Five KPIs that are crucial to optimising Google Shopping campaigns for apparel brands

Digital success is an essential priority for forward-thinking fashion and apparel brands as consumer behaviours evolve and spending continues to move online.

To make sure they have the best chance of capturing that shift, retailers have to be smarter about the data they’re using and the outcomes they’re measuring. So in this article, we’re taking a closer look at five critical retail KPIs that shape digital success on the most important platform out there – Google Shopping.

KPI 1: Cost per acquisition (CPA)

CPA is such an important metric for apparel brands – because to increase revenue, you need to either sell repeatedly to the same customers or find new customers to sell to. Both are vital areas of focus.

Acquiring new customers in meaningful volume is a pay-to-play game, so the key for fashion brands is acquiring customers in a scalable and cost-effective way. This should always involve optimised Google Shopping ads that drive inbound web traffic, but many brands could also benefit from looking at what happens once the user gets further down to the funnel towards the point of purchase. For example, Amazon’s advertising offering sits very close to the moment of purchase, and can be a powerful driver of conversions.

KPI 2: Customer lifetime value (LTV/CLV)

Customers make you money. Where CPA helps you focus on efficiently finding more customers, LTV allows you to measure if your average CPA is tolerable. Between the two metrics, you get a clearer picture of how valuable each acquired customer truly is, bringing your understanding of advertising effectiveness to the next level.

There are various ways to measure LTV, depending on your business model. The simplest formula is to go step by step and determine average purchase value, purchase frequency, and then customer lifespan.

Here’s what that looks like:

Average purchase value (sometimes called average order value or AOV) is the sum of revenue for a given period, divided by the number of purchases in that 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. That makes your average purchase value £20. If those 500,000 purchases came from 100,000 unique customers, your average purchase frequency is five/year.

Putting those numbers together gives you the average value of a customer in a given year. If the average order is £20 and the average number of annual orders is five, then your average customer value for the year is £100. Then you can multiply this figure by how long customers typically stay with your brand to understand their ‘lifetime’ value. If customers start purchasing products at 18 and stop at 28, the average lifetime value would be £1,000.

LTV is a great KPI to help set performance targets for remarketing and loyalty, but it can also be used to help contextualise other metrics and make decisions based on long-term outcomes rather than short-term costs.

For example, a useful way to understand the real value of acquiring new customers is to slice up your LTV data by acquisition channel. If customers you acquire from Google Shopping are worth more over their lifetime, then allocating more budget to that channel might be worthwhile.

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 common benchmark is an improved speed to market that gets products out to customers as fast as possible.

However, this goal ignores a crucial point – that 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 (back-end attributes, product data, and sometimes product content) in order to get them online as fast as possible. While this ticks the box of reaching the market quickly, it doesn’t necessarily make sense to prioritise speed over quality with a platform like Google Shopping.

That’s because Google Shopping optimisation relies on accurate, carefully collated data. Without it, there’s no point publishing Google Shopping ads quickly when the algorithm will punish them for corners cut along the way.

Time to revenue focuses on how long it takes for a product or line to reach a set revenue goal. This helps brands understand how quickly products actually succeed in the market, rather than just how fast they can get them there.

KPI 4: Return on advertising spend (ROAS)

Return on advertising spend is a key metric for digital teams, because it can help to shape their product marketing strategy. Whenever 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 digital marketing in a very direct way. For that reason it’s a helpful tool for distinguishing between the value of promoting individual products or sets of products, as well as helping to determine the right level of bid to set for certain keywords.

However, ROAS’s importance and significance can be undermined by digital teams crowing about their massive numbers. If your return on advertising spend doesn’t take account of the final metric below, then it’s massively lacking in meaning.

KPI 5: Margin

The final and most important metric of all is how much you’re actually making at any given time. After you’ve spent money on marketing, production, fulfilment, and warehousing, how much is each product actually making you?

If digital leaders in fashion can answer this question on a per-product basis, their marketing instantly becomes more effective. Even a rough idea of which products have the best margins can be combined with an understanding of organic sales velocities to generate a clear and actionable list of priority products for marketing promotion.

Traditional ROAS isn’t much help here, but new, more sophisticated forms are – and you can read more about them here.

New technology puts retail KPIs front and centre

Many of these KPIs will be familiar to digital leaders and their teams. As will be the challenges of reporting on them accurately and actioning changes.

To make the best use of the data and insights these metrics have to offer, fashion and apparel businesses need intelligent software that can aggregate everything in real-time and pull out the right recommendations.

Upp. is that intelligent solution. Google Shopping management software that aligns with financial and marketing goals so that retailers can sell more, profitably.

Get in touch with our team to find out more about how using Upp. can move the needle on your most important KPIs.