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This post originally appeared on the blog of Bainbridge Growth. It is being republished by The Current with permission.
For direct-to-consumer brands, supply chain and fulfillment operations are critical components in ensuring items reach customers in a timely fashion. They can also play an unsung role in driving profitability.
In this post, we'll dig into the reasons why managing your supply chain is critical for DTC brands and explore three strategies you that can help you:
- Increase customer satisfaction
- Increase Contribution Profit
- Enable higher CAC’s so you increase customer acquisition
- Increase top-line revenue
Let's start with the "why."
COVID put the supply chain front and center
Remember, 90% of all goods are shipped by container ship. Recent supply chain stats are bleak:
- By October 2021, 600 container ships were stuck outside of ports while waiting for capacity to be cleared and moved for import clearing.
- By September 2021 shipping containers hit a high of $19.5k per container and ended the year at $9.5k per container as compared to the year prior of under $2.0k (that's about 5x times higher!).
- Transit time can be anywhere from 2 to 6 months without delays and up to 8 to 9 months with delays.
The increased costs and times have a cascading impact on a DTC business.
- Do you have the cash to increase inventory levels?
- If you buy too little or get timing wrong, you will have stockouts and miss revenue opportunities
- Are you able to predict and time the inflow of inventory and have the cash to fund ad spend at that time to drive sales?
But there's another impact that you may not think about - supply chain inefficiencies can actually impact your CAC. Here's what I mean:
How supply chain issues affect your Customer Acquisition Cost
At Bainbridge, we believe Contribution Profit is a critical metric especially in terms of setting your CAC. Understanding your LTV:CAC ratios and payback periods are critical to profitable growth. So we focus on fully-loaded CAC compared to Contribution Profit over fixed time periods such as six months, 12 months, 18 months.
As you save dollars on supply chain and fulfillment, you increase Contribution Profit. That increased Contribution Profit can then be used to increase your target customer acquisition cost (CAC). This just means that when you save one dollar in expenses, you increase your profit by one dollar and therefore you can use that extra profit for customer acquisition.
So to illustrate how this works, we put together a simple table that shows the units economics, an individual unit’s profitability, before and after supply chain optimization. As you can see in the example, the optimization reduces supply chain and fulfillment costs which can be reallocated to customer acquisition purposes. The company in our example below, can increase their CAC from $30 to $42, a whopping 40% increase and achieve the same Contribution Profit After Marketing. What would you do if you could increase your CAC budget by 40%?
So, how do you make these paper savings real? Here are three strategies you can implement.
1. Ordering the optimal inventory amount
Ordering the right amount of inventory and improving your timing of orders is a good place to start. You have to balance the fine line of ordering sufficient quantities to avoid stockouts without over-ordering inventory. Over-ordering inventory can lead to increased warehouse storage fees, increased spoilage, and inefficient cash trapped in unsold inventory that you could be using to sell through that same inventory.
We have illustrated a depiction below for two storage cost scenarios. Under both scenarios we use the same sales velocity, the same total sales and time frame, but as you can see the Cost Per Bin/Month is one-third the cost of the inefficient inventory ordering.
So how do you efficiently order inventory? Companies that are good at this are usually good at what-if scenarios. They have access to data and models that allow them to quickly simulate multiple scenarios with multiple assumptions. They can quickly test smaller orders, unexpected delays, different timing of payments in order to find the balance where they feel comfortable. And because they have tested the scenarios, they know what they can do if the unexpected happens.
The below table shows the cost savings you can achieve by ordering the optimal inventory amounts to unlock sea shipping and reduced unused storage space.
2. Streamlining packaging and kitting
We all know that packaging is an important part of customer experience and especially for DTC ecommerce brands where that is the first physical point of touch for a customer. But have you thought of the things you can do to optimize your fulfillment that could result in faster delivery or reduced costs?
When you set out to create an amazing packaging that your customers would love you probably weren’t thinking about associated fulfillment costs and shipping expenses. You may be surprised to hear that your packaging may actually be the reason you are spending up to 40% more on shipping. Because shipping carriers have to standardize the shipping costs and the way they calculate it, they have a very rigid shipping calculation structure and your product has to fit into one of them. This means that if you miss a dimension by just 1/10th of an inch, you will be categorized in another (generally way more expensive) shipping category.
In more dramatic cases, we have seen that simply re-organizing the packaging allowed shipping savings of more than 40% which dramatically improved unit economics and allowed the DTC ecommerce brand to re-invigorate a new and more scalable customer acquisition and business strategy.
3. Optimizing warehouse location
Warehouse locations are a key component to a successful DTC ecommerce business. A good location can shorten the customer fulfillment time and enhance the customer journey. As we know, a positive customer experience leads to higher repeat purchases. Additionally, warehouse locations can have a major impact on the shipping costs and therefore potential to achieve massive savings as opposed to your less savvy competitors. A smart warehouse location plan can help you take reduce costs by taking advantage of a few fulfillment "hacks":
Yes, we said it and you heard us right. Section 321 is a Customs and Border Protection (“CBP”) shipping type that allows for goods to clear through customs tax and duty-free. This shipping type exempts low-value (less than $800/day/customer) shipments from taxes and duties as long as the shipment complies with the eligibility requirements. This strategy can save up to 15% off on your cost of goods. We've seen this strategy attribute high-single digits to DTC ecommerce net income margins.
Benefit from shortened shipping zones
US shipping carriers use shipping zones to standardize and determine the distance of the product you are shipping. As you probably already know, the further you ship an item the more it costs…especially if it is heavy. Savvy DTC ecommerce businesses understand this concept and utilize it as part of their supply chain and fulfillment strategies.
As you can see in the below pictures, you have a US map that has only one fulfillment center (left) and another US map that has three fulfillment centers (right). When only one fulfillment center is considered you might have shipping zones up to Zone 8 as opposed to the shipping zones of three fulfillment centers down to Zone 5.
The below is a generic warehouse selection to help visualize the effect of shipping zones. In order to strategically select the best location for yourself, you should analyze which areas you have historically shipped to the most.
Moving from a single 3PL to three 3PLs across multiple regions has an average cost savings of 25% and a 15% reduction in average transit time to customers. The below table shows the cost savings warehouse location strategies by eliminating import duties and choosing warehouses that are closer to their destination.
Although every business is unique and there is no one size solution that fits all, we do know that every business can benefit from a more optimized supply chain and fulfillment strategy. By making your packaging more efficient, switching or adding warehouse locations, drilling down into your current 3PL vendor expenses, or capturing tax benefits through Section 321, you can achieve massive savings anywhere.
Trending in Operations
Constructor's Eli Finkelshteyn shares principles for responsible use of generative AI, and an experiment.
This is an article about how to approach the use of ChatGPT for improved ecommerce experiences without breaking shopper trust in the process. You probably aren’t expecting Jurassic Park references, but I’m going to make one anyway.
There’s a line of foreshadowing early on where Jeff Goldblum’s character speaks about the complexities and ethics involved in cloning dinosaurs. He says something to the effect of, “Everyone got so excited that they could that they never even stopped to consider if they should.”
ChatGPT, and transformers in general (the technology underlying ChatGPT and a lot of the newer software that’s emerging in the search and discovery world) are incredibly exciting. One of the most exciting parts is how easy it is to build something with ChatGPT, and we’re currently seeing a glut of new software that does just that. Still, what isn’t clear is how to leverage this technology in ways that aren’t just gimmicks, but are actually helpful to people.
It’s clear to just about everyone that we’re in a hype cycle, and that’s why it’s so important for new technology being marketed as “powered by ChatGPT” or “powered by transformers” to prove its business value and usefulness to end users. Not to mix blockbuster movie references, but with great computing power comes great responsibility.
So it’s a good time to ask the multibillion-dollar question: how can technology companies use ChatGPT responsibly and in ways that actually benefit people in the months and years to come?
We’ve adopted some overarching principles internally at Constructor that will serve as our north star as we continue to innovate in this space. As we came up with them, we realized they could be useful as best practices for technology companies in general, and especially those like us who are serving large e-commerce companies. As more and more ecommerce leaders across B2B and B2C evaluate AI solutions in the middle of a hype cycle, we think it’s especially important to publish our principles publicly.
Our hope is that if we stick to these principles, then we’ll maintain our customers’ trust while innovating on new technology, and we’ll do this while doing the right thing for shoppers as well.
1. Experimentation is a prerequisite for ROI
Lots of companies can release a cool-looking new product and make claims about its efficacy, but it’s important for all of us to recognize that we’re early in our understanding of what applications of ChatGPT are genuinely useful to humans, and which are just science projects.
Why? Because the vast majority of those results are still unproven.
With ecommerce technology, for example, it’s important to consider whether a technology partner is going to actually deliver a product that has a legitimate impact on revenue or user happiness. Succeeding at that is ultimately a manifestation of extensive experimentation, including testing, failure, iteration, and re-testing — over and over again. Like most good things, data science takes time. It’s complex, and it’s nuanced.
Why is this so important for all of us in ecommerce tech to recognize? Because if we release a bunch of gimmicky technology and promise it’s the next big thing, then when we do come up with something useful, no one is going to trust us anymore.
The critical takeaway here is that any breathless proselytizing about most ChatGPT-based tech at this stage is counterproductive and simply not honest. If a vendor says they know for certain where the gold is right now, it’s just very unlikely to be true.
That’s the critical difference between a culture of experimentation versus one that’s only interested in shipping the “new hotness,” no matter the results. Before a product goes to market, the company that created it needs to be able to explain, and ideally prove, how it will bring ROI.
Is it just a novelty, or will it — in our case as an ecommerce product discovery company — actually help shoppers discover more products they want to buy in a way that’s more convenient, more natural, or more delightful than what they already have? And how do we know?
At Constructor, we’re excited to be experimenting with ChatGPT and large language models and transformers, both internally and with willing customers. We’re excited about the experiments we’re doing, and we hope the customers testing them are too, but we also want to be very clear that these are still just experiments. I’m providing a sneak peek at one experiment we’re very excited about below, but please read on before watching it:
Because here’s what we’re not doing: we’re not claiming we’ve invented the best thing ever. We’re not promising 10000% ROI. This is an experiment we’re excited about, but there is a real possibility that it doesn’t work out.Taking risks is what innovation looks like. The difference is that at the end of the day, our charter is to create real value (and ideally revenue) for our customers — and we won’t sell them a product that delivers anything less.
2. ChatGPT for ecommerce should be trained on ecommerce data and built for the needs of ecommerce
Ecommerce is full of unique problems and use cases for the ways people find products and content. For example, an add-to-cart and a purchase are both “conversions,” but they’re very much not the same type of conversion. Software that’s built for ecommerce has to understand the distinction, because it’s incredibly important to the KPIs that B2C and B2B ecommerce companies care about.
That’s the primary reason that we built Constructor’s AI core from scratch — the keyword-matching and vector search algorithms that work for general document search just aren’t the best technology to apply to ecommerce product discovery where you have rich feedback from users via their clickstream, along with zero party data like answers in a product-finding quiz. And the same principles apply when we apply ChatGPT to ecommerce.
The idea here is, let’s not try to boil the ocean. We don’t need to create Artificial General Intelligence that can answer every type of human query. We just need to create a very specific form of Artificial Intelligence that does one thing (helping shoppers discover products they’ll love, in our case) very, very well.
In order to return the most personalized, attractive results to a shopper’s query, ChatGPT needs to be augmented with AI models trained on ecommerce-specific data like clickstream behavior, average order values, margins, and product attributes. What’s really exciting here is that it’s the underlying technology itself that has the potential to completely reshape ecommerce. At Constructor, for example, we are working on using transformers to provide better product retrieval and filter out irrelevant results in search queries. It’s possible that this work may have the greatest impact on customer revenue, even more than the “conversational commerce” element of ChatGPT. But we don’t know yet — that’s why we’re experimenting.
(Image courtesy of Constructor)
Another advantage to training transformers on ecommerce data is that it also might mitigate some of the public concerns around ChatGPT’s accuracy. We only surface products for shoppers based on their own zero-party data and an ecommerce company’s own catalog. This heavily limits the types of wrong answers the system can give, and is about as accurate (and effective) as you can get. You may not be able to ask the ChatGPT solution at your favorite retailer about the year Albert Einstein was born, but it will be much better equipped to help you find a shirt you’ll love, or that one snack you tried and enjoyed, but can’t remember the name of. That’s a sacrifice I think most companies will be willing to make.
3. ChatGPT should build — not erode — your customer relationships
We’ll be releasing the full results in the next few months, but our team at Constructor recently performed a survey of 400+ U.S. online shoppers. We found that more than half of them were at least somewhat hesitant about using ChatGPT to find products on websites.
In our current landscape of third-party cookies and data breaches, that response is understandable. And ChatGPT could trigger a similar backlash if it makes shopping uncomfortable or intimidating. New tech can be scary, and it’s a fair concern that you might not want to ask your grocery store to create a shopping list of your regular purchases if it automatically adds sensitive items like gas relief medicine without asking you first.
We don’t have all the answers yet (as a company, an industry, or even a society) for how we’re going to solve these problems. Some of it, especially in this experimental phase, will be creating more transparency for the shopper. Expedia is an example of a company approaching this the right way, in my opinion. They recently launched a ChatGPT interface, and they’re very open about it being experimental and not trying to “trick” customers into using it. It’s a small but important step in building customer trust and delivering the value that leads to long-term relationships.
(Image courtesy of Constructor)
Questions will come up as we break new ground here. They’re important to talk and think about, and that work is the shared responsibility of retailers and the partners they work with. Ecommerce companies and their technology partners coming together to consider these murky waters — and being willing to think through new solutions to put customers first — will be absolutely critical.
A balanced approach
The amount of excitement and buzz around the (virtual) water cooler here at Constructor when it comes to ChatGPT can’t be overstated. Speed to market is a noble pursuit in this agile, volatile economy, and we are experimenting every day to figure out which of our ideas with ChatGPT and transformers will bring customer value and which require rethinking.
But we also want to balance that excitement with humility. When ChatGPT and transformers are raising legitimate questions from consumers, from companies, and even from others in the AI community, moving forward carefully and intentionally is equally important.
In this retail tech arms race, it’s the companies who widely release technology that doesn’t help their customers that have the most to lose. Ultimately, AI shouldn’t exist just for AI’s sake. Artificial Intelligence needs to yield real value if the companies using it want to be valued by their customers. We hope that our customers have come to trust us for doing right by them and their shoppers, but recognize that trust is something we have to constantly earn and maintain. My hope is these principles will help us and the wider technology ecosystem do exactly that as we embark on this next exciting adventure in AI.
Eli Finkelshteyn is co-founder and CEO of Constructor, an AI-powered product search and discovery platform tailor-made for ecommerce. This piece originally appeared on Constructor's blog, and was reprinted with permission.