How To Prove The Worth Of AI In Digital Fund Marketing

Published: 23 April, 2020

The marketing sector is increasingly realising that artificial intelligence (AI) can improve client journeys and experience and drive sales.

And this is why so much money is being invested in AI. According to one survey, 90% of marketing executives across the world are using AI to improve the way they connect with customers.

And this is equally true of the fund marketing sector, where the worth of AI is now well known.

But what is not so well known is how to demonstrate this worth in terms of actually boosting assets under management.

So, how do you demonstrate ROI when it comes to this new technology?

Here are three ways that can help you demonstrate the worth of AI to those that matter:

Make it understandable

AI is complex, so you need to employ a data scientist – someone who understands how to apply and get the best from it by exploring data, making predictions and finding structure. But relying on data scientists to feedback to stakeholders can create a disconnect further up the chain of command, as those who hold the purse strings but don’t necessarily understand the technology.

So, you must ensure that the AI models being used to analyse data and make recommendations are as understandable as possible to the people involved in the decision-making process. This will mean some hard work and communication between your data scientists and marketers, so that everything is presented clearly and effectively.

Do this right and you will build confidence amongst all stakeholders and be able to demonstrate what AI is doing and its benefit.

Focus on the end goal

All your fund marketing activity needs to be framed within one overarching question – how does this help to raise assets? And this applies to AI as well. It is only as good as the task it is given, so you must make sure that all activity can be shown to have a positive effect on the ultimate aim of raising AuM. And this must be done before AI is let loose, rather than trying to retrofit it around existing activity. This makes it much easier to demonstrate worth further down the line.

Take it one step at a time

AI isn’t a magic wand, so you must build up its efficiency over time.  Effective AI strategies are about achieving incremental improvements, by learning and modifying and running tests to improve algorithms and make better predictions. This will take some trial and error but ultimately it will allow you to present much better proof of worth, as you can show that the technology is performing well.



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