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Equip’s psychographic segmentation helps close gender gap

Dan Purves




The four per cent reduction in the superannuation savings gender gap for 45-55 year olds at Equip Super has been attributed to improved communication from the use of psychographic segmentation.

Psychographic segmentation divides membership into groups based on traits, values and attitudes derived from data such as number of visits to the website, pages visited, switching behaviour, salary sacrifice, voluntary contributions, calls to the helpline and insurance position.

The strategy has also enabled the super fund to report how effective campaigns have been among different member segments, as it allows a greater understanding than is typically available from splits along demographic lines, said Geoff Brooks, executive officer of strategic marketing and communications at the $7 billion super fund.

“Our members’ psychographic cuts across age segments,” said Brooks. ”You can have a 30-year-old who is passionate about their investments and a 50-year-old who is passive about their investments and it’s to do with personality type.”

“We’ve got a bunch of people in the under-35 age group who are 100 per cent invested outside the default option. Some have 100 per cent in growth and on the other side we have some with 100 per cent in conservative. It reflects the personality and it’s a matter of tuning the communication to suit that person and demonstrate you understand and know about them.”

Brooks added towards the end of March the gender savings gap had closed by 4 per cent for women aged between 45-55 years old as a result of the move-the-dial campaign, which had been using insights from psychographic segmentation to more effectively deliver communications.

The ability to launch campaigns based on member segmentation came after seven months of research that involved heat mapping membership activities. Out of this, Brooks’ team of two analysts were able to identify 26 segments based on behaviour. They then aggregated members into eight categories plus pensions (split into advised and non-advised), which were then overlaid with Roy Morgan’s Helix Persona, though this had to pass the “sense test”.

“We had one example where Roy Morgan Helix Personas told us members in an area were probably in a lower socioeconomic group, but we had power station workers there who are quite well-paid by any standard so, we had an outlier group. We couldn’t just rely on the Roy Morgan data; we had to look and understand members as well,” Brooks said.

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    Employer retention

    Brooks added the insights from psychographic segmentation were also useful in deepening relationships with employers – a strategy that should be pursued as super funds needed to move beyond their traditional “utilitarian” role to become “intrinsic to their offer to employees”.

    “It’s also about employer retention because they are the distribution of the product, particularly for industry funds,” Brooks said.

    “It’s important to have a retention policy for employers as well as employees, so the more threads you can build to employers the stronger those ties are going to be in the future when super arrangements are reviewed.”

    Psychographic segmentation has helped Equip Super to speak to employers on how employees are going collectively, how the workplace is performing against others, and what factors are causing this behaviour or not causing it.

    “We should think about employers as communities in the same way you’d think demographically about where person lives as influencing their experience and behaviour,” Brooks said.

    “If you think about larger employers, they are a collection of people sharing a collection of experiences, similar interests and priorities throughout the day. You start thinking differently; about what we talk to these people about as a community.”

    “Therefore, the conversation extends beyond super and you are contributing some value add in other areas because there are specs about their employees lives [as a community] which we can see which they don’t see.”