Welcome to Predictive Marketing University

Jacob Shama, PhD
Learn how to leverage data science to improve your marketing and boost revenue

Examples of Predictive Marketing

TRANSCRIPTION:
Here are a few examples for using Predictive Marketing.

Reading about Predictive Marketing in the media gives the feeling that it involves some kind of magic. However, there is nothing further from the truth. Predictive Marketing is rooted deep in science and uses math, statistics, data mining and machine learning to deliver its predictions.

Predictive Marketing has been popularized by companies like Amazon, Facebook, and Netflix that are all using sophisticated algorithms to engage their customers, increase sales and advertising efficiency.

One famous use-case of using Predictive Marketing is Netflix’s “House of Cards”, which won the Emmy award in 2013. Netflix used data from its 27 million US subscribers. According to their analysis, movies directed by David Fincher, the director of “The Social Network”, were watched from beginning to end.

Kevin Spacey is one of the most popular actors, while the British version of the “House of Cards” has done very well. When they combined the three elements, they figured out that “House of Cards” was going to be a hit series.

However, this is not the first time that Netflix is using data to get greater engagement with content. Over 800 engineers are working at Netflix and its recommendations algorithm is responsible for 75% of viewer activity.

In fact, predictive analytics is so fundamental to Netflix’s business model that in 2009 the company offered 1 million dollars to a team or an individual that would improve its recommendations algorithms.

The prize was given to a team of scientists that improved the algorithm by a little more than 10%.

Amazon is another famous use-case of Predictive Marketing. The company recommends products and services to users based on their past behavior. Some say that recommendations are responsible for as much as 30% of Amazon’s sales.

The potential of Data-driven marketing has attracted a lot of attention. Some of this attention came from venture capitalists and industry players that invested over $5 billion in the past few years in Data-driven and predictive marketing.

What explains this large investment in Predictive Marketing? Predictive has the potential to significantly improve the effectiveness of sales and marketing.

For example, according to lead generation platform Madison Logic, the average cost for B2B lead is $43. If only 1% of these leads, for example, will convert to a deal, the cost of this deal (only for lead generation) would be $4,300.

However, if we improve conversion rate to 2%, the cost of the deal is significantly lower and sums up to only $2,150. If we improve conversion rate to 3%, the cost of the deal would decrease to $1,433. This calculation does not include other benefits from higher conversion rate such as increase in the efficiency of the sales force and the increase in motivation of the sales reps.

If you have any question, feel free to contact me directly at PMU@mintigo.com or on Twitter using my handle @JacobShama.


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