1. CASE STUDY
RegistrationConnect
MAJOR RETAILER GAINS 5X LIFT IN SUBSCRIBER VALUE BY
TARGETING THEIR IDEAL CUSTOMERS
The Challenge
A large Retailer tasked with aggressive goals to acquire new email subscribers employed co-registration as a tactic to
grow their subscriber list. However, they found that the new co-registration subscribers had lower than expected email en-
gagement and low buyer conversions. In order to better allocate their investments, they needed to understand why and
how to improve.
The Solution FREQUENT BUYER SEGMENT COMPARISONS
Using the Connection Engine platform, they Co-registration Organic
were able to compare attributes of their co-
30%
registration subscribers against their organic
subscribers, and quickly found their profiles 25%
didn’t match.
The co-registration subscribers had lower in- 14% 14%
13%
comes and concentrated in different geographic 11% 11%
regions compared to their organic subscribers. 7% 8%
6%
4%
Beyond the basic demographics, the two 3%
categories had completely different purchas-
Corporate Hiking &
ing tendencies. General subscribers favored Attire Fitness Camping Hunting Senior
Fashions Fishing
categories such as corporate attire, fitness,
and hiking, while the co-registration subscribers
were into hunting, fishing and senior fashions.
To help better identify the Retailer’s ideal customer, Connection Engine built a predictive model that leveraged comprehensive data
and advanced analytics to build a robust profile of their best customers.
The Result SUBSCRIBER PERFORMANCE COMPARISON
RegistrationConnect vs. Leading Coreg Provider
The modeling revealed that their typical organic subscriber had the following
characteristics: higher net worth, purchased frequently online, was a heavy
RegistrationConnect Leading Coreg Provider
shopper in corporate apparel, skewed over age 50, were more likely to use
an American Express card, and over concentrated in the Northeast. Using
6.0
this data, RegistrationConnect created a targeted co-registration campaign aimed 5.0x
5.0
ONLY at subscribers that fit well against their ideal customer profile. This
assured that only the people that met those specific characteristics would 4.0
be invited to subscribe to their list. 3.0
2.8x
2.0
The result was a dramatic increase in key performance metrics. First, these 2.2x
new subscribers were more engaged with the client’s email programs. 1.0
Key email metrics of opens and clicks were up 2.2x and 2.8x respectively. 0.0
Open Click Conversion
But more importantly, these targeted subscribers converted to purchasers five Rate Rate Rate
times more often.
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