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  1. 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. 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. 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. 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. 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