How the auto aftermarket ecosystem peers into the future with day-by-day mobility data

This article is the second in a series about how companies from diverse industries can leverage driving data as a service to inform business decisions and increase revenue.

People are driving differently these days. Auto aftermarket businesses that have traditionally relied on historical patterns or months-old data are turning to more advanced data analysis to understand driving behaviors and anticipate inventory and service needs.

How so? Let’s take a look at a few service areas for real-world examples:

• Tire distributors are looking at miles traveled and hard braking to anticipate tire repair and replacement needs.
• Auto body, mechanical, and glass repair shops are looking at hard braking and collision data to predict an increase in service requests.
• Oil change businesses are looking not only at miles traveled, but also to where those miles originated and ended, and whether the drivers are locals or passing through. This helps businesses anticipate oil change requests and predict which locations will be most profitable, and further, better predict what key products to have in stock to best serve customer demand.
• Brake repair shops are evaluating not only miles traveled but also the frequency of trips to understand shifts in driving behaviors. For example, if local consumers start driving farther distances at higher speeds, there may be less brake wear and vice versa.
• Auto parts stores are turning to miles traveled to understand that, for example, although daily commuting has decreased, longer trips may have increased. What’s more, with miles driven they can anticipate which counties will need more (or fewer) stores.

Municipalities are also capitalizing on this new source of driving data. They are using it to understand trouble spots that need attention, such as blind corners that cause hard braking, communities with higher distracted driving, or intersections with a high percentage of collisions.

Fact: Driving data is highly predictive of consumer need

Auto aftermarket organizations understand that driving data is predictive. A spike in miles traveled from a certain county, for example, can help businesses understand that in a week or so, tires will need replacing, engines will need maintenance, and glass will need repairing.

But that advance notice is greatly diminished if the data is limited in scope or dated. Sure, companies can download average miles driven from the Department of Transportation, but it’s likely 9 weeks old and only pulled from cameras on freeways. That’s a narrow and dated view of what’s happening on the roads.

How do we know that recent driving data — within 24 hours — is highly predictive of auto aftermarket customer opportunities? We tested it. For various businesses, Arity researchers pulled their “customer opportunities” data count for a specific period of time and for a specific geographic location, such as a county.

When overlaid with Arity’s Driving Events and Vehicle Miles Traveled data for those same locations and time period, we found that, again and again, specific driving activities highly correlated with auto aftermarket consumer demand. For example, a 2% increase in collisions led to a 2% increase in customer inquiries.

What’s more, with a high degree of consistency and accuracy, we could pinpoint the lag time between the activity and the inquiry. In other words, these companies could “see” into the future by days, sometimes more than a week, in advance with access to Arity’s database of driving data, arguably one of the largest and deepest database of driving data.

Layer miles traveled with other driving events, such as hard braking and collisions, and you have a multi-faceted view of driving behaviors specific to the locations where auto aftermarket companies are focusing their efforts.

Driving data services solve long-standing business challenges

If the old methods of predicting auto aftermarket needs produced murky results at best, day-by-day driving data is like a crystal ball. Here are just a few of the business challenges that recent driving data and insights can help solve for auto aftermarket companies:

• Selecting the most profitable site locations
• Predicting manufacturing and inventory needs
• Avoiding missed opportunities, such as when backorders or long wait times drive customers to the competition
• Staffing up ahead of an anticipated rush
• Creating timely marketing campaigns
• Forecasting revenue
• Realizing factors causing lost opportunities, such as above market pricing

How to select the best auto aftermarket driving data services solution

From manufacturing and warehousing to distribution and retail, companies in the auto aftermarket ecosystem can benefit from multi-faceted driving event and miles traveled data and insights. But not all data services are created equal.

When looking for a driving data services solution, organizations need:

• Day by day data, not months old data
• Driving behaviors from all types of roads, not only freeways or expressways
• Nationwide data, as well as the ability to select by state, county, or group of counties
• An understanding that out of miles driven in a given area, how many people are residents and how many are just passing through
• Driving behavior data they can overlay with business data to find correlations and predict lag time
• Data beyond miles traveled such as number of trips, hard braking, collisions, and other types of driving behavior data

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