I have developed a simple attribution calculator in JS. Given 2 or more binary channel variables it calculates the weights based on some probability calculus. Basically the credit of x1 for y’s conversion is given by the conditional P(y|x1 and not x2).
This was inspired by Huayin Wang’s approach Huayin blog.
Marketing Mix Modelling has been around for a long time, digital attribution (non last click) has been around for maybe the last 5 years. The challenge is how to come up with a holistic evaluation approach that gives all media the correct credit.
This is tricky because digital data is at user/cookie level whereas traditional media (TM) data is aggregated. However I think they can be combined. The trick is to merge the data at a particular level. For instance if the TM is at region and date/hour, then you can insert a hypothetical, weighted TM event into the digital data. For example if the GRP for region A at hour 10 is 120 then insert such an event for all users that had a digital event a few hours after 10 in region A. The assumption here is that usually TM precedes a digital event (eg search). Here you can use Adstock or other sequential functions to create a lasting effect. Once you have created such artificial events you can run your model of choice to predict conversion and hence assign credit to channels. Note that the TM->digital assumption introduces some bias in your model.
You could also give a higher weight to Outdoor media for (digital) mobile users as they usually are on the go. If you have demographics in your TM and digital data you can match even better.
We used Ocado for many years for our food shopping and got very used to their website. The Waitrose website despite some improvements is still behind. It is quite slow and the login page has some bugs.
It doesn’t even have an auto-fill basket option. This github page has some simple Python code to predict items that should be auto-filled: Github Hopefully a Waitrose developer will get inspired.
I think privately educated children have 4 advantages over publicly educated ones:
1. More funds to attract better teachers
2. Genes: parents that have higher IQ which makes them earn more
3. Richer parents which are giving more support and better protection, they want to see the money invested pay off
a. Schools sometimes exploit this and involve parents in school activities
4. Self selection: set of students that enter the school have higher average attainment at the start and less weak students pull down the average (since the public schools are deprived of these gifted children it works against public schools)
This means that it is much easier for them succeed. This is not to say that public students cannot achieve success but there are many barriers for them.