AI will improve the way advisers market to potential financial services leads.
There has been no shortage of debate over the use of AI and machine learning in the financial service sectors. Last year saw the rise of robo-advice in the sector. The problem, however, is that many of us approach the topic with preconceptions that can set us on the wrong road.
AI has nothing – or at least very little – to do with the “rise of the machines” in banks, for example, where touch screen devices are increasingly replacing tellers. In reality, all that’s happening here is that customers are directly accessing the same systems that the tellers use – it’s more a case of cutting out the intermediary.
In the context of digital marketing, though, AI is all about the most important commodity of all in the modern business environment: information. The world of 2018 generates more data than ever before, and sometimes from the most unlikely of sources.
Every website visit, online purchase, social media ‘like’ or app download leaves its own data trail and has its own story to tell. The sheer volume of data being created, shared, stored, processed and analysed is truly mind boggling. For those in the financial services industry, this brings its own challenges, and the new data age has prompted the introduction of the General Data Protection Regulation (GDPR), which came into effect in May 2018.
AI means greater personalisation
Another misconception is that using AI somehow depersonalises the customer experience. Used well, the opposite is the case. The fact is that whoever can draw the clearest insights from all the information that is out there is in a position to deliver a better and more tailored offering.
If there’s one thing that’s guaranteed to turn any of us away from a marketing communication, it’s the feeling that we are being “blanket bombed” with generic sales pitches that might or might not be relevant to us.
Let’s take a simple example using buyer personas:
Persona A is female, in her early 20s with student debt and dreams of getting on the property ladder.
Persona B is male, early 50s and contemplating early retirement.
Clearly, both could benefit from financial advice, but their needs, aspirations and interests could not be more different.
Now, anyone with a list of clients and a pen and paper can offer two separate marketing campaigns to reach these two targets. But the beauty of AI is that it can dig deeper, providing more detail and using a greater number of data points.
Knowing Persona A has student debt and wants to buy a house is one thing. Being able to zero in on how much her monthly payments are likely to be, the kind of property she is going to be looking for, the approximate deposit she is going to need and other such factors, and then being able to discuss these detailed factors in marketing material is another.
AI improves efficiency of delivery
There is a well-worn theory in marketing called the rule of seven. This states that a lead will need to hear your message seven times before he or she will take action and convert into a client. That sounds like a lot of communication, but it will bring you results.
The thing is, this is the age in which 2-minute YouTube videos are rapidly replacing 2-hour movies and key information is exchanged within the magical limit of 280 characters as dictated by Twitter.
In other words, communication needs to be short, concise and on message. And while it’s debatable as to whether millennials and Gen-Z really do have shorter attention spans, there is no doubt that they have far more sensory inputs competing for their attention.
For these reasons, experts in SEO and digital marketing suggest that the rule of seven should really be the rule of 10, 20 or even 30. This is where AI can really give digital marketing a boost in terms of narrowing the focus and optimising effectiveness. The latest AI-powered tools can analyse and predict the efficacy of your marketing campaigns and provide consistent and tailored messages across all platforms and channels.
AI and machine learning provide financial marketers with enhanced tools to directly connect the activity and behavioural inputs of potential clients with consumer-centric marketing outputs. And these inputs might come from an array of sources, including website enquiries, interactions via social media and various others. Machine learning allows the data to be analysed using advanced algorithms to get the best possible understanding of consumer intent, and therefore to provide tailored responses.
Best of all, automation means these responses can be delivered in real time, exponentially increasing the chance of warm leads getting even hotter and converting into clients.
Improved lead scoring
AI allows finance marketers to use predictive lead scoring techniques to identify not only what nature of communication to share with what leads, but also which of those leads are the most inherently likely to convert or respond.
Marketing automation software that combines cutting edge AI with business information data can carry out continuous scoring in real time, calculating and assessing the probability of a given lead converting to a client.
This scoring can draw from a wide range of inputs. These include:
the chosen engagement platform
the level of interest users are showing in terms of number of visits to your site and time spent there
and the depth of engagement, for example sharing or retweeting social media posts.
The software can even use this information to accurately assess how close they might be to committing, i.e. at what stage they are in the sales funnel. Lead scoring in this way helps to determine the whether, what and when of marketing communications.
Better, faster and cheaper
The “impossible triangle,” beloved of MBA lecturers the world over, says that when searching for quality, speed and cost, we have to sacrifice one for the other two. AI as a marketing tool is the exception to the rule, helping financial advisers to achieve a marketing strategy that is better, faster and cheaper than ever before.
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