Exploit Your Ecommerce Data to Unlock New Business Growth
By Matthew Ferguson
A little while back we were working with a big retail chain, and they were thinking about pulling the plug on Amazon and eBay. They were putting more and more work into it, and their listing count had grown but sales were down. They were frustrated and ready to completely write off selling through marketplaces.
But they hadn’t dug into their data. When we ran some quick comparisons, we found that none of their key products had been restocked. Their best sellers across several brands hadn’t been reordered over a two-year stretch. Then we saw that their product prices were getting lower but their shipping rates were up. Overall they were less competitive than they had been two years before.
How on earth did they miss such simple things? Well, when you have a large sales volume and/or a team of people working in the business, you don’t “just know” that kind of information. You have to go looking for it. But when you do routinely examine your data, those things are really easy to spot.
But using data isn’t just a matter of regularly comparing sales figures, it goes much further than that. To put it frankly, data is make or break for ecommerce businesses. It can uncover problems, optimize current sales and guide you down new paths. That’s when you really start unlocking its power.
You don’t have to be a data nerd
Here’s an example from the opposite end of the spectrum. We worked with a smaller seller who stayed very close to their sales figures and margins. They had a streamlined operation with a lot of automation, so there was very little overhead and manual intervention. This is a great situation to be in, because then all your energy can go into reporting.
By staying close to the data, they could see exactly when to increase margins and not lose sales
This seller was excellent at spotting where they could be competitive on margins. They used short-term tactics such as selling at rock-bottom prices where they made minimal profits. But by staying close to the data, they could see exactly when to increase margins and not lose sales. The competition would give up or move on, leaving this seller to capture the market. That’s what they did, again and again, very successfully and profitably.
Does this mean you have to become a “data scientist”, who loves stats and Microsoft Excel? Well, it definitely helps, but it’s not a necessity. Most people don’t love to analyze reports, and you don’t have to. Simply by comparing top-selling products, price points, margins, sales velocity and other easy metrics, you can usually see what’s happening in your business. Once you have your spreadsheets and reports set up, maintaining and analyzing them can be quick and easy.
If you want to dig deeper and work on specific questions or problems – such as those in the examples below – you will need to build up some basic data skills. But this is your business data, so it’s all familiar stuff. The mindset for analyzing it might take some time to develop, but it’s well worth the effort.
What makes good data? GIGO and more
What’s GIGO? No, it’s not a terrible film starring former lovebirds Ben Affleck and Jennifer Lopez (that’s Gigli). GIGO stands for “garbage in, garbage out”. It means that if you collect data that is inaccurate or incomplete, then the reports you generate from it will also be inaccurate or incomplete. You need to collect good data to provide meaningful insights later.
So the data needs to be accurate, but exactly what type of data should you be collecting? Usually, the more data that you can collect the better. If you log every cost, every sale, every piece of data around the buyer, the order, the item and everything in between, you will have a rich environment to examine.
The longer the timeframe of the data, the better the statistics and accuracy will be. Countless times I have worked with sellers who have used one week’s worth of data to “prove” a theory. In a week, there are too many random factors that might be playing a part. A few days of data usually proves nothing. A few weeks might. A few months is ideal. Years’ worth of data is great if you have it.
So before you get started analyzing, do your best to collect data that is:
As accurate as possible
As complete as possible
Covers as much time as possible
Now the health warning
In the next section, there are three examples of how to work with your ecommerce business data. They could help you to:
Increase profitability
Reduce shipping costs
Get a better deal from suppliers
Sounds wonderful, right?
Yes, it can be. Using data well can completely transform your business, but it does require some patience and learning. If you go off at half-cock then you might shoot yourself in the foot. So don’t make rash decisions and send your business backwards.
One specific problem is that, being human, we all examine data with preconceived ideas. We start looking for something specific that we want to prove, and we end up ignoring the data that does not fit what we are looking for. It’s called confirmation bias. You have to remain very objective when looking at your data, and let it tell you where to go. It’s OK to have a hunch, just don’t be afraid to be proven wrong.
Another issue I see is that a lot of sellers don’t use the right metrics. Many of them monitor their sales velocity without tracking profitability, for example. Making sales is great, but if you sell 10,000 units at $1 profit per sale, is that better than 500 sales with a profit of $25 each? Choose the right metric to fit the problem you are working on.
So be cautious and methodical, but do follow the data where it naturally takes you. Do not be a slave to the past, gut feelings or unjustified beliefs. The data is telling you how to be successful, so make sure you listen to it.
Scenarios
I’ve chosen three typical situations where there’s a lot to gain from data analysis. I’ve tried to make them fairly generic, but they won’t fit every situation. They won’t be optimal for every situation either.
Working with data sounds boring, but it actually calls for a lot of lateral thinking and creativity. It’s not about taking a cookie-cutter template and applying it no matter what. So adapt and change the ideas below however you need to fit your own business model, aspirations and challenges.
#1. Optimize SKU profitability
Sales per SKU is easy to report on, but can be completely different to profitability. Your best SKUs for sales might be your worst for profit. That’s something you should find out!
Data you need to collect
Besides the sale price and purchase costs, you should collect all other direct costs for each sale: marketplace fees, payment fees, shipping costs etc.
How to query the data
Try to generate reports such as:
Profit per unit for each SKU
Net margin for each SKU
Number of units sold per month per SKU
Sales volume and profitability by product category
Year-on-year bestseller profitability comparisons
What to do with the results
Unless there is some compelling strategic reason to continue, you should stop selling low profit (or loss-making) SKUs even if the sales volume is high. In fact, particularly if the sales volume is high! Low margins still generate a profit, of course, but those products are tying up cash that you could invest in better inventory.
High-margin products (or categories) with low sales volumes could be good targets for investment in inventory or marketing.
Also consider
You could get more sophisticated and capture indirect costs, such as rent and staffing, and factor them into the profit calculation. This will make a big impact if you products range widely in value.
Typically the bigger you get, the more data you will want to capture. But there is a point where the amount of work going into capturing the data is greater than the gains you get from it. If you have a three-man team, it’s unlikely to be worth the effort. If you have a medium to large organization, it becomes increasingly worthwhile.
#2. Reduce shipping costs
Shipping is a hugely important aspect of ecommerce. Customers are very sensitive to delivery speed and reliability, so it can be a little nerve-wracking to start changing something that’s working for you.
But margins are important too. If you could squeeze a few percent more by fine-tuning the parcel carriers and service levels you use, without sacrificing performance, why wouldn’t you?
Data you need to collect
Comprehensive customer, order and shipping data including date shipped, carrier and service used, package size and weight, shipping cost, destination etc.
How to query the data
Generate reports along these lines:
Number of shipments per week by different parcel size and weight bands
Number of shipments per week for different countries
Number of shipments per week for different marketplaces or other sales channels
Average shipping cost for the categories above
What to do with the results
Your findings could take you in different directions, but there is potential to:
Leverage your current parcel carrier(s) for better rates
Switch carrier or service for a certain class of parcel (e.g. by size, weight or destination)
Switch to FBA or a 3PL for a certain class of parcel
Also consider
Monitor for any changes in your typical parcel mix every month. A new product line that sells well could change the situation if the item is unlike your existing products in size or weight.
Also compare rates again when carriers change their prices or introduce new services, or a new mail consolidator enters the market, for example. Even if your business stays the same, the logistics industry is evolving rapidly.
#3. Get a better deal from suppliers
It pays to be well-informed about product sales and profitability for each supplier you work with. That can give you more leverage when negotiating discounts, planning orders, and responding to their requests.
Data you need to collect
You need to have the same profit and sales information outlined above, and be able to segment it by supplier. Then bring in purchasing data, such as typical reordering frequency and quantities, and the levels at which your suppliers’ volume discounts increase.
How to query the data
These reports should be useful:
Monthly sales volume for each supplier
Monthly profit for each supplier
Unit sales velocity and reordering data for each supplier
If you can drill down into those reports by brand and product category, and down to individual SKUs, that’s a big help too.
What to do with the results
For each supplier:
If there is a mix of fast-moving and slow-moving stock could you do a deal on order quantities?
Do they have other variations of best-selling SKUs that you do not currently sell?
Can you get additional leverage by telling them how they compare to your other suppliers, or to the average?
Also consider
Your suppliers only know what they’ve sold to you. They can only guess at your sales and profitability, and those assumptions may be far from the reality. Once you know the full picture, you can use it strategically to make better use of your cash and to improve supplier relationships.
Suppliers can often be flexible. If you can figure out exactly what you need from them to help your business grow, then ask them and they should at least try to accommodate you. After all, your success is their success!
Data can change your life
Reporting can change your business model and direction. The right data, if followed, can change your whole life too…
Here’s one last story. A few years back a young man started selling vintage video games on eBay, from his college dorm. Now he’s a millionaire. But he didn’t get there selling video games.
He followed the data, not his own belief. He adapted his plans based on what the data told him.
The games sold well, and the business started to grow. He had some knowledge of fitness products, so tried out a few new lines in that category. The fitness ranges started producing strong numbers and while their sales were lower, they were more profitable per sale and easier to source and keep in stock.
Over time, the data was telling him clearly that fitness products were worth more investment. So he started manufacturing his own items and cut out the suppliers, increasing profits further. He took this step because the numbers told him that sourcing the products, importing them directly and warehousing the containers would be more profitable than going through a distributor.
Then he expanded to Amazon, where fitness products sell very well. But he also decided to take on more categories including tools and baby products. Was that just a step in the dark? No, he did it because the data suggested a gap in the volume of products in those categories compared to the number of potential buyers, and the existing sellers had pricing he knew he could undercut. That’s where he made his fortune – a long way from vintage video games.
He followed the data, not his own belief. He adapted his plans based on what the data told him. He never tried to force the data to fit his goal or plan, which is something too many sellers do. And now he’s reaping the rewards.
Good data and reporting can help you make decisions with less risk. It allows you to see how your business is performing, where the market is going, and where you can fit into its expansion. As long as you don’t limit yourself arbitrarily, the data will always lead you in the right direction.
(SOURCE)
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