Customer Analytics in Retail - Know Thy Customers


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A solution to decode the mysterious ways in which customers move is closer than you think.

Customers are at the heart of any business. One unshakable rule of any business is to “know your customer.” In today’s business climate, this means using Business Intelligence (BI) to analyse complex customer data. With BI, companies can answer a wide range of critical questions about their customer base.

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Customer Analytics in Retail - Know Thy Customers

  1. 1. Technology Know Thy Customers A solution to decode the mysterious ways in which customers move is closer than you think. By Sanjay Mehta C ustomers are at the heart of any business. One unshakable rule of any business is to “know your cus- tomer.” In today’s business climate, this means using Business Intel- ligence (BI) to analyse complex customer data. With BI, companies can answer a wide range of critical questions about their customer base. The questions can include: businesses have introduced customer • Who are my company’s seg- relationship management systems. ment-wise top revenue-generating These systems collect large volumes customers? of data about customers, which • What are the cross-selling / up- contain valuable information that selling opportunities in my business? can allow a business to improve its • Which customer segment has customer relationships and services. contributed most to revenue growth? Typically, CRM applications focus • Which type of customers look on transaction recording and report- for discounts? ing what has transpired. However, in • Which types of customers have order to become proactive and truly highest number of returns? shape the future of a business, it is Companies can improve inven- customer profiles enables manage- • Which types of customers are important to predict what customers tory planning and strategy by lever- ment and monitoring. most profitable? want and how they will react. In ad- aging the full potential of customer Customer Analytics in Retail can Business analysts, marketing dition to understanding customers, loyalty data, sales transaction data answer all of these questions, and managers, and other decision makers it is paramount for any enterprise and store data, with Customer Ana- more. It draws critical insights from need detailed information regard- to understand how its business has lytics in Retail. It’s designed to help your sales, customer-centric Key Per- ing customers’ tastes, current trends, performed at any given time in the campaign managers, promotions formance Indicators (KPIs) like Cus- evolving market conditions, etc. past, and compare it with its current managers, loyalty program managers tomer Profile, Customer Behaviour, They need to ask tough questions status and projections of the future. and other key functions exploit the Customer Trend (Buying Pattern) about their customers and delve fur- However, it is becoming essential hidden relationships between prod- and Customer Loyalty. These met- ther into the data to understand how that not only is the analysis of busi- ucts, customers and store data sets. It rics are made from the data to cre- their customers’ behaviour aligns ness performance done on real-time provides overall assessment on each ate a more complete picture of your with their production processes and data, but also actions in response to single customer: profitability, loy- customers’ behaviour and its impact sales cycles. analysis results can be performed in alty and buying behavioral patterns on your business. In order to improve processes real time and instantaneously change (trends). This information modeled Customer Analytics in Retail lets with customer interaction, retail business process parameters. and analysed versus time along with you: WWW.PROGRESSIVEGROCER.COM AHEAD OF WHAT’S NEXT APRIL 2010 • PROGRESSIVE GROCER • 67 l : :
  2. 2. • Analyse customer types and information to direct your activities • Understand customer purchase area of accountability and the im- profile individual customers on retaining high value customers. patterns and trends in various mar- pact that its particular metrics have • Monitor and compare trends in ket segments and concentrate on on other areas. Customer Analytics customer type, customer base size, Customer Satisfaction weaker areas to improve sales in Retail supports company-wide buying, contribution to revenues, alignment through scorecards that product mix, customer ranking, Changes in your customers’ buy- Using Customer display metrics and KPIs. Employees profitability, and more ing patterns, an increase in their rate Analytics in Retail can proactively manage their areas • Evaluate customer profitability of returns, or the length of time they and see how accountability for other and cost to serve take to pay invoices are all indicators Deploy Customer Analytics in areas is distributed throughout the • View buying patterns, average of their satisfaction with a company. Retail to leverage metrics from hun- company. Performance issues can be order sizes, and number of purchases Examine these and other indicators dreds of business questions to resolve identified and analysed, and result- in a specific time period to gauge individual customer satis- three common customer issues: ing insights communicated to those • Monitor customer type and faction and to identify overall trends • Visibility – achieved through responsible. This ensures that tactics customer-specific aging schedules that can be leveraged into increased easy access to customer data and are aligned with strategic goals across by number of transactions and total customer value. Firms should iden- guided analysis the company. dollars tify downward trends to retain cus- • Accountability – achieved • Assess customer satisfaction by tomers before they leave. through distribution of scorecards Reliability – Turn data number of adjustments, delinquen- • Reliability – achieved through into Action cies, returns, shipping delays, buying Customer Loyalty optimising, integrating, and consoli- frequency and trends dating data into a single view Sales, product and customer data • Distribute customer informa- Encapsulate customer insight in often reside in a variety of databases, tion across the organisation for op- order to build long lasting customer Visibility – Accurate enterprise resource planning (ERP) erational management and reporting relationships: the right offer to the Reports, on Time systems, and unconnected spread- and analysis needs right customer through the right sheets across your company. Chang- • Provide self-service or on-de- channel can help maintain high lev- Acting on the basis of trends re- es in one source are not reflected in mand reporting and analysis els of customer satisfaction. More vealed through customer behaviour another, leaving customer-facing Customer Analytics in Retail lets accurate measurement of customer reports can often mean the differ- employees to work with outdated or you evaluate and rank your most satisfaction is possible through BI. ence between success and failure. inaccurate information. Customer valuable customers, monitor and Acting on positive trends while they Analytics in Retail integrates sales, analyse their overall value to your Advantages of using occur can drive increased sales, sat- product, and customer data into one business, and understand their buy- Customer Analytics in isfaction, and loyalty, while spotting central source of data and metrics for ing behavior. These insights help you Retail negative trends too late in the game a complete profile of your custom- focus your attention on attracting can result in lost customers. Cus- ers that everyone in the company can and retaining customers whose be- • Derive critical information on tomer Analytics in Retail lets you rely on. Changes in customer activ- haviour will help your organisation customer behaviour identify both positive and negative ity based on sales activity will be re- reach its strategic goals. • Sort out critical customer de- trends and deliver critical informa- flected in product performance and Dynamic reports, ad-hoc analysis tails like top revenue generating tion and analysis in a format that en- customer profile data. In this way, and powerful metrics answer critical customers, most profitable custom- ables quick decisions. Pre-built ana- critical customer data is constantly business questions and track key cus- ers, purchase trends at different cus- lytic pathways ensure that the right updated and optimised for a consist- tomer performance indicators that tomer profile levels, percentage of questions are always asked and the ent pool of performance metrics and are grouped into the following cat- return customers and also customer right information is always returned. KPIs. egories: segment with potential bad debt risk Sales can access specific customer in- • Customer Profiling and Valua- • Work on key areas appropri- formation such as activity at a partic- Typical Customer tion ately for effective marketing strategy ular customer over a certain period Dimensions & Measures • Customer Satisfaction with the information generated of time. Marketing can study trends in Retail • Customer Loyalty • Group out the best customers in product lines. Finance can easily based on factors such as revenue, extract trends in sales, gross margins, • Regular, normal, occasional Customer Profiling and purchase frequency and services revenue, and other relevant statistics. customer (based on frequency/dura- Valuation costs and concentrate activities on Users can drill down by customer, tion of visits) retaining and increasing number of product margin, or revenue by prod- • Professional, academic, teen, Defining your best customer in- high-value customers uct line, and get the most up-to-date household, bachelor (based on prod- volves several factors: the revenue • Sort out customer buying results within minutes rather than ucts bought) they generate, the frequency of their trends and patterns, return rates, days or weeks. • Service sensitive, price sensitive purchases, the cost to serve them, time to pay and other factors to • Power, normal, entry level cus- and more. Analyse each of these fac- judge customer satisfaction issues Accountability – tomer tors in isolation or combination to and take appropriate action before Customer Metrics for All • Demographics, customer type create profiles of each of your cus- they affect your bottom lines (business-consumer, mass based) tomers and evaluate their respective • Identify fast-moving products Companies derive maximum • Average revenue per month, ex- value to your business. Analyse cus- and cross-sell scope to align produc- value from their customer base when pected yearly revenue tomer profiles by sales channel or by tion and marketing force to take accountability for sales, production, • Use of loyalty programs industry segment to identify cross- benefit of this information in assess- and customer profiling are integrat- • Seasonality indexes sell opportunities, new markets, or ing product performance over a seg- ed and aligned. Each department • Statistically derived clusters under-performing markets. Use this ment of customers needs to understand its respective (homogenous groups of customers) 68 • PROGRESSIVE GROCER • APRIL 2010 AHEAD OF WHAT’S NEXT WWW.PROGRESSIVEGROCER.COM l : :
  3. 3. individual customers to specific segments • Customer Service Staffing: Face to face customer service staff count / total staff count • Visit to Buy Ratio: Sales Trans- action Count per period / Visit Count per Period Customer Service • Total number of customer claims • Customer profitability • Cost per delivery per customer • First request versus agreements • Orders delivered in full • Orders delivered on time • Documentation • Accuracy of the sales forecasting • Service performance against standard criterion Other Customer-Centric KPIs in Retail • Conversion Rate – Tracks how many visitors to the store are turned into customers. • Average sales per customer or transaction – Total sales for a given period divided by the number of cus- Customer Analytics in Retail also • Total number of units sold in a Retail Customer KPIs tomers or transactions for the same lets you: given period divided by the number period 1. Identify good customers by of customers or transaction for the • Customer Gross Profit = Cus- • Inventory store conversion rate • Turnover same period tomer sales - Customer cost of goods – The number of transactions in • Number of transactions • Conversion rate: sold for a period a given period divided by the total • Profit • The number of transactions • Customer Lifetime Purchase number of customers who entered • Life-time value in a given period divided by the Value: Monetary value of each cus- the store during the same period 2. Identify non returning cus- total number of customers who tomer’s life time purchases from the • Coupon conversion percentage tomers entered the store during the same retailer – Percentage of coupons that have 3. Identify customers by various period • Customer Profitability = Cus- been used by customers selection criteria: • Sales per Hour (for store or as- tomer Sales - (Customer Returns • Profit per customer visit – Prof- • Purchased product X in the past sociate) – selling hours only: - Customer Cost of Goods Sold + it obtained from each customer visit. • More than X transactions in the • Actual sales for the store divided Customer Promotion Expenses + This way you can easily set goals for past y months by the number of selling* hours dur- Activity Based Cost of Servicing your sales team in order to increase • Customers with mobile tel- ing the same period (*selling hours Customer) for a period profits ephone numbers are used here rather than total labour • Customer Purchase Freq • Units per customer or transac- • Customers with email addresses hours Count: Count of customer purchas- tion – Total number of units sold in a 4. Identify customers abusing re- • Sales per Hour (for store or as- es transactions over a period of time given period divided by the number turns policy sociate) – total labour hours: • Customer Purchase Value: Mon- of customers or transactions for the 5. Identify “promotion friendly” • Actual sales for the store di- etary value of each customer purchase same period customers vided by the number of labour hours during a period with an average value • Customers per day/week used during the same period for all purchases for the period • Items per customer Key Performance • Time spent in the store: Average • Customer Reference Question: • Average sale per customer/ Indicators time spent by customers in the store A rating from 0 to 10 that indicates transaction can be measured through sophisti- if the customer would recommend • Units per customer/transaction • Average sale per Customer/ cated techniques utilising RFID and the store • Conversion rate (customer into Transaction: wireless technologies or manually. • Customer Sales by Segment: sale) • Total sales for a given period di- Reason for this measurement: there This formula is dependent upon • Percentage of income from re- vided by the number of customers or is a direct correlation between the defining customer segments (based turn customers transactions for the same period time customers spend in a store and on age, education, lifestyle, income • Percentage of returning cus- • Units per customer/transaction: how much they buy. and other factors) and associating tomers within measurement period WWW.PROGRESSIVEGROCER.COM AHEAD OF WHAT’S NEXT APRIL 2010 • PROGRESSIVE GROCER • 69 l : :
  4. 4. Customer loyalty KPIs in Awareness and adoption of BI loss. Retail organisations have plen- State of Adoption Retail among enterprises are definitely ty of employees and such number on the rise. The maturity of BI of un-productive hours can cost a Information technology research 1. Total customers lost adoption can best be seen with the lot. The HR department, equipped and advisory firm Gartner Research new economy companies, includ- with these facts and analyses, can says only 30 percent of companies • The total number of customers ing those in the retail sector. Cur- now plan and take necessary action. that have deployed BI consider their who do not buy your goods again rently, most retail enterprises have This is just one area within an HR deployments “very successful” – the • Number of customers includes: deployed and stabilised ERP/CRM/ domain. Likewise, BI can help any vast majority is labeled “somewhat the number of first customers and SCM or core business (transaction- retail organisation like any other successful.” One reason for this is customer loyalty removed al) applications and are thus looking industry for ad-hoc reporting, dy- low levels of user adoption – less than for a tool that can leverage the IT namic MIS and complex analyses one-third of the potential users of BI 2. The rate of customers investment in these packaged ap- and take informed and proactive tools are using them. Actual usage of lost after first time plications. We are also seeing great decisions, thus saving time and cut- BI tools is almost always much less purchases interest from verticals such as retail ting costs. With customer analytics than expected due, largely to the dif- for adopting BI for increasing their as explained above, BI helps boost ficulty in learning and using BI tools. • With total customer purchase competitiveness and transparency, revenue. Thus, a high rate of ROI According to Gartner, “Business first time removed/total customer respectively. happens quickly on BI. users must get the data, reports and purchases first time In India, there is a general aware- analysis they need for their jobs from • If this rate is low, that may be ness on the theory and concept of Total Cost of Ownership multiple sources and in multiple due to some causes: your product is BI. They are spearheading BI adop- (TCO) forms. However, the BI initiatives not suitable, or the product is good tion by going in for separate BI units of most enterprises lack the maturity but has not been advertised well within the organisation to provide Contrary to the traditional BI and depth of deployment needed to the `right’ product to the `right’ providers (MNC), operational BI meet business demands.” 3. The rate of customer customer at the `right’ time and leaders like MAIA Intelligence’s Most of the existing BI players loyalty loss price. Retail industry is one of the 1KEY have low TCO considering (traditional BI) are primarily focused early adopters of BI in India. Cur- the Enterprise License Cost, IT user on strategic BI alone. These tools are • With total customer loyalty rently, the demand for BI solutions involvement during deployment, expensive and used by only top tier lost/total customers loyalty available is largely being driven by MNCs and IT user involvement for support, management level, expert users; the • This is one of the most serious large enterprises. BI solutions seem implementation, training and over- over 85 percent of the business user ratios that you need to note: this to have gained more acceptance and all Business Value delivered. These pyramid is deprived of a BI for MIS, may happen because products and significance in retail where custom- BI tools provide end-to-end BI with analysis and monitoring / gauge per- services became more expensive, or ers play a pivotal role in the future of low TCO. The unlimited users li- formances, which if provided can new and better products with com- the company. censing policy helps reduce TCO help them get gain visibility into petitive prices appeared as the no. of users increase in case the business and drive performance The return on Investment of 1KEY. Whereas in MNC’s BI, and get everyone working towards a 4. The life cycles of a (ROI) the TCO would go up as the no. common goal. customer of users increase due to user based The Business Intelligence mar- ROI on BI is high and fast. Let’s licensing policy. Implementation of ket is growing and continues to • Formula: a total relationship take an example of a HR Analytics. 1KEY happens as fast as within two evolve. There’s still plenty of room with customers/total client relation- Data captured through show-card days and business users are trained for growth; it has only penetrated ship on employee entry and exit can be in just few hours. So the TCO is 10 to 15 percent of the known user analysed for actual working hours, very low in case of BI tools like base, but there is a vast opportunity 5. The rate of customers thereby tracking the productivity 1KEY. for business intelligence well beyond who return today’s known markets. A Gartner report “Hype Cycle • The number of customers who for ICT in India 2008” expects the are repeat buyers/total customers BI market in India to reach US$ • This rate is high that will let 46.8 million by 2012. India is a you know your products are attrac- huge market for business intelligence tive to customers and is fast growing with double digit figures, even in this slowdown. The 6. The rate of new overall BI market in India is at a customer nascent stage, with a huge uptapped opportunity for vendors to capture. • The number of new customers BI can deliver on this promise if de- you gain in a specific period of time ployed successfully because it can • Any sharp increase or decrease improve decision making and opera- here implies that either the business tional efficiency, which in turn drives is expanding or it’s losing customer the top line and the bottom line. ■ loyalty Sanjay Mehta is CEO, MAIA The state of BI adoption Intelligence Pvt. Ltd in India 70 • PROGRESSIVE GROCER • APRIL 2010 AHEAD OF WHAT’S NEXT WWW.PROGRESSIVEGROCER.COM l : :