As an industry, marketing fundamentally exists to understand and influence human intent, ideally to persuade buying behaviour or at minimum, brand recall. With the advent of multi-channel engagement, brands now have access to vast volumes of data around customer behaviour.
Smart marketers are increasingly turning to Artificial Intelligence (AI) systems to analyse, optimise and monitor these datasets to gain valuable insights. These could include simple engagement systems like chatbots to sophisticated propensity models to predict buying intent.
This AI processes multiple signals and produces correlations that aren’t apparent to humans. Some of these inferences drawn might be inherently sensitive in detail. A seemingly innocuous social-media promotional campaign for a brand could use AI-driven sentiment analysis on customer-generated posts and help the brand in segmenting customers based on personality types. Further on, AI offers an unfair advantage by combining alternate data to infer deeply personal preferences derived from identity resolution thereby creating a 360-degree view of the customer – the holy grail in marketing. This suddenly puts brands into a unique position where they know more about the customer than, perhaps the customers themselves, thereby driving such hyper-personalised campaigns including targeted advertising.
Some real-world examples of how AI is embedded within the digital marketing context include dynamic product placements on web searches and social media, advertising on video-sharing platforms, personalised promotions by e-commerce players and hyperlocal advertisements on location-aware mobile apps.
This ability to feed on intimate knowledge about customers, even on a segmentation basis, opens ethical challenges for marketing. Not many customers are aware of this value exchange they are facilitating by opting in to engage with brands across channels. AI brings this ability to transform vast amounts of complex, ambiguous customer information into insight and can influence buying behaviour.
Specifically, in retail banks, consumer financial service providers and insurers, such marketing automation, enabled by AI is now almost a boardroom imperative. Constrained operational capacities and cost optimisation with digital products mandate less dependency on humans, especially in a post-pandemic context. An unplanned outcome is that financial inclusion decisions are now being automated at scale with or without humans in the loop, risking treating customers unfairly. For example, access to credit cards, loans and mortgages are, at minimum, influenced, by machines at a statistical scale. Similarly, health and life cover pricing decisions, as well as renewal offer within insurance are now being automated.
Responsibility, trust and ethics are not just designed for codes of conduct but have a whole new meaning in the age of data-driven marketing. Customers expect your brand and your marketing to be transparent and purpose-led. You clearly fulfil a high impact function within your organisation in building trust and responsibility. This moral obligation is beyond any data privacy regulatory compliance.
If you are a Chief Marketing Officer of a digital bank, insurer or even a small fintech company, we strongly urge you to build accountability and confidence in your AI with end-to-end transparency and visibility to help safeguard the interests of your customers and their trust in your brand.
