The Science Behind Doing More with Data
(Data Science Blog Series, part 2)

This blog is the second article in our AutoAlert Data Scientist editorial series.

This series provides key data science terms and important uses in automotive software.

This builds on blog one’s crash course in data-related buzzwords and builds upon the leading-edge technological capabilities of doing more with data.

But how?

Over the past fifty years, the widespread digitization of data has turned simple data storage into an infinite source of additional insights.

Instead of storing all records of customers’ vehicle purchase information in a dealer management system (DMS), this historical data is used to generate leads for future purposes.

Our data can help calculate which previous customers are eligible for a trade-in upgrade with a minimal payment walk.

The number of questions asked, answered, analyzed, and reported by strategically storing and querying data is staggering. Descriptive analytics is the term to describe this process.

However, that is not the limit. We are just getting warmed up! Can you tell we love data?

At AutoAlert, we can do more with data by using Predictive and Prescriptive Analytics.

Instead of describing patterns in the data, we can use the patterns to predict future events and recommend actions to take.

Predictive and Prescriptive Analytics involves formulating business questions and decisions in the language of mathematics and leveraging the exponential growth of computing power to solve complex equations describing the behavior of many data points.

For Example

• When looking through previous customers to generate leads, it’s more effective to consider many factors than just looking at one at a time. (i.e., if customer A has “this” and “this” true). Rule-based categorizations and reporting can indicate increased buy rates for each individual factor but cannot consider every possible combination of all aspects.
• Instead, we can write a mathematical equation representing the relationship between each factor and the buy rate, then use computing resources to solve for a model that best fits existing data points.
• Finally, we use the model to rank our current customers in terms of the likelihood of purchasing a vehicle today, such as in AutoAlert’s Customer Buying Predictor Ranked Scores.

Data mining is a general term that refers to turning stored data into actionable insights.

The mining analogy is helpful, but the term is a bit misleading. It is like calling the extraction of valuable minerals “earth mining” as opposed to the more familiar terms “copper mining” or “gold mining.”

With data mining, we are mining through data in search of actionable insights or knowledge utilizing an extensive range of techniques.

The concept of mining also requires intelligence; random processes will never be as efficient at finding actionable insights in vast amounts of data as intelligently directed searches.

Data mining efforts are translated into mathematical equations and solved programmatically. As a result, some of the intellectual steps of data mining are offloaded to computers and machines. Data mining, therefore, quickly begins to overlap with another buzzword.

Descriptive analytics, predictive and prescriptive analytics, and data mining used by AutoAlert have continually revolutionized the dealership-customer relationship.

AutoAlert seamlessly puts all this data science into practical and easy-to-use tools and workflows to drive more sales to your dealership.

AutoAlert makes data easy to use and accessible from anywhere, creating direct opportunities for meaningful connections and seamless online and offline experiences.

As the industry continues to experience the benefits of incorporating AI into their dealerships, we expect this trend to continue as the new normal.

AutoAlert AI-driven platforms offer comprehensive solutions for every customer-facing dealer department, including service-to-sales, data mining, marketing, employee engagement, and customer experience.

AI assists dealerships of every size advance growth at an increased rate than experienced in years past, ultimately leading to greater profits.

Innovative AI is only as good as humans knowing how to use it. To get your teams started, AutoAlert offers the most robust, award-winning employee training program in the industry – offered by real humans.