Data Analyst - Customer Experience (Digital Platforms)

About Springer Nature Group

Springer Nature opens the doors to discovery for researchers, educators, clinicians and other professionals. Every day, around the globe, our imprints, books, journals, platforms and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood and used by our communities – enabling them to improve outcomes, make progress, and benefit the generations that follow.

About the Brand

Macmillan Education provides world-class content in the most relevant, engaging and flexible formats to support students, teachers and institutions in lifelong learning. Visit macmillaneducation.com and follow @MacmillanEducation / @MacmillanELT

Job title: Data Analyst – Customer Experience (Digital Platforms)

Area: Customer Experience and Support

Starting date: June 2024

Location: Warsaw, Poland - Hybrid Working Mode

Role Description:

Macmillan Education is creating a new generation of world class digital learning products, which integrate the best in digital technology with the best pedagogical design. This offering comprises a whole suite of products and services for the Adult, Secondary and Primary market segments. 

The Data Analyst will provide internal stakeholders with actionable analysis and insight into the behaviour of users of our digital products. The role will own analytical products such as dashboards, web analytics and funnel analysis. 

You’ll be working in close collaboration with the Digital Product and Technology leads and their teams to understand strategic priorities with a view to reinforce customer-driven and evidence-driven decision-making, enhancing customer experience and delivering growth impact. 

Role Responsibilities:

• Work proactively and independently with colleagues from Customer Support and Experience, Product Management, IT, Publishing and Finance to create, own and execute data analytics projects that blend commercial, technical and customer needs.
• Collaborate with colleagues from our data analytics commercial team (partly based in our Warsaw office) to contribute to our data centre of excellence.
• Work with stakeholders to understand what the key performance indicators, success metrics and business questions are for their areas, and find the best ways to leverage the data available to answer them
• Provide clarity and creativity in how the data available can be used beyond the existing KPIs in order to identify development priorities and detect growth opportunities: what can it tell us about the types of digital content our customers like the best or can learn from the most effectively? What might the implications be for how we commission content? What can we learn from analysis of user pathways? Are there tools within our platform that receive especially high or low usage? What can we tell from quantitative data about possible reasons for this?
• ‘Join up the dots’ between sales data, account activations and platform usage analytics to help us learn more about our customer funnel, enabling us to target communications according to behaviour, with a view to driving up exploitation and usage of digital products
• Through liaison with our Market Intelligence and Sales teams, model how educational and technological trends may impact usage of our digital platforms
• Develop usage forecasts and projections to inform infrastructure scaling
• Through analysis of quantitative analytics and qualitative user research, provide data-led recommendations for non-functional requirements for our platforms, such as target load speeds or download times
• Through data mining, help identify and surface issues that might be specific to a particular group of users – for example, longer load times being experienced by users of a particular device/browser combination
• On a regular basis, evaluate the achievement of KPIs from across Digital Product and Content; develop regular reports to be shared with senior management
• Own and maintain the analytics solutions that have been implemented. Keep abreast of any relevant technology updates required, and continually refine and adapt analytics dashboards as our digital products, customer priorities and KPIs evolve
• Enhance data collection and drive consistency and best-practice for front-end tracking approaches; team up with relevant technical teams for implementation
• Over time, set the analytics strategy for Digital Product, and determine the core analytics solutions that are needed to ensure that the right data is available to drive decision-making in content and feature investment in the future
• Provide training to the wider team to develop their core analytics skills and support data-driven decision-making across the department.

Key Relationships: 

• Colleagues from Customer Experience and Support, Product Management, IT, Publishing and Finance

Skills and Qualifications:

• University degree with a strong analytical/quantitative background or equivalent experience (e.g. Data Science, Statistics, Mathematics, Econometrics, Physics, Computer Science etc.)
• Excellent working knowledge of analytics data products (such as Google Datastudio, Looker, BigQuery, Dataform, Colab, Analytics, Tag Manager or equivalents from other vendors) 
• Good working knowledge of SQL and one other technical language (Python, R, JS or solution specific language)
• Demonstrable experience of using data insights and analytics to add tangible value in achieving the wider goals and strategy of the business
• Excellent analytical problem-solving capabilities coupled with business acumen
• Demonstrable experience in developing and communicating insights, a strong storyteller
• Self-starter with ability to work with minimal direction and high level of ownership
• Passionate about working with data
• Curiosity, reasoning skills with proven evidence of problem solving
• Familiar with Agile practices
• Statistics, data science or coding experience is beneficial but not essential

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