Predictive Modeling Decreases Acquisition Cost per Response by 37%
Introduction
The deregulation of electricity and natural gas markets has created opportunities for retail energy suppliers to find and win new customers in very competitive markets. Pel Hughes’ experience helping our service provider clients in many of the 17 states with deregulated electricity and some of the 22 states with at least a partial deregulation of gas service has given us a broad perspective on what works best to generate new customers and retain existing ones.
This case study focuses on best practices of a deregulated electricity service provider in one of these markets to effectively use direct mail to generate customer calls and PURL web visits (personalized URL landing pages) to self-enroll for service. Pel Hughes developed the predictive model in order to acquire targeted mail lists of the households most likely to respond to the campaign offers. Pel Hughes was not privy to the internal data for determining net enrollments.
Sourcing Pel Hughes to be responsible for contributing to the strategic planning & analysis, data & data analytics, print & mailing production services and real time reporting resulted in the production cost per response dropping from $61 before predictive modeling to $38 after predictive modeling.
Challenge
Before working with Pel Hughes, our client was experiencing challenges both large and small in their marketing efforts with previous direct marketing suppliers that understood production but didn’t know how to produce and execute a data driven campaign. Other internal issues were the lack of marketing data expertise and access to IT staff/systems. The lack of lead tracking from their direct marketing efforts kept them from accurately reporting metrics. Their frustration led to a meeting with USPS Business Development Representatives who in turn recommended consulting with Pel Hughes.
Our initial consultation with this large energy supplier allowed us to understand their current marketing efforts. After Pel Hughes explained how successful direct marketing programs are designed, produced and reported, the client engaged Pel Hughes to execute a customer acquisition campaign.
Control
One of the major improvements discussed was the importance of using data by developing a predictive model of the households most likely to respond to the offer; but because of the expedited schedule the client did not have time for Pel Hughes to develop a predictive model to target this initial campaign. The client requested a standard data list of credit-scored homeowners for Campaign 1 while Pel Hughes developed the predictive model for Campaign 2. A 3-way split was used to test for best offer and results showed minor differences. The quantity mailed for this initial campaign was 705,488.
Results
All responses were tracked by the Pel Hughes Campaign Dashboard including the 3-way split to test the offer. The mailing was a classic direct mail package of personalized letters; response lift notes inserted into full color #10 window envelopes with presort standard postage.
The shelf life of direct mail is often overlooked with responses still coming in 2-3 months after the last piece of mail was delivered in home. A satisfactory response of 3,937 inbound prospect calls to the client’s call center and 1,089 PURL hits for a total of 5,026 responses were recorded at a cost per response of $61.
Solution
The same basic program used in Campaign 1 was used for Campaign 2. The only significant difference was that the mail data was produced through a predictive model instead of the simple credit-scored homeowner list data used in Campaign 1. The quantity mailed for this second campaign was 999,252.
The predictive model used was a very sophisticated algorithm that uses thousands of consumer data points and was based on comparing the attributes of “Responders” vs. “Non-Responders” from client’s previous mailings. Data is then pulled from the list of prospects most likely to respond to future mailings.
Results
Responses got a 100% lift to 10,539 inbound prospect calls to the client’s call center and 1,147 PURL hits for a total of 11,686 responses at a cost of response of $38.34.
Benefits
Direct mail is still one of the most cost effective way to generate sales in deregulated energy markets with a proven cost of response of as little as $38 using the combination of predictive modeling, a decent offer and a historically powerful format. Direct mail has reach to 98% of U.S. households, is the media preference of 76% of U.S. households and a shelf life that extends months after the mail is delivered.
Other direct marketing strategies deployed by Pel Hughes to strengthen direct marketing campaigns include IP Targeted display ads, email/SMS, PURLs/GURLs, and image personalization.
