It has long been understood that different advertising channels interact and influence each other in different ways. However, only recently has the world started to gain true insight on the impact of these.Through attribution analysis we can start to truly understand the impact of every channel of your marketing. From this, we are able to build a bespoke model for you which will help us to optimize and report the true impact of your campaigns.

The benefit

The benefit of working this way is that we can establish if certain channels need to be increased, decreased or removed altogether from the marketing mix. We can do this right down to keyword-level in your PPC campaigns or audience-level in RTB – understanding how users will evolve from one interaction to another. Just because they eventually convert on a brand term doesn’t mean that this is the only touch point that happened in their journey.

Many targeting methods will be designed to drive awareness at the research stage and ultimately increase the likelihood of a conversion further down the line. Without measuring this impact, the natural assumption might be that they’re underperforming and need to be removed.

Attribution modeling at Search Laboratory consists of:

Initial modeling

Using our experience of multiple markets we will estimate an attribution model for your business. This consists of a mix of models for different path types.

Data gathering and analysis

Advanced analytics provides data on converting and non-converting paths to test the model.

Refinement of the model

Using the data, we refine and improve the model over time in order to maximize your conversions.

The output of the attribution analysis is the ability to make informed decisions on the level of spend and activity on certain channels (paid search, display advertising, natural search, email marketing etc.) or segments of those channels (brand PPC, categories of SEO keywords) in order to maximize your profit from all activity.

For more information on this please contact us on (646) 473-1826.