We are a PR agency looking for a data scientist to help us establish a proprietary model to demonstrate ROI to clients.
There are two areas that we would like to explore in particular:
We would like to understand how reading an article about a business/brand impacts the ultimate decision on whether to buy from that brand/business the next time you are in the market for their services.
Much of our work is about reputation and brand-building. Rather than driving immediate sales, we generate media coverage in the hope that those who read it will be more likely to consider our client’s business and more inclined to choose their business over a competitor the next time that they come to buy.
Anecdotally, we know this works but we would like to explore whether there is a way to quantify the value that this brand-building PR brings to the bottom line.
We have an in-house team of researchers who can work alongside potential MeasureMatch partners on this challenge.
We are keen to create a formula (or range of formulas) that we can apply to our clients to establish the value that a positive or negative media article would have on their brand. For example, if there is a negative media article about X brand, how many customers will they lose on average? If they secure a positive media article in X newspaper, on average how many leads will that produce?
Key challenges are that our work is about brand-building and reputation, is rarely product-focused and is part of a wider marketing mix so tracking direct sales is not always easy.
We work with brands across a range of sectors and secure a variety of types of media coverage in a broad spread of titles so a one-size fits all formula may not be possible but would be our dream solution.
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