The economics of Stockr

Let us introduce to you Joe; he’s a Chief Financial Officer (CFO) at Cakeware, a successful (albeit fictional) ecommerce company selling essential baking products such as materials and ingredients, tins and pans, and recipe books.

Cakeware currently operates two Shopify stores in different regions – one in the UK and one in the US, and to distribute stock they allocate a certain amount of products to each store based on their predicted performance. For example, while they sell measuring cups across both stores, they allocate more of them to the US as they’re in higher demand there.

While Joe doesn’t allocate the stock, he does hold ecommerce integration platform  an important role in this process. He needs to make sure both stores are profitable and efficient, and identify any problems which may be affecting revenue.

And with his CEO announcing the establishment of two new stores, Joe’s about to notice a big problem with their profits.

The impact of scaling up on stock control

In its current operation, Cakeware runs by having separate stock pools for each store which are allocated inventory. This works fine for now; demand is predictable based on performance in previous months, so the company can avoid both underselling and overselling relatively easily.

But, when the two new stores became live, Joe discovered some significant discrepancies in the company’s finances. Across the most popular stores, around 5% of all stock was accidentally overselling – all of which required refunds.

5% might not sound like much, but to accentuate the problem to his colleagues, he explained it through numbers.

Imagine Cakeware’s most popular store averages 500,000 orders a month. And with 5% of those orders inadvertently overselling, that’s 25,000 refunds which need to be processed.

Now, Cakeware sells a large variety of products of varying prices – but typically their stock is around £10 per item. Joe points out that 25,000 refunds translates to £250,000 using this metric, which is an enormous loss – especially with no guarantee those customers will wait until their order is back in stock.

The unseen costs

To accentuate his point, Joe decided to go a bit deeper with his report. It was all well and good showing the CEO and COO how much revenue was being missed due to refunds, but there were other more subtle consequences which made this an even bigger issue.

First of all, Cakeware is a company which greatly values its customer service and reputation. To show that, whenever an order goes wrong or a customer is inconvenienced, they offer a 10% discount on their next purchase. While this helped retain customers who had been disappointed by an undelivered and refunded item, it also meant they were reducing their profits for the next month.

Plus, there was still no assurance that people would stick around after using their discount; the poor experience might still leave a bad taste in their mouth. He estimated that, while most new customers would use their discount, only around 5% of those would become repeat consumers.

There were also the costs related to customer service. Both time and money is spent processing refunds and issuing apologies and discounts; he even discovered that the  If they were having these issues during peak periods like BFCM, when customer support is already pushed to their limit, it could spell disaster.

Finally, there’s the impact of underselling. Joe pointed out that issuing refunds due to overselling wasn’t the only problem they were facing; they were also underselling products in their less popular stores, meaning they had large quantities of leftover stock which, if other stores had access to, could be easily sold.

Fortunately, he had a solution to offer:

The price of Stockr

works by unifying the stock pool of multiple Shopify stores. That means, if the UK store is selling rapidly, it doesn’t have a specific amount of allocated stock; it can take from other stores which perhaps aren’t performing as well. And when a store is underselling, you’re not left with warehouses filled with unsold products; they can be used for stores which otherwise would have oversold.

It also updates stores within a millisecond, so even if you do completely run out of stock across all stores, there’s no risk of still overselling.

To convince his colleagues of the benefits and value for money Stockr provides, he did some research into the potential costs saved.

Stockr charges the merchant a set amount per transaction, and that amount doesn’t scale upwards based on how many orders you’re getting – so even if you’re getting hundreds of thousands a month the price will stay the same.

Even so, Stockr charging a fixed price wasn’t enough to fully convince Joe’s colleagues, so he decided to put that price point into context. Stockr, more than anything, is like an insurance plan. During one month, Cakeware might be fine and have few issues with over and under selling – but the next, they could have to issue £250,000 worth of refunds for one store and be left with hundreds of unsold products in another. Not to mention the time and resources spent on dealing with thousands of unhappy customers.

It’s about mitigating risk. And the money spent on Stockr is a drop in a hat compared to a minimum of £250,000 in lost revenue.

That explanation was enough to convince the CEO and COO to implement Stockr, and after the first month, the benefits were obvious. Overselling was eliminated and underselling was greatly reduced; they were retaining more customers; customer support was able to focus their attention on other issues like website UX; and revenue was through the roof, allowing them to scale even faster.

For more information on Stockr and how it works,  Patchworks is an experienced integration provider with a range of software solutions to aid our clients and partners in scaling their business.