Attribution Strategies for High and Low Consideration Products in Paid Media

Consideration in the buying process is a key factor that affects both the marketing strategy and the attribution model we implement. Differentiating between high and low consideration products or services significantly influences how we approach digital advertising.

For low-consideration products (whether B2B or B2C), purchasing is more impulsive, the decision process is brief, and the focus is on aspects such as availability and price. Here, attribution tends to be more straightforward. A model that focuses on the user’s most recent interaction is often used, as these products have a short decision cycle and a transactional focus.

On the other hand, when we talk about high-consideration products, the approach changes significantly. Decisions typically involve multiple stakeholders and require more time and analysis. In the B2B realm, this means long and complex sales cycles. Here, it is essential to choose an attribution model that captures the cumulative impact of each interaction, adjusting the attribution window to properly reflect the customer journey. The goal is to attract, educate, and build trust throughout the process.

Let’s consider a practical example: a campaign to sell a standard printer in the B2B space versus a campaign for a complex ERP software. This contrast illustrates how different levels of consideration require distinct approaches in terms of attribution models, to adapt to the complexity and duration of the decision process. The printer, being a low-consideration product, might have a shorter attribution cycle, possibly incentivised by a direct offer. But the ERP software would require multiple touchpoints: remarketing ads, downloadable content, forms, demos, and meetings, with the value of each interaction needing to be assessed to understand the customer’s journey.

The important thing is not to apply the same analytical criteria to all campaigns, but to recognise the nature of the product and how users progress along their journey. In paid media, it’s essential to adapt the attribution model based on the type of consideration and the value of the product or service. In addition to optimising campaign performance, you’ll also gain specific insights into purchasing preferences, friction points, and customer decision patterns.

What kind of products or services do you usually manage in your campaigns? High or low consideration? Let me know in the comments.

Redefining Attribution: Strategies for Low-Quality Data

I am going to share one of the methods I have used to make a good attribution of sales data, leads, etc. when the data is not very reliable or of questionable quality.

The method consists of the following: first, I classify the channels from most reliable to least reliable, according to the history of the quality offered in the data of each channel, or whatever criterion is considered most appropriate. Then, I assign the results to each channel in the established order, starting with the most reliable channels, until I reach the last channel and assign the rest of the results that could not be attributed to the previous channels.

This method has worked quite well for me when I have an internal database on the website that tells me the total number of sales, leads, or whatever KPI I need to measure. The ideal scenario will always be to try to get as much accuracy as possible in the data we get from the tools, but there are cases where this is not possible.

The main limitation of this method is that it does not consider the possibility that multiple channels may have contributed to a single conversion.