Digital Analytics Jobs in Chicago

At Harnham, we recruit at all levels across the full remit of digital analytics skills including Web Analysis, Online Content, UX design / architecture, Search Engine Marketing including SEO and PPC, Affiliate Marketing, Digital analytics strategy and Planning and E-commerce.

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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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How Digital Analytics & Marketing Help Shape E-Commerce

Since the days of store window displays, the shopping experience has been just that; an experience. So, what happens when you want to recreate the visceral and emotional experience of shopping from within the confines of a computer screen, smartphone, or tablet? Enter Digital and Marketing Analytics. According to a recent report by Adobe, e-commerce sales have seen a 77% jump year-over-year which at any other time in history should have taken 4 to 6 years. The COVID-19 pandemic has helped to escalate and drive these numbers leaving some businesses scrambling and others raking it in. So, what’s the difference? Data professionals. The Role of Data in E-Commerce Whether you buy online and pick up in store or have a product delivered to your door, the role of shopping has irrevocably changed. Ensuring consumers get the personalized experience they’re used to from the days of brick-and-mortar stores, retail stores have turned to Digital and Marketing Analytics to give their customers the shopping experience they’re used to within a different format. Professionals within the UI/UX Design vertical are particularly sought after. Buying habits are changing and competition is fierce. So, how does Data affect e-commerce? Here are 3 examples: Know Your Customer. No longer a lamented visage from yesteryear, knowing your customer is inherent to the survival of an online retailer.  Data professionals bring to life the customer through historical data, demographics, and creates products and services which elicit an emotional response to stop, look around, and buy. And if the cart gets abandoned, follow up email campaigns to jog the memory that you were here and were thinking about buying this or that item. Get Personal. Personalize shopping has evolved into the personal shopping experience. What made someone buy a product during their last visit? Dynamic presentation and emotion-driven verbiage can certainly contribute.  When an online retailer knows what the buyer wants or needs and presents it in a way that resonates. This is the personalization once the domain of sales clerks.  From the Data you enter at checkout to the social media platforms and search engines with information like what you’re looking for, where you’re located, your purchase history and more can sometimes leave the personalized experience out in the cold. Bridging the old personalization with the new is the key ingredient for successful online retailers. Sell Where Your Consumers are Buying. If your customers are on Facebook looking for a product or service, sell to them where they’re looking. Though reviews are still important, even more prevalent is the range of social influencers to help buyers make decisions. Enter social commerce. Layout, design, Data gathering, collecting, and analyzing all have a slightly different flavor within this construct.  Data Professionals in Demand Within the Digital Analytics and Marketing specialism are a variety of Data professionals in demand as retailers are forced online. Businesses need E-Commerce Analysts to help present the new normal for the online retailer. As buy online and pick up in store convenience increases as well as purchases made from devices such as your smartphone, there’s been a rise in demand for Web & Mobile Product Management as well. Digital Transformation is no longer at the doorstep of business, it has crossed the threshold. And rather than focus on one tool or another, the impetus is on the importance of having more than one tool at a candidate’s disposal. What candidates want has changed and evolved as well. Salary and bonuses have dwindled while the demand for experience and professional development have become rallying cries for finding and retaining top talent. For more information In our recently released 2020 Salary Guide we discuss each specialism. What’s working. What isn’t. And how businesses can hire and retain top talent to keep their projects on track and their businesses running smoothly. You can download your copy here.  If you’re interested in Data and Technology, Risk or Digital Analytics, Life Sciences Analytics, Advanced Analytics & Insight, Data Science, or Computer Vision, we invite you to check out our latest jobs. If you’d like to learn more, contact one of our expert consultants: For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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