Behaviour data will change how you run your brokerage.

Top 5 things you will do differently when you start creating financial market behaviour data.

Let me first define what I mean by behaviour data in the context of generating a customer experience in real time time leveraging AI and ML. I will discuss these in much more detail in a separate article but if you develop and capture data points in how the users, the markets and the content is behaving you have the key to both understanding and controlling the financial customer experience.

It’s helpful to compare a traditional example with a new behaviour data driven example. Let’s say the marketing team wants increased activity in equities. Typically the team would select a single stock, get the analyst to write some commentary, the sales teams to get on the phones and run some banner ads. For me this is arse about. Behavior data dictates whats likely to be most engaging because of the confluence of verticals; user - what are your customers interested in, markets - what are the markets buying and selling and the content - what is the market analysing and talking about?

The strategy should be to leverage what’s trending in the behaviour data. For example. these 5 equities have a trend score of x because user interest, market price action and content interest means that they will be the most engaging to the user, not whats most interesting to the desk head or marketing lead. A good financial experience platform will be constantly leveraging these engagement opportunity, automatically - this is one for another day but its a great chat about automated engagement.

Lets get back to how your brokerage will change from top to bottom when behaviour data drives how you engage with your customers:

Sales Contact Strategy

I refer to this as Sales Optimisation, the ability to improve how a sales team operates once it has access to real time behavioural data across the three main verticals. You will know why, how and when to contact a customer, driven by the data rather than the campaign plans.

Its super important to broaden the user behaviour capture outside of trading activity only, as its a very narrow view of whats interesting to the customer and limits your ability to monitor whats trending in all user cohorts. A good financial experience platform will map and score all user interactions to the markets through instruments, topics and economic events.

A sales team who is able to see exactly what a customer likes and what they are currently interacting with is a huge insight and will dramatically improve targeting strategies and increase conversion. Sales Optimisation is all about matching sales activity to behaviour data and it is a winning strategy.

Content Strategy

I think most brokers are pretty lazy about their content strategy, lots of old school content flowing through chronologically into feeds and emails, alerts etc. This is then overlaid with some decent quality market commentary and analysis. However the whole strategy is old school, its based on subjective decisions and acceptance of whats coming out of the content houses, is what it is.

Some important points to make here:

• Its absolutely the right approach to have 3rd party content but its value is significantly diluted when its broadcast and not personalised - in essence to most people its market noise not market insight

• When you create behaviour data from your users and how the interact with every piece of content it creates return on investment data points. You could be paying 10k+ a month for a content feed that isn’t getting any engagement - a good financial experience platform will give you direct data on interaction to behaviour which will give you an ROI on all your content sources.

• In house content should be written to match or modify the preferences of the audiences. Don’t waste time on content you don’t know will land well - monitor the behaviours for trends in instruments, topic or eco events to feel the pulse - it will improve your focus and increase engagement

• Micro content targeting - love this one - often brokers (and banks) create quite lengthy multi instrument content. When you have very granular user market preference behaviour you can break down the content into smaller packages that can be targeted at users who are most likely to engage with it.

Marketing Strategy

It’s a massive change for a marketing team to move from a planned, reactive, single channel marketing strategy where decisions on what to market when are decided and implemented. Behaviour data enables a continuous automatic engagement cycle to be implemented.

Trends emerge in the 3 behaviour verticals which identify that something is happening of note. These trends can then be delivered to users who are most likely to engage. Cyclical, event based marketing makes way for continuous, personalised engagement that improves in accuracy and effectiveness over time. This is a key goal of any real-time financial experience platform.

Risk Management

By properly understanding the 3 verticals of behaviour you can start to monitor or front run when that behaviour begins to become trade execution - the more in depth your behaviour data the more likely you are to understand if there is a risk developing in your exposure.

It could be as simple as the risk management seeing anomalies in user behaviour around a certain instrument before price action begins to emerge - this may provide an advantage in managing your risk and its an insight that will change how you manage you A and B book.

Education

Understand behaviour, understand how to change it. Personalised financial markets and trading education can have a significant impact on how traders navigate the financial markets, manage risks and take advantage of opportunities. By understanding every interaction of a user and other users you can develop models which describe and classify a performance and maturity level that can be matched to a suitable education plan.

Intervention strategies should also be a key capability of your financial experience platform - by monitoring all behaviour you can intervene when behaviour trends towards a poor rating or even intervene when an action isn’t beneficial - simple example being reminding a trader that they perform better on average when a stop loss is put in place on execution.

Education can also be personalised from an instrument, topic and eco events stand point ensuring ‘how to’ is framed in the market preferences most likely to get cut through - for example how to trade ‘Tesla’ is different on how to swing trade ‘Cable’ - targeting and personalisation matters.

Customer centric strategies

Running your business on behaviour data fundamentally moves your customer to the centre of your business, continually seeking to better understand their needs and building experiences and technology to better meet them.

Thanks for listening.

Cheers

Adam