Type: Critical Essays
Sample donated: Tonya Osborne
Last updated: December 29, 2019
Understanding customer behaviour and improving customerexperience is critical in competitivemarket place. Today’s customer expects personalized experiences with retailersand brands. To meet such expectations and to improve the business growth, companiesseek various customer analytics techniques and apply insights from customersacross the globe.
The dataset we have chosen for analysis consists of data of acompany called dunnhumby. Dunhumby enables Retailers and brands to tap into themost advanced customer analytics technique to provide the best services to meettheir customer’s expectations. As part of this project, we intend to applyvarious data analytics techniques which can help retailers to decide on theamount to be spent in acquiring customers. Data DescriptionThere are 7 tables provided for the analysis. These tables needsto be consolidated and the data needs to be cleansed, transformed, and turnedinto meaningful information before Analysis.Our Analysis is based on the Acquistionstage of Customer Lifecycle which provides useful insights to the company todecide upon the amount to be spent on acquiring the customers.Below is the listof the tables. 1)hh_demographic : This table consists of demographic information for households withthe details such as household_key,Age_Desc,Marital_status_code,Income_desc,homeowner_desc,hh_comp_desc,household_desc,hh_comp_desc,housegold_size_desc,kid_Category_desc.
Household_keyfield is unique, and can be used to join the tables as required. 2)Transaction_data : This table consists ofall products purchased by households with the details such ashousehold_key,Basket_ID,Day,Product_ID,Quantity,Sales_Value,Store_ID,Coupon_Match_Disc,Coupon_Disc,Retail_Disc,Trans_Time,Week_No.Household_keyuniquely identifies each household.Basket_ID uniquely identifies the purchaseoccasion. 3)Campaign_table: Thistable lists the campaigns received by each household in the study.
Eachhousehold received a different set of campaigns. 4)Campaign_desc : Thistable gives the length of time for which a campaign runs. So, any couponsreceived as part of a campaign are valid within the dates contained in thistable.
5)Coupon : This tablelists all the coupons sent to customers as part of a campaign, as well as theproducts for which each coupon is redeemable. 6)Coupon_redempt :Thistable identifies the coupons that each household redeemed. 7)Product dataset: Thistable contains information on each product sold such as type of product,national or private label and a brand identifier Techniques Below techniques will beimplemented to solve our business case of deciding on the customer acquisitioncost.
1)Market Basket Analysis: o On the basis of thebasket of the products purchased,what recommendations can be made by thecompany to improve the sales?o What offers can be givenby the company on the basis of the products purchased ?o Assess LTV for eachcluster.o Assess Retention Rate.o Identify the bestmarketing methods according to each cluster.o Assess which marketingsegment has the highest Return of Investment on marketing campaigns.o Which demographicfactors (e.
g. household size, presence of children, income) appear to affectcustomer spend?o Does direct marketingimproves customer acquisition?o How many customers arespending more/less with time?Which segment of customers are growing faster? 2)Next Best Offer 😮 What is the next bestoffer the company can provide to its customers? Key ChallengesSome of the challenges we may face as part of the analysisprocess are as follows:1) Sampling the data fortrain,test and validation datasets.2) Evaluating accuracy ofthe prediction model.3) Assessing overall returnof investment on the cost associated with acquiring the customers.