Data Science for Marketing

Let our Data Scientists be your “Secret Weapon”.

 

Use Ziva Data Science expertise, to not only analyse your data yet, additionally to move your emphasis and follow up on opportunities. As your partner, Ziva Data Science will demonstrate how information gets to be significant in an important way. Keep in mind, it’s “Data Science”, not “Rocket Science.

 

Data still resides in structures, which can only be described as muddled, marketers are still being deluged by torrential slides of disorganised information, and data silos still exist between organisational functions. The volume and assortment of new information keeps on mounting, on organisations that are already struggling with this deluge of information, allowing the data to be used to gain advantage, when frequently utilised in problematic ways by competitors and fraudsters. In the meantime, companies like Ziva have developed the expertise to address the torment of information deluge that organisations are suffering today, by the use of predictive analytics and the development of a unified customer view.

data scienceImportant campaigns and the prediction of customer behaviour, can no longer be carried out by the reliance on the marketers instincts alone. Influence to shape product innovation and customer engagement, must come from the leverage of big data. Data analysis to inform decision-making now drives the best marketing efforts, and audience convincing campaigns are created the coupling of data insights with creativity.

Marketing has recognised the need to be more efficient and effective, but all the information on the planet is unimportant unless the marketers have the right ability sets to carry out deep analysis. Thus the prerequisite for a Data Scientist with solid analytical abilities, narrating powers, systems knowledge, and business discernment expected to get genuine worth from information and data.

As the use of computerised media continues to advance, along with the ascent of technological innovation, the case that the individual marketer with the most status always knows best, consistently no longer holds true. The problem is compounded by the numerous marketing experts that are considering themselves to be data scientists today, since they decided to take a look at customer data. They are merely looking at the business and they’re managing unadulterated data. This practice has nothing to do with data science, as they don’t use any statistical techniques to concoct their outcomes or to weight them.

Let Ziva Data Scientists be your “Secret Weapon”. They will allow your brands to not only spend their marketing budget more wisely and efficiently, but additionally help you beat the competition. Let us be your marketing departments own expert. Staying on top of the media landscape today is becoming progressively difficult, and more a data challenge than a creative one.

Data Science is an interdisciplinary field about procedures and frameworks to concentrate learning or experiences from data in various forms, either structured or unstructured, which is a continuation of a portion of the data analysis fields such as statistics, data mining, and predictive analytics, similar to Knowledge Discovery in Databases.

 

Overview of Data Science

Data science draws from numerous fields within the broad fields of mathematics, statistics, chemometrics, information science, and computer science, including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition and learning, visualisation, predictive analytics, uncertainty modeling, data warehousing, data compression, computer programming, artificial intelligence, and high performance computing, and utilises their techniques and theories. Of compelling interest in data science, are the strategies and methods that scale to big data, although we do not consider the discipline to be limited to big data. Instead of analysis, big data solutions quite often are focused on organising and preprocessing the data. The growth and importance of data science has been enhanced by the development of machine learning.

Data preparation, statistics, predictive modeling (insights), and machine learning in various areas of expertise such as marketing optimisation, fraud detection, marketing analytics, risk management and public policy, are utilised by data science to investigate problems. Data science accentuates the utilisation of general techniques such as machine learning that apply without changes to multiple domains. This methodology contrasts from the non-scaling rationale of customary insights with its accentuation on area particular, domain-specific knowledge and solutions.

In many domains applied and academic research are influenced by data science, these include speech recognition, robotics, machine translation, search engines, digital economy, and additionally the biological sciences, medical informatics, health care, social sciences and the humanities. Economics, business and finance are also heavily influenced by data science. Data science is a newly emerging field, encompassing a number of activities, such as data mining and data analysis, and is an integral part of competitive intelligence from the viewpoint of business.

 

The Data Scientist

Data and analytical abilities are utilised by data scientists to manage large amounts of data, and to find and interpret rich data sources. Despite hardware, software, and bandwidth constraints, the data scientist merges data sources, ensuring consistency of datasets, to create visualisations which aid in understanding data. The data scientist builds mathematical models using the data and presents and communicates the data insights and findings. In days rather than months, by exploratory analysis and rapid iteration, the data scientist is often expected to produce answers, and to get and present their results by the use of dashboards, which display current values, as opposed to the more traditional statisticians use of papers and reports.

McKinsey & Company have projected a global excess demand of 1.5 million new data scientists. While Harvard Business Review has dubbed data scientist as, “The Sexiest Job of the 21st Century”, and made it an occupation which it popularises.

 

Apply Marketing Data Science To Transform Business Decision Making

Ziva data scientists have the abilities to gain understanding and extract insight from big data that can be utilised to deliver personalised customer experiences, aid in the refinement of loyalty programs, and give your marketing campaigns the edge. The larger part of what organisations do today is either created in digital form, like email or Web, or tracked digitally, in the form of barcodes or sensors. The massive growth of digitisation, has created in measurement a revolution and for the enhancement of business decision making and innovation, a groundbreaking change and opportunity has occurred.

Ziva utilises systematic observation, testing and measurement to study broad behavioral patterns, drilling down from the aggregate to the individual with the aim of producing new innovative insights that will in turn improve business outcomes. The mastery of this methodology requires us to have three capabilities: architecting data, applying science and influencing action. Giving us a broader scope of impact, enabling us to be more prescriptive, while being equipped to prompt far-reaching changes in your organisation when required.