Brands are uncovering holistic consumer insights with transaction data

Jonathan Chin, Co-founder, Facteus

The landscape of consumer insights has been traditionally navigated through customer surveys, detailed web analytics, cookie tracking and first-party data collection. These techniques, foundational to retailers’ and brands’ understanding of consumer behavior, predominantly hinged on self-reported preferences, online engagement metrics and data gathered directly from customer interactions. 

While these methods have provided valuable insights, they often offer a limited perspective, constrained by the inherent biases of self-reporting and the scope of online user activities. Now, the industry is transforming by integrating actual purchase transaction data. This innovative approach exceeds the boundaries of traditional methods, providing a deeper and more authentic insight into consumer spending habits. 

This emerging trend is not just enhancing but revolutionizing the domain of consumer insights, uncovering new customer segments, reshaping marketing strategies and discovering unique consumer preferences or connections.

Traditional consumer insight tactics are susceptible to inherent biases and limitations

Traditional consumer insight methods, such as customer surveys, web analytics, cookie tracking and first-party data, have been instrumental in shaping the understanding of consumer behavior. However, they come with inherent limitations.

For instance, customer surveys are often plagued by self-reporting biases. Consumers may only sometimes provide accurate responses due to memory lapses or the desire to present themselves in a particular light. There is also inherent bias in survey takers, and the panel will only cover part of the customer base.

Meanwhile, web analytics and cookie tracking are confined to online behaviors. However, they provide an incomplete picture of their overall spending habits unless they also capture the consumer’s offline activities. Additionally, tightening privacy laws means that cookie data, once a staple in digital marketing and consumer insights, is becoming less reliable. Businesses can no longer rely solely on this data to comprehensively understand online consumer behavior.

While first-party data offers valuable insights into how consumers interact with a specific brand or retailer, it does not reveal their behaviors and preferences outside that ecosystem.

Transaction data offers a holistic perspective on consumer preferences

Successful brands and retailers use actual purchase transaction data to open up a broader and more accurate window into consumer behavior.

Unlike traditional methods like shopper surveys and web analytics, transaction data captures a more extensive range of consumer spending behaviors. In addition to showing what customers buy from a particular retailer or brand, this data offers insights into their spending patterns across different sectors and categories. 

For example, transaction data can reveal that inflationary pressures impact a consumer segment, and their non-discretionary spending, like mobile bills, grocery costs, insurance payments, etc., has increased. This can explain drops in average order values (AOV) and help a brand build a strategy around this new economic paradigm the consumers are facing.

Transaction data offers a more holistic view of consumers’ preferences and habits by providing insights into their purchases outside a given retailer. It can show if consumers who frequently purchase health foods also invest in wellness and fitness services, uncovering correlations and lifestyle choices that transcend singular retail experiences.

Transaction data also removes the guesswork in interpreting survey responses or online engagement metrics. It represents actual consumer behavior, delivering more reliable and actionable insights.

Equipped with transaction data, businesses can construct dynamic consumer profiles that reflect changing trends and preferences in real-time. Traditional methods struggle to achieve this level of detail and timeliness. 

By unlocking new consumer segments, transaction data opens the doors for further brand opportunities

Perhaps most significantly, transaction data unveils previously unrecognized consumer segments. Businesses can identify niche markets or emerging trends that traditional methods might overlook by analyzing spending patterns.

For example, a local coffee shop chain analyzed broad transaction data and discovered a compelling trend: many of their regular customers are also frequent shoppers at a popular direct-to-consumer (DTC) fashion brand known for its sustainability and modern designs. This overlap reveals that their customer base has a strong affinity for trendy, eco-friendly products.

Leveraging this insight, the coffee shop introduces a new line of merchandise in collaboration with the DTC brand. This range includes stylish, reusable coffee cups, eco-friendly tote bags and coffee-themed apparel. The two brands also initiate a joint marketing campaign, harnessing the DTC brand’s appeal to attract fashion-conscious, environmentally aware consumers.

This strategic partnership, born from transaction data insights, broadens the coffee shop’s appeal to its existing customers. It also attracts new patrons identifying with the DTC brand’s values, enhancing brand loyalty and expanding its market reach.

While traditional consumer insight methods have provided valuable information, the advent of real transaction data offers a more comprehensive and accurate perspective on consumer behavior. This shift addresses the shortcomings of earlier methods and enhances businesses’ ability to understand and cater to their consumers’ evolving needs in a more holistic and informed manner.

Sponsored by Facteus