Customers have always gravitated toward companies they trust. Today, however, rapid technological advancement, escalating threats to cybersecurity and data privacy, and growing reliance on AI have made trust more critical—and more elusive—than ever. Consumers are increasingly aware of risk in the digital world, and they're becoming more selective in how they engage with companies online. For instance, nearly half of consumers say they're more reluctant to accept website cookies than they were three years ago, and less than half of recently surveyed wireless customers feel comfortable using AI chat bots for support.
Modern organizations must therefore strike a careful balance: harnessing technology’s scale and efficiency to connect buyers with their brands, while ensuring those connections lead to meaningful and transparent relationships. Companies that are unwilling, or unable, to address growing concerns around digital security and ethics risk the loss of consumer trust, and along with it, the loyalty of their audience and the longevity of their brand.
Data privacy
Data collection and analytics play a critical role in enabling personalized and relevant experiences, and in turn, positioning companies for more timely engagement, stronger customer relationships, and higher CLVs. However, many customers have their guard up when it comes to trusting businesses with their data. A significant 86% say they'll only share their data if a brand clearly discloses why it's needed.
They have valid reasons to be wary. Years of high-profile incidents of data misuse (or even abuse) by major companies have created an environment where the potential benefits of sharing data are offset by the potential for exploitation. If digital brands wish to regain the confidence of their online audience, they'll need to establish a track record of ethical data collection and responsible usage. In practice, this may mean creating privacy-forward policies, and providing transparent touchpoints where customers are invited to provide (or withdraw) consent to share their information. It also means governing that information in a way that prevents unauthorized access, mishandling, and leakage.
To encourage customers to take the leap of sharing their personal information, it's important to offer real value in exchange for their trust. A third of customers say they’ll share data in exchange for coupons or discounts, while others may be motivated by free product resources, or exclusive products and perks. In essence, companies must prove they deserve access to customer data, not only by backing it with robust privacy and governance protocols, but by delivering tangible benefits in return.
Cybersecurity
By shifting much of their communication and transaction activity to the digital space, businesses have been able to drive significant boosts to growth and efficiency, but in doing so, they've made themselves more vulnerable to cyberattacks. Cybercrime may not be top-of-mind every time a customer makes a transaction, but on the occasion that a breach does take place, the damage done to customer confidence can be devastating. More than half of customers say they won't share personal data with a company that has previously been affected by a breach, and nearly 40% will go as far as cutting all ties with the brand.
To prevent loss of revenue, customer loyalty, and brand credibility, tech-enabled organizations must develop effective cybersecurity protocols to safeguard their customers' data, as well as their own. While this may seem like an obvious step to take, Cisco's 2025 Cyber Readiness Index found that only 4% of companies worldwide had reached a "mature" level of cybersecurity readiness, despite 71% of organizations predicting that their operations would be disrupted by a cyber incident in the next 1-2 years.
As cyber incidents grow more prevalent and sophisticated, organizations can no longer afford "good enough," reactive measures. Instead, they must take a proactive approach—regularly assessing their security infrastructure and addressing any gaps through a combination of software implementation and employee cybersecurity training. While these efforts require an investment of time and money, companies that prioritize cybersecurity often see significant ROI in the form of customer loyalty, positive brand reputation, and a lowered risk of regulatory penalties.
Artificial intelligence
AI tools are impacting CX across industries, and in many cases, bringing greater relevance and convenience to the customer journey. However, customers have significant concerns about its place in business, with only 31% of survey respondents saying they trust companies to use AI responsibly. Much of this concern stems from uncertainty about AI's ability to maintain service quality, deliver accurate information, and safeguard personal data.
There are also questions surrounding the use of data for LLM training. For many organizations, the most useful AI functionalities require input data to be sourced from their customers' behavior, which gets back to ethical issues around trust. While many of the same strategies for handling general data privacy can be applied successfully to AI as well, there are some unique challenges. Chief among them are the continually evolving nature of AI software, and the "black box problem," which refers to a lack of clarity around how AI tools arrive at their results.
When AI decisions cannot be explained, customers are forced into a position of blind trust, unable to ascertain which data was used to reach a given conclusion or whether it was handled in accordance with company standards and industry regulations. And that raises concerns that go well beyond privacy. If the basis for a decision is unknown, it becomes difficult to trust recommendations and determinations, even when they're highly consequential, such as a medical diagnosis or a loan application decision.
This is what makes "explainable AI" (XAI) so important.
With processes and tools that make model behavior more transparent and interpretable, organizations can cultivate greater trust among customers. In practice, this might mean establishing clear, well-publicized guidelines for AI usage, carefully vetting vendors to ensure their solutions meet industry privacy standards, or deploying interpretability tools, such as simplified models that closely mimic a more complex model's behavior and serve as a proxy explanation.
Trust as a KPI
The temptation of technology is that it can boost performance beyond what a human would ordinarily be capable of. However, in the pursuit of performance, the human relationships at the heart of business can start to be overlooked. In some ways, trust can be seen not only as an end in and of itself, but as a broad measure of success across all of the ways that an organization communicates and interacts with its customer base.
It's even been shown that the greater the commitment a company has towards building digital trust, the more likely it is that they will have a high rate of growth. So while a business strategy that targets a variety of KPIs may end up creating the conditions for improving trust, competitive digital enterprises stand to drive enormous value by focusing on maximizing trust itself.
Zoho offers a suite of intelligent enterprise business software, including an award-winning CRM suite, the industry's only comprehensive analytics and BI platform, and a powerful low-code development ecosystem.
