The New Zealand Automobile Association increases response rates and savings with SAS®

The New Zealand Automobile Association Inc. (AA) has taken an analytical approach to optimizing the customer and membership potential of its overall operations and the results – in a relatively short time – have been impressive. Direct marketing costs have been dramatically reduced; marketing response rates doubled; the organization's customer contact center has achieved major efficiencies; customer satisfaction has measurably improved; and operational cost savings have flowed throughout the organization.

The AA was founded more than 100 years ago and was established to provide breakdown assistance and related services for its members. The AA is now a multifaceted enterprise offering motoring and accommodation advice, maps, insurance (including general and life insurance), and other financial services. The AA is also a strong advocate for motorists within New Zealand's commercial transport sector and government.

Applying analytics for smarter decision making
In late 2007, the AA set out to increase market share for its insurance business. To achieve this goal, the company first needed to establish member and customer transaction data sets to enable analysis for better informed decision making by the marketing executives.

A Customer Insight Team was formed under the leadership of Mark McCabe, AA's Senior Marketing Manager. As he explains, "Before November 2007 we had no real analysis of customer behavior. We had records of our insurance policy holders and the road service activity reports and information about our more than 1.2 million members, but nothing in the form of market analytics. There was no market analysis resource and no facility to cross-sell to our base."

The data available at that time was in different formats and resided in a number of different silos. Marketing data was separate from roadside assistance data, insurance data was separate from other financial data and so on. In addition, data also needed to be imported from census demographics, land title records, postal address lists and other sources.

In considering various possible approaches, the team decided upon a trial examination of SAS analytical tools, and this trial quickly proved SAS software's suitability as the foundation for the company's future marketing decision making. In parallel with the trial period, SAS New Zealand strategic implementation partner Offlode Limited was engaged to conduct the data discovery process and carry out the necessary data mining.

Reduced costs, increased response rates
McCabe said the first part of the business to be addressed with the new marketing analysis capability was the life insurance arm: AA Life. "We were looking purely at marketing efficiencies at that stage. AA Life had been sending out some 400,000 mailing packs a year in what was a very simple approach to making targeted selections. There was no business intelligence applied in terms of who to make which offers to, and when and how. We didn't have the capacity to focus on, say, the more profitable targets or those most at risk of cancelling their business with us because we had no real picture of who or where they were.

"We set out to work with the marketers to improve efficiencies, to cut out the loss-making aspects of the campaigns and apply behavioral and other analysis to focus specific messages only on the people who might be receptive to them," McCabe says.

Equipped with its full SAS license – the AA had not previously used SAS – McCabe's team set about building a propensity model for the life insurance campaigns by taking in data from across the whole AA group and third-party sources. This included AA's membership data, road service usage data, and records sourced from the life and general insurance operations.

McCabe explains, "This laid the foundation for identifying what types of people ought to be good prospective new customers for AA Life. The model was developed from those early beginnings to where – six months down the track – we had enough experience to be able to identify the cost break-even point for the design and targeting of mailing campaigns. The end result was that we were able to reduce our mailing volumes by 40 percent while, at the same time, achieving greater success."

Depending on the campaign, response rates have improved by more than 50 percent and, in many cases, have doubled.

SAS® produces benefits throughout the organization
Aside from the very impressive marketing benefit, McCabe said the organization has also enjoyed operational benefits, adding, "With structured analysis, we are not throwing as many applications at the marketing operation. Our people are not spending processing time that may or may not produce results. So we have made a big operational saving as well as a marketing saving."

AA Life's mailing campaigns are supplemented with telephone follow-up by the organization's customer contact center, and here, too, a better understanding of customer behavior has helped lower overall marketing expenses. With fewer mailers to follow up, the AA's contact center needed fewer agents to make calls, and the cost of running the center was reduced by 20 percent. Further savings were enjoyed through a reduction in the use of third-party telemarketing services.

In addition, notes McCabe, "Customer satisfaction levels and our image in the community will have improved, too." Previously, AA agents were making calls to people who had been poor targets for the mail campaigns and who could thus have been alienated by the unwelcome phone call.

Summarizing the New Zealand Automobile Association's experience of being able to exploit customer intelligence to date, McCabe says, "It is fair to say that the benefits of using SAS have flowed right through the organization" and while he declined to quantify those benefits in money-terms, he was prepared to concede that they amounted to "hundreds of thousands of dollars" a year.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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