As ever, this year’s MemberWise Digital Excellence Report showcased some fascinating insights into the current status quo and future thinking of Membership Organisations on a range of topics.
At iota-ML, the most striking takeaways were that;
- 100% of Membership Organisations believe AI will have an impact on membership in the next three years, and
- the need for personalisation is becoming increasingly important across the market.
As a company who harnesses AI and Machine Learning to drive member engagement through personalisation, you can see why these stood out to us!
To give both AI and Member Engagement the spotlight they deserve, I wanted to cover off both in separate blogs.
In this first blog, we’ll look at the impact and potential use cases of AI within Membership and Trade Organisations.
The Impact and Advantages of AI Adoption for Membership Organisations
AI is already having a growing influence across a multitude of sectors, and we’re certainly at the beginning of widespread adoption from a marketing communications standpoint.
Whilst it’s true that Membership Organisations are likely to be behind the curve – with inherently data and technical driven industries most likely to be early adopters – I agree with the “100%” that believe AI will be a major factor in the next three years (if not sooner…)
But where can AI be used effectively? And what are the advantages (and disadvantages) for early adopters?
Early Adoption: A Smart Move or Risky Business?
The Digital Excellence Report points out that AI adoption amongst Membership Organisations is still very much in its infancy, especially amongst smaller organisations. So there are still a lot of potential early-adopters out there!
One of the advantages of being an early adopter in a space with so much intrigue and focus is that an organisation and its members will gain early exposure to various AI tools and applications. They will be having conversations with experts in the space around what AI can bring to the organisation and its members, providing a huge opportunity for innovation and to be seen as a thought leader in the “Membership & AI” space.
The downside to “first-mover advantage” however is that early adopters are likely to open themselves up to mistakes due to a lack of initial experience, understanding and resources. Early AI driven projects may not therefore deliver on the requirements.
It’s therefore crucial that strategic planning and expertise is involved in the execution of AI – especially as an early adopter. Utilising experts in the field, who understand the feedback loop and the data needed to feed the tool will be crucial for Membership Organisations looking to be innovative and becoming early adopters.
Another crucial factor in any AI project is to identify the key use-cases you’re looking to harness AI for, and what the ROI requirements are, ahead of initiating the project.
Where Else Can AI Help Membership Organisations?
The use case for AI varies from market to market, and from organisation to organisation. The Digital Excellence Report highlighted that within medium & large organisations are using AI to;
- Solve member challenges (5%)
- Establish member issues and apply appropriate response (5%)
- Support member journeys on their website, via a Chatbot (3%)
One immediate issue to highlight here is that using AI to solve member challenges is tricky, as a potential decline in the relationship may already have begun.
At iota-ML, we firmly believe that the use of AI is more productive when applied to more proactive data strategies, allowing Organisations to better anticipate member needs. Member engagement is something that should be looked at more proactively rather than reactively.
AI and Machine Learning can be used effectively here. Enhanced Machine Learning can be used by Organisations to predict member behaviour and, for example, put the right message in front of them at the right time.
Summary
It’s clear that AI is going to have a major impact on Membership Organisations over the next few years – from both an automation / process perspective as well as a member engagement perspective.
Whether you want to be an early-adopter of AI depends on your adversity to risk or reward.
Early adopters, especially those focused on member engagement (which we’ll address in our next blog), have a huge opportunity to be innovators in a market which realises the potential of AI, without rushing to adopt.
Regardless of whether you want to be first in the pool, or be more of a follower, it’s crucial to ensure you have the expertise and guidance required in order to ensure your AI strategy can be utilised with the tools and the data you have, and deliver against your objectives and ROI targets.
At iota-ML, we’re here to help you workshop through AI and Machine Learning, how it can benefit your organisation, and how it can align with your objectives. Please contact me or our Chief Sales Officer, Matt, for more information.
Leave A Comment