CONSULTANT(E) CRO – CONTENT SQUARE
Paris, Île-de-France / €45000 - €55000
€45000 - €55000
CONSULTANT(E) CRO - CONTENT SQUARE
Cette société spécialisée dans la data recherche son/sa consultant(e) CRO pour continuer à développer sa forte croissance.
Si vous avez envie de rejoindre une société innovante où vous aurez la possibilité de mettre à profit votre connaissance de Content Square tout en développant vos connaissances stratégiques et Analytics, ce poste est fait pour vous !
Rattaché(e) au responsable data, vous aurez pour missions principales l'amélioration de l'expérience utilisateur et l'optimisation des conversions. Ceci inclus:
- Recherche utilisateurs (quali)
- Audit CRO , optimisation des conversions, suivi des performances
- Formations clients
- Bac +5 en École de Commerce / ou diplôme équivalent
- Première expérience sur un rôle similaire
- Maîtrise de Content Square et sa certification
- Connaissance d'un outil de Web Analytics (Google Analytics, AT Internet, Adobe Analytics, autres)
Merci de me faire part de votre CV et je vous recontacterai au plus vite.
Why Marketing Teams Need to Fill Their Data Skills Gaps
Data can be leveraged in a myriad of ways and be beneficial to numerous business functions.
In marketing, for example, data is playing an increasingly important role in helping brands get closer to their target customers, which ultimately improves the bottom line. Businesses that use data-driven marketing strategies have five times more ROI than those that don’t.
Despite this potential, a new survey has revealed that data analytics is one of the biggest skills gaps in marketing departments. Below, we break down this new research and explain why it’s crucial to fill your company’s data skills gap and build a data-driven marketing team.
So why does this skills gap matter?
The recent research revealed more than a third (34.4%) of the 3,000-plus respondents identified a lack of data analytic skills in their marketing department. For B2B marketers, the figure drops to 29.9 per cent, while it’s 34.6 per cent for B2C marketers, and jumps to 39.6 per cent for businesses with a mix of both.
These findings are particularly pertinent as marketing isn’t a department that operates within a bubble, rather it has its tendrils in every part of an organisation, so when marketing isn’t functioning as optimally as possible, neither is the business.
Businesses that are not harnessing the insights that data analysis offers, are missing out on the ability to understand and meet their customer’s preferences. Making decisions that are not grounded in data means that a business is operating in the dark – throwing ideas at the wall to see what sticks rather than already knowing what will work because the data has told them so.
Many companies have realised that it’s no longer good enough to guess what customers might want or need from a product or service, but to instead have hard evidence to back up these choices. A data-led marketing strategy can revolutionise marketing efforts in numerous ways such as:
Behaviour analysis and personalisation
By analysing a customer’s behaviour, such as their e-commerce and website browsing habits, marketers can ensure that the businesses’ landing pages, calls to action and other marketing tools are working as they should be, and use this data to better tailor content and improve the customer experience.
Behaviour analysis might include examining customer interactions, such as where and when they click on a website, even down to which pages consumers are lingering on for longer. The content you are producing might be incredibly insightful and smart, but that’s irrelevant if customers aren’t reading it. Once you have understood where people do and don’t spend time and which content attracts the most engagement, assets can be shaped to scoop up people who might otherwise leave a site, further entice already interested parties and inform other marketing activities.
For example, if you’re a business that sells clothes, you can use data analytics to determine which colours and styles are most popular among your customers and create content such as fashion tips or trend reports including these colours and styles.
Through monitoring the current behaviour of customers, businesses can also more easily identify when and how their preferences change. For example, if visitors to written pieces are dropping off, you could consider incorporating more video content. Reacting to the subtle changes in customer behaviour can help companies to maintain their position in the market and increase their revenue by tapping into new pools of customers.
Predicting customer patterns
But data isn’t just for making better in-the-moment decisions. It can also help to pre-empt future customer behaviour, allowing businesses to make proactive decisions based on previous trends, rather than acting reactively.
Predictive analytics is the use of data algorithms and techniques to define the likelihood of future events or results, based on historical data from customer habits. It allows marketers to forecast a customer’s “next move”, such as which consumers are most likely to buy again, and therefore prioritise customers.
Based on previous patterns of behaviour, businesses can predict website engagement points where, for example, a customer may convert, but also areas where consumers might lose interest or drop off – friction points such as filling in a form. This information enables businesses to make choices that ensure that the customer experience is as smooth and effective as possible.
How can this skills gap be filled?
The effectiveness of data analysis is dependent on talent being able to carry it out. At Harnham, we specialise in data hires for marketing. In other words, through experience, our consultants have built a comprehensive picture of what marketing teams need when it comes to data marketing talent. When it comes to hiring a data marketing professional there are a wealth of skills to look for, including:
- Being a problem solver – a candidate who can identify logical ways to overcome problems and offer solutions.
- Having a good grounding in coding languages such as SQL. Whilst it can be beneficial to have more advanced modelling skills using R or Python, some companies will have data science teams to support on this side.
- Experience with visualisation tools and with programs such as Tableau or Looker – which can be hugely valuable in hitting the ground running.
Most crucial, however, is the ability to tell a story with the data and make something complex easy to digest. During an interview, businesses can identify how someone translates recommendations and if they are able to recognise and illustrate the commercial impact that their work will have.
If you’re interested in applying your data skills to a role in marketing or are looking to bolster the success of your business by hiring a Data & Analytics specialist, you’ve come to the right place contact our team today.
Resume Tips for Professionals in Risk Analytics
Resume Tips for Professionals in Risk Analytics
There are a number of online guides about how to write a good resume, and everyone seems to have an opinion about what works, what the latest style is, and how many pages your resume should be.
In general, much of the resume advice out there is subjective. However, at Harnham, our consultants shift through countless resumes as part of their day-to-day jobs. Because of this, we have an in-depth understanding of the types of resumes that get a company’s attention, and the ones that don’t.
With this in mind, here are a few resume tips from our consultants on what to consider when drafting your resume, specifically for professionals in the Risk Analytics space.
What’s Going to Get You That Interview?
One of the most important things to keep in mind when drafting a resume is your overall goal. If you’re putting together or updating your resume, we’re going to go ahead and assume you’re using it to secure an interview, and ultimately, land a job.
A while nobody secures a role from the content of their resume alone, a poorly written resume can cost you the opportunity to even get to the interview stage.
So, what are the most important content elements to consider when drafting a resume?
- Structure: Decision-makers should be able to find the information they need quickly and easily.
- Concise communication: It’s important to show your ability to communicate clearly.
- Spelling/grammar: Sounds simplistic, but this will be looked at. Remember your resume is a document that you should have taken time to produce, so small errors will be costly.
Below, we’ll dive into more detail on what a solid structure looks like, and how to make your content stand out.
What Does the Structure Look Like?
This may well differ and is dependent on the level of role you are applying for. You will need to put yourself in the shoes of the decision-maker – what are they looking for in order to progress you to the first stage interview?
If you are a recent graduate, they will be looking at your education, but if they need people with experience, then this is the most important element for them.
Regardless of the level of the role you’re applying for, make sure to start your resume with a short statement about yourself. This profile shouldn’t be too informal and should focus on highlighting the strengths and skills you possess, relevant to the role on offer.
How to Summarise your Experience
Technical skills (SAS, SQL for example) tend to be important for roles in Credit Risk, so all relevant skills and technical knowledge like these should be highlighted.
However, what’s even more important is to clearly show how the application of your technical skills, knowledge, and experience had a positive impact on your current and/or previous company.
For example – if you came up with a new strategy for improving accept rates whilst reducing bad debt costs, show the data behind this change, and clearly outline the impact. Include precise, but not in-depth, detail to highlight your achievements.
“Reduced bad debt costs by 13% whilst increasing accept rate by 7%” is a lot more positive than “Reduced bad debt costs and increased accept rates”.
Also, it is worth explaining how you achieved something. If you had an idea that was put into practice, then go into a little more detail. Not too much – this is just to get you an interview after all, and you need to have something to tell them when you get to meet them beyond this information, but it should be just enough to make them interested to learn more.
For example, “I devised a refer rate strategy, coding daily lists in SAS. Once automated, refer rates fell by 15%. We saw an instant 8.3% reduction by implementing daily lists to underwriting.”
If you have experience managing people or a portfolio, reflect the exact detail of the team or portfolio. This will get across your ‘gravitas’ more than a general statement about management. Again, detail is the key. For example:
- ✅ Use this: Delivered circa £25mm reduction of in-year credit loss through more effective collections strategies
- ❌ Not this: Delivered a reduction of losses through collections strategies
- ✅ Use this: Primarily responsible for UK Portfolio, which peaked at over £10BN in receivables
- ❌ Not this: Managing a UK portfolio and a team of analysts
In other words, don’t just say what you did. Explain how your actions made a tangible impact on the business.
How Long Should Your Resume Be?
Again, everyone has an opinion on this. As a guide, 2-3 pages is a standard length. This gives ample space to concisely communicate your work experience, achievements, and education – whatever level of role you may be applying for.
Should You Include Your Interests?
Personality is important in roles within Credit Risk Analytics. You are presenting to people and dealing with stakeholders in other business teams and will need to have well-developed communication and interpersonal skills.
You don’t need to include too much information on your out-of-work interests but you need to show that you have interests other than just application strategies for credit cards. Please bear in mind though that you should not include any jovial comments – your resume should be read as a professional document.
Final Tip: Know Your Stuff
Make sure you are very familiar with your resume before any interview, including any quoted figures. This document has successfully secured you the opportunity to sell yourself to a prospective employer, so know the content thoroughly. By doing so, you will be well prepared and able to confidently answer questions on all aspects of your work, achievements, and education.
Are you looking to progress your career in Credit Risk Analytics? For market insights into the current market, information on job opportunities, and advice on your CV, get in touch with someone from our team today.
How Big Data and Risk Analytics Can Help Fight Climate Change | Harnham US Recruitment post
Data is all around us. We use it to calculate our calories and our steps to ensure a healthy body. We use it track our packages and ensure delivery to the right location. We look to it to check the weather for exercise, driving conditions, and in extreme cases, safety preparedness. But, could we use it to fight climate change? Could we use it to reign in swiftly rising temperature changes which could affect our food and ecosystems? Greener Choices for Greener ProductsPeople have more choice than ever before. They also have information at their fingertips and can see at a glance the benefits or the drawbacks of purchases. From how their food is grown to how far their food is delivered to the practices of companies from oil and gas producers to the wearables on their wrist.Climate change and Big Data have been linked, but mostly to determine greenhouse gases and effects of pollutants. But with the rise of consumer advocacy groups, farm-to-table traditions, micro-and macro-farming, and a desire to know more about what we’re putting into our bodies, consumers are dictating greener options from the markets.The Business of Climate Risk AnalyticsAs consumers take note of climate change, companies are merging knowledge of climate change risk into their financial decision making. How will climate change their business practices? How will it be scaled based on how climate science rules inform financial risk assessments not yet developed?The markets need just as much information as consumers when it comes to climate risk. These assessments are intended to businesses determine consequences, responses, and likelihood of the impacts of their actions. Enter climate risk analytics.Climate Risk Analytics uses risk assessment and risk management based on natural disasters and their impact. However, the climate is not in a static state. It’s ever-changing and those changes are often in the extremes with little information related to averages. This complicates risk assessments as do the differences in regional projections.How AI Can HelpBig data combined with climate risk analytics is getting an additional boost from artificial intelligence. AI techniques are being used for a variety of situations such as disease tracking, crop optimization, and monitoring everything from our heartbeat to endangered species.Solutions from advances in Deep Learning and Machine Learning could solve global environmental crises while assuaging financial risk with predictive modelling. Yet barriers to effective solutions from AI include cost and regulatory approval. But if these items weren’t an issue? We could determine such vital information as water availability and ecosystem wellbeing.Water and ecosystems aside, AI can help: Track and monitor endangered speciesImprove energy efficienciesOptimize wildlife conservation Fight poaching of endangered speciesTrack mosquito populations to prevent diseaseWarn populations of upcoming storms• Inform agriculture, health, and climate studiesDetermine water, forest, and urbanization changesSome vineyards in California use AI to determine if vines receive enough or too much water.AI’s ability to process large amounts of information quickly are a boon to the ever-changing climate, its risk assessments for businesses, and its benefits to consumers and investors who want to know what businesses are doing to keep everyone safe.In Honor of Earth DayThis week we celebrate Earth Day. It’s a day to remember and honor the earth who gives us our air, our food, our animals, plants, fish, and so much more. From Greta Thunberg’s School Strike for Climate to Naomi Klein’s book, The (Burning) Case for a Green New Deal, climate is front and center of our thoughts and our survival.Here at Harnham, we are specialists in risk analytics recruitment and have a range of vacancies on offer for skilled professionals. Want to be part of the movement working with Climate Risk Analytics or the effect of Artificial Intelligence in our environment? Harnham may have a role for you. From Big Data & Analytics to the Life Sciences, there’s something for everyone interested in the Data industry.Check out our current vacancies or contact one of our expert consultants to learn more. For our West Coast Team, contact us at (415) 614 – 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
CAN’T FIND THE RIGHT OPPORTUNITY?
If you can’t see what you’re looking for right now, send us your CV anyway – we’re always getting fresh new roles through the door.