It’s fairly well-established among marketers that when not taking a targeted approach, customers are likely to receive communications on products or services irrelevant to their needs at that moment in time, leading to an apathetic or non-response. However, achieving the sophisticated communications they’d like relies upon good data and flexible, usable systems. In today’s world, and in financial services in particular, a colossal amount of complex customer data is created and processed on a daily basis. For marketers, it can be something of a challenge to corral this data and create effective communications to drive people to take action. Martin Boddy, CEO at Jaywing, looks at how to face this challenge.
Customers increasingly know that in the course of servicing their financial products, organisations have information which could be used to make other product approaches that are appropriate to their individual circumstances. Failing to demonstrate that you understand this can be both damaging to the customer’s relationship with the brand and counter-productive in driving engagement. Not only that, but each communication about a product the customer isn’t interested in is a missed opportunity for informing them about a product they are likely to be interested in.
To build that understanding, the marketing process within any business should always begin with thorough data analysis. Gaining new insights about your customers, who they are and how they behave and using this information to predict their future requirements plays a crucial role in informing what to talk to them about and when. Plus, as being consent is key, it’s important to understand the customer’s receptiveness to marketing communications. Too many, irrelevant communications, sent at the wrong time can be damaging to the relationship with the brand.
It takes specialist skills to turn the multitude of data available from a wide range of sources into useful insight that can be used to drive communication strategies, which deliver greater value from customers. To understand how to increase that value, it’s important to model all aspects of customer behaviour, including likelihood to respond, to repay, to buy other products and also usage patterns of the product in question; for example will the customer stop using the product once the promotional period has ended? Having this level of insight means the focus isn’t purely on chasing numbers and allows you to target the most profitable business to be targeted.
Move towards trigger-based communications
Historically, marketing in the FS industry has tended towards a blast approach to communications, with brands executing large volume monthly campaigns with few variants attempting to sell products to a mass audience without tailoring of the communication or offer to different customers. However, there is much evidence that the most effective marketing campaigns are customer-centric, with activity being planned and delivered based on the needs of the customer. Whilst this has long been a goal for marketers, data, systems and resources have made it difficult to achieve. Now, new tools and approaches mean there is a definite shift towards more triggered-based activity, including emails, direct mail and dynamic website content targeted at individuals or small groups of customers at an appropriate time suggested by their account operation. A trigger-based approach means sending out hundreds of targeted, personalised communications every day, as opposed to a large volume of communications once a month.
This approach poses many questions of marketing processes, both in terms of people and technology, but these problems can, and are, being overcome. The response rates of smaller, more frequent and carefully targeted campaigns are many times higher than those for large generic ones. In addition to improving response rates, this approach also builds customer confidence in the brand. In terms of channels, we see very much that customers have a channel preference. Direct mail still has a role to play for some customers, especially in relation to more complex products, whereas other customers have a clear preference for everything to be done via email or online. There are no rules here, it’s a case of monitoring how the customer responds (or not) to different channels and taking appropriate action on the back of that.
Contact optimisation uses predictive modelling to work out exactly which combinations of contacts, products and offers the customer prefers to receive and therefore where the direct marketing budget should be spent. Banks can choose the best action for the customer based on their needs, lifestyle and preferences, and their value to the bank. They can then use this to target the customer and offer personalised content.
However, it’s important that applying for an offer, or getting more information, is as easy as possible for the customer. For example, whilst an email can’t contain much personal information as it is insecure, it could be linked via a customer login screen, to a pre-completed form or a personalised information page about that particular offer. It’s not enough to deliver a targeted offer only for the customer to be directed to standard product brochures on the website. The onus here is on the organisation to carry a personalised offer through the application process and remove as many barriers to conversion as possible.
Measure the customer not the campaign
Online marketing also traditionally uses platforms that track campaign-based behaviour (e.g. email opens, click-through or direct mail responses to a specific campaign) rather than the behaviour of individuals to marketing communications over time. With emails in particular, it’s useful not only to establish if the customer opened the email, but also which links were clicked at an individual level. In doing this, the customer may have provided some information about preferences, or a future intention to purchase a product. Whereas if a product has been mentioned several times over a year and the customer has never showed any interest, that too is something which needs to be taken into account in future targeting.
Often, implementing such change requires significant effort and budget so you need to be sure you get it right before rolling out company-wide. One technique we’ve employed is to use a “model office”. This allows a new approach to be tested and refined and the benefits quantified before it’s fully rolled out. For Aviva, the objective was to introduce a much more interactive relationship with new customers, gathering their opinions and intentions and talking about products in much more personalised terms. This began with a new database to bring the disparate customer data together in one place. This rich information was used to create insights and enable highly personalised direct mail, email and outbound call communications to be developed.
When we took this approach for Aviva, our pilot saw customers that would previously have been treated separately by three different business units unified in a single strategy. The results were an impressive 67% increase in cross-sales from a ‘sales through service’ approach. The “model office” encompassed creative, analytical, technical and digital specialists who came together to create the new environment, from understanding what customers want, to new systems and platforms, to deliver new messages aimed at customers, rather than siloed products.
Bringing customer data together and using it to develop new insights about customers enables FS marketers to develop much more effective strategies to communicate with them. As highlighted, the important next step is to make the connection from insight to highly personalised action to make it deliver value to the business. After many years of personalisation being talked about as the promised land, skills and technologies are coming together to make it a reality, enabling FS marketers to create effective data-driven, highly targeted marketing that leads to much better results. At the same time, the bar is being raised in terms of what customers come to expect. With this in mind, it’s likely that over time brands taking a more traditional generic product approaches will increasingly be left behind.