How to leverage transactional data to improve customer loyalty

Transactional data provides up-to-date information about your customers’ purchases and their behavior before hitting the “Buy now” button. This data includes details like time and date of purchase, payment type, product and quantity purchased, as well as any discounts or promotional codes that were used.

What makes transactional data more valuable than many other types of data (like first- or third-party cookies) is that it can be leveraged to improve and build upon customer loyalty. Let’s examine the most common ways brands use transactional data to build customer loyalty and how it can also be used to improve customer loyalty efforts.

Leveraging transactional data

The amount of data found inside a transaction allows brands to make many data-supported observations about their customers. One of the most important factors is that transactional data comes directly from purchasers of your products or services. You are not extrapolating data from all site visitors or in-store shoppers. With this dataset, you can be confident in the knowledge that using this data to make plans and reach out to customers will be successful.

Here are some of the most common observations transactional data allows you to make.

1. Geography

Location is key to business. Whether you run a physical or online store, knowing where your customers are located is hugely important. It can help you determine merchandise planning, make your deliveries more efficient, and, in the case of brick-and-mortar stores, give you an idea of where to build your next location.

Geography also allows you to gather additional data about your customers when examining their purchases. For example, if you sell skiing gear, you may see an uptick in sales in the fall (before ski season) and a downturn in the summer. This type of seasonality can also help with moving products to locations where they will be most useful and can help to reduce end-of-season blow-out sales because of too much inventory.

2. Payment type

How people pay for products is telling, and with the recent rise of payment plan apps, such as Sezzle and Afterpay, understanding your customer transaction data is even more important. You’ll also be able to quite easily see the cost of acceptance per transaction. Cost of acceptance relates to different credit card fees charged by each credit card platform, and most definitely affects your overall revenue.

By analyzing this data, you can quickly determine what the best credit cards are for your business and also analyze if you should be offering different forms of payment that might be more consumer-friendly—and friendlier to your bottom line.

Additionally, you can also use payment type transaction data to target operational issues. Things like card read fails and delayed processing times can be easily pinpointed when examining transactional data. And making your checkout process more efficient leads to fewer dropped carts and more satisfied customers.

3. Promotional codes and discounts

This is perhaps one of the biggest—and most useful—examples of transactional data. While you may have a group of shoppers who are unswayed by promotional offerings, chances are most of your customers love a good deal.

Analyzing the types of promo codes and discounts that result in the biggest uptick in sales or cost per transaction can allow you to pinpoint your most effective promotions.

You may find that a 10% offer doesn’t move the needle, but free shipping does. Or you may find that “Buy one and get one 50% off” is less enticing than 25% off sitewide (same discount, different distribution).

On top of that, because you run promo codes for a set period of time, it’s easier than ever to review the transactional data for that timeframe and draw conclusions. You can cross-reference sales with any of the other transactional data types like location or payment method. The combinations of factors can also lead you down a rabbit hole, so make sure you establish what data you want before you start running reports. In most cases, you’ll want to focus on the amount of money customers saved versus what your company earned, and do the math to determine if the increase in sales was worth the savings.

Why transactional data is important for customer loyalty

The beauty of this data is that it gives you the chance to offer “personalized” sales to your most loyal customers with little effort. Even though transactional data is anonymized, it still allows for enough personalization to speak directly to certain consumer segments.

By understanding how promo codes and discounts impact sales in certain parts of the country, you can tailor your offerings to these customers. You can also analyze the purchase of specific products and determine when it might be the best time to offer a deal. To take the skiing example from above: Perhaps you want to move some ski jackets earlier this year to make way for more inventory. You could offer a discount or promo code early, using the previous year’s sales data to determine the timing. This should result in people buying earlier and allowing you to move more merchandise.

Get more insight with transactional data (through Lytics)

To truly take advantage of your company’s transactional data, it’s important to have access to the right tools and the right experts. Lytics helps companies like yours leverage transactional data every day with Cloud Connect, a reverse ETL that takes your data and provides audience insights quickly. To find out how you can leverage your organization’s transactional data and learn more about why it’s crucial, register for a free trial of Cloud Connect today.