FROM ONE-TIME BUYERS TO LIFELONG CUSTOMERS: INCREASING AFTER-PURCHASE ENGAGEMENT IN WEALTH

Introducing digital channels within private wealth and DIY investment management brought a fresh perspective to customer communication. Interaction with customers became more measurable, fast, and affordable, creating useful feedback loops supporting the continuous development of new features and services.

However, many innovative financial journeys emphasise engagement in the onboarding and prepurchase stages of the experiences, leaving customers with simplistic monitoring tools after they execute. In our experience, there is significant potential to engage your customers on an ongoing basis after they have committed to your services. Unlike gamification engagement practices, data-driven financial analytics suggests alternative strategies to achieve your customers’ financial goals, generating more demand for your services through responsible and relevant interactions that build trust in the long-term.

IS GAMIFICATION ALWAYS THE RIGHT STRATEGY TO PURSUE?

There are several ways to foster engagement in a digital environment. Gamification often comes to mind due to its simplicity and efficiency. This set of practices uses game design principles and mechanics to make non-game contexts more engaging and enjoyable. In the financial context, gamification can be used to highlight milestones as the user navigates the journey.

For example, DIY investment apps can shoot fireworks in the interface when the user purchases financial instruments or compare the financial performance of users’ holdings to encourage competition. In recent years, regulators have become increasingly concerned about the introduction of gamification practices in the financial space. The American Securities and Exchanges Commission (SEC) suggests that while these developments have lowered entry barriers and increased access to financial markets for investors with limited means, the downside of gamification is that it can induce trading that is more frequent or higher risk than an investor would choose in the absence of these gamification engagement practices. Our recent blog investigated the potential issues and alternatives to such an approach.

THE POWER OF VISUAL AND INTERACTIVE FINANCIAL-DECISION MAKING

Another way to make financial experiences more engaging is by offering analytical tools that could help your customers demystify the impact of macroeconomic phenomena on their financial position or visualise how the investment risk levels influence the time it takes to achieve their goals.

This strategy brings engagement practices into the domain of your financial institution – your digital and hybrid journeys would serve your customers’ understanding of their available options, rather than entertainment. Besides, leveraging financial simulation engines like OutRank® would enable your customers to visualise and forecast the impact of their economic decisions on a holistic, balance sheet level, scaling the efforts of your financial advisers to serve more customers than previously possible.

For example, armed with this technology, your customers can analyse the impact of selecting their pension provider, while considering all the other dimensions of their economy, such as investments, mortgages, savings and taxes. After incorporating a financial simulation engine to power your financial journeys, your institution will become a go-to platform for evaluating the broadest range of financial decisions, from the pursuit of additional training to boost one’s income to saving for retirement.

Providing Personalized Service Through Proactive Notifications

You can also encourage your customers to learn more about their financial situation by sending them relevant and actionable notifications, recommending personalised strategies to achieve their financial goals. For instance, you could use this engagement tool to inform your customers if their investments have drifted from their desired risk levels over time. We designed our simulation engine to analyse the entire personal balance sheet of wealth management customers, as well as their risk preferences and goals, so it can create and send relevant and actionable adjustment suggestions at scale. In addition, we equipped OutRank® with proprietary machine learningdriven clustering functionality that can enable banks, insurers and wealth managers to provide their customers with better deals regarding their investments.

By analysing customer preferences data, this technology can recommend financial products similar to their existing holdings but with a more sustainable profile, managed by a different manager or, if relevant, having lower fees. Providing your customers with these alternatives via proactive and responsible notifications on how they can improve their economy would encourage them to deepen their relationship with your firm and reach their goals faster.

Increase The Relevancy Of Your Marketing Efforts

Due to its highly regulated nature, the financial industry is a problematic space for innovative demand generation techniques such as gamification or machine-learning driven recommendations. When it comes to marketing, financial institutions rarely act as early adopters, especially in comparison to Big Tech, choosing tried and tested strategies to avoid bias and manage risks.

However, today’s financial sector can leverage their own analytical capabilities to personalise their marketing. This can be done, for example, by using simulation engines like OutRank® to recommend educational resources based on the customers’ financial situation. Sending more relevant articles, videos, and other resources on personal finance, investing, and retirement planning will nurture your relationship with customers and encourage repeat business.

DATA-DRIVEN AFTER-PURCHASE ENGAGEMENT: CUSTOMER LOYALTY, REPEAT BUSINESS AND MARKETING AT SCALE

After-purchase engagement driven by financial analytics offers a range of benefits to financial institutions. First and foremost, by leveraging this technology, institutions can foster relationships with their customers at scale, building trust and educating them about financial strategies to achieve their goals. Fostering engagement based on customers’ needs will improve customer satisfaction and loyalty.

Second, with an in-depth holistic analysis of your customers’ economies and machine learningdriven clustering functionality, you can recommend portfolio improvements, better deals, or increased recurring investments to meet goals leading to more repeat business and increased revenue.

Third, you can leverage your analytical capabilities to recommend more relevant marketing and resources based on the customers’ financial situation, continuously nurturing the relationship with them. This targeted, data-driven strategy will not only lead to a significant increase in the efficiency of your wealth business, but also help you capture demand across all channels.

ZALIIA GINDULLINA HEAD OF BUSINESS DEVELOPMENT KIDBROOKE

ZALIIA.GINDULLINA@KIDBROOKE.COM