing which encompasses creative new marketing programs and services provided to each consumer.

Additionally, specific customer buying and browsing habits can be tracked and stored automatically. Furthermore, loyal, long-term customers and lost or unhappy customers can be identified and targeted for promotion. Profits when being earned from customers are dissimilar. The 80–20 rule that “20 per cent of your customers will account for 80 percent of your business” concludes that finding and maintaining the best customers is essential for retail success.

Retailers employ customer-specific marketing programs and services to retain loyal customers and keep them happy, such as customer loyalty cards and frequent customer discounts. Implementation of this marketing concept is possible only when retailers have detailed knowledge of customers, which may store in the data warehouse.
The primary reason to maintain and document the lifespan of customers is to increase customer satisfaction, which results in increased sales, profitability and good review.

These efforts come from understanding the absolute importance of retaining existing customers in the long run. Data warehousing provides the following functions for increasing customer satisfaction:

● Identification of customer purchasing habits and patterns.
● Understanding the personal needs of every customer and optimizing according to that.
● Targeting, analyzing, acquiring, retention, and micro-marketing programs for the most profitable customers.

Retailers are facing hardships in understanding and utilizing the generated datasets to help managers in deciding and optimizing inventory, setting a profitable price, coming up with new product lines, and looking after customer satisfaction. Thus, to assist in overcoming these obstacles, data warehousing is one of the most integrated, effective, and user-friendly solutions since it binds all available data sources in a central corporate data repository and organizes data in such a way that it answers business questions with ease, accuracy and speed.