Head of Conversion Rate Optimisation
London / £60000 - £70000
£60000 - £70000
Head of Conversion Rate Optimisation
Digital Marketing Agency
Up to £70,000
Hybrid Working in London Area
An Award-Winning Digital Marketing Agency are looking for someone to head up their Optimisation function. The role balances strategic and hands-on work and looks to grow the team to 5x profitability!
After finishing an internal restructure to streamline efficiency, this brand are now looking to expand their client's ROI capabilities with an increased emphasis on Analytics & Personalisation being used to drive business decisions. They work across a plethora of sectors, with excellent reviews and a high quality of work being produced.
You would be leading a team of 2 Conversion Rate Optimisation Analysts, and managing 3rd party resources, whilst also owning client relationships and providing technical expertise as-and-when needed. The Head of CRO is expected to evangelise Optimisation internally and externally with clients to sell their team, but also the wider brand.
- Extensive AB Testing experience
- Ideally, client-facing background but not essential
- Line Management/Leadership experience
Salary and Benefits
- Basic salary of up to £70,000
- Flexible Working
- 4.5 day working week.
- Private Medical
- 28 days holiday
How to Apply
Please register your interest by sending your CV to Corey Haigney via the apply link on this page.
IBM, Coremetrics, Google Analytics, GA, Omniture, SiteCatalyst, Adobe Analytics, Analyst, Web, Digital, Online, Website, Financial Services, Finance, A/B, Test, Split, Multivariate, MVT, Tracking, Code, Tagging, Tags, Insight, Client, Agency, Management, Strategy, CRO, Conversion, Optimisation, Optimizely, Test and Target, Adobe Target, Maxymiser, VWO, Visual Website Optimiser
What is Product Analytics?
What is product analytics?
Knowing how well, or not, your customers or service users interact and engage with a product is integral to the success of your business.
Whether it’s a bed from a furniture store or a button on a website, having the insight to understand how easy it is to use or how desirable it is amongst your customer base, then enables teams to go back, tweak the product and optimise it to its full potential.
This is where product analytics comes into its own. Those working within the field – product analysts – are integral in increasing conversion rates – whether that’s purchase rates or how user-friendly a product is – using a mixture of digital customer analytics and data science. From the NHS to Ikea, product analysts are highly sought after in nearly every industry as they strive to make their services and products the best they can possibly be.
What happens if work needs to be done on a product?
Initially, product analysts would undertake testing, such as AB testing, to decipher if there is a more favourable way of presenting the product or service to their customer base. They may also look at implementing tools such as personalisation, a newer capability on the market, to target their service to a specific user, making it more relevant and therefore able to boost conversion.
Once the product analysts have gathered any insights on what would optimise the tools, products, and services, these are then taken to stakeholders to kickstart the process of improvement. From here, updates are made by teams such as those in user experience (UX), and the product is re-launched and continually monitored.
The different arms of product analytics
Product Analytics, while seemingly a straightforward division of Data & Analytics, is extremely broad and split up into a multitude of sub-divisions. So, while all teams may be integral in spotting room for optimisation, their exact role will be different to another analyst.
For example, a trend analyst will analyse trends over a specific period, learning about those patterns and then optimising products or services for those times. Tesco, for instance, will be prepared to put the purchase button of turkey, pigs in blankets, and roasting potatoes at the front and centre of its website at Christmas.
Journey analysts however will measure where customers come from to engage with a product or service, be it a banner ad, an email, or a social media post. They’ll also look at where in the customer journey purchasers or users drop off, finding kinks in the service experience that need to be ironed out.
How to get into product analytics
Like the sound of what a product analyst does? Here’s how to work your way into the industry.
Most businesses will aim to hire individuals with an extremely proficient maths or statistics background; business analytics qualifications will also stand you in good stead as will data science. Additionally, you’ll need to showcase a good understanding of SQL – the tool most frequently used within the sector.
Degrees are no longer as important as they once were, especially in the current climate where there are more vacancies than skilled candidates. Many businesses are far more open to hiring potential employees who hold a few crucial skills and then upskilling them as they go, rather than finding the polished product.
However, the division doesn’t usually see graduate-level talent enter, it can take up to 18 months of work until candidates can think about becoming a product analyst. However, once you’re there you can expect a starting salary of £35,000+ and the opportunities to reach up to £120,000 per year.
Product Analytics is a relatively new division within data and analytics, but one that is gaining traction at rapid rates. By 2028, the area is predicted to be worth $16.69bn as it gains popularity across businesses worldwide, helping them to both streamline and optimise their products and services.
If you are interested in entering the world of product analytics, please speak to one of our team today or take a look at our vacancies here.
How Data-Driven Strategy Can Save Your Business Money
How data driven strategy decisions can save your business money
As business deliverables grow and budgets are rolled thinner, efficiency is the word of the moment. In any economic climate it's crucial that business operations are functioning as efficiently as possible and that every decision is underpinned by a business rationale.
However, as we move into a period of uncertainty – with a global recession looming on the horizon – ensuring that strategic business decisions are grounded in data becomes ever more pivotal. As a business leader there will always be factors outside of your control – that comes with the territory – but taking time to ensure that you have a good understanding of the elements you can influence will place you in the best possible position for navigating the parts you cannot.
As the old adage goes, ‘information is power,’ and the more of it that you can glean from your business processes, the better scope you'll have for achieving success and cost savings. Consider launching a new campaign or product; you wouldn’t just assume that it has gone well. You would instead look to track its real-time progress towards its intended goal via tangible KPIs. The same goes for any strategic decision. You’d want to know that the data supports your choice. So where is data most useful?
The enemy you know...
When faced with uncertainty, it can be tempting to bury your head in the sand and hope it goes away. But the reality is that it is always better to know what you are dealing with. Now is the time to reaffirm your grasp of your business’ operations and gather any insights, positive or negative, that may help you to plan ahead. Consider each element of your organisation and review the information that may help you to identify areas for improvement. With enough intelligence in your weaponry, you can be clearer on whether parts of your business may be more vulnerable to fluctuation and how you are likely to be affected by the economic climate.
For instance, if you are involved in the provision of a product or service, consider each stage of your supply chain. Pull in all relevant figures around your suppliers and outgoings and consider if there are any gaps in your understanding or areas lagging behind. Methods such as supply chain management have enormous potential for improving operational efficiencies and in turn costs.
Taking a data-driven approach allows you to better predict production and inventory changes closer to real-time, and usually involves the use of technologies. For example, Artificial Intelligence (AI) and Machine Learning (ML) models powered by supply chain data, log data and third-party sources can help improve the supply chain by identifying data patterns, then forecasting potential outcomes. What’s more, AI and ML models can create forecasts that have different confidence levels, informing supply chain leaders how likely the forecast is.
Holding a mirror up to your business
No matter the purpose of your organisation, cash remains king. And with 25 per cent of businesses failing due to cash flow, it’s more important than ever to have a solid understanding of how it contributes to your business.
For your business to continue to perform its intended function, it needs to remain profitable. But that doesn’t just mean making shedloads of money (although that won’t hurt), it's about making sure that those funds are being funnelled to the right place at the right time.
Cash flow refers to the movement of funds through your business. It can be affected by anything from tax deadlines to funding partners – in essence, anything that changes, halts, or facilitates the flow of money through your organisation. The health of your cash flow controls your every ability, including being able to offer competitive salaries and retain staff.
Where data and analytics can help is by providing strong visibility into the sources and uses of your cash, diving deep into your transactions and establishing how both ends of your supply chain are coping.
Business Intelligence (BI) and analytics software can automate cash flow analysis and provide tools to consolidate data, simplify cash flow planning, and accelerate decision making. The aim is to provide more accurate financial figures and take the guesswork out of the cash flow analysis process.
Maintaining a clear picture of your income and outputs will better enable you to make strategic decisions about your business that save money, but also to manage the unexpected. Being aware of pain points is just as important as recognising successes. For instance, if you know that a supplier is going to increase their rates in a way which will impact your Q1 budget, you may decide to delay your hiring drive until costs level out.
Data’s answer to a crystal ball
Forecasting is arguably where all of this data gains real business relevance. Forecasting is a process of estimating future events based on historical and real-time information by analysing trends. The more information that you can build into your forecasting, the more useful and accurate it will be. Knowledge such as upcoming price increases, internal staff changes and new legislation will all be crucial to informing your strategic decision making and ensuring you are not caught by surprise.
To use a price rise as an example; by combining information about the impact that an earlier increase had on a specific department in the business with real-time data such as current staffing and capacity, you can anticipate what the business implications of an upcoming rise might be.
And there are tools able to dig deeper still – predictive modelling can estimate more granular, determined outcomes using data mining and probability. Essentially enabling you to ask more ringfenced questions from specific data sets.
By choosing a desired outcome, such as the purchasing of a specific service, the model works backwards to identify traits in client data that have previously indicated they are ready to make a purchase soon. Predictive modelling runs the data and establishes which of these factors contributed to the sale – knowledge which can then be built into the decisions you make about your service offering.
Ensuring that decisions are grounded in data has always been pivotal for business profitability but as we face a period of economic downturn, it may be worth moving it higher up your priority list.
Looking to inject greater insights into your business with talented data professionals? Speak to one of our experts 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.
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.