By Patrick Costello, Senior Product Strategy Director, Optimizely
According to Bain & Company, uncertainty is one of the key factors affecting marketing teams within financial services companies. For example, there’s a lot of uncertainty around when consumers will become less concerned about personal safety in favour of other product features. Similarly, it’s unclear whether marketers will be able to develop the agility needed to remain relevant in times of ever-changing consumer preferences.
Digital-first financial services are here to stay post-Covid, so financial services companies must manage change and reduce this current uncertainty by involving the whole business in improving the customer experience.
Our work with customers and partners has shown that there are three key approaches that enable marketers to move faster while reducing uncertainty and keeping pace with consumer expectations. These include the creation of content based on evidence, rolling out new features in a tightly controlled environment and continuous optimisation and personalisation of customer experiences.
Create content based on evidence
The research by Bain & Company noted above has found that successful marketing leaders tend to conduct tests more frequently, which helps the whole marketing team to learn how consumers behave and create content that drives engagement.
Leading digital companies like Amazon and Google have a well-established culture of experimentation, where they continuously test to determine how customers are behaving. In fact, a highly developed culture of testing adds certainty to the process of improving customer experiences.
Rapid testing and experimentation can reveal how customer habits are changing, and what features they highly value and interact with, in order to inform business decision-making.
By continuously experimenting with its quadrillions of landing pages, online travel company Booking.com successfully transformed from a small Dutch start-up to the world’s largest online accommodation platform in less than two decades.
Roll out new features with control and safety
Traditional software development cycles normally rely on fragmented data from a variety of sources instead of a single unified view of the customer. This means that new releases do not necessarily resonate with customers and require painful ‘rollbacks’, for example to previous versions of a website.
By putting customer data at the centre of product development and carrying out early exploratory testing, companies can establish if a feature is likely to resonate with customers before actually building out the full feature code. They can deliver frequent and small releases and rollback easily if needed, thereby reducing uncertainty and risk.
One of our customers, a major US airline, used an early exploratory test to validate customer demand for instalment payment options on its website. Rather than implementing this feature straight away — and risk losing revenue — the test included creating a minimal user experience, in this specific case measuring clicks on an icon.
The data collected allowed the team to develop a business case for the new feature and enabled informed decision making around resources and future potential. Ultimately, the new instalment payment option resulted in a significant uplift for the business.
Personalise and optimise experiences
What constitutes as a great experience differs significantly from person to person and also depends on the wider context. Over the past 18 months customer behaviour and expectations have changed profoundly, adding new complexities to the customer experience equation. A strong personalisation and optimisation strategy helps financial services marketers engage with users at an individual level by connecting the right message to the right user at the right time.
Such an approach requires continuous improvement and iteration, and the adoption of ever more sophisticated personalisation capabilities.
Any personalisation strategy is underpinned by core segmentation which includes identifying psychographic characteristics of audiences, their affinities and intents. One-to-one personalisation can be achieved with the help of machine learning (ML) capabilities, where businesses can map out who their audiences are and their needs at any given point in time.
Continuous personalisation and optimisation not only reduces risk and increases certainty, but also has a demonstrable impact on revenue. In fact, three in four companies have increased their digital revenue by over 5% through always-on optimisation and personalisation, according to Digital Experience Economy Research.
By releasing features in a controlled manner, creating new content based on evidence and introducing continuous personalisation, organisations can move fast while ensuring their relevance to each and every individual in the long term.
