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Using Artificial Intelligence to Retain Members

Microsoft Dynamics |

By Adam Legge, Director of Development at Silverbear

Imagine if you could predict when – and why – your membership was about to decline. Suppose you could gain insight that enabled you to know who, by age, gender or even by name, was about to ‘drop off’ and be able to do something to stop it.

Those who remember the Grays Sports Almanac that time-travelling Marty McFly purchased in the future, in order to be able to return to 1985 and place bets on the winning sports events, may see a similarity. Knowledge is power, after all.

Whilst we cannot travel forwards in time to glean information from the future, which can then be used to alter the past, we have developed a service through Microsoft’s Azure Machine Learning that will allow membership organisations to predict those members who will not renew and, in turn, test interventions to prevent this from happening.

As the possibilities afforded by Artificial Intelligence (AI) become clearer, organisations are increasingly trying to identify ways in which this emerging technology can be incorporated.

Until very recently, AI has typically been reserved for product specialists, who, albeit inadvertently, have made the technology less accessible, prevented its widespread adoption and prolonged its journey into the mainstream.

However, a recent collaboration between Silverbear and Microsoft demonstrated that not only is this about to change, but also that businesses are already in the process of developing creative ideas around AI that have the potential to revolutionise their sectors.

Following the collaboration, and after having spent 2018 developing the model, we believe that Silverbear will become the first membership software business to integrate AI in a meaningful way by the close of this year.

The idea is simple. Membership organisations can identify at-risk members via a proven metric-led framework model.

Using AI to facilitate renewal predictions, we will be able to help our customers identify who, on an individually named basis, will renew their membership. As the system is an iterative process, which enables the platform to learn more each time data is fed into the system, the process only becomes stronger, more accurate and more valuable.

By arming membership organisations with enough information to spot patterns and predict potential issues, they have the ability to reach out to members before an issue arises.

Importantly, the data is not solely limited to that made available within the membership platform. Those organisations looking at the bigger picture may want to establish the impact a major event, such as Brexit, has on its members’ decision to discontinue. Equally, social media sentiment at any given point could also be measured against the actions of members.

It is understood within the membership sector that member engagement and member retention are highly linked. This point is supported by Memberwise, the leading free membership and association professional network, whose Digital Excellence 2019 report revealed that of the top three goals set by membership organisations, number one was engagement and number three was retention.

Now that Azure Machine Learning can be integrated with Silverbear’s technology to enable our customers to learn how failures in adequate engagement led to retention issues, and then use that information to pinpoint impending retention crises, two of these three goals can be addressed. Given how one reinforces the other, and assuming that membership organisations, through AI, can use the insight to prevent negative action, then AI may come to represent the single most effective tool in boosting the sustainability and long-term viability of a membership organisation. In a sector that can often be slow moving and resistant to change, my view is that AI will radically change the way in which organisations interact with their members.

Nobody could have predicted the scale of the impact the Internet would go on to have on the world. If AI’s impact is anywhere near as big, then the opportunities really could be endless. Who knows, maybe time travel may be possible one day after all.