Based on 2018 trends*

We all tend to theorize about seasonality in the auto industry – which months are the worst for sales? When do we get the best leads? What are the ideal days for walk-ins? But the problem with speculation is exactly that – it’s merely speculation. Many of the common truths regarding seasonality are based on anecdotal evidence, intuition, and guesswork. And while intuition is important, hard facts and statistics can provide better insight, and allow dealerships to plan ahead based on the cumulative experience of others. 

In this report, we take a deep dive into the seasonality of leads and sales in the auto industry. We’ll examine weekly, monthly, and yearly trends based on approximately 100 dealerships across America– representing over 2,282,000 leads and 339,900 sales. 

Weekly seasonality

In the chart below, you will see the number of sales per day of the week. There is a clear pattern: the middle of the week seems pretty consistent, while Saturday is the absolute strongest, and Sunday the hardest day for sales.

To determine why these differences might exist, we can take a closer look at two of the most prominent lead-types – internet and showroom, and how leads of those types are distributed throughout the week. 

The light blue columns, representing internet leads, have a pattern similar to the chart showing all leads aggregated: Sunday is the weakest day, and all other days are consistent. On the other hand, the darker blue columns representing showroom leads, have a similar pattern to the graph of all sales: Sunday is the weakest day and Saturday is by far the best. 

This breakdown makes sense, as showroom leads represent people that came into the dealership. Thus, the more people that came into the store, the more sales would be closed. Saturday is therefore both the day with the most showroom leads, as well as sales. 

Finally, the graph below summarizes the distribution of sales between weekdays, and Saturday and Sunday. More than 25% of cars are sold over the weekend, mainly on Saturdays. The rest is distributed over the remaining five weekdays.

Monthly seasonality 

After exploring weekly seasonality, we zoom out to monthly patterns in the data. The first chart below shows the average number of sales per day of the month per average dealership. The trends seem to be that sales are roughly the same for the first two weeks of the month,  and then increase towards the end of the month. This means that, in general, dealerships sell more cars in the second half, and especially in the last few days, of the month. 

This trend stands out even more in the graph below. Each section on the circle represents a day in the month; the thickness of the section represents how many sales were closed on each day. The graph shows a pretty constant increase in sales as the month approaches its end.

You might think sales spike towards the end of the month because customers know there are discounts to be had. But If that were the main reason, we’d see a correlating spike in leads in the last two weeks of each month. However, comparing leads to sales, this increasing pattern is much weaker. This means that the closing rate (sales per leads) towards the end of the month goes up, as opposed to the amount of leads.

Yearly seasonality 

In the graph below, each day of the year is one data point, representing the amount of sales per day (out of the total yearly sales). We can see that in the first and last months of the year, less cars are sold per day. We also see several outliers. For example, at the end of December there are two points with barely any sales: these are Christmas eve and day. Another outlier is around day the end of November, where many more cars are sold because of Black Friday.

In conclusion

Every industry has its dips and peaks. Acknowledging them, and preparing a gameplan in advance, is the key to overcoming seasonal dips. Tracking the performance of your marketing, advertising and sales efforts year-round will give you insight into your dealership’s unique seasonality, and help you improve operations across channels. 

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