Marketing Analysts support the client facing project and account teams by undertaking analysis and modelling of client data for the purpose of measuring marketing effectiveness and/or maximising marketing ROI.
Within this they may undertake any or all of the following types of data analysis and tasks: analysis of large data set customer level data; econometric and / or marketing mix modelling; complex correlation analysis; finding and manipulation of multiple data sources inside and outside of a client organisation; extracting, transcribing, processing, tabulating, manipulating, calculating, graphing, correlating, and preparing data for use in statistical analyses and / or presentations. Presenting work internally and externally as required.
The range of data types used would include commercial, financial, operational, media, economic and marketing data alongside customer-level transactional data.
Accountabilities and Responsibilities
To achieve the above requires undertaking a number of general and specific tasks related to the design, commissioning and delivery of RRI projects and to the provision of support for the future development of each account. These tasks include, but are not limited to, the accountabilities and responsibilities as shown below:
- Working with the client and other members of the RRI account team to obtain and process potentially multiple data sources to allow the analysis to commence.
- Development of econometric models, marketing mix models and complex correlation analyses. Able to draw critical conclusions from these models and analyses and to make recommendations to RRI and client facing team members
- Manipulating data whether the data is of a numerical, textual, visual or other kind, and also whether the data is in structured or unstructured formats; often using very large data sets including customer level data
- Preparing tabulations; financial and accounting-type calculations; graphical comparisons; pivot table analyses; complex correlations; and keeping all such prepared data in neat and clearly documented formats so that it is easy for others to follow and extend the work as may be required
- Using Microsoft Excel, Word, and PowerPoint to undertake these tasks with minimal effort, and potentially using other software such as Microsoft Access (free training in the use of other systems will be provided if/where that is required) and being able to present data in other formats (e.g. using infographic approaches) would be helpful
- Using existing spreadsheet “What if..?”” models (that may comprise many connected spreadsheet pages) to run scenarios as directed by members of the Project / Account team and then summarise the results in a logical and comparative manner
- Constructing detailed spreadsheet “What if..?”” models to designs specified by the Project / Account teams
- Producing client facing presentations to communicate the key findings from analysis in a clear and concise way. Participating in the presentation of results to senior client facing teams
Our Ideal Candidate
We have Analysts at varying levels of seniority and experience but all have demonstrated technical experience in successfully applying data sciences / complex analysis for major corporations in either client-side, agency, and/or consultancy roles in one or more of these areas: market mix modelling; CRM analytics, campaign analysis, decision tree analytics and propensity modelling; price & promotions effectiveness; customer segmentation, including psychographic modelling, key drivers analysis and structural equation modelling; artificial intelligence; media coverage modelling and effectiveness; search engine marketing analytics; social media analytics & modelling; location planning & retail operations analytics & modelling; strategic & tactical sales forecasting; category management analytics; and automated marketing & IOT analytics. They have excellent skills and technical expertise in using Excel, SAS and SPSS and the development of databases for the provision of business insights and decision support. Knowledge of R, Python, and other statistical and data analysis systems (such as IBM Watson AI, Business Objects, QlikView, Oracle, Teradata, etc) are a strong advantage for these roles; and evidence of supporting business building through e.g. providing pre-sales consultancy to identify and quantify client business opportunities is also desirable for the most senior analyst roles.
All of our Analysts are self-employed, enabling them to build a personal portfolio of clients and a level of income that suits their own lifestyle and ambitions. Remuneration is via payment for the time spent in delivering client services. Analysts report to the RRI Project Manager, Principal Consultant, Analytics Manager or Account Manager responsible for the relevant area of work they are undertaking.