Magazine article Marketing

What Marketers Can Learn from - Hollywood

Magazine article Marketing

What Marketers Can Learn from - Hollywood

Article excerpt

The art of quantitative prediction is reshaping business, government and even Hollywood.

Data-based decision-making is on the rise all around us. While marketers may well be forgiven for believing that big data has become a one-size-fits-all solution for any given marketing problem, advancements in analytics are, rightly, at the top of the business agenda.

Epagogix is at the forefront of this renaissance of data intelligence By combining advanced artificial intelligence with algorithms and traditional risk-management tools, it provides Hollywood studios with insight into the likelihood of a script's success.

So we asked Nick Meaney, the chief executive and co-founder of Epagogix, to take us behind the scenes to show how studios use analytics, and whether marketers can get in on the act.

My colleagues and I smiled at the specificity of this email request. Could we identify likely advertising award-winners, when the point of Epagogix's core film services - as acknowledged by our correspondent in his opening paragraph - is to determine earning potential, assisting our movie-studio clients to make appropriate business decisions based on that critical information. They don't ask us to forecast Oscar-winners.

We wondered why the advertising agency he worked for had not instead asked the following question, which might have more value to its own clients: 'Can you help identify the ads that will help to sell more products/garner more brand recognition or produce the best return on investment?'

Our new advertising chum, who turned out to be a very bright guy, had, however, made the generic connection between the movie world, where Epagogix plies its core services, and the field of marketing, where individuals with creative duties and those with commercial responsibilities are also compelled to find satisfactory ways to work together to please clients, audiences ... and themselves.

Epagogix is a company that helps US film studios and international independent producers to make critical decisions in the film-making process.

Feature-film-making expenses and the costs of US theatrical distribution and promotion have grown so high that some of Hollywood's most senior management figures seek objective, external advice regarding which scripts are going to be hits. We help the studio determine whether a given script warrants the allocation of its capital, regardless of the script's provenance, and how it might maximise returns from the movies in which it does invest.

Our company is able to provide movie-industry clients with accurate forecasts of North America box-office takings. We work with scripts, before large amounts of finance are invested in the production. We use our own proprietary expert process, combined with custom-built neural networks, to forecast the likelihood of success.

Neural networks are cutting-edge artificial intelligence - think souped-up computer-enabled algorithms. Each is bespoke, developed from historical data unique to the situation under analysis. They are able to crunch vast amounts of information and identify trends and patterns that, typically, would elude human analysis - and, if expertly programmed with reliable historical data, they are able to predict future outcomes. Neural networks are used in many sectors, particularly in banking and finance, but also in logistics, pharmaceuticals and beyond.

This risk-managed approach to producing films is also of increasing interest to those involved in feature-film financing - an area simultaneously appealing as a non-market-correlated investment asset, and off-putting because of the risk involved and litany of past film-investment failures.

Beyond big data: creative risk management

Epagogix grew into this niche in big data partly from our origins in the City of London. Working for a big risk-management company, I had noticed that there were opportunities for deploying artificial intelligence to better understand the huge amounts of data in relation to the risk and insurance industry. …

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