Beyond ROAS: Calculating the True Profitability of Your Ad Spend with Conversational AI Insights

When it comes to measuring the success of paid campaigns, the marketing industry has put one particular metric on the pedestal: Return on Ad Spend (ROAS).

It is partly due to its straightforwardness and the simplicity in the way it is calculated that it has become the industry standard and the key performance indicator for campaign success, mainly with paid campaigns.

What is ROAS and How to Calculate It

ROAS stands for Return on Ad Spend, i.e. the revenue generated for every pound (dollar, euro) spent on advertising. It is simply calculated using the formula below:

ROAS = Revenue / Cost

Take the revenue generated from the campaign and divide it by the amount you spent on that campaign, and the result will show how well your investment is performing. For example, if you spend £10,000 on ads and generate £20,000 in revenue, your ROAS will be 2. Since the campaign is generating more revenue than it costs, it will be marked as a success. But that’s not new information for marketing experts. What we are going to discuss in this article is the following: Does a good ROAS necessarily imply a successful campaign?

ROAS Issues and Hidden Costs

While ROAS has long been the ultimate metric to measure campaign performance, it may often obscure the real situation. By focusing only on top-line revenue, it lacks insights into the campaign's profitability. Namely, it does not take into account the costs of production, shipping and fulfilment expenses, payment processing fees, vendor commissions, and other variable operational overheads.

Let’s go back to our example. If your campaign has generated £20,000 in revenue from the initial £10,000 investment in ads, it has a healthy ROAS. However, if it also incurred £11,000 in production and shipping costs, the campaign is operating at an overall loss of £1,000.

This is why ROAS can be misleading, but also somewhat problematic as it can easily hide financial unviability, which is also why marketers today are shifting towards a more realistic metric: Profit on Ad Spend (POAS).

Unlocking Profit on Ad Spend (POAS)

Profit on Ad Spend (POAS) is a healthier metric used to decide both on the success of the campaign, as well as future growth planning. The main difference is that it does not refer only to revenue, but to revenue minus all the associated costs.

It’s obvious why, but we now need to understand how this switch has been happening.

The shift from ROAS to POAS has been made possible today through the use of conversational AI, which has the ability to use different unstructured data and analyse it for it to be used to understand the customer journey and help plan future marketing endeavours.

While traditional analytics platforms give insights into quantitative data (number of clicks, page views, time on site, bounce rates, etc.), they do not help to understand such data. By collecting data from on-site chatbots, voice assistants, messaging apps, and similar channels, conversational AI can offer insights into why your customers behave the way they do.

This “why” will help you differentiate, prioritise, and plan your campaigns without guessing, influencing not only the possibly misleading revenue, but, instead, profit.

How Conversational AI Does It

As we’ve already mentioned, conversational AI collects a wealth of customer data, capturing the customers’ intent, insecurities, issues, inquiries, and sentiment.

What seems to be an average customer conversation flow can now be used to drastically impact overall profit:

• Purchase hesitations and blockers: "Is this product compatible with my existing setup?", "What is your return policy?", or "Why are the shipping costs so high?”
• Product feedback and requests: "I would buy this immediately if it came in blue." or "I wish this model had a longer battery life."
• Competitor mentions and price sensitivity: "How does this compare to Brand Y's model?" or "Do you offer price matching?”

These data clearly indicate conversion blockers, provide information for product development and marketing, positioning, pricing and promotion strategies. The potential is fully realised after these unstructured data are transformed into structured and quantifiable data, through thematic analysis and automated coding.

By parsing thousands of conversations and categorising based on themes, topics and keywords, AI can allow marketers to track the frequency of each issue and thus help them decide on next steps and ways to improve the campaign’s performance.

This is why you need to keep focus on profit instead of revenue. While you may see strong revenue figures in campaign reports, these can often hide costly inefficiencies that affect overall performance.

For example, if a thematic analysis shows that 30% of cart abandonments follow a conversation about high shipping costs, the business has a useful insight to address a major profit leak.

A revenue-focused report might highlight a successful campaign based on high sales volume, but miss the fact that a large portion of users are dropping off just before completing their purchase. In contrast, a profit-oriented view would flag this as a critical issue - one that, if resolved, could significantly improve margins and the actual return on investment.

Similarly, if 15% of users express interest in a bundled or slightly lower-priced version of a product, acting on that insight could lead to more efficient sales, better inventory movement, and healthier profits, not just more transactions.

Conclusion

Transitioning from a revenue-first to a profit-first model is a complex task. It requires, naturally, adapting to new technologies, but it also means changing how you think, plan, and measure.

When you shift your mindset from revenue to profit, every pound spent on ads becomes accountable to the bottom line. The most ordinary customer conversations - structured into measurable insights with AI - become a rich source of intelligence guiding your profit and growth.

From a technical perspective, the best choice would be to choose a custom solution so that it can work perfectly with all your existing CRMs, ERPs, and other systems and tools, as well as to ensure data privacy and security.

If you are ready to make this shift, our team at Firney will gladly guide you through and create a solution that fits you and your team perfectly.