NTISthis.com

Evidence Guide: SIRXECM001 - Monitor and interpret online data analytics

Student: __________________________________________________

Signature: _________________________________________________

Tips for gathering evidence to demonstrate your skills

The important thing to remember when gathering evidence is that the more evidence the better - that is, the more evidence you gather to demonstrate your skills, the more confident an assessor can be that you have learned the skills not just at one point in time, but are continuing to apply and develop those skills (as opposed to just learning for the test!). Furthermore, one piece of evidence that you collect will not usualy demonstrate all the required criteria for a unit of competency, whereas multiple overlapping pieces of evidence will usually do the trick!

From the Wiki University

 

SIRXECM001 - Monitor and interpret online data analytics

What evidence can you provide to prove your understanding of each of the following citeria?

Access data.

  1. Identify organisational data collection needs.
  2. Select methods for data collection and analysis.
  3. Use selected methods to collect required data according to organisational data collection policies and procedures.
  4. Store collected data according to organisational data collection policies and procedures and legal and ethical data storage requirements.
Identify organisational data collection needs.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Select methods for data collection and analysis.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Use selected methods to collect required data according to organisational data collection policies and procedures.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Store collected data according to organisational data collection policies and procedures and legal and ethical data storage requirements.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Analyse data.

  1. Assess quality and relevance of data based on organisational data collection needs.
  2. Cleanse and filter data to ensure captured data is relevant to organisational data collection needs.
  3. Identify trends in performance through data mining and statistical analysis.
  4. Analyse data to identify and determine impact of internal and external activity.
  5. Determine return on investment of paid data collection and analysis.
Assess quality and relevance of data based on organisational data collection needs.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Cleanse and filter data to ensure captured data is relevant to organisational data collection needs.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Identify trends in performance through data mining and statistical analysis.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Analyse data to identify and determine impact of internal and external activity.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Determine return on investment of paid data collection and analysis.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Report on findings.

  1. Use data analysis to identify and report on strengths, weaknesses, threats and opportunities.
  2. Make recommendations for improvements based on findings.
  3. Present findings and recommendations in appropriate format.
  4. Communicate findings and recommendations to relevant personnel.
Use data analysis to identify and report on strengths, weaknesses, threats and opportunities.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Make recommendations for improvements based on findings.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Present findings and recommendations in appropriate format.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Communicate findings and recommendations to relevant personnel.

Completed
Date:

Teacher:		 Evidence:

 

 

 

 

 

 

 

Assessed

Teacher: ___________________________________ Date: _________

Signature: ________________________________________________

Comments:

 

 

 

 

 

 

 

 

Instructions to Assessors

Evidence Guide

ELEMENTS

PERFORMANCECRITERIA

Elements describe the essential outcomes.

Performance criteria describe the performance needed to demonstrate achievement of the element.

1. Access data.

1.1. Identify organisational data collection needs.

1.2. Select methods for data collection and analysis.

1.3. Use selected methods to collect required data according to organisational data collection policies and procedures.

1.4. Store collected data according to organisational data collection policies and procedures and legal and ethical data storage requirements.

2. Analyse data.

2.1. Assess quality and relevance of data based on organisational data collection needs.

2.2. Cleanse and filter data to ensure captured data is relevant to organisational data collection needs.

2.3. Identify trends in performance through data mining and statistical analysis.

2.4. Analyse data to identify and determine impact of internal and external activity.

2.5. Determine return on investment of paid data collection and analysis.

3. Report on findings.

3.1. Use data analysis to identify and report on strengths, weaknesses, threats and opportunities.

3.2. Make recommendations for improvements based on findings.

3.3. Present findings and recommendations in appropriate format.

3.4. Communicate findings and recommendations to relevant personnel.

Required Skills and Knowledge

ELEMENTS

PERFORMANCECRITERIA

Elements describe the essential outcomes.

Performance criteria describe the performance needed to demonstrate achievement of the element.

1. Access data.

1.1. Identify organisational data collection needs.

1.2. Select methods for data collection and analysis.

1.3. Use selected methods to collect required data according to organisational data collection policies and procedures.

1.4. Store collected data according to organisational data collection policies and procedures and legal and ethical data storage requirements.

2. Analyse data.

2.1. Assess quality and relevance of data based on organisational data collection needs.

2.2. Cleanse and filter data to ensure captured data is relevant to organisational data collection needs.

2.3. Identify trends in performance through data mining and statistical analysis.

2.4. Analyse data to identify and determine impact of internal and external activity.

2.5. Determine return on investment of paid data collection and analysis.

3. Report on findings.

3.1. Use data analysis to identify and report on strengths, weaknesses, threats and opportunities.

3.2. Make recommendations for improvements based on findings.

3.3. Present findings and recommendations in appropriate format.

3.4. Communicate findings and recommendations to relevant personnel.

Evidence of the ability to complete tasks outlined in elements and performance criteria of this unit in the context of the job role, and:

identify organisational data collection needs and follow organisational policies and procedures to collect performance data across one sales period

undertake an analysis of data captured during the above sales period to determine:

impact of internal activity

impact of external activity

customer insights

ecommerce performance

data trends

use data analysis findings to document:

strengths

weaknesses

opportunities

threats

recommendations for improved performance.

Demonstrated knowledge required to complete the tasks outlined in elements and performance criteria of this unit:

key legal and ethical considerations as related to data collection and storage

role of data collection and analysis in ecommerce

current ecommerce data collection methods:

benefits

limitations

role of data collection in identifying:

site visits

origin of customer traffic

paths to purchase

shopping cart abandonment

impact of internal and external activities

product viewings

customer behaviours online

future behaviours

social media impacts

customer relationship management and loyalty

click-throughs

net promoter score

search engine marketing and search engine optimisation

data quality measures:

validity

consistency

timeliness

accuracy

integrity

common analytical terminology used in an online sales environment

techniques to analyse and draw conclusions from data

formats for reporting data analysis.