Ask the Expert: Maximizing Customer Insights You Already Have (But Didn’t Know It)

Q: MH – Cheryl, can you explain what pass-through data is and how it differs from other types of consumer data?

A: Cheryl Zajac

We’re in the survey business, so in this context, pass-through data refers to additional information collected alongside survey data during a transaction or interaction. 

Unlike standard survey data, which might include basic demographics or other information asked of the respondent, pass-through data encompasses the details we collect about a site visitor and their purchase directly from the retailer. These are wide-ranging, such as the time of purchase, the device used, or specific product attributes. 

This data is “passed through” from the retailer with a shopper’s survey data to provide a richer, more nuanced understanding of consumer behavior.

For example, we can tie point-of-sale and post-purchase survey data to information that a retail merchant collects, such as the purchase amount, items bought, type of device used (mobile or desktop), whether the purchase was made using a discount code, and whether the shopper is a loyalty program member. 

This additional context helps the merchant understand their customers better.

Q: MH – How can businesses effectively collect pass-through data?

A: Cheryl Zajak

By integrating advanced data collection tools at various touchpoints, such as what’s offered here at Bizrate Insights. These can include POS systems, online checkout processes, and customer feedback forms. 

It’s crucial to ensure these systems capture detailed contextual information without disrupting the customer experience. 

Using APIs to connect different data sources can help aggregate and analyze pass-through data more efficiently. We offer API integration to provide our clients with real-time access to all of the information they need when they need it.

For example, a clothing retailer’s online checkout process captures device type and any promotional codes used, the customer’s membership status, and the items bought. Our surveys capture feedback about the customer’s satisfaction with their purchase experience.

Q: MH – What are the key benefits of pass-through data for a business? Can you provide some concrete examples?

A: Cheryl Zajac

Pass-through data offers several benefits. First, a business will gain deeper customer insights. By understanding the context of each transaction, businesses can gain more comprehensive insights into customer preferences and behaviors. For example, knowing that a specific customer demographic frequently purchases certain products can help tailor marketing messaging and campaign spending.

Next, it can help improve personalization. For instance, if a retailer knows that a customer prefers shopping via mobile, they can enhance their shopping journey and mobile app experience accordingly.

Finally, it’s about making more informed decision making with richer data. You might discover that certain products sell better in specific regions, leading to more targeted inventory management. A grocery store chain uses pass-through data to identify that customers in urban locations prefer organic products and tend to shop late in the evening. This insight leads the chain to stock more organic items and extend store hours in urban areas.

Q: MH – In your experience at Bizrate Insights, what specific types of pass-through data have you found to be most valuable to collect?

A: Cheryl Zajac

For businesses partnering with us, the most valuable types of pass-through data to collect might include purchase context, product and order details, and customer details.

Take an electronics retailer who collects data on the time of purchase, the specific model and color of the product bought, and customer feedback on their shopping experience. This helps the retailer understand peak shopping times and customer preferences for specific product features.

Q: MH – How does pass-through data contribute to creating a more comprehensive customer profile? 

A: Cheryl Zajac

Pass-through data enriches customer profiles by adding layers of contextual information. Behavioral data combined with the attitudinal data from our survey solutions create really robust customer profiles.

Q: MH – Can you walk us through this process?

A: Cheryl Zajac

An example would be a fashion retailer who collects data on purchase times, items bought, and customer feedback. By integrating this data, they identify that a segment of customers prefers shopping for new collections on weekends and values quick delivery.

Q: MH – Are you able to share some innovative use cases for pass-through data?

A: Cheryl Zajac

Let’s look at dynamic pricing first of all. That is, adjusting prices in real-time based on contextual data. This would include demand, time of day, and customer location. 

Targeted promotions are also a great use case. Pass-through data allows you to create highly targeted marketing campaigns based on detailed customer behavior and preferences.

I can see various scenarios using this data to inform strategy. Imagine a home goods store. They could use pass-through data to set up dynamic pricing. They might offer deals on popular items during slow hours to drum up more sales. They could then turn around and use that same data to send personalized promos to customers who’ve been eyeing similar products. 

Oh, and one more use case would be improved customer support. Giving customer support teams detailed context about previous interactions leads to more personalized and effective service.

Q: MH – Let’s explore strategy a little further. Can you discuss the role of pass-through data in improving customer segmentation and personalization?

A: Cheryl Zajac

A retailer can use pass-through data to segment customers based on their purchase history, preferred shopping times, and survey feedback. Then, they can create personalized email campaigns featuring products that match each segment’s preferences and shopping habits.

Another scenario might involve a retail client who discovered through pass-through data that a significant number of high-value purchases were made late at night via mobile devices. 

This insight would lead them to optimize their mobile shopping experience and extend their customer support hours, resulting in a substantial increase in sales and customer satisfaction.