Personalised marketing? Advisers can achieve ultra-personalisation

One of the definitions of personalised marketing is: “…a marketing strategy that uses data to create customised content for individual customers. The goal is to make customers feel like the brand message was made specifically for them by targeting their interests, demographics, and buying behaviour. This can be achieved through data analysis and market research.”

Most of us will instinctively understand this. We receive lots of personalised messages, retailers and other big brands are especially good at personalised marketing, the supermarkets especially so. It started with loyalty cards. They were launched in the 1990s by Tesco. Co-op’s green shield stamps had been a thing since 1958 but they rewarded loyalty whereas the Tesco scheme went many stages further, providing the retail giant with customer data.

Before that, of course, the privately owned butchers, fishmongers and corner shops – think Open all hours – could personalise their marketing in a very simple, but very effective way. They knew their customers by name, they knew what they regularly bought, they knew where they lived. They might offer free delivery or unofficial discounts and freebies to their best customers. They could say to a customer, ‘We got these in this morning and I put one aside for you’. Or, put another way, ‘I saw this and thought of you.’

Nearly 40 years on, the data collected through their loyalty scheme enables Tesco – and others who have followed their lead and launched their own schemes – to send personalised content and offers to millions of people.

Tesco, Sainsbury’s and the hundreds of other retailers who have launched loyalty programs don’t know their customers as small independents did – and sometimes still do – but they make up for it, with data, lots of it about the purchase behaviour of millions of consumers, which they can supplement with other data sources.

Of course, the online retailers such as Amazon, Asos and Etsy, along with platforms like Spotify and Instagram, and the marketplace giant eBay, have taken customer knowledge and understanding to another level. They are able to send personalised recommendations based on behaviour.

So what about professional services firms? Firstly, financial advisers, solicitors, accountants tend to talk of clients not customers. The generally accepted difference is that a customer is someone who buys goods or services, while a client is someone who buys services from a professional person or organisation. This highlights the difference between advisers and, say, retailers, and it also highlights the significant advantages advisers have when it comes to knowing their client.

Advisers often conduct meetings with clients, face to face or virtually, during which they gather significant amounts of very personal information. They know their clients in a way that retailers don’t and can’t. The data the big consumer brands gather is nowhere near as rich. They don’t know the reasons behind purchases for individual items, maybe a gift bought for a housebound relative or an impulse purchase. Their data maybe extensive but it’s not very deep. Whereas financial advisers, solicitors accountants, and others, are privy to significant personal information about their clients. They have real knowledge behind their data. They really know their clients.

So why ‘send all’?

Despite this depth of knowledge, professional services firms aren’t renowned for sending content that is precisely targeted to the recipient. ‘Send all’ has become the norm. This could result in pension planning content being sent to those that have retired, or details of the best fixed rate mortgages to people who have paid off their mortgage.

With the advent of Consumer Duty, this certainly isn’t ideal. In fairness, until recently, they haven’t had the tools available to enable them to target and personalise effectively.

There is though, a lot of good news. The first piece is that not only can advisory firms personalise communications in the same way that big online brands do, they can go a number of steps further – they can ultra-personalise. How so? For most IFA or mortgage broker clients, their relationship is with the firm and the individual adviser. An advantage over the retailers. Sending content from a named adviser to an individual client that is really relevant (‘I saw this and thought of you’), especially if it’s seemingly unplanned (i.e. not on the first day of every quarter for example) demonstrates a genuine understanding and relationship. It’s a step towards ultra-personalisation – offering content that corresponds to the specific expectations of each client.

Easier said than done?

A year ago, maybe. But today it’s very achievable. What you need to do…firstly, you need to get your data in order, that is cleanse it and segment it (Woven Advice can help). You need to audit your processes to bridge the marketing automation gap (Jigsaw Tree can help with this). Content Streams can provide the content and enable the personalisation and sharing of that content.

More about…

Content Streams is a transformational new content sharing platform, developed using cutting-edge technology and informed by TOMD’s own extensive experience of solving the marketing pain points of financial services firms. You can read more here.

Jigsaw Tree specialise in partnering with financial advice firms to deliver business consultancy, solutions, and operational support, including outsourcing. Jigsaw Tree’s services are tailored to enhance your business’s effectiveness and drive greater efficiency. In collaboration with Content Streams and Woven Advice, Jigsaw Tree offer a service designed to optimise your practice management system (PMS). You can read more here.

Woven Advice help financial advisers and wealth managers segment and service their clients through their integrated data management and reporting platform. While Content Streams enables advisers to share content with clients on a one-to-one, one-to-few and one-to-many basis, the better the data the better the outcome. If your data needs addressing, Woven Advice can help. You can read more here.