If there’s one thing Datamine isn’t lacking, it’s internal knowledge and expertise. And what good is knowledge if you don’t share it?
The Datamine team have written a collection of Whitepapers and Guides designed to help all manner of businesses learn how to create value from their data.
WHITEPAPERS
Datamine’s whitepapers are in-depth insights into various technical concepts and analytical challenges.
They delve into the value of individual components and offer implementation advice from our experts.
Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests, spending habits and so on. Using segmentation allows companies to understand groups effectively and allocate marketing resources to best effect.
This Datamine paper will delve into the details of segmentation and offer readers valuable insights into how they can implement this kind of analysis in their business.
Marketing automation platforms enable marketers to manage customer interactions with greater degrees of speed, precision and personalisation than were possible only a few years ago.
In this Datamine guide, we’ll help you through the fundamentals of marketing automation - what it is, who to buy it from, how to prepare for it, how to use it and how to get the most out of it.
Customer churn is a problem that plagues businesses across all industries.
This whitepaper outlines a robust approach to investigating and managing customer churn, specifically for B2C businesses, giving organisations the steps they need to begin quantifying and reducing churn.
Customer Insights come from compiling and combining data, from multiple sources, to paint a picture about an organisation's customers.
The guide defines customer insight and lays out the building blocks for creating it, how to develop an insight framework, along with the tools, techniques and analysis processes.
HR analytics is a broad concept that refers to the application of analytical strategies to the human resources department in order to improve employee performance and minimise turnover. One of the more common uses of HR Analytics is in the pay equity sphere, shedding light on an organisation’s remuneration strategies.
This whitepaper is designed to outline the benefits of data analytics on HR, as well as the potential that harnessing HR data can have in making a business more data-driven.
The General Data Protection Regulation (GDPR) is the EU’s stringent new personal data protection legislation, and determining whether or not your business is compliant is imperative to its future success. We might not be EU experts at Datamine, but we sure are data experts – data security and privacy are two of our specialities. Here’s a checklist organisations need to tick in order to avoid the potential repercussions of infringing upon the regulations.*
*Disclaimer: This is not legal advice. For a legal perspective, please consult a lawyer.
Data Strategy implementation is key to organisations unlocking and capitalising on the asset that is their data.
This paper explains the importance of data management, the issues facing those involved and how to address them. It also describes practical ways companies can begin to put their strategy into action.
Looking for a quick data fix?
Check out some of our blog posts relating to the solutions covered in the above whitepapers and guides:
"GDPR is quite frankly a minefield - made significantly more challenging by the fact that major law firms have recommended polar opposite views on many significant attributes (e.g. when you must physically delete data and where it has to be deleted from).
Datamine provided practical helpful advice, cutting to the chase. Their most important observation; ensure your business’ data policies are regularly reviewed and changed accordingly. This is key. There will be numerous challenges to the legislation and the resulting rulings will change or reinforce it - you must stay up with the play".
CEO at Cumulo9 Limited
Predictive modelling and the creation of AI and Machine Learning programs are two similar processes, and both of them are integral concepts to be across in today’s business sphere.
This whitepaper outlines the high-level process for developing such models and is written for the non-technical business professional.
