AAA Drives Customer Centricity With Savvy Data Use

Customer Experience
Customer Experience
The auto clubs federation is leveraging customer data to understand its millions of customers, allowing its 44 clubs to interact with their members in a more relevant way.
Silver: Customer Analytics

Business Boost: By leveraging customer analytics, the AAA's different clubs are able to have more relevant communications with their members, improving their experience.

Customers are very willing to share information about themselves to the brands they do business with. Savvy organizations are leveraging this data to help them deliver a better experience to their customers, allowing them to personalize their interactions.

The American Automotive Association (AAA) is committed to remaining a member-centric organization which not only provides safety, security, and peace of mind, but also anticipates the needs of its more than 53 million customers who are members of the federation's 44 affiliated auto clubs. The clubs are cognizant that in order to be successful, they need to leverage customer analytics to understand what its members require, and then respond to those needs before they ask.

However, some clubs were using simplistic customer analytics strategies and were relying on basic customer profiling. Despite hiring expensive teams of consultants and contracting third-party predictive models, the clubs weren't able to scale these initiatives and were struggling to optimize relationships. Further, while some clubs were very analytics-driven, others weren't as savvy. "We were missing opportunities to grow our business," notes Daniel Mathieux, director of the AAA's Member Relationship Management action center, which the AAA set up to help clubs with customer analytics initiatives. The action center had a four-pronged objective: Leverage national buying power of hardware, software, and market data; socialize best practices for marketing and analytics; provide customer analytics; and support clubs' membership relationship management and customer analytics initiatives.

The first task that the action center needed to master was creating a 360-degree view of AAA members through the aggregation of more than 2,500 attributes, including membership information, transactions, and demographics, with the aim of helping clubs predict member needs. In 2009 the action center implemented a predictive analytics solution by KXEN, allowing AAA to quickly create and evolve analytics models. The center's team of marketing analysts works with each individual club to create a plan and then use the automated system to deliver analytics to optimize club cross-sell, acquisition, and retention campaigns.

Increased customer visibility means that clubs know the characteristics of customers who are likely to respond to a given offer or can identify members at risk of churn. Mathieux notes that while the AAA has a renewal rate in the upper 80s, new members are the most likely to churn but their propensity to renew their membership increases exponentially when they use one of the products offered by AAA. The action center's job revolves around helping clubs find products that resonate with individual customers to increase their likelihood of making a purchase and as a result reduce the risk of churn.

Data is being used to listen to members, helping different clubs tweak their communications throughout the year, focusing on what different customer segments find most appealing. For example, Mathieux explains, some customers are more money conscious and the club can engage them in a conversation about the savings they can get on different products, like a cruise.

The federation was quick to see results. After applying customer analytics to travel campaigns for one year, one particular club reported a 42 percent year-over-year increase in sales. Individual clubs believe the campaigns have contributed to substantial incremental sales across the AAA's network, with some of the larger clubs increasing their sales by millions of dollars, revenue which would otherwise have been lost.

Further, a forecasting initiative uses customer road service history to predict call counts and the types of vehicles needed at a facility, allowing the AAA to be more agile in responding to roadside assistance requests. The federation has achieved a forecast accuracy of 89.5 percent, leading to cost savings, partner loyalty, and increased member satisfaction. "Our goal is to maintain satisfaction levels in the 80s and 90s and the biggest contributor is how quickly we can get there following a roadside assistance request," Mathieux notes.

Seeing the strength of predictive analytics and the successes achieved, individual clubs have been requesting more analytics insights from the action center, which has grown from five people when it first started in 1998 to a 30-strong team as a result of increased demand from clubs. In fact, the center uses predictive models to help clubs serving 93 percent of the AAA's membership optimize marketing campaigns.

Membership renewal rates have also increased slightly, from 87.9 percent in 2009 to 88.2 percent in 2012.

Predictive analytics is used in campaigns within clubs' call centers, stores, and websites, as well as over email, text messages, and direct mail. The plan is to extend these successes to social channels, which are currently being developed by a number of clubs. This strategy will be instrumental in helping clubs communicate with their members wherever they are.

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