©Papaioannou Kostas /Unsplash For a long time, AIPC focused on membership growth as a key engine for revenues. In a way, this makes sense, as membership fees are the biggest source of revenue for our association, while in other cases that might be the annual conference or certifications. In the case of AIPC, the ratio is 70/30, with 70% of revenues coming from membership fees. So having a KPI on net membership growth seemed the way to go.
We are however changing our focus. While membership of course remains a top priority, we are having a closer look at member engagement, which – in our case – is expressed in participation(s) to one or more of our (educational) events.
There are a number of reasons for this shift. First of all, we noticed that it is quite easy to obtain new members in certain parts of the world, but that they do so without fully embracing the values of the association – and in some case for very opportunistic reasons – resulting into short-lived memberships.
Secondly, we saw that in a number of cases the touchpoints between the association and members was limited to a single person. When this person would move jobs or retire, there was no more touchpoint, meaning we lost the advocate for the AIPC membership within that organisation.
Which brings me to the third and final point: because of the way we manage member data, we fail to match our value proposal with the correct audiences and therefore miss out on revenues other than membership fees.
Let me elaborate a bit on the last aspect. Like many associations, our CRM database has a number of layers, but it basically comes down to person/function/organization. So if we organise a sales & marketing summit, we do a campaign towards all persons in our databases who have the “tag” sales and/or marketing. The problem with this, is that our database is not a dynamic one as it does not take into account the career evolutions of a person within the member organisation. We will notice that the person no longer works at a convention centre (as we get an error message), but if a person moved from sales to operations, we simply don’t know and we continue to send the same message to a person for whom the message is no longer relevant. In some cases, we are lucky because the person will forward the message to the correct person – who might register to the event – but this does not solve our basic problem, as the database will not be (automatically) corrected.
And that is where AI – I know, but in this case it does make a difference – kicks in. There are a number of sources where you can find information on a person’s career evolution – an obvious example is LinkedIn. So what we want to achieve a link between our CRM and sources like LinkedIn, which would allow to make our database dynamic. But this is just the starting point.
Once we feel confident that the data is correct, we can actually start clustering individuals in “persona” and create matching product and services offerings at that level. Today, we already defined those persona, but do not feel sure enough about our data to start implementing the link.
So this is how the ideal situation looks like: Person A at Convention Centre X moves from operations to sales and announces this proudly on LinkedIn. This is picked up by our “AI Radar” and a congratulations mail is immediately sent to the person and we also notify the person that we will send her/him messages and offers which are in line with the new job. If Person B leaves Convention Centre X to start working at Convention Centre Y, which is not a member, a congratulations message will go out to his LinkedIn profile, expressing the hope that she/he will onboard the new employer into the AIPC Community. Or if Person C gets a promotion and has now the right profile to attend one of educational programmes, we can reach out accordingly.
There are a number of challenges with this “to-be” situation. First of all, an architecture needs to be put in place allowing to connect the dots. Secondly, a data policy needs to be defined and communicated. And thirdly, a solid tracking mechanism needs to be put in place, allowing to measure results and impact.
But if overcome, we will be able to have a far deeper understanding of our community and their changing needs, allowing to adapt our services and product offering and at the end deliver more value to our community, with additional revenues generated which can be re-invested, creating a circle of continuous improvement and value increase.
Sven Bossu is CEO of AIPC, which represents a global network of over 200 leading centres in 55 countries with the active involvement of more than 1000 management-level professionals worldwide. More information on www.aipc.org