![]() ![]() Clients are eager to use data to make a customer’s experience more personal. LBB> What’s the number one question that clients are coming to you with when it comes to how they can better use data to enhance the creativity of their content and experiences?īecky> Relevance. In a past life, Becky has helped define campaigns and experiences for brands like Vans, Gucci, Verizon, Google, Desigual, Kenneth Cole, Mars, and Pfizer.Īs a globally awarded creative, her focus on weaving creative insights and use of data to tell stories is what sets her work apart. It requires balance among three core components – data analysis, visualization, and narrative.Becky has specialised in digital brand transformation since the beginning of her career.Īt GALE, she’s won a Cannes Gold Lion in data-driven targeting for her CRM/loyalty work on Chipotle, while also leading creative on the Hard Rock and Hertz accounts. However, data storytelling requires a structured approach for organizing and communicating the insights from data. Often times, data storytelling is equated to building compelling visualizations. If an insight isn’t properly understood, is not compelling or actionable, no one will act on it. Unless businesses improve the communication and collaboration frameworks around these insights, they will experience a poorer insight-to-value conversion rate. Correspondingly, we will witness an unprecedented growth in the number and significance of insights being generated than ever before. With more self-service business intelligence tools, such as Tableau and Microsoft Power BI, the pool of business users generating insights will grow beyond just data analysts and data scientists. In other words, the need for data storytellers is only going to increase in the future. Organizations need specialists, or “translators,” who can analyze, distill, and clearly communicate information of the greatest potential value. From my experience, many data scientists with advanced degrees in economics, mathematics, or statistics find effectively communicating their analyses and insights with other business stakeholders and interpreting the significance of their sophisticated analyses within the business context particularly challenging. data engineering, rather than on the skills that convert analysis to insights and actions. ![]() However, much of the current hiring emphasis is centered on the data infrastructure and preparation a.k.a. Recently, LinkedIn reported that data analysis is one of the hottest job categories and it is the only category that consistently ranked in the top 4 across all of the countries they analyzed. The ability to take data-to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it-that’s going to be a hugely important skill in the next decades.Ĭompanies are desperately searching and recruiting data science talents. Your data may hold tremendous potential, but not an ounce of value can be created unless the data is analyzed, actionable insights extracted and translated into concrete business process action items.ĭuring a 2009 interview, Google’s Chief Economist Dr. The next elusive step is to extract value from your investments in data projects. The chances are, your business has already launched Big Data projects and has started collecting all kinds of data. ![]()
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