Search engine advertising is currently facing a turning point and is the subject of much analysis, aiming to create more efficient and better-optimized campaigns. This task is increasingly complex due to the number of players and their skills.
In recent years, artificial intelligence, in the form of machine learning, has come to play a more prominent role on media buying platforms. In the case of Google Ads in particular, this development is evident in the platform’s various solutions, formats, bid strategies, and even the delivery of our campaigns. We might feel some “loss of control” in letting the algorithms work in these aspects.
How to do lead scoring
Lead scoring is a product of the need for strategic diversification and the improvement in artificial intelligence-based strategies. It’s a system that we use to make the structure of conversions more sophisticated and assign them value to give better signals to Google. It takes us from flat conversions to conversions that come with information, and that information is valuable for campaign performance.
Lead scoring was already a common practice in e-commerce campaigns, where the monetary value of transactions and the ROAS are measurable and often the main KPIs in any analysis. Nowadays, however, a lead scoring strategy can be implemented for both e-commerce and lead generation campaigns, where conversion does not imply direct revenue for the company.
In the case of e-commerce, such a strategy would mean switching to a conversion model with fictive values or average-ticket values instead of working with the actual value of each transaction. At first glance, this may seem less accurate, but the truth is that it can work even better than the traditional method.
According to Gabriel Bueno, Paid Media Consultant at Globant Create, “Lead scoring is a product of the need for a more diversified strategy and the improvement in artificial intelligence-based approaches. We must not forget the vital role that this technology is playing, in the form of machine learning, when it comes to media buying platforms. Nowadays, we can use a lead scoring strategy for lead generation or e-commerce campaigns where conversion does not imply direct revenue for the company.”
Lead scoring involves analyzing the business’s conversion funnel for lead generation campaigns. To do this analysis, we identify the various stages or actions the user moves through before the final sale. We consider the lead generation and various micro-conversions that can provide the platform with relevant information. At this point, we can make it as sophisticated as we want, achieving such a degree of precision that most traffic can be scored through conversions of different values based on the user’s actions on the target website.
Once we have identified these actions, we create the corresponding conversions in Google Ads, assigning them fictive values that correspond to their proximity to the final sale (to which we will assign the highest value). This part is essential since it’s how we tell the algorithm what is most important to us.
Once we’ve worked out the entire conversion structure, as discussed above, and collected a sufficient data sample so that the platform has a basis on which to start working, we’ll be ready to add these conversions as campaign objectives and adopt a bid strategy where the platform now takes into account not just the volume of conversions achieved, but also their value.
A strategy change of this kind will favorably impact account performance. The aim is to provide Google with signals so that our paid campaigns align better with our true business objectives.
Learn more about Globant’s specialized services in data integration, AI, and Paid Media and Search strategy to increase the potential business return on investment, take advantage of opportunities, and achieve your goals here.
