By Simon Guttmann and Karen Lenane
All superannuation funds seek to offer a unique value proposition to their members. For some, this is led by a deep understanding of a specific industry or workplace. But over time, members change jobs, employers, industries, and in some instances, funds. While a few funds have achieved scale and maintained a dominant position in their specific industry, for many this proposition has been diluted.
The dilution of industry alignment as a compelling value proposition has not readily been replaced.
Larger funds have a value proposition centred around scale benefits: lower costs and access to investments. There is also a strong shift towards “purpose”, with several funds promoting the positive impact of their investments.
Many funds espouse a unique and differentiated value proposition for members, but does this really deliver? Are member needs by segment understood well enough to deliver a differentiated value proposition that members respond to?
The Your Future, Your Super reforms will increase the pressure on funds to articulate and deliver a differentiated value proposition for members. Unless your fund is exposed to retail, hospitality or a handful of other industries, stapling will significantly reduce the flow of new member accounts.
Funds will need to differentiate themselves, with a clear value proposition, to attract and retain members.
All funds face a trio of challenges: to engage meaningfully with different member segments, to demonstrate a clear value proposition, and to provide relevant interactions with a broad demographic of members.
For all three, understanding member behaviour is key. But how is this possible when most members have few touchpoints with their fund?
Standard member feedback such as brand and service Net Promoter Score (NPS) or Customer Satisfaction Score (CSAT) have limitations because they rely on members contacting their fund through available channels. When faced with the challenge of low member engagement, how do super funds start to understand members’ behaviour to develop relevant interactions?
We believe achieving this requires two key steps.
Dynamic profiling is the ability to leverage real-time data to create groups of members that change constantly as members meet (or fail to meet) defined criteria. It enables member segment to be continuously updated with new information about the member as it comes in. Each segment can be personalised by product, service and interaction level to fit the needs of the fund.
Dynamic profiling means a fund can target member cohorts based on recent actions and stated preferences.
For example, low-interaction members can be identified by understanding how long it has been since they accessed an app or website, contacted a service centre, made a contribution, adjusted investments or insurance, or participated in early release.
Segments can predict behaviour based on actions, indicating what is important to members. This will help to identify how best to communicate with them – and nudge behaviour.
Dynamic profiling avoids the high cost and scattergun approach of mass messaging, reduces the risk of communication of untargeted information, and provides data to develop and measure ongoing interaction. It means each member interaction will be highly relevant and over time can predict behaviours.
It is also a big benefit to fund members, because it nudges them to update their details and adjust their investment options to better suit their retirement goals and risk tolerance.
Dynamic profiling requires accurately capturing touch points and developing a meaningful member interaction that will be valued. Collecting and integrating data and developing prescriptive analytics (analysing raw data to make better business decisions) is key to understanding member behaviour and experiences, enabling the development of messaging relevant to those members.
Collecting the right data means integrating information about your members from internal sources (such as balance and account information and clickstream data) and external sources (such as social media activity) in accordance with your privacy and statutory obligations.
This data needs to be collected and integrated continuously. Member identity needs to be consistent across databases, channels, devices and internal organisational units. This means a member who appears in your core systems, in web analytics and in a member database is recognised as the same person.
Prescriptive analytics goes beyond predictive analytics to recommend – or automate – what message should be communicated to a member and at what time. In the example of the low-interaction members discussed earlier, these members could be automatically added to a new segment and, if appropriate, sent a targeted communication that is relevant to their recent engagement. Clusters of members who have a similar profile or belong to a similar segment could be sent a relevant communication.
For choice funds, the design and distribution obligations that commenced in October 2021 bring into sharper focus the need to determine exactly who their target members, to ensure their offer is appropriate, and to distribute products accordingly.
Prescriptive analytics analyses large volumes of data and enables automated analysis to help with decision making. It is a time- and cost-effective solution for dynamic segmentation. Funds that ignore it risk being left behind.
Get in touch to discuss how we can help assess your member data and data strategy, identify gaps and advise on ways to capture and analyse data to move you towards dynamic profiling.
Co-authored by Karen Lenane during her time as a Director at Nous.
Connect with Simon Guttmann via LinkedIn.
Prepared with input from David Diviny, Ed Hughes and Ivan Mukarev.