Essentral provides the resources necessary for quick and successful project implementations. Our aim is to provide the best consultants and applications experts in the field, and to provide swift and efficient progress through all phases of project development.

Our team is selected through a rigorous screening process, during which we evaluate candidate's aptitude for placement in an environment suitable to both themselves and our clients.

We manage our team to ensure that they receive all the support, training and security they require.

Essentral provides the resources necessary for quick and successful project implementations.

Areas Of Expertise

In the wide ranging field of database services consulting, Essentral provides both depth and breadth of expertise. Our consultants are drawn from both industry and academia, and are considered IT and business professions. They are all strongly committed to the company's core values of integrity, innovation, vision, and dedication to client satisfaction.

For further information on some of our areas of expertise, please see items below.

Database Design and Development

From designing, architecting and implementing database systems of all sizes to tuning and maintaining large production systems, we work alongside our clients to provide reliable, scalable and effective deliveries.

Our database consulting services include everything from initial investigations through data understanding to modelling, including process architecture, database tuning, design, coding and implemention, plus data quality analysis through to training and handover.

Essentral can provide expert database consulting services including quality database design and application development for the following databases:

  • Teradata
  • Oracle
  • SQLServer
  • SQLite
  • MySQL
  • PostgreSQL
  • DB2
  • MS Access


Analytics is the sophisticated analysis of complex data sets. It closely resembles statistical analysis and data mining, but tends to be based on physics modelling with extensive computation.

Analytics usually follows one of two paths:

  1. Uses existing patterns, metrics or performance indicators (KPI's)
  2. Uses sophisticated statistical / data mining tools to derive new patterns, metrics and performance indicators

At Essentral we take pride in our analysts capabilities, and aim to provide our clients with the most competent and highly trained personnel available.

Software Development

In today's business environment, relentless competition requires increasingly complex business solutions. Businesses must exploit emerging opportunities by rapidly adopting new technology and be open to innovative solutions.

Essentral's software development and integration services offer a wide range of consulting expertise in custom application development and systems integration.

Our services are designed to drive innovation and prepare for the future, while reducing overall costs.

We assist clients with the design, build and management aspects of their application development projects. At Essentral, it is our primary goal to help position our clients for long term success.

Business Intelligence (BI)

Business Intelligence (BI) is a term given to the gathering, storing and analysis of data to aid users in making educated decisions. To keep track of the vast amounts of information an organisation collects/generates, it is often required to use a wide range of software applications and databases throughout their organisation.

Using numerous software packages makes it increasingly difficult to retrieve this information let alone format, aggregate and process the data. This is where Business Intelligence strategies help extract the optimum information for the business.

BI represents the tools and systems that play a key role in the strategic planning process of the corporation. They allow end users to sieve through large quantities of data, both internal and external to the company and aid in the development of business strategies.

BI systems are often used in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis.

Customer Relationship Management (CRM)

Customer Relationship Management provides an integrated approach to identifying, acquiring, and retaining customers. Modern communications necessitate the need for a customer to be contacted via multiple channels to provide targetted products and services, and to improve customer/organisation relationships.

By enabling organisations to manage and coordinate customer interactions across multiple channels, CRM helps maximise the value of every customer interaction by ensuring any feedback loops required are closed off.

The challenge with CRM, is to enable customers to do business with the organisation, at any time, through any channel, while at the same time making the customers feel that they are dealing with a single, unified organisation.

As an overall strategy CRM seeks to improve business performance by identifying the customers needs and behaviours, and then matching products and services to satisfy them.

CRM is effectively a marketing philosophy based on putting the customer first with technology as a driving force.

Database Marketing

Database marketing is a form of ‘direct marketing’ using databases of customers, or potential customers, to generate personalised communications in order to promote a product or service.

The main differences between ‘direct’ and ‘database marketing’ are analysis and quantity of data. Database marketing can utilise statistical techniques to develop models of customer behaviour, which are then used to select customers (Customer Segmentation) for contact.

Due to the larger volumes of data, database marketers often utilise data warehouses to increasing the quantity of data, about customers, which in turn allows more accurate models to be built.

Database Marketing basically consists of two major tasks, Marketing Analysis and the subsequent implementation of the resulting strategies.

Marketing Analysis is iterative learning process, in which future campaigns are improved by learning from analysis of the previous ones.

Customer Segmentation

Customer segmentation is the process of clustering a customer base into subgroups of individuals that are similar in behaviour and demographics. On the basis of the segmented groups similarity, they are more likely to respond in a similar manner to a given marketing strategy.

Statistical models can assist in the generation of customer segmentation. These models can be as complex or simple as required by the business. Input variables often include age, gender, location, spend, product holdings or product usage.

Modelling and segmentation is often used to assist in customer retention, to increase usage, or to personally tailor communications for a customer.

The use of control groups is recommended to be able to more accurately gauge the effectiveness of campaigns in relation to segments.

Extract, Transform And Load (ETL)

ETL, or Extract, Transform and Load, are the processes that enable companies to move data between multiple systems, often reformatting or cleansing it on the way. Dependant on the origins and evolution of a company, data is often stored is disparate systems and in differing formats, yet for a multitude of reasons requires consolidation.

There are software packages available commercially for performing ETL, which may or may function as an efficient solution depending on the software systems being interfaced. Often it is a process that is best constructed from scratch to ensure the resultant process is completely robust.

However ETL is performed it should ensure data quality and regularity is maintained, while also being fully automated and providing a notification system for any issues it encounters, or tasks it successfully performs.

Data Warehousing

A data warehouse is a central repository for all or the significant parts of the data that an organisations different business systems collect. There is a multitude of benefits to having a centralised view of data including provision of a customer level view, a history of the interfaced data systems, marketing, revenue assurance, transactional or legal triggers, provision of unified information back to source systems etc.

The vast amount of data are collected in larger organisations means great storage and processing power is required to make sense of it. Data warehouses size and processing capacity are often limited by budget. For this information to be rapidly accessed and analysed, it is particuarly important that any processes utilising it are efficient.

Data Marts
Data Marts are smaller departmental databases containing only information required by the specific group, are more financially viable and quicker to implement.

Data Modelling & Mining

Data Modelling
Data modelling is effectively the process of designing a data structure in a format that is functional, understandable and efficient for the resources that will be using it. It is an abstraction activity whereby what is a data structure created to be suitable to the source of the data is converted to design more useful and efficient for the modelled application. In the process modelling will merge structures from many data sources into a final homogenous structure, along the way analying and eliminating redundancies while juggling having a final design not having multiple points of update for one data change vs database efficiency.

Data Mining
As the volume of data increases, the capability to intuitively analyse it for effective usage decreases. It is often becomes necessary to have advanced mathmatical and statistical knowledge. There are many techniques that can be used to find useful patterns in your data such as neural networking, regression analysis or support vector networks.


We primarily support and staff database marketing efforts in the Financial Services and Telecommunications Industries. We are a professional services consulting group dedicated to delivering database marketing solutions specific to your business needs.


Telecommunication companies are often primarily focused on reducing customer churn, increasing customer acquisition and identifying appropriate cross sell opportunities. They typically have well-developed data warehouses and have assembled an integrated view of their customers through direct, online and call centre customer contact channels.

Our personnel have assisted in projects to determine the drivers of customer churn, predict which customers are likely to cancel their plans and service in both the short term, and the longer term as well as segmentation, profiling and data services.

Banking and Finance

Banks and Financial Services companies typically have well-developed data warehouse environments. Most of these are used for deploying business intelligence and predictive marketing applications. Credit Cards and Mortgages have been two areas where necessity has driven data mining and modelling applications forward. On the whole most companies do not fully utilise the potential power of these data sources for database marketing projects.

We aim to work with your internal marketing groups, bringing in external knowledge and expertise, or filling a temporary gap in staffing.

The following are some of the services our personnel typically provide to our financial services clients:

  • Data integration from multiple sources
  • Data cleansing and preparation
  • Ad hoc reporting
  • Customer profiling and segmentation
  • Campaign tracking and measurement
  • CRM strategy consulting
  • Response to marketing campaigns
  • List generation, customer segmentation and profiling
  • Campaign planning and measurement