How Less Data Drives More Revenue

Data

How Less Data Drives More Revenue

Posted by justin.reilly on Oct 14, 2014 12:44:29 PM

"No great artist ever sees things as they really are. If he did, he would cease to be an artist."

— Oscar Wilde

Big Data can transform our lives. At their core, The Internet of Things, Connected Cars, and AI are all rooted in a singular idea: that some day we will be able to consume a tremendous amount of data, contextualize it, and deliver a meaningful experience that makes our lives easier. While we have succeeded in finding ways to collect large amounts of data, 90% of the world’s data was generated in the last two years, we are still living in a world where our tools lack context, empathy, and relevance.

A number of firms have started to show off their data chops, for better or for worse, by harnessing these tools. Facebook ran a controversial experiment to see if it could influence the day-to-day mood of its customers. OkCupid followed suit, largely in jest, releasing a study  proving the inherent vanity of its user base.

Whether the Facebook or OKCupid initiatives yielded any real value, internally or externally, still remains to be seen.

Netflix, however, has proven that a data-driven approach to screenplays and casting can lead to huge successes with its critically acclaimed series, House of Cards. The platform, which boasts a whopping 30 million ‘plays’ per day, realized a convergence of three insights that lead to the Emmy Award Winning show. Netflix users love three things: David Fincher (Director of The Social Network and House of Cards), Kevin Spacey, and the british version of House of Cards. Through meta data, user preferences, and ‘suggestions taken’ (a metric that tracks how many times you choose a show that Netflix suggests for you), they are able to pinpoint what you like, why you like it, and what to show you in the future. Netflix has seemingly created a secret sauce for content creation.

So why not continue down this path to optimize beyond the creation of shows and start allowing crowdsourced feedback to influence the plot?

Netflix CEO, Reed Hastings, says this will never happen. Largely due to the fact that his artist refuses to be influenced by the data. Hastings showed Fincher metrics indicating plummeting user drop-off during the brutal dog-killing scene in Season 1 Episode 1. Fincher’s response to Hastings, “Don’t ever tell me that again.”

 

As Pando Daily founder, Sarah Lacy, put it:

“Content has a big data problem, but that problem is not about crowdsourcing story lines. It’s about targeting the people who actually want to sit through that gory dog-killing scene.”

Data can inform Art. But if it dictates the brush strokes, we lose the painter. And his Truth.

In stark contrast to Hastings and Fincher, Scandal creator, Shonda Rhimes has openly admitted that she has allowed fan feedback to influence the direction of her show. Some would argue that this has saturated the narrative and will lead to an increasingly inauthentic show, should Rhimes decide to continue beyond a 5th season.

So what did Netflix get right?

Hastings & team focused on three main keys for translating Insights into great Content:

  1. Understand Your Target Audience — Being Customer Centric isn’t giving all of your customers exactly what they want. It is understanding the wants & needs of your top customers; the ones that hold the key to long-term profitability for your brand.
  2. Minimum Viable Data — Focus on the 3–5 pieces of information that will help you understand what your top customers want & need. Everything else is clutter.
  3. Context is King — Data is meaningless without Context. Once you know who your customers are and what they want, it’s time to hand over the insights to your best creative resources and let them build the most relevant, empathetic piece of content (read: art) imaginable.

At the end of the day, your goal is to provide as much value to your customers at the exact moment when they need it most. Why churn the ocean? Start small. Be relevant. And they will remember you for it.

Topics: Big Data, Digital Marketing, Customer Experience, Innovation