What's the revenue for every dollar spent on a marketing campaign? This question leads to understanding return on advertising spend (ROAS). Marketing teams should expect a profit, but how much? And how does this knowledge shape strategies?
ROAS helps in budget allocation, campaign optimization, and future planning. Though it seems simple, it's complex to measure and doesn't always reveal the whole picture.
This article will cover what ROAS is, its significance, calculation methods, ways to enhance it, and its limitations for marketing teams.
Return on Ad Spend is a ratio that measures the revenue generated from an advertising campaign against the cost of the campaign. This metric is calculated by dividing revenue generated by the cost of the advertising.
Measuring advertising performance against costs allows marketers not only to improve upon their campaigns, but also to prove to stakeholders that campaigns are working and bringing in revenue.
However, ROAS is one of many quantitative metrics performance marketers can use to audit performance, and it has its own limitations. It’s also important to track qualitative metrics like sentiment and brand awareness, as these metrics tend to be upstream leading indicators of future performance.
Typically, return on ad spend is calculated on an individual campaign basis, although marketers can calculate program wide ROAS averages and use this to compare to individual campaigns when launching new initiatives.
ROAS isolates the effectiveness of individual ad campaigns, calculating only the gross revenue per dollar spent, providing precision in ad effectiveness evaluation.
In contrast, ROI, or return on investment, encapsulates a broader profitability perspective, incorporating all costs — ad spend, labor, technology, overhead, cost of goods sold, etc. — and expressing net profit as a percentage of these.
How to calculate ROAS?
ROAS is a ratio that is easy to comprehend. Marketers can divide the revenue that an ad campaign generated by the cost of the ad campaign and get a return on ad spend. The higher the ROAS, the greater the return on investment from that individual campaign.
To calculate ROAS, marketers need to document the amount of spend and measure conversions and sales per campaign. They also need to determine a reasonable payback period for the ad campaign – in other words, the amount of time allotted to measuring the return on investment after spending on the campaign.
Tracking sales from ad campaigns
One of the most difficult parts of measuring ROAS is measuring and attributing the conversions in the first place.
Depending on the business model, there may be multiple steps involved in calculating a dollar value for the return. Additionally, for multi-channel marketing teams, assigning credit to a given touchpoint is not straightforward.
As for measuring conversions, marketers typically use website analytics in conjunction with tracking pixels (such as the LinkedIn Insight Tag) from the advertising platforms themselves. Often, marketers also create UTM parameters (text strings added to a web link to track where visitors come from) that allow them to precisely define attributes of their campaigns like source, medium, campaign name, and specific content in the ad.
From there, marketers need to choose an attribution model. This can be very complex, but basically, an attribution model is a system and set of rules for assigning credit to a given touchpoint in the customer journey.
Common models include the last click model, which credits the final touchpoint before conversion, and the First Click model, which credits the initial interaction. More complex models like linear, time-decay, and position-based distribute credit across multiple touchpoints.
Advanced attribution tools and software can help track these journeys, providing a more accurate picture of how each campaign contributes to sales or conversions.
ROAS is best used to compare the results and spend of individual advertising campaigns among each other and against a baseline average.
This helps marketers optimize ad spend and reallocate resources towards higher impact efforts. Basically, a low ROAS campaign would signify that the campaign either needs to be optimized and improved or shut off to create room to spend on higher ROAS campaigns.
ROAS shouldn't be used to assign program-level ROI to advertising efforts, nor should it be compared across companies and industries, as there are many nuances to the metric.
What is considered a good ROAS?
A "good" ROAS is dependent on several factors including the industry, the specific business model, profit margins, and overall business goals and strategy.
However, a general benchmark often used is a 4:1 ratio, meaning $4 revenue for every $1 spent on advertising.
This is widely considered a baseline for profitability in many sectors. It's important to note, though, that this is a generic guideline.
Businesses should consider their unique circumstances, margins, and objectives when setting their own ROAS targets. For example, a highly profitable SaaS product may have an entirely different ROAS expectation than a retailer in a competitive space with low margins.
Additionally, strategy can play a role in ROAS expectations. Sometimes, a business may need to operate at suboptimal ROAS levels while they focus on market penetration and building brand awareness against incumbents.
Marketers should also remember to consider other key performance indicators such as Marketing Efficiency Ratio (MER) or LTV/CAC Ratio and not just rely on ROAS alone to gauge the effectiveness of their advertising campaigns.
There are many factors that can impact ROAS, from advertising targeting to demographic segmentation, and of course ad placement, creative, and messaging. There are also external or indirect factors that can influence ROAS, like brand recognition and external trends and factors.
The first step in improving ROAS is accurately measuring it, the next step is to diagnose the potential reasons for lower than average ROAS.
Once the reason is uncovered, marketers can utilize some of the below methods to make improvements:
- Improve ad targeting through detailed audience segmentation and personalization. Reaching the right audience at the right time is one of the impactful ways to improve campaign effectiveness.
- A/B testing ad elements—headlines, images, call-to-actions. This can help identify audience preferences, boosting click-through-rates, conversion rates, and revenue.
- Optimize bid management in paid ad platforms. Avoid overpayment for clicks, impressions, or overly repetitive campaigns with diminishing returns.
- Optimize landing page experiences. Much of the effort is focused on the ad itself, but the landing page that the ad directs to is also important. This can improve conversion rate as well as quality scores in paid search ads.
- Build retargeting campaigns, focusing on previously interested individuals. Using behavioral data like visits to pricing pages, past purchases, or engagement with an email list or gated asset improves campaign targeting and effectiveness.
Additionally, track ROAS over time, as some campaigns take a while to build up and generate returns, while others tend to have diminishing click-through-rates and conversion rates over time.
Marketers can also begin to correlate campaign ROAS with other broad initiatives like brand marketing, content marketing, and SEO, which tend to be more difficult to measure on a per-campaign basis.
First, ROAS only considers gross revenue, not profitability.
It doesn't account for costs beyond ad spend, like product costs, cost of goods sold, or overhead, leading to an overestimated impression of campaign success. This also makes it difficult to compare when running advertising campaigns across different product lines, where profitability may differ by a large amount.
Second, it typically doesn't consider customer lifetime value.
If a campaign brings repeat customers or accounts that expand gradually over time, ROAS can undervalue its true benefit.
Similarly, the time window to attribute revenue is unclear and differs vastly across business models. Even in ecommerce, among the simplest of digital business models, customer lifetime value can vary a lot. For marketers running ad campaigns for enterprise software companies or anything with a long sales cycle, it’s even more difficult.
For example, if an ad campaign is set up to drive conversions to an ebook - which would distinguish a marketing qualified lead - what is the correct time window to calculate if that lead closes into a client?
Third, ROAS incorrectly assumes equal value for all conversions.
Different products or services may have different margins, so a high ROAS for a low-margin product may not be as beneficial as a lower ROAS for a high-margin product. In the B2B context, the conversion value of an ebook versus a demo request versus a whitepaper may have different values, and these values could change over time. Thus, it’s difficult to assign a specific value to certain conversions.
Finally, attribution can be challenging in a multi-channel marketing environment, making it difficult to accurately assign credit to a specific campaign for a particular conversion.
Looking at any metric in isolation tends to obfuscate understanding for marketing teams.
Therefore, while ROAS provides utility and insights for ad efficiency and determining the effectiveness of new campaigns, it doesn’t fully capture business health, long-term customer value, or even the true value of certain advertising campaigns.
To complete the picture on an individual ad campaign, other metrics like click-through-rate, engagement rate, conversion rate, and quality score can help marketers understand if the campaign is resonating.
As a metric, ROAS was very useful when marketing mixes were less complex. For example, determining advertising spend on television ads on a given market and an associated increase in sales in that market was relatively straightforward.
Today, brands are often dealing with a mixture of digital and offline channels, as well as varying business models, products, segments, and campaign types.
Because of this variance, the payback period – the period of time it takes to break even on an investment – of any given advertising campaign could be very different, complicating the calculation of ROAS.
A more useful northstar metric in today’s digital landscape may be Marketing Efficiency Ratio (MER). This is effectively a blended ROAS metric that takes into account the total revenue generated from total ad spend. It parses out new customers from existing customers to further clarify the efficiency of ad dollars spent, and it seeks to analyze the marginal effectiveness of increased ad spend.
To have a better holistic understanding of advertising investments, marketers should also evaluate ROAS in conjunction with other metrics like Customer Acquisition Cost (CAC), Customer Lifetime Value (CLV), and overall Return on Investment (ROI).
CAC assesses cost-effectiveness of customer acquisition, CLV measures the total revenue from a customer throughout their interaction with the business, and ROI broadens the view of profitability.
ROAS, then, is a simplistic yet still useful metric to begin understanding the value of advertising campaigns.
However, there are several nuances and limitations to explore, including how cost is calculated, how return is calculated, payback periods and where ROAS should fit in the mix of metrics marketers can use to attribute campaign success.
In addition to comparing individual advertising campaigns, marketers can also summarize campaign data for each channel, and compare the ROAS of each marketing channel.
For instance, If one channel consistently delivers a higher ROAS, marketers may want to invest more in that channel.
This is where the simplicity of the ROAS metric can be its downfall, however. Marketers should remember that each channel might cater to different stages of the customer journey, and marketing channels have synergies that are not often reflected in campaign ROAS.
Therefore, a lower ROAS does not necessarily indicate a failed campaign.
Some campaigns may be vital for awareness or engagement, even if they don't directly lead to sales.
LinkedIn Ads not only helps marketers measure return on ad spend, but improve it through a variety of tools.
The platform’s advanced targeting options enable precision outreach to the audience most likely to engage with a company’s offerings.
Comprehensive analytics and reporting, coupled with conversion tracking, give marketers insights into campaign performance and allow necessary adjustments in real-time.
The LinkedIn Insight Tag offers in-depth understanding of website visitors and enhances retargeting efforts, while Matched Audiences focus on engaging those already interested in a brand’s products or services.
With Lead Gen Forms, gathering high-quality leads is simplified, boosting conversion rates.
For B2B marketers, LinkedIn's Ad Targeting capability promotes efficient targeting of specific companies or decision-makers, resulting in improved ROAS.