Transactional data is a holistic term for information generated by an organization from processing business transactions. To put it better into context, transactional data are generated whenever transactions are made, either from a financial, logistical, or business point of view.
What is transaction data?
This refers to the data obtained from exchanging goods or services, often for money. Transaction data hold essential information about the exchange, including but not limited to the time of the transaction, prices for items purchased, place of purchase, method of payment, and other important information associated with the transaction.
Due to the modern nature of transactions, the data can be generated in different ways and formats. Typically, transactional data records are generated at the point of purchase or point of sale. This can equally be as simple as exchanges made over electronic mediums and against conventional sales points.
Transactional data are generated from different business process points and can lead to a voluminous amount of data. To reduce the complexity of tracking down data, each transaction data is often assigned a unique ID that aids in identifying and analyzing the collected data.
What is master data?
Master data is foundational data needed for running a business operation. It gives better context to each business, including information about people, assets, and places needed for the smooth running of the business.
Master data are essential to the operation of any business, and the master data available for each business unit depends on what is needed for such a business niche. Master and transactional data are two of the many essential data required to better understand an organization's business processes.
Types of transactional data
While the use and importance of transactional data know no bounds, the use also depends on the type of transactional data collected. Although there are different types of transactional data, they mostly always fit under three classifications: financial, work-related, and logistical.
The common types of transactional data examples include:
- Order and purchase data: As the name implies, this is transactional data related to tracking the number of times customers order and purchase particular products. This type of data also collects information about the purchase timeline, the amount spent method of payment, etc.
- Customer service data: You can collect real-time transaction data about how your customers relate and interact with your business. This includes the type of complaints made by the customers, the duration for resolution, feedback, and other measures of customer satisfaction on resolution outcomes.
- Returns data: Information about returns of defective products is another crucial type of transactional data. It helps you understand how often purchased products are returned and how much was refunded. This can also aid in triangulating the reasons for the returns and possibly how to plug such leaking holes.
Who can use transactional data?
Transactional data in an organization is quite specific, as the end result is used to improve sales, increase marketing coverage and understand pain points for customer services.
Based on the results and impact of transactional data, the following set of people are often more involved with the use of the data:
Sales managers: Sales and business managers typically use transactional data to follow the sales figure of the organization and analyze how well it has performed in a financial year. The sales manager's duties include understanding purchase patterns and how to leverage that to boost sales or design new sales strategies.
Marketing managers: In the case of a marketing manager, the goal of using transactional data is to understand the trends and patterns of customers and how this affects their purchasing behavior. Information from this data analysis is incorporated into the design of campaign materials to effectively target specific market audiences.
Operations managers: One advantage of using transactional data is the insight it provides in highlighting areas of inefficiency in the business or redundancy. The job of an operational manager with this information will be to remove inefficient steps and processes and strengthen the system to reduce cost and get better value for money.
Why are transactional data important?
You might have been bombarded with this buzzword and wondered about the fuss. Every modern business organization requires transactional data to track what customers/consumers purchase, their preferences, and other metrics needed to improve business operations.
Transaction data serves the following purposes:
Enhanced customer experience
Transactional data can help you quickly identify business pain points and other difficulties your customers might be experiencing. This form of information can help you strengthen areas of business operations and help your customers carry out transactions more efficiently. The use of transactional data in delivering superior customer experiences and reduce complaints and churn.
Understanding customer purchasing pattern
One major use of transactional data among giant companies is to follow the trends and understand buyer behavior. This information can help you make intelligent and timely decisions about better marketing your products and services to the right consumers. Also, you can use the data to further improve sales of low-performing products while maintaining sales of high ones.
Monitoring sales channel
Most key business processes use different sales channels to optimize sales or reach larger populations in various countries. A key way of using transactional data is monitoring the sales and profits from the different channels. You can explore a lean and agile business operation by maximizing the use of only sales channels that bring in the highest sales.
Optimizing efficiency in businesses
Transactional data serves as a guide to navigating the process of optimizing businesses for efficiency. This includes but is not limited to making decisions about the methods of delivering services or analyzing costs against efficiency to get the best value for money.
Increasing sales and profitability
The main goal of almost all product and service-offering organizations is to increase sales as well as the profit-making potential of the organization. Gathering and analyzing transaction data can give you the leverage to discover the minefield of growth and profitability available for your business or organization.
Challenges of using transactional data
As good as transactional data are and come highly recommended, they also have challenges that can limit their effectiveness or usage. Some of these challenges are inherent to transactional data, while a handful is peculiar to the context of individual businesses where they are applied.
One major challenge attributed to transactional data is that it is time specific. If the data is not used within a particular period, it loses relevance and becomes redundant. For instance, transactional data collected from the previous year can be inadequate or misleading in making decisions for a new year due to changes in variables over time. The implication of the time-bound nature of transactional data means that it needs to be analyzed and used for decision-making within reasonably defined time frames.
Another common challenge that impairs transactional data is the database used for collecting such data. Suppose the transactional database is not correctly set up or programmed. In that case, it can result in the generation of inaccurate or incomplete data. Often, when noticed, this challenge can easily be fixed by carrying out an upgrade of the system.
The main concern about collecting transactional data is the worries over data security. Customers, and rightly so, can be worried over what type of data is collected about them and how much security is provided to such data. Various regions also have legal requirements and standards regarding collecting and utilizing data.
Data encryption is one of the strategies that can be used to ensure that any data collected are kept secure and that any unwanted access is prevented. Other modern cybersecurity can equally be deployed to guarantee maximum protection.
What method should be used for transactional data?
As described in an earlier section of this article, the potency of transactional data is also impacted by the method used in collecting the data and how it is used. Effective data use can be a turn-around point for businesses and bring about the much-needed scaling up. The various ways of effectively using the data include:
Getting best hands
Transactional data cannot be well utilized if it is not well analyzed. In most cases, there might be a need to hire data analysts or engage a consulting firm to manage the collected and analyzed data generated. This increases confidence in getting reliable data that can be used for decision-making.
Multiple data collection
Transactional data comes in different types, and to get a better picture of how the organization is truly performing, it is highly recommended that multiple data types are collected. For example, financial and logistics data will provide better insight into why there are delays in goods delivery than using financial data alone,
Value added activities
The goal of businesses should be to get the best value for each process. Analyzing transactional data can highlight areas to focus on that can bring about value addition.
Data visualization tools come in handy for explaining the trends observed in the analyzed data. This includes using charts and graphs, making it easier for a phenomenon to be explained with a snapshot.
Analyzing transactional data
The rule of thumb of transactional data is that for each purchase made by a customer, they leave behind a large trail of important information. What makes the difference is how this information is gathered and used. The three major variables that are especially useful for analyzing transactional data are – product, price, and time.
A thorough analysis of transactional data holds boundless opportunities for businesses and organizations. The beauty of transactional data analysis is that it is not just reflective of a single product; it can also give insight into other product categories. For instance, you can derive from a shopping cart analysis what products are purchased together and under what circumstances.
It is best to enhance the information obtained from this analysis by combining internal and external data.
Transactional data refers to the information generated after exchanging goods and services. It is key in optimizing business processes and making strategic management decisions to help deliver superior customer experiences and increase sales and profitability.
There are different types of transactional data, and when all of these are used together, they provide ultimate business analysis, potential solutions and help in keeping business operations smooth.
You need to generate transactional data for your business and get deep analytical data insights if you haven't yet.