Why many auto parts sellers struggle with business analytics.

Why many auto parts sellers struggle with business analytics.

Nowadays everyone is talking about Data Science, AI, Machine Learning. You’ve probably got the impression that you need to somehow use these technologies in your company. Advanced analytics techniques - which require cross-domain expertise in statistics, business, and computer science - are understandably intimidating for just about any small to medium business. But if you’re in the car parts & accessories industry, the learning curve for these technologies gets even steeper. In this article, we’ll explain why that’s the case and what you can do about it.

High SKU count

The first problem is the shear volume of parts data that’s out there. If you’re serious about selling car parts online, you have to have broad coverage of manufacturers and model years. But with thousands of model years, and thousands of parts and accessories available, we quickly breach the territory of millions of SKUs you need to handle. Not to mention the work of keeping titles, descriptions and images up to date for all those SKUs.

For this reason, many operators struggle with where to even start looking at this data. When you carry so many products, it’s difficult to maintain an intuitive, hands-on understanding of your data. Business owners become overwhelmed when facing the question “how do we use this data to drive decision making?”

This problem requires some technical expertise. You’ll likely need support from someone proficient with data to work through the first few “data driven decisions”.

High volume data

As if the SKU count issue wasn’t enough, we then have to face the volume of transaction data. Because there are so many products to cover, many businesses resort to a dropshipping approach to fulfilling auto parts. This is a cost effective way to meet your customers’ needs for very specific car parts. But since dropshipping margins are so thin, most businesses operating this way rely on high volumes of order data to remain profitable.

This is a great business model, but when it comes time to analyze your data, it creates new problems. Your datasets are much harder to process than other industries. With high order volumes, you get larger file sizes. So while other businesses can ramp into data analysis using Excel, your data may be too large to even open in Excel! Or you might get the file to open, but notice that Excel is so laggy you can’t get anything done, among other issues. I’ve even seen cases where too-large datasets caused the built-in search function to break, meaning you’re left with no way to find data in your spreadsheet - kind of defeats the purpose of data analysis.

The solution here is most likely to migrate to a new toolset. That may mean a new spreadsheet tool based in the cloud - where other servers can do the heavy lifting in place of your laptop. Or it could mean migrating business analytics to a code-based approach using tools like Python or SQL for reporting and analysis. This will of course require more technical expertise and a way to get your data into these systems.

Data in disparate systems

Ok, now you’ve overcome the issues of how to work with large volumes of data. But unfortunately, you might not be out of the woods yet. Depending on how you run your business, you might face the issue of having data in disparate systems. That basically means your data is spread out across multiple platforms. You might have financial data in an accounting system, inventory and HR data in an ERP system, order data in an eCommerce platform, marketplace sales data in Amazon, Walmart, eBay… and a hundred other places.

But to answer business questions, you really need all that data in one place. Manually joining the data for analysis can be done, but it’s painful and error-prone.

Some companies are already a step ahead by using operations automation platforms like Channel Spyder which aggregates most of your data in one system. If your company uses Channel Spyder or a similar technology, you’re one of the lucky ones who will have a much easier time exporting data for analysis. For everyone else, you’ll probably need to hire a data professional to merge the data for you, taking appropriate precautions to preserve data integrity.

They lack the expertise to go beyond Excel

We’ve seen that the answer to all these problems is, “you need a data expert”. You may already have been familiar with all the issues we’ve discussed, but nonetheless lack the expertise to resolve them on your own. Maybe you’ve been “making it work” in Excel but are held back from realizing the full advantage of leveraging your data. It’s just an unfortunate fact of this industry that you’ll probably need to either learn these skills or hire someone who has them.

Just too busy

So you understand the barriers to implementing analytics in this industry. And you know you need to have data science skills on your team. The last barrier is that you’re just too busy to learn the tools. Whether you’re doing this yourself or you’ve got an Excel analyst on your team. The reality is most car parts sellers are too busy putting out fires to take the next step in this journey on their own.

That’s why many car parts companies decide to hire out their analytics work. Which leads us to one more issue that could arise…

Hiring analysts who don’t understand their business.

The most ambitious car parts business owners realize all the problems we already discussed and try to get ahead of it by hiring out a data analyst to pick up the slack in these areas. Unfortunately, that doesn’t guarantee they become a “data driven company” overnight. All too often, data analysts you hire off of freelancer sites are just Excel jockeys who lack the technical skills to do anything you couldn’t do if you had the extra free time. That’s not to say there’s anything wrong with these people - but their toolset won’t be sufficient, for the reasons we explored above.

What’s worse, many don’t understand the intricacies of the auto parts industry, so you get stuck double checking all their work because they didn’t know the right questions to ask.

In other words, you need to hire someone who has both the data science background and the industry experience to give you an ROI.

At Bro Analytics, we strive to sit at the perfect intersection of those two points - competent in tech and in your business. That’s why our customers have seen such great results. They’ve improved their margins and are saving tens of hours per week putting out fires, which they can now put toward growing their business. But most importantly, they have the peace of mind that comes with understanding their business operations. They know things are running smoothly, because they see it in the data.

What to do about it?

You certainly can’t give up on analytics - this stuff is the future! And if you ignore it, you’ll get left behind by your competitors who don’t.

So if you’re dealing with the problems we discussed in this article, it should be your priority to find a data professional who can help launch your first true analytics project. You could see a turn around in as short as a week - and once you see the power of this approach, you’ll never go back to the status quo.

Whether you contact us, or seek out a contractor (just be sure to vet them!), taking a data driven approach to your operations is going to change your business for the better.