We are seeking a commercially minded personalisation and AI activation leader to define and scale how customer data, predictive intelligence and AI-enabled decisioning are translated into relevant customer experiences and measurable business impact.
The role will own the group-wide personalisation roadmap, identify and prioritise high-value use cases, and work across CRM, Loyalty, MarTech, Ecommerce, Analytics and brand teams to activate Customer 360 insights across channels and customer journeys.
The ideal candidate combines strong lifecycle marketing and personalisation expertise with practical experience using predictive models, experimentation and AI-enabled activation. This is not purely a campaign-management or data-science role. It is responsible for turning customer intelligence into scalable activation strategies, proving incrementality and ensuring personalisation delivers measurable commercial value.
Role Mandate
- Own and drive the group-wide personalisation and AI activation roadmap across brands, channels and customer journeys.
- Translate Customer 360 data, behavioural signals and predictive insights into scalable targeting, next-best-action and personalisation use cases.
- Identify and deliver high-impact AI-enabled activation opportunities that improve engagement, conversion, retention and customer lifetime value.
- Establish clear measurement standards for personalisation use cases, including incrementality, ROI and business impact.
- Create a repeatable operating model for identifying, prioritising, testing and scaling personalisation initiatives across the organisation.
Key Responsibilities
Personalisation Strategy & Roadmap
- Define and maintain the enterprise personalisation roadmap aligned to customer, commercial and brand priorities.
- Identify the highest-value opportunities across acquisition, engagement, conversion, retention, cross-sell, upsell and reactivation journeys.
- Prioritise use cases based on customer value, commercial impact, data readiness, technical feasibility and speed to market.
- Build a balanced portfolio of quick wins, scalable use cases and longer-term AI-driven capabilities.
- Ensure personalisation activity moves beyond isolated campaigns toward reusable decisioning and activation capabilities.
AI-Enabled Activation Use Cases
- Develop and operationalise AI-enabled personalisation use cases across CRM, digital, ecommerce, loyalty and paid/owned channels.
- Work with Analytics and Data Science teams to convert predictive models into practical customer treatments and activation strategies.
- Define use cases such as next-best-action, next-best-offer, propensity-led targeting, churn prevention, cross-sell, replenishment, recommendation and lifecycle intervention.
- Translate model outputs into clear business rules, audience logic and activation journeys.
- Ensure AI use cases are explainable, commercially relevant and suitable for scalable deployment.
Customer 360 & Audience Strategy
- Translate Customer 360 insights into meaningful segments, audiences and customer decisioning strategies.
- Define scalable audience frameworks based on customer behaviour, value, lifecycle stage, affinity, intent and predicted outcomes.
- Reduce overreliance on static segmentation by introducing more dynamic, behavioural and predictive targeting approaches.
- Partner with CRM, Loyalty and MarTech teams to ensure audience logic can be consistently activated across channels.
- Identify gaps in customer data, identity or attributes that limit personalisation effectiveness and drive resolution with relevant teams.
Experimentation, Incrementality & ROI
- Establish a clear experimentation framework for personalisation and AI activation use cases.
- Define appropriate control groups, holdouts, A/B tests and pilot structures to measure incremental impact.
- Ensure performance reporting distinguishes correlation from proven incremental business impact.
- Track uplift across key metrics including conversion, frequency, retention, average order value, engagement and customer lifetime value.
- Build business cases and post-implementation reviews to demonstrate ROI and inform future investment.
Use Case Prioritisation & Quick Wins
- Identify high-impact quick wins that can demonstrate value rapidly using available customer data and existing MarTech capabilities.
- Assess use cases based on commercial value, data readiness, implementation effort, dependency and scalability.
- Create a transparent use-case backlog with clear prioritisation criteria, owners and expected outcomes.
- Balance short-term value delivery with development of longer-term strategic capabilities.
- Ensure successful pilots are industrialised rather than remaining isolated experiments.
Activation & Journey Design
- Partner with CRM, Loyalty, Ecommerce, Product and channel teams to translate personalisation strategies into customer journeys.
- Define decision points, trigger logic, treatment strategies and channel sequencing for key customer moments.
- Ensure experiences remain relevant and coordinated across email, app, web, push, paid media and other channels.
- Drive consistency between audience strategy, content strategy, decisioning and channel execution.
- Identify opportunities to automate journey decisions and reduce manual campaign dependency.
Data Science & Analytics Partnership
- Act as the key business partner to Data Science and Analytics for personalisation-related models and use cases.
- Translate commercial problems into clear analytical and modelling requirements.
- Evaluate whether predictive models are suitable for activation based on accuracy, interpretability, stability and commercial usability.
- Challenge models that perform technically but do not translate into practical business outcomes.
- Ensure model performance and business impact are monitored after deployment.
MarTech & Capability Enablement
- Partner with MarTech and Engineering teams to define the capabilities required to support scalable personalisation.
- Identify gaps across CDP, CRM, decisioning engines, recommendation platforms, customer identity and activation tooling.
- Help define requirements for real-time decisioning, audience orchestration and AI-enabled activation.
- Ensure technology investments are tied to clear use cases and measurable customer or commercial outcomes.
- Support vendor and platform evaluations where personalisation capability is a key consideration.
Governance, Privacy & Customer Experience
- Ensure personalisation strategies follow applicable data privacy, consent and governance requirements.
- Partner with Privacy, Legal, Data Governance and Security teams to ensure appropriate use of customer data and AI.
- Establish guardrails to prevent over-targeting, inconsistent customer treatment or inappropriate use of predictive signals.
- Ensure personalisation improves customer relevance without creating a fragmented or intrusive experience.
- Maintain transparency around assumptions, targeting logic and AI-enabled decisioning.
Stakeholder & Cross-Functional Leadership
- Act as the central personalisation and AI activation partner across Loyalty, CRM, MarTech, Ecommerce, Analytics, Product and brand teams.
- Influence senior stakeholders on where personalisation can create the highest business value.
- Align business teams on common use-case priorities and reduce duplicated or fragmented personalisation initiatives.
- Translate complex analytical and AI concepts into clear commercial recommendations.
- Drive accountability for delivery, adoption and measurable outcomes across cross-functional teams.
Key Stakeholders
- Internal: CRM, Loyalty, MarTech, Ecommerce, Digital Marketing, Product, Customer Strategy, Analytics, Data Science, Engineering, Finance, Data Governance, Privacy, Legal and brand/market leadership.
- External: MarTech and AI platform providers, consulting partners, data science specialists, systems integrators and activation agencies.
Qualifications & Experience
- 7–9+ years of experience in personalisation, CRM, lifecycle marketing, customer strategy, digital marketing, MarTech, analytics-led activation or a related field.
- Demonstrated experience designing and scaling personalisation, lifecycle or audience strategies.
- Practical experience working with predictive models, propensity models, recommendation engines or AI-enabled customer use cases.
- Strong understanding of customer segmentation, lifecycle journeys, next-best-action and behavioural targeting.
- Experience defining and measuring incremental business impact through controlled experimentation.
- Demonstrated ability to convert analytical insight into commercial activation and measurable outcomes.
- Experience working in complex, multi-brand, multi-channel or multi-market organisations is preferred.
- Bachelor's degree in Marketing, Business, Analytics, Economics, Data Science, Information Systems or a related field. Advanced qualification is advantageous.
Technical & Functional Skills
- Strong knowledge of personalisation, CRM and lifecycle marketing frameworks.
- Strong understanding of Customer 360, segmentation, audience management and customer decisioning.
- Practical knowledge of predictive analytics, propensity modelling, recommendation strategies and AI-enabled activation.
- Experience with experimentation, A/B testing, holdout groups and incrementality measurement.
- Understanding of MarTech ecosystems including CRM, CDP, marketing automation, decisioning and activation platforms.
- Ability to define use cases, business requirements, journey logic and measurement frameworks.
- Strong commercial and analytical capability with the ability to assess ROI and prioritise investments.
- Familiarity with SQL, BI tools or analytical platforms is advantageous but not mandatory.
- Strong presentation and storytelling capability with senior leadership audiences.
- Leadership Capabilities & Behaviors
- Commercially focused, with a strong bias toward measurable customer and business outcomes.
- Able to connect customer insight, AI capability and business strategy into practical activation.
- Comfortable challenging assumptions and pushing teams beyond traditional campaign-based approaches.
- Strong stakeholder-management capability across business, technology and analytics functions.
- Structured and outcome-oriented, with the ability to prioritise across multiple use cases and dependencies.
- Balances innovation with practicality, focusing on use cases that can be implemented, measured and scaled.
- Curious about emerging AI and personalisation capabilities while maintaining disciplined governance and customer relevance.
- Creates alignment across teams and drives shared accountability for delivery and results.
About us -
CSi (Customer Strategy Intelligence)
CSi is a newly established strategic business unit within Landmark Group, bringing together the organization's most critical growth-driving capabilities into one integrated engine. Designed to shape the next phase of retail innovation, CSi unifies Data & Analytics, Loyalty (Shukran), Partnerships & Co-brands, Performance & Digital Marketing, and Customer Product & Martech under one vision. At its core, CSi stands for Customer, Strategy & Intelligence—placing customer experience at the center, enabling smarter business decisions through data, and leveraging AI and Business Intelligence to power every interaction and outcome.
Joining CSi means becoming part of a high-impact team where Product, Data, AI, and Customer Experience converge to build solutions that serve millions of customers across multiple brands. This is an opportunity to work on meaningful business challenges, take ownership of strategic initiatives, and help redefine how modern retail operates in the region. We are looking for individuals who think customer-first, enjoy solving complex problems through data and technology, and are passionate about AI, Martech, Product, or Analytics. If you're looking to contribute to a fast-paced, highly visible environment where your work drives real business impact, CSi offers the opportunity to build the future of customer intelligence on a scale.
Landmark Group
Our journey started in 1973 with a single store in Bahrain. Since then, we have grown into a global retail and hospitality group. The proud creator of 50 plus value led, own-built brands across retail, hospitality, food, and leisure. Over the years, our UAE-based group has evolved into a comprehensive retail and hospitality entity, with over 2400 retail stores, leisure, and hospitality outlets, spanning the GCC, Middle East, India, Southeast Asia, and Africa. Landmark Group headquartered in Dubai, UAE is one of GCC's largest omnichannel retailers and India's top home and fashion retailer. We take immense pride in the organic growth of our retail brands, which have blossomed into household names. From Max, Splash, Babyshop, Centrepoint, Shoemart, Home Centre, Emax, Fitness First, to Fun City, to name a few, our brands span across a multitude of categories, enriching the lives of countless families over the past decade.
