The customer sales journey is one of the most important and most difficult things to track for business owners. Understanding how clients go from initial awareness to finally converting is a key factor in making smart decisions when it comes to marketing efforts. Yet, this path has never been clear.
When I started working in paid search in 2010, last-click attribution was the standard practice. Conversions were largely attributed to lower funnel channels, and initiatives like brand campaigns and remarketing efforts were pure gold because they showed strong conversions and returns. While marketers still knew upper funnel channels were important for brand awareness, many businesses deemed them as underperformers due to not receiving credit with this attribution model.
Still today, some companies use last-click attribution when trying to gauge channel success. The issue with this is that this data provides a largely inaccurate and misleading picture, as it only relies on the last touchpoint along the consumer journey. Following only the last-click attribution model, companies will neglect upper funnel efforts that are needed for demand generation and long-term growth.
So What Should Replace Last-Click Data?
At first, data-driven attribution was the perfect solution. This method distributes the conversion credit across multiple platforms and touchpoints, providing a much better consumer journey picture. Brand awareness and mid-funnel initiatives were finally given credit, and advertisers were able to see that their investments were creating conversions. Unfortunately, this attribution method is still not 100% accurate. In order to close the gaps created by privacy restrictions and cross-devices, each platform has developed its own solutions using modeled conversions and black-box reporting.
For example, Google Ads utilizes enhanced conversions to improve tracking accuracy. However, even with these solutions, each individual platform still doesn’t see the entire consumer journey, and each uses different models to assign credit.
What Does Gauging Success Look Like?
The reality is that there is no single source of truth that can fully capture performance. Success can no longer be solely gauged on perfectly attributed data or rely only on platforms like Google Ads or Meta data.
Instead, businesses need to start looking for trends across multiple data sources to evaluate performance. This may include a combination of:
- Blended metrics like Marketing Efficiency Ratio (MER) or Customer Acquisition Cost (CAC): MER helps to provide a high-level view of your overall marketing profitability. It is calculated by taking your total revenue and dividing it by your total ad spend. A higher ratio indicates better efficiency. CAC tells you how much it costs you to acquire a new customer. This number should be lower than your Customer Lifetime Value (LTV), the average revenue or profit earned from each new customer. CAC is calculated by taking your total marketing and sales costs to gain a new customer and dividing that number by your expenses.
- Directional patterns with platform reporting: For example, if platform conversions are increasing and the overall business revenue is increasing as well, it could be inferred that the marketing efforts are having a real impact on the business. However, if a platform is reporting increased success but the overall business revenue is flat, then it is likely that conversions are being overly attributed to that particular channel.
- Incrementality patterns: When spend is scaled up or down, do the total business metrics follow suit?
Measuring What Actually Matters
None of these signals alone can prove success, but when used together, they can help determine if marketing efforts are driving growth. Your paid search strategy will need to be consistently evaluated and validated against platform performance and trends that align with the actual business outcomes.
