In a consumer world where purchasing decisions are increasingly influenced by social media reviews, hash-tagged gossip and AI slop, it is becoming more difficult for businesses to acquire the trust of their customers in the swirling tide of synthetic content. Yet with ‘the brand’ playing a key value-creating and capital-anchoring role for commercial organisations, there is a direct line between trust, CAC reduction, pricing power, higher LTV and crisis resilience.
With many consumers now defaulting to active scepticism about large business organisations, traditional annual surveys like NPS/CSAT are too slow and shallow to capture customer behaviour trends in real time. “What we’ve been seeing in recent years has been the decay of brand trust,” explains Sam Blaxland, Executive Officer of the Customer Service Institute of Australia.
“I think the bigger issue that we’re experiencing is that customers’ attention spans and patience have been declining too. As a digital society, we’re getting used to experiencing things faster. It’s apparent in the growing focus around conflict de-escalation and psychosocial wellbeing that we’re seeing in contact centres that customers are more demanding and more frustrated when they don’t get what they want.”
So, how are Australian businesses developing actionable frameworks for accurately measuring trust and tying these metrics more directly to commercial outcomes?
“There’s a natural knock-on effect when it comes to measuring customer satisfaction. organisations need to be looking at customer sentiment frequently, because their customers are more focussed on the most recent experience as a bellwether for how they think about an organisation as a whole,” Sam says.
“Beyond this, there are more practical psychological issues at play. Annual surveys mean that there can be up to 12 months between a customer interaction and the survey, so their recall of customer service can erode. We’re more inclined to remember negative experiences than positive ones as a rule, so the collective responses of customers will skew negative.”
“The key shift is that customers no longer trust brand claims by default. They trust accumulated evidence,” according to Jodi Murray-Freedman, Chief Marketing Officer at Baker’s Delight.
“Every interaction either deposits into your ‘trust account’ or withdraws from it,” she says. “I think we’re seeing scepticism at every stage of the customer journey, but it presents differently depending on where the customer is.”
“At the awareness stage, the first question is often: “Is this real?” Consumers are increasingly questioning content authenticity, influencer partnerships, reviews and even images. Deepfakes, AI-generated content and online scams have conditioned people to verify before they believe.
“At the consideration stage, scepticism shows up as increased validation behaviour. Customers don’t just visit a brand website anymore. They check reviews, search Reddit, look at creator content, compare ratings and seek third-party proof. They’re effectively running their own due diligence process,” Jodi says.
During purchase and service interactions, trust becomes operational. People assess how easy it is to transact, whether information is consistent, whether a chatbot provides accurate answers and whether they can access a human when needed.
“We’re more inclined to remember negative experiences than positive ones.”
So, if the traditional surveys are falling short, what does a 2026 framework for accurately measuring trust look like?
NPS and CSAT are still valuable, but they’re no longer sufficient on their own, Jodi says. “I think of them as the equivalent of an annual health check. They’re useful for understanding longer-term sentiment trends and benchmarking performance over time. They tell us how customers feel.”
“But the challenge is that trust doesn’t decline annually. It declines in real time. A broken digital experience, an AI hallucination, a data privacy issue, or a customer service failure can create trust leakage long before an annual survey detects it,” she says.
Trust today needs to be monitored with the same discipline applied to financial or operational performance. The best organisations combine survey data with behavioural data, reputation signals and operational metrics so they can identify trust issues as they’re emerging, not months later.
“Episodic customer satisfaction surveys – built into an organisation’s CRM and send out the survey invite immediately following the customer interaction – are a great starting point,” according to Sam.
“While you need to be conscious of the risks of over-surveying customers and ‘survey fatigue’, they can deliver a higher response rate and a more representative and accurate metric of customer experience, and importantly, can be implemented across the customer journey at key ‘moments of truth’ to give a complete view of the customer experience. Behavioural data on the customer – repeat purchasing, channel switching, referrals – add another layer of insight to your data if you can match it to the individual.”
With organisations rapidly adopting AI solutions, how can CX leaders scale digital efficiency without losing customer authenticity?
Sam suggests this comes down to how AI is being implemented and transparency about how it’s used in customer interactions.
“Certainly there’s a risk in thinking agentic AI is the solution for all issues of scale and efficiency, but we’re seeing AI effectively deployed by organisations in a few ways. Probably most common is the use of AI as a tool for making contact centre staff more efficient.”
“The other common approach is in using AI to handle the high-volume of simpler customer requests and to triage and route inquiries efficiently – AI is becoming part of customer facing functions. We’re seeing 2 common consequences out of this. 1 internal, 1 external.”
“With simpler requests now being handled by AI, the cognitive load carried by your contact team is dialled up. They’re now consistently having to deal with complex issues all of the time. We’re certainly seeing contact centres managing this additional stressor as an HR issue by providing more support and tools to manage the additional load,” Sam reports.
“The external issue is the transparency of AI use. Customers aren’t so much frustrated by AI agents per se but they are unimpressed when an organisation isn’t open about using them. In the eyes of some customers, that’s ‘bait and switch.’ It is essential that organisations are explicit about their use of AI, that the voice on the other end of the phone may be AI generated.”
The biggest mistake some organisations make is treating trust as a single metric, according to Jodi..
“Trust is actually the combination of what people say, what people believe and what people do. That’s the framework I use.”
Jodi’s process incorporates the 3 tiers:
1) Social listening, brand watch or meltwater sentiment, earned media sentiment, share of voice, review sentiment and complaint themes “tell you how trust is being discussed in real time.”
2) Brand trust scores, consideration, brand relevance, confidence, value perception and reputation tracking “help you to understand whether trust is strengthening or weakening over time.”
3) Measure repeat purchase behaviour, loyalty engagement, referral activity, complaint rates, opt-in rates and churn because, Jodi says, “behaviour is often the most honest measure of trust because customers vote with actions, not words.”
It can be difficult for CX and digital transformation leaders to build a compelling business case for connecting the trust metrics directly to financial outcomes.
“Unfortunately, we don’t see trust as a corporate metric yet. While NPS is often talked about as a measure of customer experience, our experience is that it’s rare for an organisation to be talking about their NPS in their financial reporting or their risk management framework. That said, we are increasingly seeing proxies for it when organisations are talking about their performance. While Customer Lifetime Value (CLV) has been around for a long time as a metric of potential income – and used as a yardstick to validate CX investment – we’re seeing a lot of companies inferring a causal link between NPS and repeat spend using their own data to connect the two. It’s few and far between where we’re seeing organisations presenting evidence of the link between trust and reduced customer acquisition costs or customers paying a premium,“ Sam says.
“Behaviour is often the most honest measure of trust because customers vote with actions, not words.”
When analysing friction across high-volume digital touch points, the strongest indicators of real-time trust decay tend to be behavioural because they’re harder to manipulate and they appear faster. By paying attention to behavioural data, you can often see frustration signals long before a customer leaves an unflattering review or submits a complaint.
Jodi suggests focusing on 6 leading indicators: spikes in checkout abandonment, declining conversion efficiency, support escalation rates, complaint volume, intensity & themes, opt-out behaviours and a decline in review sentiment.
“I often say trust leaves fingerprints before it leaves financial results. The goal is identifying these fingerprints early,” she says.
Interaction data is “surprisingly” still untapped by a lot of organisations, Sam adds.
“With the ready availability of automated call transcribing, there’s a real opportunity for organisations to turn this data into rich CX insight – something that AI does exceptionally well. Similarly, there’s real opportunity in empowering your frontline teams as a source of insights – they’re talking to customers everyday, and have first-hand knowledge of the customer experience. It’s a real opportunity for organisations to build structured mechanisms for capturing friction points and customer sentiment directly from the frontline.”
“The truth is there isn’t a universally perfect weighting model because every sector behaves differently,” Jodi notes.
“However, in most consumer-facing businesses I would start with 50% behavioural signals, because behaviour reflects actual customer choices. 30% weight on the perception matrix, because belief drives future behaviour. 20% on governance and risk indicators, AI incidents or compliance issues for example, because risk indicators are often low frequency but high impact.”
Her professional experience has led her to conclude that you do not to build a trust score for reporting purposes.
“Build a trust score that predicts retention, advocacy and growth. If it doesn’t predict commercial outcomes, it’s probably measuring reputation rather than trust.”
“Trust reduces friction. When customers trust you, they require less persuasion, less discounting, less reassurance and less paid media to convert.”
Trusted brands retain customers longer, earn stronger advocacy and recover faster during disruptions.
“That’s why I increasingly describe trust as a financial multiplier, not a communications metric. It amplifies the effectiveness of almost every growth lever in the business. And in an AI-driven world, where scepticism is rising, that multiplier effect will only become more valuable,” Jodi says.