It's no secret that loyalty apps are growing globally right now. ResearchAndMarkets.com states that the global loyalty management market is expected to grow from USD 8.6 billion in 2021 to USD 18.2 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 16.3% during 2021-2026.
These numbers don't lie. If we take a closer look at the world's most successful companies: Mcdonald's, Sephora, Starbucks, etc. They have outstanding loyalty programs. For instance, Sephora's Beauty INSIDER is considered the most successful loyalty program, followed by Starbucks' Starbucks Rewards; this is clear evidence of how loyalty apps contribute to a brand's success.
Each brand's success comes from understanding its customer base and applying gathered information to create compelling offers and ads suited to its customers' constant needs.
Loyalty apps are excellent tools for boosting sales and building a brand's persona, yet that's a small fraction of their power. Loyalty apps' major features stem from collecting data which helps corporates get insights on their customer's behavior, the list of best-selling products/ services, and reviews.
Since we mentioned data usage to improve businesses, it's crucial to know that it comes in many shapes and forms.
Example: Data analytics analyzes raw data to draw meaningful, actionable insights that inform and drive smart business decisions.
Data analytics help get both.
- Internal Operational Insights: How employees engage with a particular tool, analyzing any events that could be linked to a decrease in sales.)
- External Insights: Identify the best customers among your members through a customer lifetime value analysis, customer retention rate, and customer satisfaction score. Etc.
Regardless of the type of data, internal or external, they all support one thing, achieving customer satisfaction to sustain the business for the longest time. However, a kind of data can be classified under the external insights you must consider and apply to draw more attention.
We are finally discussing the main topic for this blog, Transactional Data.
Sorry to keep you waiting, but let's know all about transactional data, from the definition, its types, and its benefits for businesses.
Part One: Definition
Transactional data are data obtained after completing a transaction.
Transactional data includes:
- Time and date of purchase
- Price of product
- Quantity
- The existence of any discounts or promotions redeemed
- Payment method
- The type of product or service that is captured at the point of sale.
Part Two: Transactional Data Types
Instore transactional: It's any payment on an account made in a store by customers, whether cash or credit.
Online transactional: Payment methods are done by customers while shopping online that includes a mobile wallet, Debit/credit card.
Part Three: Transactional Data Benefits
Despite categorizing transactional data as a part of the external insights in data analytics, its benefits cover both customers and business owners. So here are the main perks of transactional data.
1. Accurate insights: Using transactional data, you can analyze the spending habits of both current and new customers to identify where, when, how much, and how often they spend. This leads to number 2.
2. Proper Targeting: transactional data gives insights into the customers you're attracting, where they come from, and how much money they spend. From here, you can study all the data given to create flawless ads and offers to help you reach your desired customers without failing to reach your target.
3. Time-Focused: you can create reports for specific dates based on transaction data when you want to investigate peak sales months and low sales months.
4. Differentiating Payment Methods: Transaction data are analyzed based on the type of transaction; debit or credit. This helps you identify the types of transactions the potential trade partners prefer and will help you understand their preferences.
5. Elevating Customer Experience: Brands can also use transactional data to understand what differentiates their new, existing, and loyal customers. By understanding the differences between these segments, you can tailor your strategies and marketing to engage them better and, more importantly, track their performance.
These methods evoke the customers' feeling of being seen and appreciated, which elevates their experiences and increases their loyalty to your brand.
Conclusion
Transactional data can be considered a pillar in determining ways to approach your customers. Its specific features that allocate the different types of audiences from gender, class, age, products they choose to purchase, and reviews are essential to keep your business up and running. Transactional data isn't just figuring out if people pay cash or credit, online or in-store. There are more than meets the eye to its benefits. For an accurate and efficient method to collect transactional data, you need an innovative dashboard that simplifies the complexities. Don't hesitate to contact zeal if you want to jump-start your business.
