1. RETAILInsight
Know Thy Customer
In a business where
customer is king,
Sanjay Mehta
demonstrates how the
latest reporting tools
can help retailers
understand customers
and serve them better
C
Customers are the heart of any business. One
unshakable rule of any business is ëknow your customer.í
In todayís business climate, this means using Business
Intelligence (BI) software to analyse complex customer
data. With BI, companies can answer a wide range of
the future of a business, it is important to predict what
customers want and how they will react. In addition to
understanding customers, it is paramount for any
enterprise to understand how its business has performed
at any given time in the past, and compare it with its
critical questions about their customer base. The current status and projections of the future. However, it
information generated through business intelligence can is becoming essential that not only is the analysis of
help you answer many questions about your business: business performance done on real-time data, but also
Who are my companyís segment-wise top revenue- actions in response to analysis results can be performed
generating customers? in real time and instantaneously change business
What are the cross-selling/up-selling opportunities process parameters.
in my business? Companies can improve inventory planning and
Which customer segment has contributed most to strategy by leveraging the full potential of customer
revenue growth? loyalty data, sales transaction data and store data with
Which type of customers look for discounts? customer analytics in retail. Itís designed to help
Which types of customers have highest number campaign managers, promotions managers, loyalty
of returns? programme managers and other key functions exploit
Which types of customers are most profitable? the hidden relationships between products, customers
and store data sets. It provides overall assessment on
Business analysts, marketing managers, and other each single customer: profitability, loyalty, and buying
decision-makers need detailed information regarding behavioural patterns. This information modelled and
customersí tastes, current trends, evolving market analysed versus time along with customer profiles
conditions, etc. They need to ask tough questions about enables churns management and monitoring.
their customers and delve further into the data to Customer analytics in retail can answer all of these
understand how their customersí behaviour aligns with questions, and more. Customer analytics in retail draws
their production processes and sales cycles. critical insights from sales, customer-centric KPIs like
In order to improve processes with customer customer profile, customer behaviour, customer trend
interaction, retail businesses have introduced customer (buying pattern) and customer loyalty. These metrics are
relationship management systems. These systems collect made from the data to create a more complete picture of
large volumes of data about customers which contain the customersí behaviour and its impact on the business.
valuable information that can allow a business to
improve its customer relationships and services. Customer Analytics in Retail lets you:
Typically, CRM applications focus on recording Analyse customer types and profile
transactions and reporting what has transpired. individual customers
However, in order to become proactive and truly shape Monitor and compare trends in customer type,
RETAIL BIZ MARCH 2010 23

2. RETAILInsight
customer base size, buying, contribution to revenues, Customer Profiling and Valuation
product mix, customer ranking, profitability, and more Defining your best customer involves several factors: the
Evaluate customer profitability and cost to serve revenue they generate, the frequency of their purchases,
View buying patterns, average order sizes, and the cost to serve them, and more. You can analyse each
number of purchases in a specific time period of these factors in isolation or combination to create
Monitor customer type and customer-specific aging profiles of each of your customers and evaluate their
schedules by number of transactions and total dollars respective value to your business. Analysing customer
Assess customer satisfaction by number of profiles by sales channel or by industry segment will help
adjustments, delinquencies, returns, shipping delays, you identify cross-sell opportunities, new markets, or
buying frequency and trends under-performing markets. You can then use this
Distribute customer information across the information to direct your activities on retaining high-
organisation for operational management and reporting value customers.
and analysis needs
Provide self-service or on-demand reporting Customer Satisfaction
and analysis. Changes in your customersí buying patterns, an increase
in their rate of returns, or the length of time they take to
Customer analytics in retail lets you evaluate and pay invoices are all indicators of their satisfaction with a
rank your most valuable customers, monitor and analyse company. Examine these and other indicators to gauge
their overall value to your business, and understand their individual customer satisfaction and to identify overall
buying behaviour. These insights help you focus trends that can be leveraged into increased customer
your attention on attracting and retaining customers value. Firms should identify downward trends to retain
whose behaviour will help your organisation reach its customers before they leave.
strategic goals.
Dynamic reports, ad-hoc analysis and powerful Customer Loyalty
metrics answer critical business questions and track key Encapsulate customer insight in order to build long-
customer performance indicators that are grouped into lasting customer relationships: the right offer to the right
the following categories: customer through the right channel can help maintain
Customer Profiling and Valuation high levels of customer satisfaction. More accurate
Customer Satisfaction measurement of customer satisfaction is possible
Customer Loyalty. through BI.
24 RETAIL BIZ MARCH 2010

3. RETAILInsight
Advantages of Using Customer Analytics
in Retail Typical Customer Dimensions and Measures
Using the data gathered from consumer transactions in Retail
and analysing it can help you:
Derive critical information on customer behaviour Regular, normal, occasional customers (based on
Sort out critical customer details like top revenue- frequency/duration of visits)
generating customers, most profitable customers, Professional, academic, teen, household, bachelor
purchase trends at different customer profile levels, (based on products bought)
percentage of return customers and also customer Service-sensitive, price-sensitive
segment with potential bad debt risk Power, normal, entry-level customer
Work on key areas appropriately for effective Demographics, customer type (business-consumer,
marketing strategy with the information generated mass based)
Group out the best customers based on factors such Average Revenue per month, expected yearly revenue
as revenue, purchase frequency and services costs and Use of loyalty programmes
concentrate activities on retaining and increasing Seasonality indexes
number of high-value customers Statistically derived clusters (homogenous groups
Sort out customer buying trends and patterns, return of customers).
rates, time to pay and other factors to judge customer
satisfaction issues and take appropriate action before customer, product margin, or revenue by product line,
they affect your bottom lines and get the most up-to-date results within minutes rather
Identify fast-moving products and cross-sell scope to than days or weeks.
align production and marketing force to take benefit of
this information in assessing product performance over Accountability ñ Customer metrics for all
a segment of customers Companies derive maximum value from their customer
Understand customer purchase patterns and trends base when accountability for sales, production, and
in various market segments and concentrate on weaker
areas to improve sales. Retail Customer KPIs
Using Customer Analytics in Retail Customer Gross Profit = Customer Sales - Customer
Deploy customer analytics to leverage metrics from Cost of Goods Sold for a period
hundreds of business questions to resolve three Customer Lifetime Purchase Value - Monetary
common customer issues: value of each customer's life time purchases from
Visibility ñ Achieved through easy access to the retailer
customer data and guided analysis Customer profitability - Customer Profitability =
Accountability ñ Achieved through distribution Customer Sales - (Customer Returns - Customer Cost
of scorecards of Goods Sold + Customer Promotion Expenses +
Reliability ñ Achieved through optimising, Activity Based Cost of Servicing Customer) for
integrating, and consolidating data into a single view. a period
Customer Purchase Freq Count - Count of customer
Visibility ñ Accurate reports, on time purchases transactions over a period of time
Acting on the basis of trends revealed through customer Customer Purchase Value - Monetary value of each
behaviour reports, can often mean the difference customer purchase during a period with an average
between success and failure. Acting on positive trends value for all purchases for the period
while they occur can drive increased sales, satisfaction, Customer Reference question - A rating from 0 to
and loyalty, while spotting negative trends too late in the 10 that indicates if the customer would recommend
game can result in lost customers. Customer analytics in the store
retail lets you identify both positive and negative trends Customer Sales by Segment - This formula is
and deliver critical information and analysis in a format dependent upon defining customer segments (based
that enables quick decisions. Pre-built analytic pathways on age, education, lifestyle, income and other
ensure that the right questions are always asked and the factors) and associating individual customers to
right information is always returned. Sales can access specific segments
specific customer information such as activity at a Customer Service Staffing - Face-to-face customer
particular customer over a certain period of time. service staff count / total staff count
Marketing can study trends in product lines. Finance can Visit to Buy Ratio - Sales Transaction Count per
easily extract trends in sales, gross margins, revenue, and period / Visit Count per Period
other relevant statistics. Users can drill down by
RETAIL BIZ MARCH 2010 25

4. RETAILInsight
customer profiling is integrated and aligned. Each
department needs to understand its respective area of Customer loyalty KPIs in Retail
accountability and the impact that its particular metrics
have on other areas. customer analytics in retail supports Total customers lost
company-wide alignment through scorecards that The total number of customers who do not buy your
display metrics and KPIs. Employees can proactively goods again
manage their areas and see how accountability for other Number of customers includes: the number of first
areas is distributed throughout the company. customers and customer loyalty removed
Performance issues can be identified and analysed, and
resulting insights communicated to those responsible. The rate of customers lost after first time purchases
This ensures that tactics are aligned with strategic goals With total customer purchase first time
across the company. removed/total customer purchases first time
This rate is low that may be due to some causes:
Reliability ñ Turn data into action your product is not suitable, or the product is good
Sales, product, and customer data often reside in a product but has not been advertised well
variety of databases, ERP systems, and unconnected
spreadsheets across your company. Changes in one The rate of customer loyalty loss
source are not reflected in another, leaving customer With total customer loyalty lost/total customers
facing employees to work with outdated or inaccurate loyalty available
information. Customer analytics in retail integrates This is one of the most serious ratios that you need
sales, product, and customer data into one central source to note: this may happen because products and
services became more expensive, or new and better
products with competitive prices appeared
The life cycles of a customer
Formula: a total relationship with customers/total
client relationship
The rate of customers who return
The number of customers who are repeat
buyers/total customers
This rate is high that will let you know your products
are attractive to customers
The rate of new customer
The number of new customers you gain in a specific
period of time
Any sharp increase or decrease here implies that
either the business is expanding or it's losing
customer loyalty
of data and metrics for a complete profile of your
customers that everyone in the company can rely on.
Changes in customer activity based on sales activity will
be reflected in product performance and customer
profile data. In this way, critical customer data is
constantly updated and optimised for a consistent pool of
performance metrics and KPIs.
Customer analytics can help:
Identify good customers by turnover, number of
transactions, profit and life-time value.
Identify non-returning customers
Identify customers by various selection criteria:
Purchased product x in the past
More than x transactions in the past y months
26 RETAIL BIZ MARCH 2010

5. RETAILInsight
Customers with mobile telephones Conversion Rate ñ Tracks how many visitors to the
Customers with email addresses store are turned into customers.
Identify customers abusing returns policy Average sales
Identify ëpromotion friendlyí customers.
Key Performance Indicators (KPI) for
Customer Analytics in Retail
Profit in retail can only be generated by sales on
the shop floor. There are various parameters
that are used to figure out the success of a
retailer and its performance over time. These
parameters are as follows:
Average Sale per Customer/Transaction:
Total sales for a given period divided by the
number of customers or transactions for the
same period
Units per Customer/Transaction: Total
number of units sold in a given period divided
by the number of customers or transaction for
the same period
Conversion rate: The number of transactions
in a given period divided by the total number of
customers who entered the store during the
same period per customer or transaction ñ Total sales for a given
Sales per Hour (for store or associate) selling hours period divided by the number of customers or
only: Actual sales for the store divided by the number transactions for the same period
of selling hours (other than labour hours) during the Inventory store conversion rate ñ The number of
same period transactions in a given period divided by the total
Sales per Hour (for store or associate) total labour number of customers who entered the store during the
hours: Actual sales for the store divided by the number of same period
labour hours used during the same period Coupon conversion percentage ñ The percentage of
Time Spent in the Store: Average time spent by coupons that have been used by customers
customers in the store can be measured through Profit per customer visit ñ Profit obtained from each
sophisticated techniques utilising RFID and wireless customer visit. This way you can easily set goals for your
technologies or manually. Reason for this measurement: sales team in order to increase profits
there is a direct correlation between the time customers Units per customer or transaction - Total number of
spend in a store and how much they buy. units sold in a given period divided by the number of
customers or transactions for the same period
Customer Service Customers per day/week
Performance in retail completely depends on the Items per customer
customer, the transactions that take place and the Average sale per customer/transaction
customer satisfaction the customer goes home with. This Units per customer/transaction
customer satisfaction will result in later transactions. The Conversion rate (customer into sale)
performance for any retailer can be measured by the Percentage of income from return customers
following parameters: Percentage of returning customers within
Total number of customer claims measurement period.
Customer profitability These measures can help you judge whatís best for
Cost per delivery per customer your business and your customers. Customer analytics is
First request versus agreements a very important tool in better understanding the
Orders delivered in full customersí wants and behavior. Only after
Orders delivered on time understanding the customerís behaviour can a retailer
Documentation strategise and build on top of these results. After all,
Accuracy of the sales forecasting understanding the customer is work half done and the
Service performance against standard criteria. other half is made easier.
Other customer-centric KPIs in the retail
industry include: The author is CEO, MAIA Intelligence Pvt. Ltd.,
RETAIL BIZ MARCH 2010 27