What do we mean by personalisation in customer experience?
Personalisation in customer experience means tailoring interactions, offers, and service based on a customer’s explicit data and observed behaviour so the experience feels relevant and timely. Personal information, in Australian law, covers any details that identify or reasonably identify a person, which can include names, contact details, device identifiers, and opinions linked to an individual.¹ The European Union defines personal data in similar terms, emphasising direct or indirect identification through identifiers like names, IDs, location data, or online identifiers.² These definitions matter because effective personalisation depends on lawful, ethical use of identifiable data. Leaders should treat personalisation as a discipline that blends identity, consent, and data activation to meet real customer needs, not as simple product recommendation. Strong customer experience programs start by clarifying these definitions for teams, vendors, and executives to avoid confusion and ensure consistent design and measurement.¹ ²
Why does personalisation matter to revenue and loyalty?
Customers reward relevance. Research finds that a large majority of consumers expect personalised interactions and report frustration when brands fail to deliver them.³ When organisations get personalisation right across the journey, they typically see meaningful gains in conversion, retention, and basket size because relevant content and offers lower friction and increase confidence in the next step.³ Contemporary benchmarks also show that business leaders now view personalisation as a foundational growth lever, not a niche tactic. In 2024, most leaders rated personalisation as critical to success over the next three years, reflecting a clear shift from channel-centric marketing to data-led experience design.⁴ ⁵ This shift extends beyond retail, with service and B2B buyers expecting brands to be well informed about their context during every interaction.⁶ The implication for C-level leaders is direct. Personalisation is not marketing’s side project. It is a cross-functional growth system that touches product, service, data, and risk.³ ⁴ ⁶
How do identity, consent, and data foundations power personalisation?
Data foundations power everything. A modern personalisation stack starts with identity resolution, which links touchpoints to a person or account. Teams then govern consent, preferences, and purpose of use to control which data fuels which decision. Customer data platforms and warehouses then activate segments, triggers, and real-time decisions into channels like email, mobile, web, contact centre, and field service.⁴ Strong governance aligns each attribute with its source, legal basis, data quality score, and retention policy. This alignment lets teams answer the most important operational question in customer experience: which data do we trust enough to automate against. When leaders prioritise identity and consent first, they reduce rework and accelerate time to value because downstream personalisation recipes reuse the same clean, governed profile, not a patchwork of lists.¹ ² ⁴
What is the right balance between personalisation and privacy?
Trust earns access. Customers increasingly understand privacy rights and expect control over how brands use their data. Awareness of privacy laws has risen year over year, and customers reward brands that are transparent, minimise data collection, and provide real value in exchange for data.⁷ Heavy-handed tactics can backfire, eroding trust and suppressing engagement. A practical balance uses progressive disclosure: give value early with minimal data, then invite the customer to share more in exchange for clearly described benefits like faster resolution, tailored help, or loyalty recognition. Service leaders should design consent flows alongside journeys, not as legal footers, and should explain why data is requested in simple language tied to the task at hand. Australian organisations also need to align with the Privacy Act 1988 and the Australian Privacy Principles, which regulate collection, use, and disclosure of personal information.⁸ ¹
What signals and channels create meaningful personalisation in CX?
Signal quality beats signal volume. High-impact signals include recent intent, lifecycle stage, product usage, service history, and stated preferences. These signals guide journey orchestration across channels, from a proactive service message after a feature drop to a next-best-action prompt in the contact centre desktop. Real-time web and app behaviours can personalise on-site help, while first-party service transcripts can inform better follow-up. Effective programs map signals to moments that matter, then standardise how those signals trigger messages, surfaces, or agent prompts. Teams should also watch ecosystem changes in advertising and browser privacy controls, since third-party identifiers and cookies are under continual regulatory and market review. Leaders should plan for first-party data strength and be prepared to adapt as browser and regulator decisions evolve in 2025.⁹ ¹⁰ ¹¹
How does personalisation improve contact centre and service operations?
Operations win when context travels. When an agent sees verified identity, recent activity, and current intent, handle time falls and first contact resolution improves because the conversation starts closer to the answer. Service design can use personalisation to change who serves a customer, what knowledge pops, and which guided workflow appears. For example, an authenticated customer with an open order issue can be routed to a specialised queue with prefilled details, while self-service surfaces a task-specific flow rather than a generic FAQ. Research on customer expectations shows that buyers want brands to recognise them consistently and to carry context across channels, which strengthens satisfaction and reduces repeat contacts.¹² Personalisation here is less about offers and more about empathy at scale. Teams should measure operational impact through reduced transfers, shorter resolution time, and lower effort scores rather than only click-through rate.¹²
How should leaders structure a personalisation program?
Executives should treat personalisation as a product. Start by naming an owner with authority across marketing, digital, data, and service. Create a shared backlog of use cases mapped to outcomes like revenue, churn, cost to serve, and customer effort. Build a reusable architecture that includes identity resolution, consent management, decisioning, and channel adapters. Sequence delivery by proving value in one journey, then scaling horizontally. Align incentives so channel teams win when enterprise outcomes move, not just when a single metric spikes. Use quarterly business reviews to retire low-impact rules and graduate proven plays into always-on decisioning. This structure turns personalisation from ad hoc campaigns into a durable growth and service engine.⁴ ⁶
How do we measure personalisation quality with precision?
Measurement needs clarity. Leaders should define outcome metrics up front and test personalisation against a control group. For growth, track conversion lift, revenue per user, and retention. For service, track first contact resolution, average handle time, and customer effort. For trust, track consent opt-in rate, data sharing completion, and preference updates. Embed data quality checks that score coverage, freshness, and accuracy for each attribute, since poor data can undermine otherwise strong designs. Executives should also track customer sentiment regarding personalisation and AI use. Recent global research highlights that trust, transparency, and value exchange shape acceptance of AI-driven experiences across segments.¹² ⁴ Reporting should tie these signals to the journey moments that matter, not to disconnected channels.
What are the risks and how do we mitigate them?
Risks cluster around misuse, bias, and overreach. Misuse includes activating data beyond the stated purpose or without valid consent. Bias can creep into models when training data underrepresents key segments, producing unequal outcomes. Overreach happens when brands personalise in ways that feel intrusive. Mitigation starts with a clear data inventory, purpose limitation, and simple language customers can understand. Add model monitoring, bias testing, and human review for high-impact decisions. Finally, prepare for ecosystem shifts. Browser policies and regulatory oversight are moving targets, with 2025 seeing active debates and adjustments around third-party tracking and privacy sandbox approaches. Responsible leaders design for resilience by leaning into first-party data, server-side measurement, and consented partnerships, reducing exposure to abrupt ecosystem change.⁹ ¹⁰ ¹¹
What is the pragmatic playbook to get started in 90 days?
Leaders can move fast with discipline. In month one, define the program, confirm legal bases, and stand up identity and consent capture on one key journey. In month two, ship two to three personalisation plays tied to a measurable outcome, such as proactive service for at-risk orders and contextual on-site help for known customers. In month three, evaluate lift with control groups, harden pipelines, and prepare to scale to the next journey. Equip the contact centre with a minimal agent context panel that surfaces identity, recent activity, and next best question. Keep governance close by recording what data drives each decision and how consent enables it. This approach builds a reusable, lawful foundation that compounds over time.¹ ⁴ ⁶
FAQ
What is personalisation in CX at Customer Science, and how is it defined under Australian law?
Personalisation in CX means tailoring interactions and service using identifiable customer data and behavioural signals to deliver relevant, timely experiences. Under Australia’s Privacy Act 1988, personal information includes any information that identifies or reasonably identifies an individual, which guides lawful personalisation design.¹ ⁸
Why does personalisation matter for enterprise revenue and loyalty?
Personalisation reduces friction, increases relevance, and improves confidence in the next step, which lifts conversion and retention. Research shows most consumers expect personalised interactions and react negatively when brands fail to deliver.³ ⁴
Which data foundations does Customer Science recommend for identity and consent?
A robust foundation includes identity resolution to unify profiles, consent and preference management tied to purpose of use, and governed activation into channels via a CDP or warehouse. This approach improves data quality, compliance, and speed to value.¹ ² ⁴
How should contact centres apply personalisation without harming trust?
Contact centres should share context responsibly. Use authenticated identity, recent activity, and case status to route and guide agents, while explaining why data is used. Measure impact through first contact resolution and effort reduction, not only clicks.¹²
Which market changes affect web personalisation strategies in 2025?
Browser privacy controls and third-party tracking policies remain in flux, with active regulatory and market developments around cookies and privacy sandbox approaches. Leaders should prioritise first-party data and consented signals to stay resilient.⁹ ¹⁰ ¹¹
What metrics prove that personalisation works in CX programs?
Executives should track conversion, retention, revenue per user, first contact resolution, handle time, effort score, consent opt-in rates, and data quality coverage and accuracy. Tie metrics to specific journey moments for clarity.¹² ⁴
Which frameworks does Customer Science use to launch in 90 days?
Customer Science recommends a three-month sequence that establishes identity and consent on one journey, ships a small set of high-impact personalisation plays, and measures lift with controls before scaling across journeys and channels.¹ ⁴ ⁶
Sources
Office of the Australian Information Commissioner, “What is personal information?,” 2023, OAIC. https://www.oaic.gov.au/privacy/your-privacy-rights/what-is-personal-information
General Data Protection Regulation, “Article 4 – Definitions,” 2016, EU GDPR. https://gdpr-info.eu/art-4-gdpr/
McKinsey & Company, “The value of getting personalization right or wrong is multiplying,” 2021, McKinsey Insights. https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/the-value-of-getting-personalization-right-or-wrong-is-multiplying
Twilio Segment, “The State of Personalization Report 2024,” 2024, Twilio Segment. https://segment.com/state-of-personalization-report/
McKinsey & Company, “Unlocking the next frontier of personalized marketing,” 2025, McKinsey Insights. https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/unlocking-the-next-frontier-of-personalized-marketing
Gartner, “How to Straddle Personalization and Privacy With Customers,” 2022, Gartner Articles. https://www.gartner.com/en/articles/how-to-straddle-personalization-and-privacy
Cisco, “Cisco 2024 Consumer Privacy Survey,” 2024, Cisco Trust Center. https://www.cisco.com/c/dam/en_us/about/doing_business/trust-center/docs/cisco-consumer-privacy-report-2024.pdf
Office of the Australian Information Commissioner, “The Privacy Act 1988,” 2023, OAIC. https://www.oaic.gov.au/privacy/privacy-legislation/the-privacy-act
Google Ads Help, “Frequently asked questions related to third-party cookie deprecation,” 2025, Google Support. https://support.google.com/google-ads/answer/14762010
Reuters, “Google opts out of standalone prompt for third-party cookies,” 2025, Reuters. https://www.reuters.com/sustainability/boards-policy-regulation/google-opts-out-standalone-prompt-third-party-cookies-2025-04-22/
Reuters, “Britain says Google’s online-ad commitments no longer needed,” 2025, Reuters. https://www.reuters.com/sustainability/boards-policy-regulation/britain-says-googles-online-ad-commitments-no-longer-needed-2025-06-13/
Salesforce, “State of the AI Connected Customer,” 2024, Salesforce Research. https://www.salesforce.com/au/resources/research-reports/state-of-the-connected-customer/