Digital success is an essential priority for forward thinking fashion and apparel brands in 2019, as consumer behaviours continue to evolve, and consumer spending growth is almost entirely found online. Per Forrester, apparel sales online in the last 6 years have seen a CAGR of 14%, whereas offline sales rose just 1%.
To get a share of that growth, leaders in apparel ecommerce have to be smart about the data they’re using and the outcomes they are measuring. Here are 5 KPIs for digital success in apparel ecommerce.
KPI 1: Cost per Acquisition (CPA)
CPA is such an important metric for apparel brands because to increase revenue, you need to sell more to the same customers or find new customers to sell to. In truth, both are vital areas of focus.
Acquiring customers in meaningful volume is a pay-to-play game, so the key for fashion brands to powering ecommerce growth is to acquire customers in a scalable and cost-effective way. This should involve the use of platforms like Google Shopping and Facebook advertising to drive web traffic, and many brands could also benefit from considering the other end of the funnel – Amazon’s advertising offering is closer to purchase intent and as such, brands often see higher rates of conversion.
For tips on lowering cost per acquisition on Google Shopping, check out our blog post all about Google Shopping optimisation.
KPI 2: Customer Lifetime Value (LTV/CLV)
Customers make you money. Where CPA can help you focus on efficiently finding more customers, LTV can be used to aim at getting more money from those customers.
Between the two metrics, you can fully understand how valuable each acquired customer becomes, bringing your understanding of your advertising effectiveness to the next level.
There are various ways to measure LTV. Which is best depends on your business model. The simplest formula is to go step by step and determine average purchase value, purchase frequency, and customer lifespan.
Here’s what that looks like:
Average purchase value (sometimes average order value, AOV) is just the sum of revenue for a given period divided by the number of purchases in the period. Purchase frequency is calculated by dividing the number of total purchases in a period by the number of unique customers in that period. Let’s say your revenue is £10 million for the last year, and you had half a million purchases in that year. That makes your AOV £20. If those 500,000 purchases came from 100,000 unique customers, your average purchase frequency is 5 times per year.
Putting those numbers together gives you the average value of a customer in a given year. The average order is £20 and the average number of orders is 5 for a year, so your customer value for one year is £100. Multiply this by how long customers typically stay with your brand to understand their ‘lifetime’ value. If customers typically start purchasing your products at age 18 and stop buying them by the time they’re 28, the average lifetime value is £1,000.
LTV isn’t just a good KPI to measure to set performance targets for remarketing and loyalty though. It can also be used to help contextualise other metrics. For example, a useful way to understand the real value of acquiring new customers is to slice lifetime value data by acquisition channel. For example, if customers you acquire from Google Shopping are worth more over their lifetime, then having higher cost per acquisition on that channel might be worthwhile. Lifetime value helps to make decision making based in longer term outcomes rather than short term costs.
KPI 3: Time-to-revenue
Looking internally at business processes and setting clear goals is a necessary step to improving and growing as a fashion brand. One core goal for many apparel brands is to improve their speed to market, getting products out to customers as fast as possible.
However, this ignores a crucial point: being in the market is not the same as succeeding in the market. Often, fast fashion brands produce poor quality digital representations of their products (in the sense of backend attributes, product data and sometimes product content) in order to get it out as fast as possible. While this ticks a box to reach the market fast, it doesn’t necessarily make sense to prioritise speed over quality in every instance.
Time-to-revenue is a metric which focuses on the time it takes for a product or line to reach a revenue goal. This helps brands to understand how quickly products actually succeed in the market, rather than simply measuring how fast they can put them there.
KPI 4: Return on advertising spend
Return on advertising spend, or RoAS, is a key metric for digital teams because it can help to shape your strategy around product marketing. When you’re promoting products across channels, it’s vital to be able to associate purchases with the advertisements and listings that lead to them.
RoAS measures the effectiveness of your digital marketing in a very direct way, and for that reason it’s a helpful tool for distinguishing between the value of promoting individual products or sets of product; or for determining the right level of bid to set for certain keywords.
However, its importance and significance can be undermined by digital teams crowing about their massive RoAS. If your return on advertising spend doesn’t take account of this final metric, it’s already massively lacking in meaning.
KPI 5: Margin
The final and most important metric of all is how much money you’re actually making at any given time. After your marketing spend and the cost to create product content and data, and after fulfilment and warehousing, how much margin is each product actually making you?
If digital leaders in fashion can answer this question on a per-product basis, their marketing can instantly become orders of magnitude more effective. Even having a rough idea in terms of which products offer higher margins can be combined with an understanding of organic sales velocities to generate a clear and actionable list of priority products for marketing promotion.
Many of these KPIs will be familiar to digital leaders and their teams, just as the challenges of actually reporting on them in an accurate and timely manner, then actually actioning changes based on that information will be all-too-familiar.
To make the best use of the data you can collect about your team’s performance, you need an intelligent technology which can aggregate that data in real time and pull out the right recommendations for you to action. You need a technology solution to automate the manual work of creating quality product content for your ecommerce and digital marketing channels, helping your team to hit their targets and start moving the needle on these strategic KPIs.