Head of CRM & Insights

Solihull
2 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Engineering

Head of Artificial Intelligence – Smart Manufacturing

Head of Commercial Analysis and Reporting

Head of Hardware

Head of Software Engineering | £150k – Java, Machine Learning, and Data-Driven Innovation

Head of Data Science and Analytics

Head of CRM & Insights | The Midlands | Hybrid | Salary up to £95k Basic + Bonus + Pension + Car Allowance

Our client is a leading multi-channel retailer, based in The Midlands, and are looking to appoint a Head of CRM & Insights to the team. This role is a pivotal position designed to leverage data and customer insights to drive business growth.

The Head of CRM & Insights will play a critical role in shaping and executing the company's customer relationship management and insight strategies. This individual will be responsible for driving customer retention, engagement, and loyalty across all channels by using data aggregation techniques and personalisation strategies. The role will require a deep understanding of customer data, the ability to extract actionable insights, and the expertise to tailor CRM campaigns to individual customer preferences.

The successful candidate will manage a team and work collaboratively across departments to ensure CRM and insight strategies align with the overall business objectives.

Key Responsibilities In The Position of Head of CRM & Insights

Customer Insights & Analytics: Lead the aggregation and analysis of customer data from various touchpoints, including website interactions, transaction history, and customer feedback. Leverage this data to develop actionable insights and create a deep understanding of customer behaviours, preferences, and needs.
Personalisation: Use data aggregation to drive personalisation strategies across all customer touchpoints. Ensure tailored and relevant messaging, product recommendations, and offers are delivered to customers based on their individual behaviour and preferences.
Cross-functional Collaboration: Work closely with Marketing, Sales, IT, and other departments to ensure CRM initiatives are integrated across the business. Collaborate with the Data Science and Analytics teams to ensure data aggregation efforts align with CRM and personalisation objectives.
Data Aggregation Tools & Platforms: Champion the use of data aggregation tools and CRM platforms to ensure a single customer view is established. Work with relevant teams to continuously enhance data collection, integration, and management processes.
Reporting & Budgeting: Regularly report on the effectiveness of CRM initiatives, customer insights, and campaign results to senior management. Develop and manage the CRM & Insight budget to ensure resources are allocated efficiently.
Technology & Tools: Stay up-to-date with the latest CRM technologies and tools. Ensure the company is using the most effective platforms to aggregate and personalise customer data, driving CRM success and customer insights.
Customer Experience: Work alongside the customer service and digital teams to ensure that CRM efforts align with the overall customer journey, enhancing both online and offline experiences through consistent and personalised communication.
Compliance: Ensure all CRM strategies and customer data management practices comply with relevant data protection and privacy laws, including GDPR.To Be Considered For The Position of Head of CRM & Insights, You Will Offer The Following:

Education: A degree in Marketing, Business, Data Analytics, or a related field is preferred.
Track Record: A minimum of 8 years of in CRM, customer insight, or a related role, with at least 3 years in a leadership position. Experience within a multichannel retail environment is highly desirable.
CRM Platforms & Tools: Strong proficiency in CRM platforms (e.g., Salesforce, Microsoft Dynamics, or similar), data aggregation tools, and personalisation software.
Data Analytics & Personalisation: Proven in using data aggregation techniques to create a unified customer profile and develop targeted, personalised experiences.
Campaign Management: Proven in planning, executing, and optimising CRM campaigns, with a focus on personalisation and delivering results based on data-driven decisions.
Customer-Centric: Deep understanding of customer experience principles, with a passion for driving improvements in customer loyalty and engagement.
Compliance Knowledge: Knowledge of data protection laws, including GDPR, and experience in ensuring CRM practices align with legal requirements.Apply today to find out more and be considered!

BBBH32792

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.