Customer Segmentation

Location: Hawthorn East, VIC

Duration: 5 months

Proposed start date: ASAP

Project Background

The business is a retail leader in Australia and New Zealand and a supplier to project builders, commercial tradespeople and the housing industry.

The business’ total revenues are mostly generated from retail customers. The commercial customer profile differs further from retail customers, requiring a higher touch and more individualised relationships.

Commercial customers transact using a membership to access discounted pricing and credit facilities. This enables each commercial customer’s touch points to be combined.

Research to be Conducted

Specific use cases are currently going through prioritisation and scoping. Most uses cases will be underpinned by customer segmentation varied dimensions based on the business driver.

Toolsets (all available):

  • Python, R
  • Data bricks
  • Excel
  • Teradata SQL

Potential use cases:

  1. Extended product purchases:
    • Identification of sales opportunities within customer groups (defined as providing all aspects in the construction of a new building). Create profiles based on purchasing behaviour. Run gap analysis on individual purchasing behaviour against segment profile to identify leads for account managers and/or direct marketing communications.
  2. Targeted direct communications:
    • eDM (Electronic Direct Mail)
      Product marketing emails to customers are currently supplier and merchandising driven this use case will look to use segmentation to better utilise this form of marketing.
  3. Price optimisation:
    • Understanding optimised pricing structures for commercial customers.

SKILLS REQUIRED

We are looking for a PhD student with the following:

ESSENTIAL

  • Data & statistical modelling (i.e. machine learning, supervised & unsupervised learning, data mining and other like techniques)
  • Programming in data related language (Python, SQL and R)

DESIRABLE

  • Customer Behaviour Analytics
  • Segmentation
  • Price elasticity of demand

Expected Outcomes

The collaboration will take place within an Agile framework. This approach means our goal is to identify specific use cases where analytics can deliver a transformational change. Rapid prototyping is used to test and learn where the most feasible opportunities exist to add value.

Expected outcomes during the period of engagement are:

  • Establish minimum data asset required to deliver the customer analytics use case.
  • Software model: New customer segmentation engine, based on purchasing behaviour, that can be trained for different use cases.
  • Identification of critical data gaps required to evolve the segmentation model for use case and preparation for use case backlog.
  • Prototype for use case 1, that can be piloted and scaled.
    • Example: Targeted direct communications: eDM use case is expected to deliver a stand-alone segmentation engine to generate
      • Flat file output to be consumed by merchandising team, and
      • Integrations to eDM delivery platform and our CRM platform.
  • Identify ways data quality can be improved and provide feedback to relevant business owners

Additional Details

The intern will receive $3,000 per month of the internship, usually in the form of stipend payments.

It is expected that the intern will primarily undertake this research project during regular business hours, spending at least 80% of their time on-site with the industry partner.  The intern will be expected to maintain contact with their academic mentor throughout the internship either through face-to-face or phone meetings as appropriate.

The intern and their academic mentor will have the opportunity to negotiate the project’s scope, milestones and timeline during the project planning stage.

Applications Close

22 May 2019

Reference

APR – 0846

  • Justin Mabbutt Business Development - VIC
    (03) 8344 6991 / 0413 050 952
    j.mabbutt@aprintern.org.au