Amazon PPC RoAS Audit Best Practices

The insights of auditing are crucial for any business when it comes to planning, setting goals, and keeping track of performance. The importance of auditing is only amplified by the increasingly competitive nature of trading on Amazon — it presents plenty of opportunities for businesses, and so well-informed self-awareness and strategy are required in order to succeed.

Effectively planned PPC campaigns — based on in-depth data analysis and strategic manipulation of algorithms — are one way to achieve success on Amazon. Another means of facilitating success is to use audits which properly appreciate ‘Return on Ad Spend’ (RoAS) as a metric. RoAS is, in essence, the inverse of ACoS, and offers utility by clearly benchmarking the success of advertising campaigns.

In this blog, we are going to provide answers as to what the best PPC and RoAS audit practices are on Amazon. So let’s get started. 

1. Set foundational goals

The results of audits are most useful when applied to pre-existing business goals. This of course requires setting goals to begin with, and keeping them in mind alongside the upshot of any audit.

Business goals can involve more general aims like rapid expansion, long-term growth, or the launching of a new product. Similarly, you might also set explicit goals like the use of Amazon PPC in order to drive organic traffic — a somewhat unique opportunity relating to Amazon’s  ‘A9’ algorithm — or the maximization of profit margins in relation to already existing products. 

Things to consider:

Whether you’re managing PPC campaigns, developing brand awareness, or conducting an audit interpretation — it can only properly be achieved once a clear conception of business aims (both short and long-term) are in place.

Depending on your goals you may decide to focus on metrics other than RoAS in your audit. For example, aggressive expansion of market share will require a greater ACoS (and as such, will result in a proportionately lower RoAS), so considering success solely in terms of RoAS is inappropriate. Despite this, RoAS audits (and RoAS metrics more generally) are highly appropriate when judging campaign profitability.

Pro tip: Very simply, RoAS is Ad Revenue / Ad Spend, and Amazon is equipped to provide these RoAS figures (as well as their constituent factors) in relation to specific campaigns, so this step is relatively easy. 

To properly consider campaign profitability however, you need to understand your break-even RoAS — which brings us onto the next section.

2.Benchmarking break-even ROAS

From RoAS you can easily calculate how much money you’ve made after advertising costs, but you can’t accurately assess if your ad campaign is actually profitable until pre-advertising profit margins are considered too. A proper consideration of these profit margins (and therefore profitability) is what break-even RoAS calculations are designed to do.

These calculations provide your business with a ‘break-even point’ for a given ad or campaign. Essentially, this more holistic calculation isolates the minimum RoAS required for you to turn a profit once all costs are considered.

Calculating break-even RoAS

We’ve already covered how to calculate your standard RoAS, but the break-even is more complex. To calculate break-even RoAS however, you need three figures:

• Revenue: The income earned from selling products.
• Cost of goods sold (COGS): This contextualizes revenue. Costs might include production and manufacture, taxes, sales fees (including Amazon’s commission), and other storage or logistical outgoings imposed by Amazon for FBA sellers.
• Gross profit: This is revenue minus COGS.

For example: If you generate £100 in sales at a COGS of £70, then your pre-advertising profit margin would be £30 (or 30%). That means that your break-even RoAS is the inverse of 30%, or 3.3x (a.k.a 333%).

After calculating your gross profit, divide it by revenue to get your pre-advertising profit margin. To then establish break-even RoAS, take the inverse (1/n) of the pre-advertising profit margin figure and view that as a minimum target for profitability, and as a benchmark for campaign success. With this target in mind, you can identify whether your ad spend and subsequent RoAS calculations surpass it or not.

Things to consider:

For a complete picture, break-even RoAS points should be established on a product specific and campaign specific basis, as well as averaged across the entirety of your business portfolio. Similarly, even with break-even RoAS in mind, it can be difficult to set a target RoAS or to interpret audits when your varied business goals might necessitate lower (or even initially negative) RoAS figures. In the following subsection, we’ll consider one more means of combating these concerns.

Suggested reading: If you want to learn more about how to calculate your break-even RoAS, check out our blog — Break-even RoAS calculator guide

The power of CLV-adjusted break-even ROAS

An additional metric, to assist in setting RoAS targets and justifying strategies involving lower RoAS, is ‘customer lifetime value’ or ‘CLV’.

CLV is the total profit generated by a customer during their entire purchasing relationship with a business as well as their potential future purchases. This long-term outlook is required to effectively interpret RoAS audits and to set various RoAS targets. With additional insight into profitable customer demographics, you can be more justified in carrying out a range of processes, including: 

• Placing competitive bids
• Training your attention on certain products
• Cutting your advertising losses
• Determining acceptable customer acquisition costs
• Changing predicted break-even points long-term

The utility provided by CLV is not effortless however. It requires large amounts of customer data, and customer data isn’t always easy to come by on Amazon, particularly when CLV calculations depend on:

• Understanding where best to capture data
• Having enough data to produce behavioral models and forecasts
• Balancing quantitative and qualitative reports
• Retaining accuracy by processing the above in real-time

Strategies to help:

Data-crunching and CLV calculation might be unfeasible given your in-house capacities, but using third-party analytics tools can be a viable and effective alternative.

You need to deploy a platform that utilises machine learning and AI best practices that are designed to process the volumes of data required for complex metrics, like CLV. The mounds of customer data generated by consumers is available to retailers, but in order to be useful, it requires extensive analysis that formulates predictive customer models. Specifically, this kind of customer data can help eCommerce businesses to curate behavioural models that inform and can integrate into your business strategy. So the benefits of CLV should be obvious, and so should the need for a third party platform. 

Suggested reading: For more information about customer lifetime value calculations, check out our blog — Can CLV Calculations Ever Be Accurate?

3. Interpreting and influencing RoAS trends

So, you may now be asking, how best to interpret and impact differing RoAS trends with regards to individual campaigns and strategies?

Higher RoAS

Business aims of increasing profitability and margin best align with high RoAS approaches. To make the most returns from your ad spend it may be necessary to manually bid on a product-by-product basis for terms that are most likely to convert into sales. Essentially, this is the process of search term optimisation introduced earlier.

When well-executed, terms which are ‘exact match’ in nature (i.e. where the search terms correspond directly with the product offered) have the highest conversion rate — they match greatest with what the customer has explicitly searched for and so intends to buy. Exact match bids can maximise PPC and ad spend efficiency by allowing you to bid only on relevant terms designed to generate sales.

Still, this style of bidding strategy can be problematic. When it is done without proper research and without a thorough grasp on the data, exact match bidding can unfavourably limit product visibility on Amazon. This can result in wasted resources, sales loss, and damage to rankings.

Strategies to help:

One approach is to employ AI analytics to crunch the data associated with optimal search terms and Amazon customer behaviors. With assistance from third-party analytics your bids on terms will be more conducive to an increased RoAS, whilst avoiding the downfalls of sub-optimal keywords. 

Consider reading: To learn more about search term optimisation, check out our blog — What is Search Term Optimization? 

Lower RoAS

Sometimes an initially lower RoAS is a necessary consequence of an approach to PPC and advertising directed at a certain demographic. If your ad campaigns are costly but designed to acquire customers with high predicted CLV, you may well have to first endure lower RoAS in favor of longer-term returns (and higher RoAS).

Lower RoAS is also acceptable if your goals involve aggressive strategies more generally. These strategies might be aimed at driving growth, research, market expansion, or edging out competitors.

Another reason for having a low RoAS is that you’re only targeting your own branded terms. For example if you’re selling Calvin Klein jeans, unless your keyword strategy incorporates the standard searches for jeans, such as ‘blue jeans’ not just ‘calvin klein jeans’, then you’ll successfully show to customers that are not just explicitly searching for your brand. You’ll gain recognition from customers looking for all jeans, not just yours, making your digital reach much further than if you only deployed branded search terms. 

Strategies to help:

Essentially, these instances by necessity generate a lower RoAS, as your spending commitments are large but favor longer-term high returns. One important thing to take away here is that unhealthy fixations with higher RoAS can in the long run damage the total amounts of money your business makes.

Diversity of RoAS types

It isn’t just long-term business goals which vary in their degrees of RoAS, the ad types constituting campaigns can be just as diverse. Sponsored brand ads and sponsored product ads may produce varying amounts of RoAS. This is dependent on how ‘top of funnel’ or ‘bottom of funnel’ they are, and how much planning and optimisation has gone into the more targeted (and potentially risky) types of ad campaigns.

Ultimately, more discerning Amazon merchants will aim at different target RoAS for the various products they sell. Interpreting your audits with diversity in mind, and allowing your RoAS targets to be influenced with a degree of strategic flexibility is going to best facilitate your selling potential.

Suggested reading: for further insight into different ad types, check out our blog — How to master Amazon Sponsored Product ads

Analytics tools are essential to next-level PPC audit outcomes

Audit insights can be both interpreted (and incorporated into) a variety of business goals, strategies, and outcomes. It is important though to ensure that enough data can be isolated and processed for these robust audits, and to accommodate their conclusions in your PPC and ad campaigns.

Whether establishing optimal search terms or calculating complex metrics like CLV, we have discussed here just how beneficial analytics tools and AI can be in assisting business functions. We at Nozzle are pioneers in this respect. We have built a platform that is designed to produce the aforementioned robust type of audit, so that you can focus your time and energy on the most crucial information, and put that information to use in seeing out your business goals. 

If this type of assistance is something you feel your business needs, or if you’d just like to know more, then please get in touch.

Suggested reading: For further information on what our platform can offer you, check out our blog — 4 Things Nozzle Has To Offer