Best Practices for In-Store Data Collection: Balancing Efficiency, Privacy, and Data Retention

Effective customer communication is crucial for retention and growth, and it begins with the collection of contact information at the time of purchase. Online purchases are more conducive to gathering customer names, mailing and email addresses because this information is necessary for shipment and confirmations.  However, for those with brick-and-mortar stores, collecting customer contact information at POS is more of a challenge as it is not necessary to complete the transaction. It’s essential to show the value in providing this data while ensuring data privacy and complying with evolving data retention regulations. The following provides best practices and key considerations for in-store data collection.

What to collect at POS

Ideally, marketers would like to collect the first and last name, land address, email address, mobile and opt-in preferences.  That is likely too much to collect at one time.  It is recommended to complete the customer profile by collecting missing elements over multiple visits to respect time and reduce the perception of privacy invasion. 

Asking for first/last name and email address is a good place to start for several reasons:

  1. You can instantly add the buyer to your email program, if they agree.
  2. For a relatively small price, email reverse append processing can provide name and land address needed for direct mail, without requiring further input.  Marketers will generally mail customers unless they specifically contact them to be removed from the mailing list.
  3. Email addresses facilitate other types of digital ad serving such as via Facebook and Instagram.

Next, try to collect the land address which is needed for marketing via direct mail and is very important for creating a customer profile. If the customer will not provide a given element, at a minimum, collect the name and ZIP code to start.  This information, coupled with the store of purchase, can be used to find the full land address using 3rd party data providers who can hone in on those who live within driving distance. Caveat: 3rd party address append is less effective in tourist locations where customers travel long distances. The more data points that are collected at POS, the greater the likelihood of finding a correct match to these data repositories which will allow the building of a robust marketing database. 

Other information that can be useful includes demographics, such as Month/Day of birth for birthday programs.  Some cohorts might be better to infer than request, such as gender.  If products purchased are more likely associated with one gender vs. another, skus can be used to accomplish the desired goal.

Demonstrate Value and Obtain Consent

Customers will be more likely to “share” if they perceive there is value in it.  Clearly explain why you are collecting customer information and how it will be used.  Value can come in multiple forms such as exclusivity, with early access to new products, sales, special events and more.  Customers are likely to give their contact details to become part of loyalty programs where points are earned towards rewards.  Be sure to obtain verbal consent to enter them into marketing programs that require an OK to communicate such as email and SMS (text).

The Process of Data Capture at POS

  • Engage the Customer: Explain the benefits of providing contact information
  • Collect Key Data: Start with email address and add to the profile over time
  • Create/Retrieve Customer Profile:  Use the provided contact information to create a new profile or retrieve an existing one.
  • Link Purchases to Buyer: Use the POS system to link the purchase details (items bought, total amount, date, and time) to the customer’s profile.
  • Create a Marketing Database: All transaction data from the POS system, including linked customer information, can be ingested into a centralized data repository where marketing campaigns can be created using buyer data that has gone through hygiene and data aggregation processing. 
  • Derive New Cohorts for Segmentation/Analysis: Elements (such as RFM, recency of last purchase, number of purchases, and spend by product) can be derived from purchase.
  • Market/Measure/Adjust: Develop, execute and evaluate marketing campaigns that will resonate with your buyers and encourage the next purchase.
  • Database Updates: Regularly update the marketing database with the latest purchase activity to ensure customer profiles are current and accurate.

Collection Methods and Accuracy

Data is usually collected by the sales associate during the checkout process. While common, this method can be fraught with spelling errors and compromise privacy as everyone on line listens to the conversation. Sales representatives may bypass data collection if the store is busy or they are not held accountable for capturing it.  They may even enter the store’s email and land address just to complete the transaction.  If this occurs, you will need to suppress those addresses from direct mail and email. 


  • Add data capture to performance reviews.  Train staff on how to accurately collect data and why it is so important.  Track this metric by store and employee and reward good performance.
  • Reduce errors by having customers enter their information directly using tablets or kiosks.
  • Implement address verification systems to ensure the accuracy of the data collected. This can involve real-time validation tools that correct any errors on the spot.
  • Enable customer look up at POS using one key piece of data to bring up the full profile so that you do not have to ask for all information each time they purchase.

Measurement and Variability in Data Capture

It is rare to be able to tie a customer profile to all retail purchases.  Understanding the capture rate by store is important.  This metric is expressed as a percentage and can be computed by dividing the number of purchases with contact information by the total POS transactions for a given store.   Analyses based upon retail sales with <100% capture rate require extra consideration, as results may be understated.  Analysts can apply an adjustment factor to estimate performance at full capture.  Caveat: this is not a perfect science as certain transactions are more likely to be captured than others.  Capture rates can vary by payment type, product, price point, store location and more. 

  • Payment Type: Customers using credit/debit cards are more likely to provide contact information for security and verification purchases than those paying cash. 
  • Price Point: Customers are more willing to provide contact information for high-value purchases, as they often want digital receipts and warranty information.
  • Returns: Most stores require contact information to process a return. This helps to identify chronic returners and potential fraud situations.
  • Brand and Product Line: Luxury brands, furniture, jewelry and electronics achieve higher data capture rates compared to everyday consumables.
  • Store Activity Level: Busy store associates with long lines are less likely to be concerned with collecting customer profile information.  Store activity varies by location, urban vs. suburban, as well as seasonally, peak vs. nonpeak shopping periods.  Store manager commitment to the process is also a factor.

Privacy and Data Retention

When collecting personally identifiable information (PII), familiarize yourself with the evolving rules and regulations, like GDPR (General Data Protection Regulation) and CCPA (the California Consumer Privacy Act), which are required for data collection, storage and consent.  Individual states have their own rules. What is acceptable in one state may not be ok in another.   Data privacy has become so important that many companies have a dedicated team to ensure compliance.

Create a privacy policy and then live by it.  Clearly state the purpose for data collection and how it will be used. Use the collected data strictly for the purposes stated at the time of collection. This builds trust and adheres to privacy principles.  Provide a method for opting out of various contact methods such as direct mail, email and text messaging. Date and post the policy on your website and in stores. Update to reflect changes.

  • Data Minimization: Collect only the information that you need and avoid “nice to have”.  The more data that you collect, the more risk you assume as you are responsible for keeping it safe from hackers and scammers.
  • Data Handling & Retention:  Determine how long customer data will be retained and ensure data is deleted after this period.  Incorporate encryption of collected data to protect against unauthorized access and data breaches.  Implement role-based access control to limit customer data to only those employees who need it for legitimate business purposes.
  • Certifications & Audits: It is recommended that all who handled PII data obtain official certifications such as ISO, SOC, HIPPA and PCI (where applicable).  This will require regular audits of your data retention practices, ensuring compliance and the identification of areas for improvement.  3rd party penetration testing is also recommended to ensure your data storage is not easily compromised.
  • Customer Rights: Provide customers with the ability to access their data and request its deletion. This can be facilitated through a self-service portal or by contacting customer service. Allow customers to update or correct their address information. Keeping data accurate and current is crucial for both marketing effectiveness and compliance.

The Role of Customer data

Capturing customer contact information facilitates sophisticated marketing programs that can drive incremental revenue.  It is also critical for the evaluation of these strategies to understand what is working and to what degree.  Train and incentivize store associates to Explain, Ask and Enter.  By following best practices, you can balance the need for valuable customer information with the responsibility of protecting it to maintain customer trust and loyalty.

Elisa Berger, Ph.D.

About Elisa Berger, Ph.D.

Elisa Berger, Ph.D., is Principal and President at Cross Country Computer (CCC). Elisa has been successfully helping database marketers achieve their ROI goals for nearly three decades. She earned her Ph.D. in Applied Research at Hofstra University.
This entry was posted in Data, Data Management, Data Privacy, Direct Marketing, Email, Marketing Strategy and tagged , , , , , , , . Bookmark the permalink.

Comments are closed.