Ohio University
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Customer Analysis & Relationship Building = Sales/Revenue

MARK4360
Closed
Douglas College
Douglas College
New Westminster, British Columbia, Canada
Brita Cloghesy-Devereux
Brita Cloghesy-Devereux
Faculty - Marketing
(2)
5
Timeline
  • February 15, 2024
    Experience start
  • April 6, 2024
    Experience end
Experience
1/1 project matches
Dates set by experience
Preferred companies
New Westminster, British Columbia, Canada
Any company type
Any industries

Experience scope

Categories
Customer segmentation Digital marketing Marketing analytics Data analysis Marketing strategy
Skills
relationship building customer data management promotional strategies customer analysis sales
Learner goals and capabilities

How well do you know your customers? Are you targeting the RIGHT customers? Do you waste resources on low-value or unprofitable customers? Here’s how our students can help, by: analyzing your customer data/database(s); extrapolating your three best customer segment opportunities; creating three unique customer profiles / ‘relationship policies’; and, developing targeted, segment-specific promotional strategies. Based on your organization’s individual needs, this outline can be adapted.

Learners

Learners
Undergraduate
Any level
35 learners
Project
25 hours per learner
Educators assign learners to projects
Teams of 6
Expected outcomes and deliverables

Per team (usually 5-6 teams)

  • Presentation [10 mins./team] – depending on your availability (and Covid), either in-class or by on-line video conference
  • Final report [approximately 6 pages] - including the aforementioned sections, supported by visuals, grids, graphics, charts etc.
Project timeline
  • February 15, 2024
    Experience start
  • April 6, 2024
    Experience end

Project Examples

Requirements

Based on previous experience, to ensure the best results for you and the students, this project needs to be supported by two important elements: good data and collaboration. You providing robust data forms the basis of student analysis and future recommendations; your participation and involvement leads to better outcomes and useful results.

Data presents itself in a variety of formats. Here are some historical examples -- by no means prescriptive or exhaustive -- that have proven useful: customer data (segment analysis, purchase behaviour); product data (description, SWOT analysis, sales/marketing, pricing); industry/market data (general environment, competitive analysis, market research); CRM data (if you have it – corporate or account information; lead source, score or status etc.).

Students can sign a standard non-disclosure agreement (NDA), if desired, prior to the project launch to support data privacy.

The final report will include:

  1. Overview - a brief overview of your industry, followed by an executive summary of key findings.
  2. Data mining - an analysis of your data sets, including a deep understanding of your current situation which could include: customers types, sales, distribution channels, marketing/media channels, a compare/contrast summary of figures year-over-year by sales numbers, accounts, regions etc. – all dependent on types of data provided.
  3. Segmentation - the identification/justification of your company’s THREE (3) best customer segment opportunities
  4. Persona - THREE (3) personas, each representing the goals and behaviours of the above hypothesized segment groups – with a goal to understanding each segment on three levels, as: Buyers, Users, People.
  5. Relationship Policy - THREE (3) business-customer relationship policies that articulate (per segment) a unique value proposition, customization, pricing and preferred communication channels.
  6. Promotional Campaign – THREE (3) high level promotional campaigns – ie: the translation of each relationship policy into sales.
  7. Summary – a brief synopsis; final insights and conclusions.