Increasingly data- and tech-intensive environments have amplified the significance of trust across all sectors of our economy for three reasons:
- Customers struggle to comprehend advanced technologies such as video analytics, robotics or AI and the resulting uncertainty compromises their trust assessments;
- The requirement to provide sensitive, personal data as part of interactions leads to growing trust concerns, in particular in light of widely published data breaches;
- The move towards an online economy reduces tactile, trust-building personal touchpoints.
The rapid speed of these changes means that in many cases customers do not have the time to build experiences in these new environments fast enough and as a result develop trust concerns.
Consequently, the trust-intensity of our economy, i.e. the role that trust plays, is on the rise. Previous research has shown that organisations providing ‘trusted convenience and experience’ using digital technologies have a competitive trust advantage in the form of
- Advocacy – Customers who trust an organisation tend to recommend it within their networks and with this encourage others to buy
- Retention – Trusting customers continue to buy due to their reinforcing positive experiences and as such remain loyal as there is a lower information asymmetry
- Engagement – Customers who trust an organisation will buy new products and services earlier leading to accelerated adoption curves
- Contribution – Customers are willing to contribute more data, dedicate more time and ultimately pay more to those organisations they trust.
This is why QUT’s Centre for Future Enterprise commits significant capacity to its research theme ‘The Trusted Enterprise’.
Our purpose is to empower organisations to develop, manage and benefit from trust.
Our research is dedicated to the rigorous design of trusted customer relationships in data- and tech-intensive environments.
We call this Trust Experience (TX) design, an entirely new discipline which will help professionalising the management of trust. We study and develop design principles and operational approaches that allow to
- Reduce uncertainty and the role of trustless technologies (e.g., blockchain)
- Reduce vulnerabilities of customers
- Increase confidence via trust signals (e.g., in the form of confidence-building statements in financial reports or published positive user experiences in platforms such as TrustPilot)
Further research projects are dedicated to essential prerequisites of trust management (trust governance, trust mining) as well as outcomes, extreme trust and return-on-trust.
Increase benevolence with specific practices (see ‘The Benevolent Enterprise’ paper)
In particular we research the following TX mechanisms:
Trust by Choice: Omni-Trust: Customers do not only select their preferred channel of interaction based on convenience, but also based on their individual trust assessments. For example, customers will choose their form of identification (loyalty-card, app-based, biometrics) that they trust the most in a specific context though it might not be the most convenient one. Omni-trust is dedicated to offering the right choice at such moments of trust and is an important extension of the dominating focus on omni-channel.
Trust by Acceptance: Real-World Cookie: Web cookies are by now an established entry point into online interactions. However, a corresponding, transparent point of accepting different intensities of tracking and personalisation does not exist for in-store experiences. In our related research, we design tech-enabled real-world cookies – on entering a store customers would be automatically WiFi-onboarded and can opt in. This way, they could choose the degree to which they like to engage with the retailer who in response tailors pricing, wayfinding or experience design for those trusting customers who are willing to share relevant data.
Trust by Individualisation: Trust Persona: Trust is a subjective assessment and as such differs between individuals. In our research on trust persona we develop archetypes for trust persona which can be differentiated based on their preferred trust signals (e.g, product reviews, expert assessments) and the comprehensiveness of their trust concerns. The latter might be narrowly centred on product qualities, also encompass related supply chain matters (e.g., carbon emissions) or include value-based assessment of the organisations providing the products. A deep understanding of the trust persona that matter allows organisations to tailor customer interactions to the very specific trust requirements of their customers (e.g., show expert reviews to those customers who research product features intensively). Further research projects are dedicated to essential prerequisites of trust management (trust governance, trust mining) as well as outcomes, extreme trust and return-on-trust.
Trust Governance: Organisations who are making trust a primary concern, will not only require the conscious design of trusted processes, but also new roles and responsibilities. In this research project, we study the profile and impact of dedicated roles such as Chief Trust Officers, Trust Experience (TX) Designers or Trust Architects.
Trust Mining: Organisations tend to have poor insights into the extent to which they are trusted. They either rely on third party, but highly aggregated surveys, engage in their own expensive manual data collection or use metrics (such as NPS) that are poor trust representations. Using the growing data footprint to derive indicators for customers’ trust has the potential to feed real-time trust dashboards and accelerate related decision making. In particular we study the potential of data and process mining as a source of such trust signals.
Extreme Trust: Extreme trust exists when we trust a provider more than ourselves. This is already the case in healthcare, but it is only starting to emerge in areas such as finance or retail. We study success and context factors for successful extreme trust leading to scenarios where grocery retailers, for example, would shop for their customers or banks offer algorithms that conduct financial transactions on behalf of their customers.
Return-on-Trust (RoT): Trust is not a means to an end. However, metrics that easily and efficiently illustrate the context-dependent correlation between trust and qualitative and quantitative outcomes are at infancy. Deepening our understanding of RoT creates confidence among executives in their decision making when it comes to balancing transactional and trust-based value propositions.
Out of scope
Trust is a rich concept with many facets occurring between various stakeholders. As focused researchers we have to be equally aware of what we do not research, not because it does not matter, but simply because we are mindful of our capability and capacity. Trust-related topics out of scope for us are internal trust (e.g., trust in workforce, trust in supervisor), macro-economic trust topics (e.g., trust in media or government in general), trust repair and sociological or psychological research on inter-personal trust.