What did Netflix pioneer that made them a ton of money? No, not subscription DVD-by-mail service, although in fairness, that did fetch them a bucketload of cash. We are talking about what has become the modus operandi for most companies nowadays—data driven marketing.
Companies are now catching on to the Netflix trick of using big data for data-driven decision-making. The strategy is so successful that some companies are splitting and forming companies rebranded as data companies, specifically aimed at handling the big data.
More than 90% of Americans use the internet, while a special breed (31%) is almost always on the internet. That’s a lot of data to work with.
Want to get your mind blown? Check this out: people share 300 hours of YouTube videos. Every Minute. Meanwhile, on Facebook, users share 500 terabytes of data daily.
Here’s a look at how companies can capitalize on data-driven marketing, personalized marketing, data-driven marketing B2B, and customer persona, to their advantage.
Examples of companies successfully using data-driven marketing
Consumer-centric mass user platforms like Facebook, Netflix, Amazon, and Google generate data and insights that create personalized marketing for customer personas.
The following companies harness their data’s power to transform their industries:
1.Amazon
They use big data for two main reasons: product recommendations and dynamic pricing. Amazon utilized the big data AI for data-driven marketing, leading to 2.5 million price changes and a 29% sales increase.
2.Coca-Cola
Coca-Cola took advantage of image recognition technology to determine what photos users shared socially that included the company’s popular drink. The company subsequently used the data to create personalized marketing ads that resulted in a 4X higher click-through rate.
How companies can leverage big data for marketing
The right strategies can help create customer persona and data driven marketing B2B to boost sales. Here’s how companies can benefit from data driven marketing:
- Predicting what audiences want
- Targeted advertising
- Customer acquisition and retention
- Improved media stream scheduling
- New product development and content monetization
Areas of Opportunity for Media and Entertainment Companies
Print and broadcast media has always been an avenue to create billions of dollars through consumers. For the longest time, these channels worked. However, in the wake of the data-driven era, the leopard must change its spots.
Data-driven operations offer massive opportunities, including cloud infrastructure, artificial intelligence (AI), and analytics for personalized content.
a) Cloud Infrastructure
Large media companies must focus on changing their cloud infrastructure for scalability. Think of social media, which must grapple with thousands of unstructured data in the form of photos, videos, and conversations.
The content management system must handle the volume and, through all that different content, come up with usable data and match it to people’s interests. Otherwise, terabytes’ worth of usable information is simply lying around unused.
b) AI
Artificial Intelligence is a technology that uses machine learning and programming to mimic human thinking. AI is incredibly helpful in predicting anything from consumer behavior to systems’ performance. Media companies can use AI to provide valuable insights into certain services or products.
c) Analytics for personalized content
Media companies should focus more on understanding their targeted audience to create more personalized content. Business Insider suggests that Netflix thinks its customized recommendation engine is worth roughly $1 billion annually.
Using that as inspiration, media companies should use analytics to a point where personalized marketing through contextual recommendation is possible. Their algorithms can suggest what users want to watch at any given moment.
In closing, it should be standard practice for media companies to invest in separate companies to milk the most out of data driven marketing. They can also take a leaf out of companies using data-driven operations.
