CHAPTER – 4

ANALYSIS OF DATA

Whether you love, hate or remain indifferent towards data, it’s impossible to deny its

importance in today’s business landscape.

Businesses across all sectors and industries collect data and perform data analysis , to

better understand their customers and business processes, in an effort to boost

productivity, reduce expenditure and gain competitive advantage.

For this reason, Business Intelligence  (BI) tools – that report  on, analyze and

transform these masses of organizational data into understandable and actionable

information – are growing in popularity and importance.  

In this mini blog series, we’ll explore some of the uses and benefits of data analysis

when applied to a range of distinct industries and departments.

Today, we examine BI’s usefulness and potential within the retail industry.

BI in the retail industry

As the international retail market becomes increasingly competitive with mass

offshore production and global retail conglomerates driving down prices, the ability to

optimize your supply chain, react quickly to market place opportunities and satisfy

customer expectations has never been more important. Therefore, accessing and

maximizing the knowledge within retail data sets has never been more important.  

Understanding your customer base: What customer-centric data

should BI tools analyze and report on?

Basic customer-centric data that retailers should capture and analyze with their BI

solution includes:

Purchase types: Understand customer purchase history to help effectively

promote future product offerings to customer-base

Personal information: Help to design effective personalized marketing and

communications materials / offerings using customer name, date of birth, or

address, etc

Customer feedback and sentiment: Help establish successful product types

and improve future offerings

Frequency of customer spend: Determine the frequency and type of sales and

marketing promotions – distinguish impulse buyers from infrequent need-based

shoppers. Also detect ‘lost’ customers and formulate strategies to ‘win’ them

back

What are the key data sets that BI tools should be used to analyze and

report on in the retail industry?

There are several common data sets critical to the retail industry that BI tools should

be used to report on and analyze. These include:

Sales data

o Point of sale data

o Gross margins and revenue

o Turns

o Gross margin return on inventory investment

Market data

o Market share

o Competitor pricing

o Competitor product lines

o Competitor market share and customer profile

Promotional and marketing data

o Success of past promotions / customer feedback

o Total cost of promotion

o ROI on promotion

o Pricing offers

Customer-centric data

o Demographics

o Frequency

o Loyalty

o Etc (see above)

Supply chain and operations data

o Demand for product types based on region, demographic, time of year,

etc

o Identify profitable products

o Keep track of units sold (total or by category)

Merchandising data

Benefits

Developing accurate customer profiles and in-depth operational understandings allow

retailers to predict future customer behaviors and industry trends, allowing them to:

Predict customer likelihood to purchase a new product offering

Identify highly profitable customers by:

o Total value of sales, number of sales, estimated lifetime value

Identify ‘lost’ customers

Identify troublesome customers (return policies, etc)

Identify customers responsive to promotional offerings

Determine which customers will be more responsive to specific types of

marketing

Recognize which customers will remain loyal to your product despite changes

to certain product variables (price, availability, etc)

Increase profits

Develop or purchase new product lines with confidence

Develop highly targeted and successful promotional campaigns based on data

collected from past campaigns and customer feedback

Achieve accurate allocation (type and quantity) of stock across channels and

stores leading to improved efficiency at the supply chain level as well as

increased sales and profitability

Establishing measures

Careful data analysis of the above areas can also enable retailers to develop effective

measures for:

Assessing the components and success of marketing campaigns

Evaluating and determining buying patterns

Finding optimal mix of product types and quantities via region, store, season

Deciphering optimal pricing strategies for product/category types

Improving supply chain procedures

Moving forward

Retail operators not already using a BI application will need to consider the benefits of

analytic and reporting tools to remain competitive and eliminate wastage in an industry where

being in-tune with shifting customer and market trends is paramount.