Posted by Jon Berna on Oct 20, 2019 2:19:09 PM

Data analytics isn’t a recent innovation. What is different today is the amount of data at hand. Operational reports and market summaries in the eighties and nineties were valuable, but it wasn’t real-time. Ultimately, it was clunky and only a few data points were available. Today, we can gather and store significantly more information, opening new doors in marketing that were previously unavailable. But not every corner of commerce is using their data, their most valuable asset, to their advantage.


There are four widely-recognized levels of data analytics. By progressing along through the levels of analytics, businesses gain better insights into why things happened in the past. With the assistance of technology, you can be a leader at the top level of analytics, being able to predict what consumers will do in the future.

This top level is referred to as ‘prescriptive analytics.’ A simple example would be when your phone’s navigation system sends you a notification that it’s time to leave for work. This is based on the prediction of your behavior at certain times of the day, along with real-time data about traffic conditions on your route to work. Imagine if you could predict exactly when a customer’s car is due for maintenance, then serve them an ad with a reminder or coupon automatically. We can.

Let’s summarize each level of analytics to help describe where we’ve been and how we get you to the top.

Descriptive Analytics: What Happened

Descriptive Analytics is basic information about your dealership’s performance. For many today this includes historical data such as:

  • Sales by employee
  • Gross profit by inventory type or service offering
  • Website sessions/users by channel

While this is valuable information it only tells you what happened in the past, not what can happen in the future. It can help you make decisions on salesperson performance, products to keep in stock, which channel’s leads are most successful – but are you actually earning customers with what you do? In this instance, you don’t really know.

Diagnostic Analytics: Why it Happened

The next level of data analytics is the ability to diagnose, or help you understand why something occurred. This helps reveal the hidden relationships between metrics.  This requires advanced data preparation, statistical analysis and data sets that are connected across silos.

  • Determining the correct level of leads for the size of your team
  • Correlation of marketing engagement on leads
  • Establishing the impact active salespeople have on overall sales

Unfortunately, this is still a rear-view look at your business. Trying to look at what you did last quarter to decide on successful strategies for this quarter is living with one foot in the past.

Predictive Analytics: What Will Happen

Here’s where you start gaining an edge. Predictive analytics is the first phase of forward-looking insights into your data. By combining the first two levels of analytics and using predictive modeling, you can forecast future trends. This requires historic data like your web traffic and inventory history, along with the relationship data from diagnostic analytics. With full transparency of this information, automotive marketing analytics tools can provide benefits such as:

  • Predict sales for a rolling 6 months
  • Predict when previous customers will buy their next vehicle
  • Predict how quickly you will sell each vehicle in inventory
  • Predict when each customer is due for their next service visit

Less than 4% of dealerships are at this level of data analysis and marketing. We aim to change that. Numerous other retail industries are starting to leverage this technology to gain efficiencies in marketing. It’s time that automotive catches up.

Prescriptive Analytics: How can we make it happen

Only Driven Data customers are at this level.  Prescriptive Analytics comes from applying machine learning to the previous forms of analytics. Machine learning essentially recognizes patterns in data then uses those patterns to automatically react to similar conditions in the future.

How can you use prescriptive analytics to give you an edge:

  • Identify vehicles that are slow moving, establish prioritization in marketing them to turn them faster
  • Spend the least amount of money you need to hit your goals
  • Allocate your spend to the right groups of vehicles

This dynamic model allows dealerships to make real-time decisions to correct the course of a campaign at a moment’s notice, while allowing you to market to the right customer at the exact right time.

Prescriptive analytics isn’t about knowing where you have been, what happened in the past, or trying to forecast what your future will be like. It’s about taking the proactive steps necessary every day to keep your brand fresh and competitive in the market while maximizing your spend.

Using a holistic approach to your data, you can take the guesswork out of marketing decisions that lead to uncertain outcomes. To learn how to level up quickly with expert support, learn more about our work with automotive marketers at

Topics: Marketing, Product, Machine Learning

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