1.1 Describe methods of collecting data for customer research | Unit 41
Unit 41: Gather, Analyse and Interpret Customer Feedback
Unit reference number: D/506/2170 QCF level: 3
Credit value: 5
Guided learning hours: 24
Unit type: Competence
Unit summary
Gathering information about customers and their needs is an important and essential process for any business that wants to understand the needs of their customers.
This unit gives you the knowledge, understanding and skills to be able to gather and analyse customer feedback and interpret it to understand customers’ requirements and how well those requirements are being met.
Successful organisations know their customers and can anticipate their needs and requirements. These organisations gather and use customer feedback systematically so that they can shape their services to meet the challenges that the business environment provides. Information about customers is also used by the organisation to develop and improve its customer service. The gathering, analysis and interpretation of customer feedback can be done in a variety of ways, some formal and some informal. Good customer information provides a sound basis for all customer service transactions.
In this unit you will learn how to identify and use appropriate data collection techniques for the purpose of customer service feedback analysis. You will be able to choose an appropriate survey method to gather customer feedback data, use different methods to analyse the data and finally, you will be able to interpret the analysis findings to help recommend customer service improvements
Learning outcomes and assessment criteria
To pass this unit, the learner needs to demonstrate that they can meet all the learning outcomes for the unit. The assessment criteria outline the requirements the learner is expected to meet to achieve the unit.
Unit 41: Gather, Analyse and Interpret Customer Feedback
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Learning outcomes Assessment criteria
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1 Understand how to gather, analyse and interpret customer feedback
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1.1 Describe methods of collecting data for customer research
1.2 Explain random sampling techniques used to collect data
1.3 Explain how to evaluate bias in non-random samples
1.4 Explain the principles of questionnaire design
1.5 Assess the suitability of a range of techniques to analyse customer feedback
1.6 Explain techniques used to monitor the quality of data collected
1.7 Explain the use of software to record and analyse customer feedback
1.8 Explain the validation issues associated with customer feedback
1.9 Explain the importance of anonymising comments from customers who do not wish to be identified
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2 Be able to plan the collection of customer feedback on customer service issues
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2.1 Identify the objectives of collecting customer feedback
2.2 Justify the reasons for selecting different data collection methods
2.3 Develop a data collection and analysis plan that specifies the sampling frame, data collection and recording methods and timeframe
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Learning outcomes Assessment criteria
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3 Be able to gather customer feedback
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3.1 Collect customer feedback using the sampling frame identified in a customer service plan
3.2 Record data in a way that makes analysis straightforward
3.3 Record data in a way that makes analysis straightforward
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4 Be able to analyse and interpret customer feedback to recommend improvements
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4.1 Use data analysis methods to identify patterns and trends in customer feedback
4.2 Use the findings of a data analysis to identify areas for improvement to customer service
4.3 Present the findings of an analysis in the agreed format
4.4 Recommend improvements in response to the findings of an analysis
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Unit amplification: Unit 41: Gather, Analyse and Interpret Customer Feedback
AC1.1: Describe methods of collecting data for customer research
- Customer research: types, e.g. primary, secondary, qualitative, quantitative
- Methods: e.g. questionnaires, telephone surveys, customer panels, face to face interviews, focus groups, mystery shoppers, on-line surveys, social media
- Random sampling: definition of a sample population; probability sampling
- Techniques: sampling for population characteristics, e.g. all buyers of a certain product; sampling frame, e.g. an organised list of all members of a certain population; random number generation, e.g. using a computer program to generate a random number between say 1 and 1000; stratified sampling, e.g. reflecting the make-up of that population
- Non-random sampling: e.g. accidental, haphazard or convenience sampling; quota sampling; snowball sampling
- Evaluating factors: comparison to target population, selection bias, over representation and under representation of particular population groups, identifying non-responsive groups
- Principles: identifying the purpose of the questionnaire, e.g. survey objective; data collection methods; order of questions; length of questionnaire; question formats; how data will be processed; piloting questionnaires
- Questionnaire design: types of questions and responses, e.g. Likert Scales, Yes/No answers, multiple choice questions, numbered responses, open ended questions,
- Suitability: e.g. survey objectives, format of customer feedback, use of survey outcomes
- Techniques: types, e.g. functional analysis to identify optimal target market by demographic; geographical analysis; statistical techniques to describe data to include: mean, mode and median, range, standard deviation
- Techniques: data triangulation, investigator triangulation, theory triangulation, methodological triangulation, standardisation of results
- Computer Software: e.g. spreadsheets, database, specialist data analysis software, e.g. Nvivo, Atlasti,
- Recording data: e.g. coding results of a survey using qualitative data coding or quantitative data coding
- Analysing data: the process of inspecting, cleaning, transforming, and modelling data, using basic statistics of important variables, e.g. mean, mode and median, pictorial representations, e.g. scatter plots, correlations and association, cross-tabulations
- Validation issues: internal validity of customer feedback, e.g. removal of bias; barriers to contacting survey respondents; correlation of results; comparison to the population being surveyed; sample size,
AC1.2: Explain random sampling techniques used to collect data
AC1.3: Explain how to evaluate bias in non-random samples
AC1.4: Explain the principles of questionnaire design
AC1.5: Assess the suitability of a range of techniques to analyse customer feedback
AC1.6: Explain techniques used to monitor the quality of data collected
AC1.7: Explain the use of software to record and analyse customer feedback
AC1.8: Explain the validation issues associated with customer feedback
e.g. larger sample increases generalisability of results
AC1.9: Explain the importance of anonymising comments from customers who do not wish to be identified
- Anonymising: e.g. increased participation, honesty of responses, privacy of respondents, complying with Data Protection Act 1998, avoid restricting access and publication
Information for tutors
Suggested resources
Books
Hayes B − Measuring Customer Satisfaction and Loyalty: Survey Design, Use, and Statistical Analysis Methods (3rd Edition), (ASQ Quality Press, 2008)
ISBN 9780873897433
Hill N, Brierley J and McDougall R − How to Measure Customer Satisfaction (2nd Edition), (Gower Publishing, 2003) ISBN 9780566085956
Leland K and Bailey, K − Customer Service for Dummies (3rd Edition), (Wiley Publishing, Inc, 2006) ISBN 9780471768692
Assessment
This unit is internally assessed. To pass this unit the evidence that the learner presents for assessment must demonstrate that they have met the required standard specified in the learning outcomes and assessment criteria and the requirements of the Assessment Strategy.
To ensure that the assessment tasks and activities enable learners to produce valid, sufficient, authentic and appropriate evidence that meets the assessment criteria, centres should apply the Unit Assessment guidance and the requirements of the Assessment Strategy below.
Wherever possible, centres should adopt a holistic approach to assessing the units in the qualification. This gives the assessment process greater rigour and minimises repetition, time and the burden of assessment on all parties involved in the process.
Unit assessment requirements
This unit must be assessed in the workplace in accordance with the Skills CFA Assessment Strategy for Business Administration, Customer Service and Management and Leadership, in Annexe A. Simulation is not allowed for this unit. All evidence of occupational competence should be generated through performance under workplace conditions; this includes evidence of achievement for knowledge- based learning outcomes and associated assessment criteria.
Unit assessment guidance
This guidance supports assessors in making decisions about how best to assess each unit and the evidence needed to meet the assessment requirements of the unit. Centres can adapt the guidance for learners and the particular assessment context, as appropriate.
The main evidence collection methods for demonstrating achievement of learning outcomes 2, 3 and 4 are likely to be a combination of observation, review of the learner’s work products and professional discussion. For AC2.1 – AC2.3 the learner’s work products may include planning notes (including the calculation of costs for data collection) and the plan and resources (e.g. questionnaire, interview questions) produced for the collection and analysis of data. Within the discussion, the learner could use these products as a basis for justifying different elements of the plan and how it will meet the customer focus objectives.
The evidence from observing the collection of customer feedback for learning outcome 3 should be supported by a discussion around the collected data (AC3.1 – AC3.3); the professional discussion could focus on the justification of how the data is recorded, how data collection was monitored to ensure compliance with the sampling frame and the rationale for the actions taken to verify compliance with the relevant policies and procedures.
The supporting evidence for AC4.1 – AC4.3 is likely to be work products that the learner has produced in the analysis and interpretation of the customer feedback; for example, for AC4.1 the learner might produce a report, graphs and/or tables based on the data that has been collected. It is essential that the work products can provide evidence of the learners understanding of the data analysis techniques that have been used and where this is not possible then the professional discussion should be used to demonstrate a sufficiency of knowledge. Witness testimony could also be used to support the learner’s competence over time.
Evidence to confirm the achievement of learning outcome 1 could be integrated into the professional discussion for learning outcomes 2, 3 and 4 which would give the learner the opportunity to link and apply their knowledge to their workplace activities as well easing the burden of assessment for both the assessor and the learner. There are plenty of opportunities to relate the assessment of the knowledge requirements to the competence activities. For example, the assessment for the knowledge in AC1.1 – AC1.4 could be incorporated in the supporting professional discussion for the competence activities for AC2.1 – AC2.3. Similarly, the same approach could be applied for the knowledge in AC1.5 – AC1.9 in relation to the competence activities across the assessment criteria in learning outcomes 3 and 4. Alternatively, evidence could be provided through the use of a reflective account, where the learner could also address the underpinning knowledge and understanding requirements for learning outcomes 2, 3 and 4. Learners’ responses or statements to meet the knowledge requirements must be at a sufficient depth and breadth to meet the level of demand of the operative verbs.
Evidence of Recognition of Prior Learning (RPL) can also be used within the unit to confirm competence. Wherever possible, the learning outcomes in this unit should be assessed holistically across the qualification.
Unit 41: Gather, Analyse and Interpret Customer Feedback
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