Unlock Marketing Insights with GeoLift
In the ever-changing landscape of marketing analytics, at Jellyfish, we embrace what we call the "triple alliance of measurement." This alliance comprises Experiments, Marketing Mix Modeling (MMM), and Data-Driven Attribution (DDA). Together, these three components are poised to revolutionize how we measure the effectiveness of marketing. They offer a comprehensive framework that not only reflects the current state but also charts the path for the future of measurement. This framework allows marketers to assess the impact of their strategies better and optimize their campaigns.
Within the Experiments component lies GeoLift. Geolft, developed by Meta, is a powerful tool that has the potential to transform how we measure marketing effectiveness. GeoLift is not only open-source and cost-effective, but it also provides a deeper understanding of the impact of marketing strategies through sophisticated analysis. It leverages Synthetic Control Methods (SCM) to create quasi-experiments based on geography. It measures the true incremental impact of marketing campaigns, aiding in strategy improvement, omnichannel performance estimation, and cross-channel optimization, all while using the universal incrementality metric. GeoLift values privacy by using aggregated data only.
GeoLift's algorithm divides areas into two groups to create a synthetic control group closely mirrors a treated group's trajectory. Testing reveals changes in these zones, providing a basis for assessing the new marketing strategy's impact. This approach is a cookie and tracking-free solution, offering retailers reliable insights into their marketing efforts without needing consumer-specific data.
GeoLift: More Than Just Code
The appeal of GeoLift is twofold. Firstly, it's cost-effective due to being an open-source package, making it accessible to businesses of all sizes. Secondly, it offers robust functionality. However, it's important to note that implementing GeoLift requires a certain level of technical expertise. Written in R, it involves a wide range of parameters that may take several weeks or months to understand fully. Nonetheless, the resources required are time and expertise, which can lead to invaluable insights for your marketing strategies.
At Jellyfish, we've taken things further by developing internal tools that enhance the GeoLift experience. These tools streamline the process, making it quicker to create designs and analyze results.
Now, let's delve into the phases of GeoLift implementation and the expected timeframes.
Data Extraction and Pre-Analysis: Laying the Foundation
The first phase can be seen as the most complex one. It starts with a thorough data extraction process, collecting data on a daily basis for each location, including both offline and covariate data. Once you've gathered this extensive data repository, the focus shifts to the design phase. The goal here is to fine-tune parameters and covariates, providing the algorithm with the necessary information to create a test design that maximizes the chances of success.
By the end of this phase, you'll have a list of areas to target or exclude in your test, insights into the test's duration and the minimum budget needed to make a significant impact.
Setup and Test Phase: Precision and Implementation
Once you've decided on a test design that looks promising for success, the next step is the setup phase. The duration of this stage depends on the chosen marketing channel. Different channels come with different levels of complexity when it comes to geographical targeting, particularly when dealing with a large number of cities simultaneously. Platforms like Facebook provide tools for targeting or excluding specific cities and even allow for customizing the radius. The main objective is to ensure you're covering the commuting zones identified in your test design.
Once the test is launched, your primary responsibility is to make regular optimizations. There's not much to be done until the test is complete and you can obtain the results.
Post-Analysis: Unveiling the Impact
After the test is finished, the next step is post-analysis. You'll once again gather data, organizing it by day and location, which serves as the basis for using the GeoLift package. This tool is crucial for quantifying the observed impact. By calculating a positive or negative lift depending on the type of test, GeoLift enables you to figure out the incremental Return On Ad Spend (ROAS) for the tested marketing channel or strategy. The significance of these findings is determined through a p-value, which indicates whether the results are statistically reliable.
GeoLift is not just a software package; it's a gateway to valuable insights. In addition to being open-source, GeoLift's expertise in handling aggregated data strengthens its role in an ever-changing environment, ensuring both privacy and accuracy. Throughout every phase, from data extraction to post-analysis, GeoLift equips marketers to uncover the real impact of their strategies. In a constantly evolving marketing landscape, GeoLift stands out as a symbol of precision and trustworthiness, reshaping how success is gauged in this dynamic field.