Join Corey Koberg for an in-depth discussion in this video Challenges and considerations, part of Introduction to Attribution and Mix Modeling.
- [Instructor] Okay, so we've considered the various models,…we've looked at some analysis,…and now it's time to think about…how we're going to operationalize this.…Now, I will admit this chapter won't be the flashiest:…there's not a ton of cool data visualizations…or fancy demos,…but if you're serious…about getting enterprise deployments done right,…this is required reading.…And, since it can greatly affect…the future of your business,…it's worth thinking it through,…and we're going to try and get you off to a good start.…So far, we've talked about the benefits…of attribution and mixed modeling…and I do believe that…to be far more advantageous than gut feel marketing,…but there are some challenges we have to think through…and overcome, and for some reason,…vendors aren't always quick to point them out.…
So that's what I'm here to do:…try and help you avoid some of those pitfalls.…There's a couple challenges around methodology.…The first thing we talked about…was the rules based attribution.…This is cheaper, it's often built in,…
In this course, marketing expert Corey Koberg dives into the basics of attribution and mix modeling. Corey explains what the models are and goes over a few of the most common ones. He shows how to approach offline data, goes into how attribution modeling and marketing mix modeling (MMM) work together, and shares best practices for using different attribution models. Plus, he walks through the challenges you may face when you start analyzing marketing data with models, and goes over an action plan that can help to ensure that your deployment goes as smoothly as possible.
- Determining why attribution is important
- Reviewing last click, first click, linear, rule-based, custom, and data-driven models
- Deciding when to use MMM or multi-touch attribution
- Considering challenges
- Evaluating and deploying