How to Improve Retention with Discount Coupons?
What makes unique codes unique?
Unique codes attached to particular customers help to define buying patterns amongst your audience. To manage one-off codes, your system needs to generate unique sequences of coupons or gift cards, which delivered to customers, become automatically assigned to their profiles. The most important thing is to be enabled to store and track data about codes and their owners. Having such an infrastructure in place enables you to create unique incentives in bulk and track individual order histories:
- Each unique code tells only one story and defines the individual preferences of your clients.
- Later on, tracked data and order histories help you to create personalized and well-targeted promotions.
- One-off codes are a guarantee of fraud control and reduction of misuses.
- They enable you to run exclusive offers, e.g., discounts for the most loyal customers.
- In case of any troubleshooting, each unique code can be quickly spotted and investigated.
- Bulk unique codes are perfect to test different promotional ideas and to figure out a strategy that works for your business.
Let’s see how you can leverage such campaigns to work on improving customer retention. I want to engage one-time buyers to repurchase using unique codes with a discount for a second order. At this point, I have no idea what coupon should be offered to make it work for my audience. Keeping that in mind, let’s test two different discounts equipped with unique codes to track which idea performs better.
Fire off a unique coupon codes campaign
First of all, new customers should get their codes automatically after the first purchase is made. It’s good to have a scalable solution from the very beginning when it’s hard to predict what kind of traffic you’ll need to handle.
Secondly, what kind of discounts should be tested in the first place? There are no universal rules of leading customers to a second purchase, but we recommend that you check around and find out what your competition or brands with similar dynamics of sales, are offering.
In this post, let’s test the following coupon campaigns:
- Bulk unique coupons with 15% discount valid for a month.
- Bulk unique coupons with 10% off valid for three days.
This a/b test shows how the expiration date influences the effectiveness of a discount. A time frame is just one of the many parameters you can, and should, test before you decide to fire off a full-blown campaign. A one-time a/b test should examine one or a maximum of two variables at once. It can be a discount amount or type, minimum order value, or product-specific configurations. Although dividing discount tests into small parts requires more time to measure all promotion properties, it is the only way to define the impact of each attribute on discount performance.
Keeping that in mind, in the described example, both campaigns have a different discount value and expiration date, but both apply to all products without additional rules. When the discount id already defined, it’s also good to check if whether or not adding a minimum order value will increase overall performance by increasing average order volume.
Requirements for launching a coupon campaign
Let’s sum up all things required to consider before launching a bulk unique codes campaign:
- What’s your goal? (e.g., increase the amount of repurchases).
- What discounts to test? (Check what offers your competition).
- What limits should be attached to codes to make it safe for my budget (like minimum order value for an amount discount)?
Quick Tip: When you’d like to upsell, it is a good (and common) tactic to set the minimum order value a little bit higher than your average order amount.
- How will I deliver the codes? (No matter what channels fit your customers, we strongly recommend that you invest in an automatic coupon workflow.)
- How will I divide my new customers? (You need two segments of new customers to test two different discounts.)
Our goal is to define a universal discount offered to every one-time client. New customers should be divided into two similar groups to make tests reliable. For example, you can create separate customer segments based on the date of the first order:
- Group A: an order in the 1st two weeks of a month.
- Group B: an order in the 3rd and 4th weeks of a month.
Customers from a Group A get a one-month offer with 15% off everything, and customers from a Group B receive 10% off if their second order is made within three days from the codes’ delivery.
Measuring coupon campaign results
When campaigns expire, it’s time for summing up results. Thanks to bulk unique codes, you can quickly sum up a number of new customers and count how many of them redeemed a code.
As you can see, customers who were offered 15% discount utilized 28% of delivered codes. In Group B, 35% placed a second order with their unique coupon. Results show that although Group A got a better offer, they utilized fewer codes than the group with a lower discount.
One of the most frequent phenomena associated with shopping behavior is a desire to avoid anticipated regrets. It is already proven that consumers find deals much more attractive when incentives are limited in time or available amount.
In the next step, I’d measure if a 15% discount offered in short-time period could sharpen up these metrics. Likewise, by dividing new customers into two representative groups, I could test flash-sale with 15% off and an additional configuration like the same 15% discount with a minimum order value.
Quick Tip: Remember, you cannot discount everything. Moreover, raising coupon value could bring more traffic, but it doesn’t mean your sales results will grow. Set your discount amount on a level that is safe for your budget, no matter the scale, and try to sharpen up discount performance using additional tactics like short expiration dates, up- or cross-selling.
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