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What We Do

We help the best talent in the Digital Analytics market find rewarding careers.

We know that Web Analytics, PPC, User Experience and Search Engine Optimisation of websites and online campaigns now command as much, if not more, focus than traditional marketing analysis techniques.

We recruit at all levels across the full remit of digital analytics skills including Web Analytics, Conversation Rate Optimisation, UX design/architecture, Search Engine Marketing, Digital Analytics Strategy and Planning, and E-commerce. We understand the wide range of tools and specialist knowledge required to work within this continuously evolving industry.

View our latest remote digital analytics jobs.

Latest Jobs

Paid Search Lead - Remote Working
Salary

£50000 - £60000 per annum + + benefits

Location

London

Description

Want to work within the healthcare space? Well versed in the PPC implementation and analytics? I would love to hear from you!

Product Lead (Media) - Remote Working
Salary

£70000 - £75000 per annum + bonus + benefits

Location

London

Description

Great opportunity to work with a leading social media platform, whereby you will shape and scale their digital advertising go-to-market strategy.

Product Analyst - 6 Month FTC - Remote Working
Salary

£50000 - £60000 per annum

Location

London

Description

As the Product Analyst, you will be responsible for all deep-dive analytics & optimisation across a fast-changing digital estate

Senior Technical Digital Analyst - Remote Working
Salary

£40000 - £50000 per annum

Location

Cardiff

Description

A market-leading insurance provider is seeking a Digital Analytics & Implementation expert to lead tagging & tracking (via Adobe Launch)

Senior Digital Analytics Developer - Fully Remote Working
Salary

£40000 - £50000 per annum

Location

England

Description

A rapidly expanding US-based digital marketing agency is seeking a Senior Digital Analyst to own all on-site tagging & tracking for a host of clients

Product Analytics Manager - Remote Working
Salary

£70000 - £90000 per annum

Location

London

Description

As the Product Analytics Manager, you will be responsible for all deep-dive analytics & optimisation across a fast-changing digital estate

Digital Project Manager - Remote Working
Salary

£35000 - £45000 per annum

Location

London

Description

As the Digital Project Manager, you will lead a team of data & technology professionals to deliver advanced product builds and analytics projects

Product Marketing Manager (Mobile) - Remote Working*
Salary

£55000 - £60000 per annum + + benefits

Location

London

Description

If you are looking for a vendor side role, where you can shape performance marketing strategy for mobile products, this role is for you!

Senior Technical Digital Analyst - Remote Working
Salary

£40000 - £50000 per annum

Location

Hove, East Sussex

Description

As the Implementation Analyst, you will be responsible for all analytics implementation using Adobe Launch across desktop, mobile & app

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Marketing Analytics - Then, Now & In the Future: A Q&A with Sarah Nooravi

We recently spoke to Sarah Nooravi, an Analytics professional with a specialism in Marketing who was named one of LinkedIn’s Top Voices in Analytics.  Sarah found herself working in Analytics after being attracted to the culture, creativity and the opportunity to be challenged. Having spent the first four years of her career working within the Marketing space, she has seen a real transition in the way that Analytics and Data Science has informed Marketing decisioning.  “I started my career in a Marketing agency within the entertainment industry, at the time it was doing things that most of the entertainment industry hadn’t considered doing yet”.  At the start of her career she’d meet entertainment giants with advertising budgets of millions of dollars who were, at the time, making mostly gut decisions with how to approach campaigns. “It was common that I’d hear, ‘I think our audience is females over the age of 35 with a particular interest and we should just target them’” she expands.  However, agencies quickly recognised the need for something more Data-driven. Entertainment businesses were going too narrow and were misunderstanding their audiences. The next step was to embed into these businesses the insights from a greater variety of sources, including social media, and to introduce more testing. That translated into a better media buying strategy that could be continuously optimised. It was a big step forward in the utilisation of Data within this realm and its clear focus on ROI.  Suddenly, the market was changing, “There was a massive spike of agencies popping up and claiming to leverage Data Science and Machine Learning to provide better optimisations for entertainment companies, mobile gaming – you name it. There was a huge momentum shift from using these gut decisions to leveraging agencies that could prove that”.  What she saw next seemed only natural, with more agencies offering Data-driven optimisation, companies looked to develop this capability internally. Sarah elaborates; “Now I am seeing these companies starting to take ownership of their own media buying and bringing the Marketing and Data Science in-house”. This shift in-house has been propelled by the major players, companies like Facebook, Google and Nooravi’s own company, Snapchat, working directly with companies to help them optimise their campaigns. This shift has changed the landscape of Marketing Analytics, specifically within the advertising space. Sarah explains, “You no longer need an agency to optimise your, for example, Facebook campaigns, because Facebook will do it for you. They are minimising the number of people behind the campaigns. You give up a little of your company’s Data for a well optimised campaign and you don’t have to hire a media buyer. There is definitely a movement now to becoming more Data-driven. Companies are really leveraging A/B tests and also testing out different creatives”.  It is this change in strategy that is seemingly taking the Marketing Analytics challenge to the next level. With opportunities to pinpoint specific audiences, companies are using their Data to understand how to approach their content, take the opportunity to experiment, and to find out what it takes to resonate with their audience. Sarah has seen the potential of this first hand: “We are starting to see a lot of AR and VR. There are meaningful ways to engage with technology to connect with the world. Moving forward, content will have to become more engaging. People’s attention spans are becoming shorter and with each decision someone makes it is changing the direction of content in the future. There has been a massive shift from static images to video advertisement and, more recently, from video into interactive video like playable adverts. People want to engage with adverts in order to understand a company’s message”.  It is within this space that she sees a gap for the future of ROI positive advertising:  “The biggest issue that I find with the creative and the content is that the value add is missing. The resonance with the brand or company, their values and mission is what is missing. Analytics alone cannot fix that. You need to understand what the company stands for, people want to connect with brands because of what they stand for – whatever it is. Especially in a time like we are dealing with right now, a pandemic, advertising spending has gone down. However, maybe there is a way to properly message to people that would resonate. Not that you want them to buy your stuff but maybe right now is the perfect time to do outreach and to help people understand your brand”. The ability to understand and predict customer behaviour is evolving, but with that, so is the customer. Whereas at the moment, you can build out experiments, you can create models that will be able to, as Sarah explains, “in real-time decide whether a user’s behaviour is indicative of one that is going to churn” and then try and create offers to increase retention.   This is the challenge of the current analytics professional – our behaviours in a global pandemic have shifted consumers into a new world. Now working for Snap Inc, she sees the potential of this from a new perspective. Naturally, like most social media channels and communication technologies, they have seen an increase in usage over the last month.  “People are wanting to communicate more as we are forced to social distance. However, we are seeing different regions engaging a lot more heavily. For example, it's Ramadan right now, people want to share those moments with one another and at the moment the way that they are having to do that is changing”.  So, it will be a question for all those required to predict behaviours to determine how many of these new lines of communication, these new habits, will have evolved. Once people are out of quarantine, are they going to continue to utilise the apps, games, social channels in the same way that they are currently? It certainly is going to be something that many within the marketing analytics space will be trying to forecast.  If you’re looking to take your next step in Marketing Analytics, or are looking to build out your team, Harnham may be able to help.  Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Charlie Waterman

Charlie Waterman

28. May 2020

‘Tis The Season Of Data: Black Friday Is Here

‘Tis The Season Of Data: Black Friday Is Here

It’s that time of year again. Decorations are going up, the temperature is dropping daily, and the year’s biggest shopping weekend is upon us.  Black Friday and Cyber Monday may have started stateside, but they’re now a global phenomenon. This year, in the UK alone, shoppers are expended to spend £8.57 billion over the four-day weekend. But, for retailers, this mega-event means more than a cash injection. In the world of Data, insights gained from shopping and spending habits during this period can dictate their product and pricing strategies for the next twelve months.  So what is it, exactly, that we can stand to learn from the Black Friday weekend? THE GHOST OF BLACK FRIDAY PAST There are a few interesting takeaways from 2018’s Black Friday weekend that will likely impact what we see this year.  Firstly, and perhaps unsurprisingly given that it’s a few years since the event has become omnipresent, spending only increased about half as much as initially predicted. There are a number of reasons for this, but cynicism plays a central role. More and more, consumers are viewing Black Friday deals with an element of suspicion and questioning whether the discounts are as good as they’re promoted to be. This, combined with other major annual retail events, such as Amazon’s Prime Day, means that this weekend no longer has the clout it once did.  However, 2018 also saw marketers doing more to stand out against the competition. Many businesses have moved away from traditional in-your-face sales messaging and some are even limiting their Black Friday deals to subscribers and members. By taking this approach, their sales stand out from the mass market and can help maintain a level of exclusivity that could be jeopardised by excessive discounts. In addition to branding, marketers making the most of retargeting saw an even greater uplift in sale. Particularly when it came to the use of apps, those in the UK using retargeting saw a 50% larger revenue uplift than those who didn’t.  So, having reviewed last year’s Data; what should businesses be doing this year in order to stand out? GETTING BLACK FRIDAY-READY WITH DATA Businesses preparing for Black Friday need to take into account a number of considerations involving both Marketing and Pricing. For the latter, Data and Predictive Analytics play a huge role in determining what items should go on sale, and what their price should be.  Far from just being based on gut instinct or word-of-mouth, algorithms derived from Advanced Analytics inform Machine Learning models that determine what should be on sale, and for how much. These take into account not only how many of each discounted product need to be sold to produce the right ROI, but also what prices and sales should be for the rest of the year in order to make the sale financially viable.  In terms of Marketing, Deep Learning techniques can be used to accurately predict Customer Behaviour and purchases. These predictions can then reveal which customers are likely to spend the most over the weekend, and which are likely to make minimal purchases. Marketers can then, in the lead up to Black Friday, target relevant messaging to each audience whether it be “get all you Christmas shopping in our sale” or “treat yourself to a one-off item”. By carefully analysing the Data they have available and reviewing the successes and failures of their Black Friday events, businesses can generate greater customer loyalty and improve their sales year-round. If you’re looking to build out your Marketing Analytics team or take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

Tamara Olori

Tamara Olori

28. November 2019

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