5 Ways Auto Parts Sellers can Increase Margins with Data Analytics

5 Ways Auto Parts Sellers can Increase Margins with Data Analytics

In 2022, if you’re not leveraging data analytics, you’re behind. But luckily, if you haven’t started yet, you’ve got plenty of opportunity to use your data to increase profits.

If you’re in the auto parts & accessories industry, there are barriers as we explored previously. But given the profit potential for becoming a data driven company, we think the juice is worth the squeeze. To get you started, this article will cover 5 areas you can apply data analytics in your car parts company.

Vendor Utilization

It’s a common scenario in the car parts business to source parts from many vendors. Whether you’re stocking inventory or dropshipping, you’ve likely run into scenarios where you work with multiple vendors who carry the exact same products.

In that case, you’ll need a strategy for deciding which vendor to use for fulfillment under various circumstances. But the right choice isn’t always obvious.

You can use cost, inventory, and historical order data to drive decision-making here. The simplest strategy is to always fulfill with the vendor that gives you the best price. But if you’re able to support more complex workflows, you can improve margins further using conditional logic. Historical order data can show you things like:


  • Which vendor is least likely to be out of stock

  • Which vendor has price hikes less often

  • Which vendor ships on time, at a lower cost, on average

  • Which vendor you have a strong relationship with


Considering all these factors in conjunction delivers in a fulfillment workflow that better aligns with your strategic business goals, rather that a short-sighted tactical decision.

Sales Channel Management

While an omni-channel sales strategy is common in eCommerce, it is especially prevalent in the auto parts industry, with many retailers listing on Amazon, eBay, Walmart and more. But your sales channel strategy shouldn’t end with duplicating listings across platforms.

A more thorough, data-driven approach will consider costs associated with selling on each platform. You likely already have an intuitive understanding of which marketplace you like selling on most. But you need to go a step further and put a number on the opportunity. By factoring in platform fees, shipping costs, expected return rates, and opportunity costs due to inventory constraints, you can adjust pricing differently on each marketplace to make sure you’re duly compensated for selling on less preferable channels.

Shipping Cost Strategy

A side effect of relying on marketplaces for a large chunk of your volume is that they often encourage you to include shipping costs in your product price (“free” shipping). But if you’re shipping parts across the country, perhaps even the globe, free shipping adds a ton of variability to your margins.

While this is one you’re never going to get perfect, historical data can have a huge impact on tightening up your margins by making shipping costs more predictable. The analysis here can get complicated, but a few important notes:


  • In general, you want to find an average shipping cost per SKU and roll that into your pricing. Often with an additional “safety margin” markup.

  • Shipping costs change over time, so you’ll want to be careful about the time horizon you use for the analysis - enough so you have sufficient data for calculations, but not so much that you’re using outdated shipping rates. Especially in a COVID shipping environment.

  • You’ll likely have SKUs with little or no shipping data, in which case you need a strategy for estimating the cost. We provide our customers with a full work-up on the strategy here, but the key idea is you use data to learn from “similar” products based on size, weight, location, etc.


With better estimates of shipping costs, you can price products more accurately, leading to more predictable profit margins.

Invoice Reconciliation

An unfortunate truth in the data world is that your insights are only as good as your data. You may have cost data loaded into Shopify, for example, and if you run a profitability report on Shopify data you appear to be well in the green. But your bank account balance at the end of the month tells a different story. What gives?

This situation is all too common, especially in an industry where businesses tend to transact in high volumes. Pricing update emails from vendors get lost. Perhaps they were never sent. So while it seems tedious, it’s necessary to validate your estimated profit numbers against your accounting system.

There are several benefits here. Maybe you discover you were invoiced incorrectly, in which case you can share your audit with the vendor for a refund. Maybe you find a pricing chance that you failed to implement, in which case you can take corrective action. Ultimately, profitability audit reporting limits the number of surprises you have to deal with as a business owner. And when a surprise inevitably does come along, you find out in days, not months, so you can get back in the green before lasting damage occurs.

Supplier Negotiations

Data analysis can also support more strategic business activities, like negotiating for better deals with suppliers.

If you make a blanket ask to one of your vendors for “better pricing”, you’re almost certain to get a “no”.

But if you can make a real, data-backed case that you’d be able to sell 20% more Honda wheels across models with a 5% discount, there’s a good chance they’ll work with you. If there’s an agreement beneficial to both parties, it’s a no brainer.

So how do you make that argument? Not surprisingly, you look at your data. Check sales trends and same-SKU pricing across vendors. Maybe I historically sold all my Honda wheels from Supplier A, but started getting and selling them at a discount from Supplier B. In that case, Supplier A might be willing to work with me to recover some of that lost volume.

That’s a simple example. There’s endless room for creativity in deals. Just remember it’s not all about the data. The data supports your argument, but it won’t get the job done on its own if you don’t already have a solid relationship with these vendors.

Know Your Numbers

The last point is more general and captures the world of possibilities that open up when you leverage your data for decision making. Know your numbers. What do I mean by this? It’s a self-fulfilling prophecy.

I mean, analyze your data. The more data analysis you do, the better you understand the data, the more opportunities you can come up with to leverage your data.

When you’re really familiar with your numbers, you see where your profits are coming from and where you’re losing money. You can tell when your numbers are off, because you’re familiar with the baseline. This helps you in 1000 different ways. It’s often subtle. But you’ll notice that less “fires” are popping up in your business than they used to. All of a sudden, operations are smoother, more efficient, and you have more time for strategy and growing your business.

So, how do you get started? You could figure this out yourself in Excel. Or if you don’t have time to waste, you can hire a team of data science experts who understand your industry to help you deliver your first real data-driven decision in as little as one week.

That’s where Bro Analytics comes in. If you’re serious about taking the first step in your analytics journey, and don’t want to waste one more minute, reach out to us here. Let’s get started.