Application
This unit describes the skills and knowledge required to select data sources and apply analysis tools to identify trends in data that inform industry directions for a product, brand or organisation.
It applies to individuals working in a variety of marketing communications occupational roles who have responsibility for undertaking data mining to support plans and strategy development in an integrated marketing environment.
No licensing, legislative or certification requirements apply to this unit at the time of publication.
Elements and Performance Criteria
ELEMENT | PERFORMANCE CRITERIA |
Elements describe the essential outcomes. | Performance criteria describe the performance needed to demonstrate achievement of the element. |
1. Determine purpose of data mining | 1.1 Identify and review relevant client or organisational requirements for data mining 1.2 Confirm potential uses of data mining outcomes and recommendations 1.3 Recognise privacy and other requirements within current legislation, regulation and organisational policy that impact on data mining activities |
2. Identify data sources | 2.1 Identify available data sources from public, client and organisation systems 2.2 Negotiate access rights and intellectual property release for relevant data sources 2.3 Rank and prioritise data sources for validity, reliability and completion rates |
3. Apply data mining techniques | 3.1 Select appropriate tools and techniques suitable for the type and expected degree of complexity in data analysis 3.2 Classify data according to relevant factors including type, content, relationships, location, demographics and maturity 3.3 Analyse data to identify patterns, clusters and relationships 3.4 Use suitable graphical tools to visualise aggregated data |
4. Report and recommend on findings | 4.1 Assess results of data mining against requirements in order to draw relevant insights 4.2 Weight insights for reliability and validity 4.3 Report data mining process and outcomes in suitable format to support the organisation's knowledge base 4.4 Document lessons learned during the processes for future use |
Evidence of Performance
Evidence of the ability to:
determine data mining requirements from client and organisational sources
negotiate intellectual property rights release
apply current industry tools and techniques to a current customer data set to identify patterns and cluster trends
prepare graphical representation of data patterns
make recommendations based on an analysis of data mining results.
Note: If a specific volume or frequency is not stated, then evidence must be provided at least once.
Evidence of Knowledge
To complete the unit requirements safely and effectively, the individual must:
list the various uses of data mining in the context of marketing communications
identify privacy and other relevant legislation related to public and private data
explain the terms 'data validity', 'reliability' and 'completion'
compare the characteristics of public, client and organisational data sets
identify and list the uses of current industry tools and techniques used in data mining.
Assessment Conditions
Assessment must be conducted in a safe environment where evidence gathered demonstrates consistent performance of typical activities experienced in the marketing communications field of work and include access to:
relevant legislation and regulations
communications equipment and technology
relevant workplace documentation and resources
case studies or, where possible, real situations
industry software packages and apps (where applicable).
Assessors of this unit must satisfy the requirements for assessors in applicable vocational education and training legislation, frameworks and/or standards.
Foundation Skills
This section describes language, literacy, numeracy and employment skills incorporated in the performance criteria that are required for competent performance
Skill | Performance Criteria | Description |
Reading | 1.1-1.3, 2.1, 3.2, 3.3, 4.1 | Identifies and analyses complex texts to determine legislative, regulatory, organisational and client requirements Reviews a range of texts to comprehend both end purpose and inherent risks of data mining Reads reported information to rank and analyse outcomes against project goals |
Writing | 1.2, 2.2, 3.4, 4.1-4.4 | Integrates information from a number of sources to develop materials suitable for purpose and audience |
Oral Communication | 2.2, 4.3 | Presents information and seeks input using structure and language appropriate to audience |
Numeracy | 3.1-3.4, 4.1 | Selects and uses appropriate tools to analyse data effectively Classifies, analyses and aggregates data effectively, using visualisation methods where appropriate |
Navigate the world of work | 1.1, 1.3, 4.1 | Recognises and follows legislative requirements and organisational policies and procedures associated with data mining |
Interact with others | 2.2, 4.3 | Selects and uses appropriate conventions and protocols when communicating with internal stakeholders and external suppliers to reach agreement |
Get the work done | 2.2, 2.3, 3.1-3.4, 4.1-4.4 | Plans and organises workload and processes to ensure compliance with organisational policies and procedures, and legislative requirements Systematically analyses information and data by identifying and evaluating patterns against set criteria Draws insights from reported information, enabling increased understanding within the organisation and opportunities for improvement |
Sectors
Business Development – Marketing