Personalisation and Segmentation

Deliver the right message to the right customer at the right time. We offer:

• Customer Segmentation: Group your customers based on behavior, preferences, and demographics.
• Personalised Messaging: Tailor your communications to individual customer needs and preferences.
• Dynamic Content: Use data-driven insights to create content that adapts to each customer’s interactions.

Data Processing (General)

General data processing transforms raw data from different sources (including legacy data), formats, and structures into actionable insights using various steps and processes. These processes are executed based on client business rules. Here’s a closer look at some of the key components involved in data processing:

Data Extraction

Data extraction involves retrieving data from various sources, including databases and files, and converting it into a usable format. This step is often the first in the data processing pipeline and is critical for gathering the raw data needed for communication. Techniques for data extraction can include importing data, API integration, and querying databases.

Data Analytics

Data analytics involves examining raw data to uncover patterns, correlations, trends, and insights that can inform decision-making. It encompasses various techniques such as statistical analysis, machine learning, and predictive modelling. By applying these techniques, we gain a deeper understanding of their operations, customer behaviours, and market trends, which helps in making informed strategic communication decisions.

Data Merging

Data merging is the process of combining data from different sources to create a unified dataset. This involves aligning data structures, reconciling differences in data formats, and ensuring consistency and accuracy. Data merging is essential for creating a comprehensive dataset from multiple databases, enabling more robust and streamlined output.

Data Cleansing

Data cleansing, or data cleaning, involves identifying and correcting errors, inconsistencies, and inaccuracies in the data. This step is crucial for ensuring the reliability and quality of the data. Common data cleansing tasks include removing duplicate records, filling in missing values, and standardising data formats. Clean data leads to more accurate information and quality outcome.

Deduplication

Deduplication is the process of identifying and removing duplicate entries from single or multiple datasets. This is important to ensure that each data point is unique and to prevent redundancy, which can skew results. Duplicates are assessed and extracted as “Probable” or “Possible” based on client-supplied business rules. This improves the quality as well as the accuracy of insights derived from the data.

Data Segmentation (Streams)

Data segmentation is a critical process involving the partitioning of single or multiple datasets into distinct, manageable subsets. This allows you to divide your customer base into groups based on characteristics like demographics, behaviour, and membership types. This enables personalised communication strategies, leading to improved customer engagement and highly relevant to the recipient.

By leveraging these data processing techniques, organisations can transform raw data into valuable insights, driving better customer communication.

Overview of Data Processing for Print & Mail

Data Processing for Print & Mail remains a crucial communication method despite the rise of digital communication channels. Known also as physical mail or snail mail, this form of communication offers advantages such as stability, SPAM prevention, and a personalised touch that digital formats often lack. Physical mail shows the recipient that the sender has invested time and effort into the communication, making it more meaningful.

Role of Australia Post

Australia Post is essential in ensuring that Print & Mail communications reach their intended recipients. Hexcen leverages extensive experience and knowledge to comply with Australia Post's requirements, ensuring efficient and effective mail delivery.

Sorting Options:

Hexcen understands the various sorting options to save money and streamline delivery:

• Small/Large volume business letters
• Bulk mail options
• Charity Mail
• PreSort Letters
• Print Post
• Reply Paid
• Unaddressed Mail (Non-Personalised communication)

Above listed are some of the popular sorting options. Visit Australia Post for further options.

Print Ready Files & Lodgements:

Hexcen prepares print-ready files upon client approval, which can be in mono or full-colour. These files are generated in Postscript or PDF formats and include postal summaries for lodgement.

Clients have two options for printing and lodging their mail:

• Affiliated Bulk Print & Mail Partners: Hexcen can organise delivery of physical mail through affiliated partners, providing a complete service package.
• Preferred Mail-house Service Provider: Clients can choose their own mail-house service provider to print and lodge their physical mail with Australia Post, maintaining existing arrangements.

Data Processing (Transactional)

Transactional data is information captured from various types of transactions. This data may include details such as:

• Time of the transaction
• Type of transaction
• Contributions
• Earnings
• Income
• Revenue
• Investments
• Payments
• Discounts
• Fees & Charges
• Other quantities and qualities associated with the transaction

Applications of Transactional Data

Transactional data is not only vital in the retail sector but also plays a crucial role in various industries, including:

• Wealth Management
• Superannuation
• Banking & Finance
• Nonprofit Organisations
• Credit Unions

These industries utilise transactional data as part of their services and are often obligated to send transactional statements to their customers, detailing the specifics of their transactions.

Challenges with Legacy File Formats

Many of our customers face persistent challenges with their legacy Customer Relationship Management (CRM) and customer communication platforms. These systems often lack the flexibility and modern capabilities needed to automate and personalise communications at scale. Compounding the issue, they frequently output outdated file formats that are difficult to integrate into current workflows or multi-channel delivery systems. While the legacy file formats are still available, bridging them into a data-driven, responsive communication framework requires specialised transformation; a challenge Hexcen is uniquely equipped to handle.

Following are some of such data files:

• Comma-Separated Values (CSV) CSV files are simple text files where each line represents a record and each record’s fields are separated by commas. This format is widely used for data storage and transfer due to its simplicity and compatibility with many software applications. However, CSV files lack support for complex data structures and can encounter issues with data containing commas, requiring special handling or escaping.
• Tab-Separated Values (TSV) TSV files are similar to CSV files but use tabs instead of commas to separate fields. Each line in a TSV file represents a record, with fields separated by tab characters. TSV files are preferred when data contains commas, reducing parsing errors. Like CSV files, they are easy to create and widely supported, but they also lack support for hierarchical data structures.
• Bespoke Text Files (TXT) Bespoke text files are custom-formatted text files designed for specific applications or use cases. They can contain data in any format, such as fixed-width fields or custom delimiters. While highly flexible, bespoke text files require custom parsers to read and write data, making them suitable for specialised applications but potentially challenging to integrate with other systems.
• Fixed Flat File Fixed flat files are text files with fixed-width fields, meaning each field in a record occupies a set number of characters. This format ensures consistency in data structure, making it reliable for legacy systems and batch processing. However, fixed flat files can be inefficient in terms of storage space and require careful handling of padding and alignment.
• Structured EDI Files Structured EDI (Electronic Data Interchange) files follow standardised formats such as EDIFACT, ANSI X12, or TRADACOMS, used for automating business transactions. These files facilitate business-to-business communications by standardising data exchange, enabling efficient and accurate transactions like purchase orders and invoices. EDI files are highly structured but can be complex to implement and maintain.
• DAT Files DAT files are generic files used by specific applications to store data. They can be either binary or text and may contain any type of data relevant to the application. The structure and format of DAT files are usually application-specific, making them flexible but often opaque without the corresponding software to interpret them.
• Multi-Record-Type Flat File Multi-record-type flat files are text files that contain various types of records, each with a different format. These files distinguish record types using keys or identifiers at the beginning of each line, enabling the storage of diverse data in a single file. They are useful for complex data processing systems but require sophisticated parsing logic to handle the different record formats.
• Corvis Flat File Corvis flat files are proprietary or custom flat files used by Corvis systems. These files have a specific structure unique to the Corvis technology, designed to store and transfer data within Corvis applications. The exact details of their format are tailored to the needs of the Corvis system, making them specialised and potentially difficult to integrate with non-Corvis systems without detailed documentation.

Different file systems offer various advantages and limitations based on their structure and use cases. CSV and TSV files are simple and widely supported but lack support for complex data structures. Bespoke TXT files provide flexibility but require custom parsers. XML and JSON support hierarchical and complex data structures, with XML being more verbose and JSON more lightweight. Excel and Access files offer rich functionality for data analysis and management but face scalability issues. Fixed flat files ensure consistency and reliability for batch processing, while structured EDI files standardise business transactions. DAT files are application-specific and flexible, multi-record-type flat files handle diverse data formats, and Corvis flat files cater to specific proprietary needs. We have years of experience working with all of these file types, making us well-equipped to handle diverse data management and process challenges.

Our Solution

Our in-house built tools, applications and Customer Communications Management (CCM) Platform offer a flexible and seamless solution to work with data extracted from your existing legacy systems to manage customer communications. This ensures you can meet your communication needs with the scale and personalisation that modern data processing demands.