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Exploit The B2b Potential And Target the User Behind The Fleet Centre

Thomas Ulbrich
22 Nov 2022
capgemini-invent

The Future of CRM

In our recently published blog article on CRM for fleet customers, we outlined the importance of CRM in B2B for automotive manufacturers, especially for white fleets. In terms of white fleets, purchases are done by the fleet manager for the whole company, including pool and multipurpose vehicles, meaning the cars don’t belong to a specific user.

In this post, we would like to focus on black fleets, which account for a significant proportion of nearly two-thirds of fleet users that enjoy a high degree of freedom in their choice of vehicle. A decisive persona in this context is the so-called User Chooser. A User Chooser is an employee with a car allowance that grants the choice of different brands and models within the limits of a company’s specific car policy.

The User Chooser: Valuable but unknown

Figure 1: white vs. black fleets

Within the framework of the respective company’s car policy, this customer has permission to select and configure the car to be ordered – often within a leasing model with two-to-four-year terms. Accordingly, User Choosers represent a very attractive customer segment. This is primarily because of the short leasing cycles, elevated purchasing power, and a high degree of freedom in choosing and configuring the desired vehicle. The high level of freedom challenges car manufacturers, but also offers great potential to reach and bind these customers.

Looking ahead, the analysis and inclusion of User Choosers into an OEM’s CRM strategy can have a significant impact on the achievement of corporate sales revenue goals. Therefore, User Choosers must be considered during the entire journey. OEMs should try as hard as possible to detect their needs and wishes to use the potential and buying power of this segment.

While OEMs have made great progress in achieving the often-claimed 360-degree view on private customers, the User Chooser remains relatively unknown and is therefore poorly taken into consideration for CRM activities. To generate the needed information on User Choosers and integrate it into CRM activities in a targeted manner, we at Capgemini Invent postulate the following hypothesis: It is essential for OEMs In the future to define and execute B2B-specific CRM that targets the individual user behind the buying center. This is done by collecting users’ personal data and connecting it to the surrounding organization.

In this blog post, we will first outline how OEMs can unlock the B2B User Chooser potential and thereby enable concrete CRM use cases to exploit the potential.

Unlock the B2B potential – Identification, Elaboration, and Execution

1. Data generation – Define the needed information sources

The biggest challenge is the User Chooser identification. To overcome this, personal and professional information must be combined:

  • Self-shared information by the User Chooser via “My Car” apps, such as myAudi, Mercedes me or MyBMW
  • Web-based information given during offer requests and vehicle configurations
  • Smart fleet data through connected fleet management systems, as outlined in our blog post, CRM for fleet customers
  • Collected information through physical touchpoints, such as workshop visits and showroom events
Figure 2: identification phase

Generate User Chooser insights through the “My Car” application and web touchpoints

Audi, BMW, Mercedes, and other car manufacturers aim to have more than 80% of their customers using “My Car” applications, such as Mercedes me or My BMW. By linking the vehicle to a customer profile, the customer shares information with the manufacturer – only with corresponding consent of course. As soon as User Choosers connect a vehicle that belongs to a company with their profile, the unknown users behind a leasing contract with a certain company become known customers. As a result, they become a customer that can be targeted with CRM activities. Making customers link their profile to a vehicle is for many reasons a key challenge for today’s OEM sales and marketing departments. It becomes even more important when looking at it from the perspective of making unknow B2B decision makers known.

Therefore, using “My Car” applications should be further incentivized and enhanced by corporate contexts to extend the set of information beyond private matters.

Web interactions are another source of information. These can also be used to enrich the data generated by the “My Car” applications. OEM homepages offer useful points of contact. Information can be generated and integrated into the CRM – system during vehicle configuration or when requesting a personal offer. Other touchpoints include channels such as social media and communities.

The objective is to generate a holistic picture and to collect personal information (e.g., age, address, and hobbies across all sources).

Integrate Smart Fleet Data

Integrating smart fleet data, as outlined in our first B2B blog post, can enhance the needed information landscape. The respective data can provide insight into the financial situation as well as the potential vehicle preferences of the User Chooser. 

In the first place, smart fleet data capturing the leasing contract provides insight regarding financial framework conditions. For example, the selected vehicle segment can already provide indications of the User Chooser’s current job position and seniority level.

In addition, the leasing contract and the restrictions on the car policy imposed by the company provide guidelines for OEMs when preparing offers for User Choosers. Specifically, this involves a degree of freedom in segment selection, OEM of choice, and the specified budget. The result is a concrete picture of the potential vehicles and services that can be offered to the customer.

Lastly, the fleet composition provides further guidelines to target User Choosers more precisely. The cross-section of the fleet composition, combined with job information, provides evidence on the single customer and draws conclusions on the User Chooser.

Request and integrate information during physical touchpoints

Physical touchpoints with User Choosers also offer great potential to close the information gaps. This can range from the initial handover at a dealership to workshop visits and driving events. The added value is gained through the insight into the geographic circumstances and the preferred dealer and potentially allocates to the current company the User Chooser is working for.

For instance, dealer and workshop visits can be used to narrow down the location and the User Chooser’s radius of movement. In this way, the personal profile of the customer can be enriched, but also point-of-interest can be considered for further cross- and upsell. To address customers in a targeted and customer-centric manner, it is essential to know their preferences. This already starts with my preferred dealer. In the future, configured vehicles within retention offers can be suggested for a test drive at the dealer of choice. For this reason, the physical touchpoints must be integrated into the CRM ecosystem established and used by an OEM.

2. Identification and elaboration – data connect, predictive analytics, and customized next-best offerings

Besides the generation of data, the effective combination of the collected information as well as the derivation of insights and next-best offers represents a major challenge. However, it is necessary in order to make the unknown known and unlock the potential of the User-Chooser-specific CRM. To overcome the challenge, we recommend the following steps.  

First, the data generated across all the above-mentioned data touchpoints must be stored centrally and connected. In the process, personal information, vehicle information, and contractual information are merged in order to generate an ideally complete User-Chooser profile.

Second, by evaluating the generated profiles and matching them with potential vehicles and services, targeted next-best offers can be integrated into CRM nurturing activities. It, therefore, requires the adaption of software able to perform predictive analytics functionalities. This is necessary to handle the amount of data and to derive specific use cases, ideally integrated into one CRM software.

3. Execution – create differentiating experiences for the User Chooser

Once the personal and corporate information of the User Chooser has been collected and evaluated, the next step is to transform the findings into the right approaches. In the following section, the focus is on two specific use cases – firstly, with the aim of triggering customer retention to increase customer loyalty; and secondly, to leverage cross-selling during the leasing period.

Customized next-best retention offer

The optimized next-best retention offer captures customer, vehicle, and company information to provide an attractive repurchase offer and thus extend the leasing cycle. In this way, OEMs can tie customers to their own brand and increase loyalty. The retention offer makes use of the previously defined steps on data collection and predictive modeling that calculates the right time to present an offer for the next vehicle. This is tailored to the customers’ needs and fleet-relevant specifications. Certain aspects, such as the car policy and the degree of freedom in the selection options, determine the framework conditions. This is especially true for User Choosers, for whom the experience can be enhanced when providing offers for pre-configured vehicles. The pre-configuration already includes certain configuration options and connected service packages that can be traced back to the User Chooser.

When such personal information as age, address, marital status, and income of the User Chooser is available, it can be complemented by additional data generated through digital interactions. For example, social media activity can be used to determine whether or not the customer is interested in outdoor activities like skiing. Such insights can be validated by the range of movement of the respective User Chooser. In this context, booked workshop dates, hotel stays, and other physical touchpoints also provide valuable insights. The case becomes even more precise when the vehicle is not only used by the User Chooser, but also by other family members. These interactions (e.g., through additional phone-to-vehicle connections) provide further clues when designing the optimized retention offer.

Now, smart fleet data can be used to determine the vehicle preferences of customers with similar job titles, income, and seniority levels. With this information, a concrete picture emerges. If this information is complemented with the My Car ID log-in, the vehicle can be assigned even more clearly. For instance, let’s assume the User Chooser has borrowed an SUV from a colleague to go on a weekend trip with the family. In the last step, the scope of action is restricted by the company car policy. The result could be, for example, an SUV offer that fits the user’s hobbies and family situation. Finally, our unknown customer becomes a known User Chooser. In the next step, the local preferences can again be included to offer a possible test drive at the preferred dealer to complete the journey.

This offer does not only refer to the subsequent period after the leasing cycle. In this way, certain vehicles from similar car segments can already be offered during the cycle. For example, an offer can be made during a customer’s workshop visit, as a replacement vehicle, to test possible interest and matching for the subsequent offer.

The advantage here is the optimization of cumbersome vehicle configurations, considering the trend is towards vehicles configured in just a few clicks.  

Need-based cross-selling offerings

Further benefits of the integration of personal and professional data are achieved through the creation of need-based cross-selling offers within the leasing cycle. This potential can be exploited by targeted nurturing with customized offers.

Based on the generated fleet insights as well as personal preferences, customer needs can be identified in a targeted manner. The development of product usage is moving away from traditional ownership and toward need-based use. In this context, intelligent products, such as Functions-on-Demand and subscription models, are moving into the foreground. This offers great potential for OEMs and for their corporate customers. At the same time, some adjustments to the CRM alignment are necessary.

Some conclusions can be drawn when a customer has the technical prerequisites for autonomous driving of L2. The hardware can potentially be activated by targeted nurturing if the offer is attractive enough and the customer’s interest can be tracked precisely. In the process, the profile of the User Chooser is reused and complemented based on smart fleet data in order to derive predictive offerings. For example, if the autonomous driving feature is used by colleagues with similar characteristics, such as job title, department, and willingness to travel, this might be an indication to consider an offer. If the respective vehicle of the User Chooser is frequently used for long-distance trips, the predictive assumptions can be validated. Based on this information, a possible interest in autonomous driving can be derived. In the next step, a special offer is to be made at attractive conditions. The offer can be directly placed via in-car notifications with a potential over-the-air activation to guarantee the most convenient experience. Further goodies, such as business packages to work in the vehicle or a massage functionality, can complement the offering. Thus, we can optimally exploit the cross-selling potential and promote customer loyalty.

By combining intelligent next-best offers and proactive recommendations, User-Chooser-specific CRM can be taken to the next level. To start in time, the following basic building blocks should be considered, all of which are discussed in the following chapter.

Laying the foundation early is key to success:

To build groundbreaking User-Chooser use cases, we recommend that you start putting these basic building blocks in place today:

Figure 3: Key success factors for the Future of CRM

CRM SERVICE HUB: Establish a CRM Service Hub, as outlined in the first blog series, to combine and process data centrally and be able to apply smart analytics to personalize communications and offerings.

B2B AND B2C DATA INTEGRATION: Integrate the private and corporate data of User Choosers, specifically their profiles and overall online behavior.

PREDICTIVE ANALYTICS:  Apply predictive analytics to target User Choosers with the right offerings at the right time based on predictive retention models in order to leverage cross- and upsell potentials.

CONSUMERIZED B2B JOURNEYS: Personalized journeys, ranging from community-building activities to offer structure.

What is your view on the relevance? Which priorities and additional use cases do you see? We look forward to hearing your thoughts!

This blog has been co-authored by Thomas Ulbrich, Christopher Rose, Alexander Stotz, and Kamil Kilic. Please get in touch if you have questions or need further information. We look forward to exchanging ideas on this particularly current topic.

Our Expert

Thomas Ulbrich

Director,Customer Transformation,Capgemini Invent