Much of the commercial value of a data scientist comes from providing the clarity and insights that vast quantities of data can bring. The role can encompass everything from data engineering, to data analysis and reporting — with maybe some machine learning thrown in for good measure. This is especially the case at a startup firm. Early and mid-stage companies’ data needs are typically far
removed from the realm of neural networks and computer vision, unless, of course, these are core features of their product/service. Rather, they need accurate analysis, reliable processes, and the ability to scale fast. Therefore, the skills required for many advertised data science roles are broad and varied. Like any pursuit in life, much of the value comes from mastering the basics. The main attribute a data scientist brings to their company is the ability to distill insight from complexity. Key to achieving this is understanding how to uncover meaning from noisy data. Describe data, to provide a detailed picture to stakeholders; Compare data and test hypotheses, to inform business decisions; Identify trends and relationships that provide real predictive value…..Statistics provides a powerful set of tools for making sense of commercial and operational data.
The main skill in such a fast-moving field is learning how to learn and relearn. No doubt new frameworks, tools and methods will emerge in coming years. While the trend toward driven-data marketing may seem intimidating, it’s not necessarily a bad thing. Data-driven decisions are already a large part of the modern SEO’s skillset. Savvy, successful SEOs know to utilize A/B testing strategies, heat mapping, and engagement metrics to evaluate and consistently improve performance in real time. As the landscape continues to shift, SEO professionals who adopt a data analyst’s mindset will be better equipped and stay more competitive than those who rely too much on older analysis and tactics. As SEOs gain more and more reliable and real-time data about our audiences, we’ll need the ability to get granular in terms of the data we are able to combine, reformulate, and interpret in meaningful ways. Many marketers are trying to drive value in their data, so they’re having conversations with board members about getting that data architecture in place, managing compliance and creating audience segments. It is a costly, time-consuming part of anybody’s role. For us to be able to create an audience sample and visibly show a return is music to the ears of any head of department trying to validate a business case to their board.
The business of marketing is now fiendishly complex to master. One wrong step and brands that have taken years to build can suffer catastrophic damage. Those swaggering, sharp suits of marketers now seem an anachronism, and have instead been replaced by the savvy hipsters who “get” the finely tuned interplay between offline and online channels, algorithms, and empathy. At the root of the successful marketer is an agile mindset coupled with an ability to adapt to consumer dynamics that can switch at warp speed. By experimenting with a host of evolving tools and technologies to test and find out what motivates customers to buy certain products, a good marketing person can track the path to purchase whilst optimizing the customer and brand experience. Few businesses can thrive without using their data effectively these days — and in marketing, data is particularly foundational. Despite its importance, that doesn’t mean the process of gathering and using this information is easy or simple (few things ever are) and it’s certainly not fail-proof. There’s always room for human error.
When collected and analyzed effectively, data delivers insights that can help increase marketing ROI and grow brand loyalty. When it’s not, it can produce results that are misleading and costly. Challenges like disparate and siloed measurement methods provide erroneous and misleading results that can do more harm than good, making it impossible to know what’s really happening in the marketplace. The majority of marketers are relying on outdated measurement methods that simply will not cut it in a fast-paced, hyper-competitive marketplace where connecting with potential customers at the right time with the right message is mission critical. Marketers are missing out on a holistic measurement approach — which is critical for marketing success — because of failure to leverage the right tools and processes. As analytics increasingly drive the future of campaigns, as industry data forecasts, there needs to be a strong emphasis on ensuring the quality of results yielded — and in doing so, marketers will be able to effectively leverage their data and analytics and more confidently make decisions to find competitive advantage.
To gain this confidence, a handful of challenges must be overcome. Some of the most common obstacles include complexity in collecting, integrating, and managing data, and difficulty implementing a holistic approach across silos. In a society with technology that is continually advancing, data is a marketer’s present and future — and it is only going to become increasingly vital for an organization’s success. There will always be quicker and inefficient ways to analyze it, especially with the influx of data as more organizations and industries go through digital transformation. But only when collected and measured accurately and effectively, will data deliver marketers increased ROI, leaving the competition far behind in the race for customers and brand loyalty.