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Technology Corner

CUSTOMER ANALYTICS in RETAIL - Know Thy Customers

PART II


Using Customer Analytics in Retail

Deploy Customer Analytics in Retail to leverage metrics from hundreds of business questions to resolve three common customer issues:

  • Visibility— achieved through easy access to customer data and guided analysis
  • Accountability— achieved through distribution of scorecards
  • Reliability— achieved through optimizing, integrating, and consolidating data into a single view

Visibility— Accurate reports, on time

Acting on trends in customer behavior; whether in sales, product, or customer profiles; can often mean the difference between success and failure. Acting on positive trends while they are happening can drive increased sales, satisfaction, and loyalty. Spotting negative trends too late in the game can result in lost customers. Customer Analytics in Retail lets you identify both positive and negative trends and deliver critical information and analysis in a format that enables quick decisions. Pre-built analytic pathways ensure that the right questions are always asked and the right information is always returned. Sales can access specific customer information such as activity at a particular customer over a certain period of time. Marketing can study trends in product lines. Finance can easily extract trends in sales, gross margins, revenue, and other relevant statistics. Users can drill down by customer, product margin, or revenue by product line, and get the most up-to-date results within minutes rather than days or weeks.


Accountability— Customer metrics for all

Companies derive maximum value from their customer base when accountability for sales, production, and customer profiling are integrated and aligned. Each department needs to understand its respective area of accountability and the impact that its particular metrics have on other areas. Customer Analytics in Retail supports company-wide alignment through scorecards that display metrics and KPIs. Employees can proactively manage their areas and see how accountability for other areas is distributed throughout the company. Performance issues can be identified and analyzed, and resulting insights communicated to those responsible. This ensures that tactics are aligned with strategic goals across the company.


Reliability— Turn data into action

Sales, product, and customer data often reside in a variety of databases, ERP systems, and unconnected spreadsheets across your company. Changes in one source are not reflected in another, leaving customer facing employees to work with outdated or inaccurate information. Customer Analytics in Retail integrates sales, product, and customer data into one central source of data and metrics for a complete view of your customers that everyone in the company can trust. 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 optimized for a consistent pool of performance metrics and KPIs.


Typical Customer Dimensions & Measures in Retail
  • Regular, normal, occasional customer (based on frequency / duration of visits)
  • Professional, academic, teen, household, bachelor (based on products bought)
  • Service sensitive, price sensitive
  • Power, normal, entry level customer
  • Demographics, customer type (business-consumer, mass based)
  • Average Revenue per month, expected yearly revenue
  • Use of loyalty programs
  • Seasonality indexes
  • Statistically derived clusters (homogenous groups of customers)

Customer Analytics in Retail
Identify good customers by
  • Turnover
  • Number of transactions
  • Profit
  • 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
  • Customers with mobile telephone numbers
  • Customers with email addresses

Identify customers abusing returns policy

Identify "promotion friendly" customers