Most dealerships made precise decisions about model sales and vehicle acquisitions to ensure that their inventory met the needs of their customers. The data collected during these processes can be confusing, hard to understand and use consistently. Many dealerships attempt to create spreadsheets to manage their data, but this can be very time-consuming. Thousands of dealership hours are wasted analyzing data that needs more consistency and standardization.
Importance of Data Analytics for Car Dealers
Today’s car dealerships face dynamic challenges, including increased competition, volatility, and cost pressure. In addition, they face inventory shortages and diminished loyalty among consumers. In 2021, these challenges were expected to persist, but a slew of new opportunities will temper them. Auto dealers can anticipate and manage these challenges with the right tools and data.
Predictive analytics help car dealers better understand their customer base. This data analytics for car dealers can be used to optimize their marketing messages. The data can be generated from several sources, including internal dealership systems and information from external industry sources. The data can also help them retain and lure back customers who have lapsed.
Data visualization can also help car dealerships better understand their customers’ preferences and requirements. Automotive dealerships collect a large volume of customer data. But because these data are stored in disparate databases, they can be challenging to use effectively. Data visualization allows dealership management to see the data in a centralized manner and make better, more profitable decisions.
Tools Available to Help Build Customer Profiles
A detailed customer profile can make all the difference in your marketing and sales campaigns. Whether you are trying to attract new customers or improve your customer service, a detailed profile will help you to know who you are dealing with and what type of products and services will best meet their needs.
Several types of software are available to help you build a customer profile. First, you need to gather the customer’s contact data. CRM (Customer Relationship Management) software keeps track of this data and can provide basic information about a customer. Free CRM platforms like HubSpot CRM can help you build a comprehensive customer profile.
Customer profiling is identifying traits that make a customer likely to purchase. This includes demographics, buying habits, and other information. This allows businesses to build scalable strategies, prioritize campaigns, and customize their offerings. It also opens avenues for deeper exploration of your customers’ needs. However, beware, a customer profile is different from an ideal customer. Identifying this ideal customer profile can be done through surveys, market research, or even by analyzing historical CRM data to get demographic details about your customer base.
Emerging Markets Offer the Opportunity to Build Customer Profiles.
Consumers in emerging markets are not typically the most demanding consumers. They are sensible and consider various factors, including price, to make their buying decisions. In addition, these consumers show considerable price sensitivity in different ways, including meticulously tracking price benchmarks. Moreover, they tend to display considerable self-restraint, a trait that makes them less likely to buy things on credit.
While emerging consumers are generally characterized as “yuppies” and “buppies,” the reality is much more complex. They are often grouped into “popular classes” or “working-class” categories. For example, many low-income consumers in Latin America are wrongly grouped into the “blue-collar” and “working-class” segments. Instead, they are best understood as members of a distinct class with distinct needs and habits.
Consumers in emerging markets are more loyal to specific brands than others. Although they are more willing to try new products, they are also more likely to stick with a select few brands. This means emerging consumers are more likely to choose high-quality products over low-cost brands with little to no brand recognition.