customer relationship management
learning objective
LO1 describe the customer relationship management process
LO2 understand how customer shopping data are collected
LO3 explain the methods used to analyze customer data and identify target customers
LO4 outline how retailers develop their frequent-shopper programs
LO5 explain verious ways to implement effective CRM programs
Jim Lewis, founder and CEO, enhanced retail solutions
in 2002, after working in store management in south Florida and merchandise management at JCPenney's corporate headquarters in Plano, Texas, I decided to open my own software/consulting firm.
At the time, retailers and vendors were collecting massive amounts of sales and inventory data that helped profile their customers' purchase behaviors [now referred to as "big data"], but they were not converting this data into actionable information they could use to make better decisions.
The first software applications we developed were for vendors.
A number of retailers give vendors access to the POS data associated with the vendor's sales.
But most vendors do not have the capability to crush this massive data describing every transaction or how to make it useful in optimizing sales and inventory at the store level.
So we developed software that summarizes the vendor's performance much like the dashboard on a car.
It allowed the vendor to communicate more effectively with its retail buyers and make actionable recommendations that the buyers appreciated.
Soon after its introduction, many retail buyers recognized its benefits and now use the software.
While our initial activities provided vendors and retailers with a tool to access how well they are performing, we now are concentrating on examining why vendors and retailers are doing well or poorly.
For example, one of our apparel clients was concerned when a large, national retail customer was going to drop their line due to low sales.
When we analyzed their sales data with the retailer, we found that the client's line was selling very well in some stores and poorly in others.
Using the census data we have in our database, we found that the stores that were doing well for the vendor's line were in trading areas dominated by minority consumers.
customer relationship management
learning objective
LO1 describe the customer relationship management process
LO2 understand how customer shopping data are collected
LO3 explain the methods used to analyze customer data and identify target customers
LO4 outline how retailers develop their frequent-shopper programs
LO5 explain verious ways to implement effective CRM programs
Jim Lewis, founder and CEO, enhanced retail solutions
in 2002, after working in store management in south Florida and merchandise management at JCPenney's corporate headquarters in Plano, Texas, I decided to open my own software/consulting firm.
At the time, retailers and vendors were collecting massive amounts of sales and inventory data that helped profile their customers' purchase behaviors [now referred to as "big data"], but they were not converting this data into actionable information they could use to make better decisions.
The first software applications we developed were for vendors.
A number of retailers give vendors access to the POS data associated with the vendor's sales.
But most vendors do not have the capability to crush this massive data describing every transaction or how to make it useful in optimizing sales and inventory at the store level.
So we developed software that summarizes the vendor's performance much like the dashboard on a car.
It allowed the vendor to communicate more effectively with its retail buyers and make actionable recommendations that the buyers appreciated.
Soon after its introduction, many retail buyers recognized its benefits and now use the software.
While our initial activities provided vendors and retailers with a tool to access how well they are performing, we now are concentrating on examining why vendors and retailers are doing well or poorly.
For example, one of our apparel clients was concerned when a large, national retail customer was going to drop their line due to low sales.
When we analyzed their sales data with the retailer, we found that the client's line was selling very well in some stores and poorly in others.
Using the census data we have in our database, we found that the stores that were doing well for the vendor's line were in trading areas dominated by minority consumers.
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