Customer Enablement Director

Corsearch
St Paul's
1 year ago
Applications closed

Related Jobs

View all jobs

Customer Campaign Data Analyst - B2C

Data Analyst

Data Analyst Level 4 Apprentice

Data Analyst Level 4 Apprentice

Senior Data Engineer

Data Analyst Level 4 Apprentice

Do you get excited when hearing about trademarks and brand protection news? YES? So do we At Corsearch, there’s no pushing trademark solutions and brand protection from our thoughts. We’re thinking about coined trademarks in the car, a detailed design search over lunch, counterfeits while sitting with the in-laws, and anti-piracy while working out We are a mission-led company, driven by a passion for making the world better and safer for our brand customers and their consumers. It’s what we do. And people come to Corsearch to be challenged, developed, supported, and valued ✅The Role The Customer Enablement Director is responsible for enhancing the operational capabilities of customer-facing teams to ensure the seamless execution of internal workflows aimed at improving overall customer experience and satisfaction. This role focuses on creating and optimizing processes, systems, resources and collateral, that enable the delivery of the value proposition at every stage of the customer journey. The role will collaborate closely with other members of the Customer Value Team and cross-functional teams to ensure alignment and adaptability in meeting the evolving needs of the business. ✅The Team The Customer Value Team’s mission is to empower Corsearch to deliver unparalleled value and outcomes to our customers by strategically aligning resources, insights, and initiatives. The team has full focus on elevating the customer experience by implementing strategies that increase satisfaction and foster long-term relationships. Improve customer satisfaction and experience by optimizing the customer journey and customer communication Drive customer lifetime value through stronger value articulation and customer outcome delivery. Enable the customer facing teams through skill and best practice frameworks, standard operating procedures and fostering customer centricity ✅Responsibilities and Duties Leading Execution Excellence and Process Optimization: Develop and lead enablement strategy for teams involved in customer retention and growth, ensuring alignment with Corsearch’s broader goals for customer retention and growth Ensure that customer-facing teams execute processes and initiatives effectively, consistently, and in line with the value proposition. Continuously review and optimize existing processes to enhance operational effectiveness and customer outcomes. Track ongoing delivery and timelines across different departments, report progress and drive accountability. Enhancing Cross Functional Collaboration: Work closely with team leaders to align enablement initiatives with identified customer journey improvements, performance goals, and product developments. Drive engagement and improvements with the 2-in-the box model (joint customer ownership between commercial and services teams) model. Work with other enablement functions to drive cohesive enablement programs across Corsearch. Developing and Maintaining Standard Operating Procedures (SOPs) and Best Practices: Create, communicate and maintain comprehensive SOPs for the customer-facing teams. Ensure that SOPs are up-to-date, accessible, and adhered to by all team members. Identify, document, and share best practices and knowledge of customer enablement with key stakeholders. Create and implement playbooks to monitor customer sentiment and support account health throughout their journey with Corsearch. Foster a culture of continuous improvement by encouraging the adoption of best practices. Productivity and Capacity Management: Develop a clear view on trends related to customer facing teams’ productivity capacity, and performance, identifying bottlenecks and process improvement opportunities. Work with customer teams and the Customer Value Team to build a clear view on analyze and inform the optimal size of customer portfolios to facilitate improvement in service quality and customer satisfaction Provide data-driven recommendations for capacity adjustments, resource allocation, and potential skill/capability gaps. Developing Skills and Capabilities: Work with Learning and Development and internal subject matter experts to drive the design of skills and competency frameworks for the customer facing teams Continuously evaluate and improve skills and competencies requirements in collaboration with HR and training teams Collaborate with the customer-facing teams to develop enablement resources, collateral, and training for Corsearch’s teams to ensure consistency in customer experience Measuring Success and Driving Continuous Improvement: Establish key performance indicators (KPIs) to measure the effectiveness of enablement initiatives in collaboration with senior data analysts. Analyze data and feedback to drive continuous improvements in processes and tools. Own the enablement tooling (e.g., Customer Success platform, project management tool), ensuring proper usage, adoption, and continuous improvement. ✅Essential Background is SaaS and Professional Services Proven change management and project management experience Proven experience in developing and leading customer enablement strategies that have driven significant improvements in customer retention and operational efficiency. Extensive experience in optimizing processes within customer-facing teams, ensuring that execution aligns with the company’s value proposition and strategic goals. Demonstrated success in designing and implementing Standard Operating Procedures (SOPs) and playbooks that have enhanced the effectiveness and productivity of customer-facing operations. Experience in driving cross-functional collaboration to dynamically align enablement strategy with evolving product developments, customer feedback and insights, as well as wider organisational goals. Highly skilled at requirements gathering, scoping and planning Hands-on experience in capacity planning and resource allocation, ensuring optimal support for customer-facing teams based on commercial forecasts and operational needs. Strong background in measuring the effectiveness of enablement initiatives through KPIs (leading and lagging), driving continuous improvements based on data and feedback. Corsearch is an equal opportunity and inclusive employer and does not tolerate discrimination of any kind. We are committed to creating a diverse and inclusive workplace where all employees feel valued, respected, and supported. We welcome applications from all individuals regardless of race, nationality, religion, gender, gender identity or expression, sexual orientation, age, disability, or any other protected characteristic. Together, we are working proactively to build a workplace where everyone can belong and be at their best selves. Together, we make an Impact.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.