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Senior Analyst, Digital Media
Los Angeles, CA
A fantastic position for an senior analyst with excellent knowledge of digital media platforms to join an LA based advertising agency. You'll be responsible for performing analysis of vertical market trends, competitors, and campaign performance (online and offline media).
ROLE OVERVIEW - SENIOR ANALYST, DIGITAL MEDIA
YOUR SKILLS AND EXPERIENCE
SALARY AND BENEFITS
The successful Senior Analyst can expect a salary of $80-100k plus a comprehensive benefits package.
HOW TO APPLY
For more information about the role press "apply now".
Marketing Analyst, Analyst, Analytics, Adobe Analytics, Google Analytics, SQL, Agency, Digital, SEO, Tableau, DoubleClick, Coremetrics, A/B testing, Social Media, Data, Digital Analytics, Digital Analytics, Media, Online Media, Offline Media, TV
£55000 - £75000 per annum
£30000 - £45000 per annum
Manchester, Greater Manchester
Are you looking for a role with ownership over web analytics and excellent opportunity to progress and develop?
€35000 - €40000 per annum + 10% prime sur objectif
Nouvelle opportunité pour un WEB ANALYST junior de rejoindre le leader du transport.
€80000 - €100000 per annum + BENEFITS
Work with leading brands in retail, fashion, automotive and the travel industry!
£45000 - £50000 per annum
A great opportunity to take on a role where you will drive digital analytics for this company and be responsible for a number of analytics functions
With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
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Applying to anything from digital out-of-home to mobile, social media to TV, Programmatic tech continues to develop at a furious pace. And as it gets more sophisticated so, too, does its power to fuel growth across multiple industries. So it goes without saying that Programmatic is set to remain a valuable part of the Ad Tech toolkit. As it evolves, brands can measure and enhance their creative campaigns with ever-greater accuracy to improve conversion rates and engagement. Here are some of the latest ways automated ads have been helping brands increase their influence over customers. SHORTENING THE RETAIL SALES FUNNEL The former might of traditional brand and advertising agency models is fading. Instead, we’re seeing the old sales funnel being redefined into a more direct buying journey. Omnichannel shopping is now the norm, and screens with their accompanying ads wield plenty of power in influencing how we shop. Thanks to growing numbers of mobile purchases coupled with Programmatic technology, brands use Data to improve the customer experience, reduce acquisition costs and push more products into online shopping baskets. And as more retailers prioritise selling stuff online, they gain more control over customer data. Which in turn feeds their automated ads and speeds up the buying journey further. BOOSTING BRANDED CONTENT REACH No worldwide media corporation would last long without using technology to make the best use of its resources. So it makes sense that the BBC uses Programmatic ads to create greater access to its branded content. Using data, the BBC can see what particular audience segments are into, from trending topics to the devices they’re choosing to devour news and entertainment. From there, the broadcaster twins its own data with wider industry stats to form insights that help to shape its content strategy. Automated media buying also reduces the labour that traditionally accompanied ad campaigns. The key advantage being that it frees up staff to concentrate on more creative tasks, according to Luke Fox, the BBC’s Head of Programmatic for the Asia Pacific. As a direct result of the automated ads, the BBC’s media placement has become more focused and effective, with branded content “getting to the right people at the right time.” An advertiser’s dream come true, essentially. It is minimal effort, too. Using Programmatic tech gives organisations better access to consumers all over the world, across a wide array of media such as podcasts. CUSTOMISED MESSAGING We all know that personalisation is a tried-and-tested marketing strategy. So it’s no surprise that programmatic ads adapt to whoever they’re targeting. Ads adapt to multiple audience variants, from age, gender, income and location right down to the device we’re using. Through constant feedback, marketers can adjust their campaigns in real time, changing their message according to where customers are, what they’re doing and how they’re responding to the ad. In theory, as more brands move their media-buying in-house, the Programmatic process becomes easier to control and adapt. Zendesk’s director of digital Aurélien Dubot certainly thinks so. After the company moved its advertising in-house, Dubot says the decision has enabled them to make instant tweaks: “We don’t wait a week or three days to adjust things, we adjust it straight away.” Whether brands choose in-house or an agency for their media buying, one thing’s for certain: programmatic is a complex system that continues to bear fruit, provided brands set clear goals for what they’re trying to achieve. Ultimately, the results will only be as good as the data, along with the marketing team’s ability to analyse it. The Programmatic industry is growing. If you’re interested in Data & Analytics, we may have a role for you. Take a look at our latest opportunities or get in touch with our expert consultants.
23. May 2019
The Ski season may be drawing to a close, but it’s never too early to start planning for next year. Born and raised in the mountains of Austria, I have been skiing all of my life. For me, it’s about freedom, enjoying the views and forgetting about everything else. But, since I’ve stepped into the world of Data & Analytics, I started to asked myself “what can I learn from my work that I can apply to my skiing”? After having a look around, I began to discover ways in which Data could support my passion. I’ve pulled together some of the most interesting things I’ve discovered and created this handy guide to help you prepare for your next trip. Here’s how you can use data to create the perfect ski trip. Follow the snow Anyone who has skied before knows about the uncertainty before a trip. Will there be enough snow? Will the weather be good? Which resort is the most suited to my ability? Fortunately, somebody has already pulled this information together for you. Two "web spiders" were built via Scrapy, a Python framework used for data extraction, the first of which extracted ski resort data. The second spider, on the other hand, extracted daily snowfall data for each resort (2009 - present). After collecting Data from more than 600 ski resorts and spitting it into 7 main regions, the spiders were able to form a conclusion. The framework then pulled out key metrics, including the difficulty of runs, meaning that skiers are now able to decide which resort is most suitable for their ability. As for the weather, onthesnow.com has recorded snowfall data from all major resorts, every year since 2009. We all know that good snow makes any trip better, so the collected data here will help skiers ensure they are prepared for the right weather, or even plan their trip around where the snow will be best. Optimise your skis Ski manufacturing is a refined and complicated process, with each ski requiring many different materials to be built. Unfortunately, this often results in the best skis running out quickly as supply outspeeds demand. To help speed up and improve the process, companies are implementing technologies like IBM Cognos* that monitor entire supply chains so that no matter how much demand increases, they have the materials to meet it. Additionally, since the majority of companies have become more data-driven, production time has been reduced by weeks. Predictions for future demand has also become 50% more accurate, resulting in a drop of 30% idle time on production lines. Skip the Queue Tired of queuing for the ski lift? There’s good news. As they begin to make the most of data, ski resorts are introducing RFID* (Radio Frequency Identification) systems. These involve visitors purchasing cards with RFID chips included, allowing them to skip queues at the lifts as there is no need to check for fake passes. The data can then be utilised for gamification platforms to turn a skier’s time on the slopes into an interactive experience. The shift towards Big Data not only has advantages for the visitors, but the management are also benefiting. In the past, it has been difficult to analyse skier’s data. Now, with automated and proper data management, the numbers can be crunched seamlessly and marketing campaigns can be directed at how people actually choose to ski. Carve a Better Technique Skiing isn’t always easy, especially if you haven’t grown up with it. Usually, ski instructors are the solution but, in the age of Data & Analytics, there are other solutions. Jamie Grant and co-founder Pruthvikar Reddy have created an app called Carv 2.0, which allows you to be your own teacher. It works by using a robust insert that fits between the shell of your ski boots and the liner. It then gathers data from 48 pressure sensitive pads, and nine motion sensors. This data is fed to a connected match-box size tracker unit, sitting on the back of your boots, before being relayed via Bluetooth to the Carv App on your phone. Carv can then measure your speed, acceleration and ski orientation a staggering 300 times a second. Thanks to a complex set of algorithms this data is then converted into an easy to follow graphic display on your phone’s screen as well as verbal feedback from Carvella. The accuracy of this real-time data could make it a better instructor than any individual person. Data & Analytics are helping streamline every part of our lives. Whilst the above can’t guarantee a perfect ski trip, they can help us minimise risks and optimize our performance and experience. If you’re able to use data to improve day-to-day living, we may have a role for you. Take a look at our latest opportunities or get in touch with our expert consultants.
04. April 2019