Leveraging Data for Impact: How to optimise your data to maximise benefits
Event Archive
In this final session, of our four part series on Data, we explored and demonstrated how you can leverage data analytics and reporting to identify meaningful insights that will inform your decision making.
We were joined by Rennie Schafer, Chief Executive of the Federation of European Self Storage Associations (FEDESSA) and Jessica Dearlove, Senior Consultant from their technology partner, ReadyMembership.
Throughout the webinar Rennie shared the lessons learnt when they transformed their approach to data so they could gain deeper insights into their membership.
They are now able to deliver automated, personalised, member experiences that increased internal efficiency and engagement delivering:
- Increase in member retention from 85 to 94%
- Reduced admin by 12 hours per week
- 18% increase in members attending events
- 24% increase in member survey responses
- A 320% increase in email click-throughs
Delegates on this webinar had the opportunity to put their questions to Rennie and Jessica and knowing that many of these answers will be valuable to others in the NFP sector, we have complied and detailed the responses below.
If you are looking for more information on leveraging your data for impact, you can access the full webinar recording by completing the form on this page, or by contacting us at hello@hartsquare.co.uk.
Q. Do you think it’s possible to over personalise? If so, how could I identify if I was at risk of doing so?
Rennie Schafer: I think there’s 2 outcomes of over personalisation. One is you filter out information that your customers and your members need. But more importantly, it’s all about cost benefit.
You could spend hours, days, weeks, months, years, personalising. If I wanted to, I could get individual emails sent to every single one of my members which were personally customised and looked amazing, and probably people would think were not automated. I could code that in it would take me hours and hours, and hours, and hours and hours. But would it give me that level of benefit? Probably not.
The more personalised you get the more individual content you still need to write because the data doesn’t write content. So, it’s really finding that balance to segment data down to a point where it’s efficient to communicate them to that level. But it’s not a waste of time to write an extra set of content or an extra element to break it down. So again, that comes back to measuring your data – how much difference do I get from this segment group to that segment group? Shall I combine them together? Am I wasting my time personalising to that level because it’s not giving me any outcome that’s relevant?
Jessica Dearlove: I think the thing to be aware about personalisation is it’s working on the assumption that people don’t want to see a breadth of content.
I remember 10 years ago, working on one of the very early dove campaigns, we would have a mechanism where you’d click on hair versus body, and then you’d be going into that that tunnel for a year. So, you’ve got to make sure that if you are personalising, that individuals are giving you enough data to ensure that they didn’t just click once on something, and then they become siloed into a communication channel when actually they might want to see much more breadth of content.
Alan Perestrello: I always think it’s great to ensure that you have the ability to do what I call push and pull so that the person can receive what I call pull content, which is really highly personalised, but not ignore the fact that you still have to provide a lot of information. Especially if you’re in a membership body where there’s quite a lot of governance and regulatory. You have a care of duty to ensure that that information is pushed out above and beyond their personalisation, so don’t forget there is a commercial objective that you have to deliver.
Q. Did you use any kind of incentive to get members to respond? Were they willing to offer up opinions and respond? Did you get the value out of it when you did it?
Rennie Schafer: I don’t generally incentivise for my data, particularly for structured industry data. We do have a system where the people that give me the good data, get access to the reports earlier, or get access to a high level of the report. So, when we’re asking for industry data and feeding that back to people we incentivise a little bit, but generally not.
However, for our weekly poll incentives definitely made a difference. For example, one of our sponsors gave away tickets to one of the big Rugby matches, and we got 3 times as many responses to that question. So, I think incentives can work although you want to make sure that you don’t incentive your data into irrelevance. You want people to be completing the form because they’ve got something to say, not because they want to win a prize.
Jessica Dearlove: One of the nice ways of incentivising it is to exchange it for content on the site. I always think that works quite well, because at least there’s a level of engagement there rather than wanting a free thing.
Q. Should you have one person in your organisation who’s responsible for this or do you see this as a as a shared role? Is everybody responsible for being good at data?
Rennie Schafer: It’s a shared role but the best thing I ever did was hire a data person. We didn’t have a dedicated tech support person – it was a shared role. However, I hired an IT role with a big chunk of their job being to manage the data. So, the data gets gathered from different people in different places, and everybody involved in that process. But I have one data person who looks after the data. So, when we have our team meetings, they are the one that’s saying: “Hey guys, you’ve duplicated this, or you’ve done that, or why are we gathering this? How we’re using that?”
Jessica Dearlove: You only probably need one data expert, but everybody’s got to take responsibility for what they’re inputting into the system because it’s got to be collected from the input perspective.
Q. Did you have a clear definition of what success was going to mean for you? As this is something we’re struggling with at the moment.
Rennie Schafer: We had a clear definition what our KPI’s were, but we’ve evolved them. Our clear definition of the KPI’s when we started were very association focused and very tangible. For example, one of our KPI’s was improving attendance and events as well as improving event engagement. For improving engagement, we explore what is and how we would measure it and we did struggle with that. But now we have one overriding KPI: net promoter. Essentially, it says that how happy is the member with membership and if they are happy with membership, then they must be engaged. This comes back to my member before that might not have any click throughs, but because we’ve helped them previously, they think that we’re on top of things. They’re engaged and we’re improving their net promoter score. So, I think you don’t want to get too carried away with KPI’s that are very operational focus. Sometimes you also need to look at the bigger picture.