Predictive Modelling for Online Advertising
No longer is the ‘spray and pray’ methodology for finding customers working. No more is spamming people with numerous, unsolicited emails effective. Never again will 'stalking' with clumsy banners be cutting edge. Today it’s all about a strategy based on finding the right prospects, using the right channels, at the right time AND making them feel like they found you – not the other way around.
I will walk attendees through Marketing Science in the era of big data. We’ll begin with defining an ‘ideal/value customer’ , and - spoiler alert - it is not set in stone, smart tracking elements and AI models will allow your company to create your own portraits of the perfect customer and adjust it as you learn more, then you will know every little thing about them – inside and out.
With this knowledge half the journey is complete. We then capture those customers – at the right time and at the right place. How? We work to understand their behaviour, we capture their signals, we leverage advertising platform optimisation models, and we let the magic of data science do its thing – and shine. Every competitive advertising platform today incorporates optimisation models. I have extensive experience with some of them (Facebook, Google, Instagram) and I want to share what I have learnt and how you can take advantage of a gigantic data science effort put into those smart machines. To illustrate all of this we’ll go through various approaches, & will conclude will the model I built; the one ultimately probed & used with data scientists – at one of the biggest online advertising platforms in the world.
Outline/Structure of the Case Study
- Introduction to the topic
- ‘ Customer Value ’
- Customer Life Time Value
- Customer Classification Models
- Leveraging what the advertising Giants have to offer
- Tagging-Marketing Tracking
- Look-A-Like Audiences (Custom Audiences)
- Conversion Optimisation
- Case Study
- Purpose of the model
- Performance of the model
- Use of it
- Wrap- up
For those that are familiar with concepts such as customer lifetime value, look-a-like audiences and conversion optimisation - this talk will provide them with approaches & methodologies that could be replicated/adapted for their organisation.
For those less familiar with those concepts - it will provide then with a brief understanding as well as example approaches.
In general - I would like people to walk out:
Understanding how to take their Marketing/Data Approach to the next level
Not just do what the big advertising platforms ask you to do, look for improvements, leverage opportunities similar to the ones shown in the case study
● Data Scientists ● Decision Makers Business ( Marketing - Business Areas) ● Insight Analysts
Prerequisites for Attendees
Basics of concepts of data modelling.