The ‘Coupon Cleanse’ That’ll Nourish Your Bottom Line
For deal-seeking customers, coupons can mean the difference between purchasing online and shopping at physical stores. I, for one, can’t resist coupons with unbeatable savings.
Who doesn’t appreciate saving money while picking up a few necessities?
At their best, coupons cultivate insane customer loyalty. Savvy shoppers plan their spending around special offers and sales. And for the budget-conscious crowd, there’s no such thing as having too many coupons.
The Flip Side of Coupons
Customers may love coupons unconditionally. But businesses may feel like they’re getting the short end of the stick. Doling out discount after discount to customers who only shop with coupons in hand … is not ideal. As coupons pile up behind the register, profit margins may be shrinking behind the scenes. So how can you tell if your coupons inspire genuine customer loyalty, instead of customer contingencies?
At some point, sending out too many coupons can backfire. This causes companies to lose money. The tell-tale sign? Your customers shop if and only if they have coupons.
So when do coupons hurt a company’s bottom line?
To answer that question, let’s first review how customers get coupons. Customers can enter a company’s coupon ecosystem through a variety of channels:
- Loyalty Programs. While checking out, customers are often encouraged to sign up for special incentives and monthly coupons through loyalty programs.
- Gift Registries. Providing your mailing address while setting up gift registries for baby showers, weddings, and birthdays can automatically subscribe you to mailing lists, depending on the company’s terms and conditions.
- Online Shopping. Purchasing items from an ecommerce site can also plop you into another customer list.
It’s possible to land on different customer lists in multiple systems if you subscribe through different channels, with a variety of interactions, repeated throughout the years. Plus, if you enter your address in different formats each time, that can further complicate the customer database.
Since I’ve been receiving multiple coupons in the mail from various retailers, it made me wonder. Why was I ‘special’ enough to get more than one coupon in the mail? Not that I was complaining. But I was baffled and beyond curious. So I took a closer look at the coupons themselves to see if I missed something.
And the answer was staring right at me. My address was formatted differently on each coupon!
Masking my personal address (for data privacy, of course!), these example coupons show the same address variations I noticed on my coupons. Keep in mind the permutations are endless if you include differences in names as well. If you enter a nickname while registering a second time (e.g., James and Jim), this will also generate multiple coupon mailers.
The Dirty Data Reality
After looking at the address and name fields on my coupons, I can only guess what happened. These companies may not have a consolidated single customer record for me.
Their systems and customer mailing lists might not be synced, cleaned, or updated regularly. It’s also possible that they may not be removing duplicate records or merging partial duplicate records.
Many companies today face this dirty data reality. They store disconnected, duplicate customer records. This triggers multiple coupons to be mailed out to the same person.
How can companies address this issue? Maintain high data quality. Clean customer databases regularly. Apply last-mile data cleansing to contact lists (a “coupon cleanse,” if you will). This would help:
- Eliminate duplicate coupons from being issued to the same person, thus lowering the number of coupons used
- Reduce coupon costs associated with printing, mailing, and distribution
- Keep coupons special, so customers don’t rely on them to shop
What can you do?
Clean your data with REV
Cleaning data is a best practice that needs to be done regularly. That way, you won’t have multiple records scattered across different systems for the same customer.
While the IT department can incorporate data quality tools and MDM to help tackle this enterprise challenge, marketers and other employees can also help. How? By being proactive about cleaning lists before uploading new contact records to their marketing automation and CRM systems. And also after pulling lists to start new campaigns or promotions.
However, the problem is employees may not be proficient enough in Excel to clean spreadsheets efficiently. And they may lack the patience or time to double-check massive customer lists properly for duplicate or partial duplicate records.
If Excel is a time-drain for you, or if you’re tired of using complicated Excel formulas to manipulate data, you can reshape and clean your spreadsheets in minutes with REV. Or, you can continue to spend hours in Excel. But you won’t believe how much time you’ll save with REV’s automated data prep shortcuts.
(Confession: I’m not an Excel pro. So I really love how REV guides me through common data prep, cleansing, and manipulation tasks. If I tried doing these things in Excel, it would take me hours. If not days. I wish I were joking. But I’m not.)
I encourage you to sign up for a free REV trial. Test out the “Resolve duplicates” feature to weed out those pesky duplicate records.
To double-check spreadsheets and remove duplicate rows of data using REV, follow these steps:
- Get Data: Export a customer list you want to double-check (it can be in CSV, Excel, or TXT format).
- Open REV: Log in to REV at https://rev-app.informatica.com
- Get started: Click “New Project.”
- Name your project and goal. Click “Continue.”
- Import Data: Click “Files” and choose your file type: CSV, Excel file, TXT. Click “Import.” (Your list will upload to REV and you can start working with it!)
- Dedupe Records: Right click on the top column you want to double-check, either by last name or email address. Find and remove duplicate customer contact records by selecting the “Resolve duplicates” filter.
- Merge and Delete: Edit the row of data you want to keep. Click the row you want to delete. REV will automatically isolate the partial duplicates for you. You can modify the fields as needed.
Make Quality a Reality
Companies may not even be aware that they are sending multiple offers to the same customer. By identifying some of the underlying problems and incorporating some data quality best practices, they can manage and monitor their data better. Data cleansing helps prevent new duplicate records from tainting their systems.
From the customer perspective, coupons can help make ends meet when funds are tight. Taking them away from customers is not the answer. (Doing so would probably traumatize loyal customers, to say the least.) I probably wouldn’t shop at certain places if I didn’t have coupons to tempt me.
From the business perspective, I can understand why companies have mixed feelings about coupons. After all, they can’t stay in business without customer loyalty. But companies need to make money in order to stay in business.
Addressing data quality issues head-on will enable you to remove duplicate customer records. And why not cut extra coupon offers off at the source? That would help save money and nourish your bottom line.
A healthy “coupon cleanse” may just be what the doctor ordered.
Need help? Ask the Data Quality Experts.
Informatica Positioned as a Leader in the Magic Quadrant for Data Quality Tools
According to the Magic Quadrant report, Informatica was praised for the “depth of its data quality capabilities” and for having tools that were “easier to use than those of competitors,” with “suitability for supporting both technical and nontechnical roles.”
If you’re looking for the right partner to help manage the accuracy, consistency, and completeness of your data, the Gartner Magic Quadrant for Data Quality Tools is a great resource.
Download the report today to see why Informatica has been positioned as a leader Gartner’s Magic Quadrant for Data Quality for nine consecutive years.
It’s Your Turn
How do you feel about coupons? How would you rate your data quality? What steps or strategies do you have in place to monitor and ensure data quality at your company? What tools do you use to clean your customer lists?
Please share your thoughts with us in the Comments section below!