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CV Tips for Marketing Analytics

Bright lightbulb among dark ones 
 

Writing a new CV can often to be a more challenging task than you initially think. Accurately portraying your skills, breadth of experience and knowledge within a few short pages is a tough task. There are a number of online guides about how to write a good CV, along with a variety of opinions on what works; questions around the latest style, layout and how many pages it should be, make this a very subjective topic.

We have written the guide below to give you some useful tips around writing your CV, based on feedback from employers about what they expect to see on a Marketing Analytics & Insight professional’s CV. Consider this quote from one of our clients:

 “…the point of having an analyst in a business is to accurately condense and analyse large volumes of data and draw out the relevant pieces of information that can have an impact on a business. An analyst should be able to sift through irrelevant information and draw everything together to highlight relevant information in a compelling way. If an analyst isn’t able to have the same approach with their CV and draw out the information that is relevant and discard the rest, it doesn’t give a good impression or an indicator that they will be an effective analyst.”

So how do you go about making sure that your CV does give the right impression and get you that interview opportunity?



Get the structure right

Layout and formatting

Content - Be specific

Tailor your CV

Your CV is your sales pitch



Get the structure right


A good structure should typically follow this order:

  • Name and contact details (Include contact number and email)
  • Personal Statement / Summary
  • Key Skills
  • Employment History
  • Education
  • Interests
  • References

However, don’t be afraid to deviate from this structure in order to demonstrate your relevance for a particular position more effectively. If you are a recent graduate, with a relevant mathematical degree, but little or no relevant employment history, you are likely to have more success by highlighting your relevant academic background above your employment history.

Layout and formatting

Use a clear layout and include headings to separate each of the above sections. Within each section use bullet points to define your role, responsibilities and skills rather than long paragraphs full of commas. This will help to make the content far easier to scan for key information and is more likely to grab the attention of the employer.

Keep the whole document relatively short, 2-3 pages maximum.

Pay attention to detail and spelling: many of our clients reject applications based on this – remember our client quote! Ensure all information is accurate; dates, company names, skills, technologies used and don’t be shy of Spell Check.

Make sure all formatting is consistent: we recommend you use the same font throughout the document and utilise bold to highlight subsections and headings. Typically, fonts such as Arial or Times New Roman are acceptable.

Content - Be specific

The content should be clear and concise, but with enough information to give the employer a solid understanding of what your role entails and what your responsibilities are.

It is useful to give a brief introduction to the company and / or team to add context, but essentially the employer is going to be more interested in hearing about your skills and responsibilities and not those of the team in general.

With regards to the data sets, statistical tools and techniques you typically employ, specific information here is also key. For example;

  • You highlight that you use SAS in your current role. Try to elaborate on this i.e. Are you using Enterprise Guide, Macro, Base? Do you write your own code or employ more drag and drop techniques?
  • You also work with propensity models. Did you build the model or are you working on existing models and validation? Do also have experience of clustering, segmentation, regression or similar techniques?
  • You work with a range of data sets. What kind of data is it; Transactional, campaign? Make sure you explain. It’s also important to remember that large data sets are typically appealing to companies; therefore ensure you refer to the size of the data sets you’ve been exposed to. For example, how many rows of data do you typically deal with, or how many campaigns are you used to running each month?

Adding these snippets of key information won’t take up a lot of valuable space, but will help give your prospective employer a more detailed understanding of your skills and level of competence, ultimately, helping boost your chance of securing an interview.  

Tailor your CV

Lastly, tailor your CV for each role you are applying for:

Carefully read the job adverts and descriptions and highlight relevant pieces of information to showcase your skills and experience that most suited to what the company are looking for.

Likewise, amend your personal statement for the same reason. Don’t be the person who applies for a Customer Insight Analyst position with a Retail & FMCG consultancy when your personal statement still says you are looking for a Marketing based role in a Client side Financial Services organisation!

Your CV is your sales pitch

Remember, CV’s are meant to be factual but they are also a tool to sell yourself, so make the content interesting, relevant and engaging – this could be the only opportunity you have to convince an organisation that you are someone they want to interview and help you stand out from the other applications they receive.



<< By Kat Heague >>

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