The Data

Hull Training and Adult Education provided us with anonymised details of all enrolments to the service during the 2021/22 academic year.

This data included, for every enrolment,:

  • The learner’s postcode
  • Information on the course / area of learning
  • The course completion status e.g. completed / withdrawn / continuing
  • The fee status e.g. paid in full / JSA remission / 16 – 18 remission
  • The course learning site
  • The students nationality / ethnicity



    • Applying The Segmentation

    Using the learner’s postcode, the Insight Team were able to assign each Hull learner to one of their 13 bespoke customer segments.

    You can find out more about the segmentation model here:  Hull Data Observatory – Customer Insight

    Overall Segment Engagement Rates

    The first step was to calculate how many learners / service users came from each segment.

    Since some of the customer segments are naturally much larger than others, then we would naturally expect more learners to come from specific segments.

    Therefore, we standardise the data by calculating the rate of engagement based on the relative size of the 16+ population within each segment.

    This allows us to directly compare the rate of engagement between segments.

    This clearly shows that the most engaged segments are:

  • Group C: Public Renting Young Families in Areas of High Deprivation
  • Group L: Young Diverse Families in Private Rent Flats and Terraces
  • Group G: Affluent Professionals in Owner Occupied Large Houses



    • This allows the Hull Training and Adult Education Service to ask questions like:

  • Are these segments their target audience?
  • Is engagement as high as it should be / could be in these segments?
  • What about segments with low engagement?
  • Would we expect low engagement in these segments?
  • Is there anything we can do to increase engagement in those segments?



    • Engagement With Specific Areas of Learning

    The next step was to look in more detail at:

  • The areas of learning done by each segment
  • The breakdown of learners in each area of learning



    • Whilst these two things sound similar – they show two fundamentally different things.

    Lets take Group C, as the most engaged customer segment, as an example.

    Across all courses, Group C are more likely than average to enrol in the following areas of learning:

  • Construction
  • Technology
  • Business and Digital



    • and less likely than average to enrol in the following areas of learning:

  • ASL Community Learning
  • ICT
  • Family learning
  • Vocational





    • When we look at the breakdown of learners in Construction courses, Group C are the most engaged segment.


    So since Group C is high in both this chart and the first chart then this means that Construction courses are an “easy sell” for this segment.






    When we look at the breakdown of learners in Vocational courses, Group C are the least engaged segment.


    So since Group C is low in both this chart and the first chart then this means that Vocational courses are a “hard sell” for this segment.






    Finally, when we look at the breakdown of learners in Vocational English and Maths courses, Group C are the most engaged segment.

    However, they were not significantly high for this area of learning in the first chart.

    This means that Vocational English and Maths courses have “room for growth” for this segment.





    Segmenting Additional Information

    The next step was to segment the other indicators to enrich our understanding of learners in each segment.

    Continuing to use Group C as an example:

    For example, now we know that Group C are also:

  • More likely than average to withdraw from courses
  • Less likely than average to pay their fees in full



    • Combining with Existing Segment information

    The final step was to combine the above learning, with our existing knowledge of the segments to inform marketing and service provision.

    Still using Group C as an example we know the following from previous research:

    Their key barriers include:

  • Lack of facilities / venues nearby
  • Lack of transport
  • Lack of info about what’s available
  • Lack of time / family commitments
  • Lack of cost
  • Perception that education / training isn’t for them



    • They are experiential decision makers: Open to new ideas, concepts and offers if they are presented in an original and entertaining way.

    Their key influences are:

  • Media: Tabloid newspapers and local / free newspapers.
  • Friends and Family: Particularly for big decisions or where they feel there is too much choice.
  • Pester Power: As families with children, messages get filtered through schools and other community activities their children are involved with.
  • TV: Big TV watchers and responsive to TV advertising, particularly with a strong emotional message.