Customer Analysis & Relationship Building = Sales/Revenue

MARK4360
Closed
Douglas College
New Westminster, British Columbia, Canada
Brita Cloghesy-Devereux
Faculty - Marketing
(2)
3
General
  • Undergraduate; 4th year
  • 35 learners; teams of 5
  • 25 hours per learner
  • Dates set by experience
  • Learners self-assign
Preferred companies
  • 2/3 project matches
  • Anywhere
  • Academic experience
  • Any
  • Any
Categories
General Data analysis Market research Customer segmentation Marketing strategy Marketing analytics
Skills
customer relationship management marketing strategy data mining research segmentation analysis
Project timeline
  • October 21, 2022
    Experience start
  • October 22, 2022
    Project Launch – approx.30 mins.
  • November 3, 2022
    Project Action Plan – approx.1.5 hrs.
  • November 24, 2022
    Q&A - approx. 30 mins.
  • December 1, 2022
    Final Presentation (Dec 1 & 3) – approx.45 mins. per class (Your attendance is optional)
  • December 3, 2022
    Experience end
Overview
Details

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.

Learner skills
Customer relationship management, Marketing strategy, Data mining, Research, Segmentation analysis
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 Examples

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.
Additional company criteria

Companies must answer the following questions to submit a match request to this experience:

The project’s success is dependent upon robust data and good collaboration: 1. Provide company data, ideally 3-5 yrs. (to allow for compare/contrast, year-over-year); provide access to that data, as data mining/analysis will form the basis of team strategies. Also, be involved -- client participation is appreciated.

Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address student questions.

Be available to connect (via phone or Zoom) with the instructor to initiate the relationship and confirm the scope and expectations are an appropriate fit for the course.