Just finished reading the book "Streaming, Sharing, Stealing, Big Data and the future of entertainment" by Michael D Smith And Rahul Telang
The pillars for the strength of the entertainment industry have always been - creativity in content, content presentation in new and attractive ways, adapt pricing mechanisms for reach. The industry was always customer centric and depended on best practices around them.
Yet, the established firms (Hollywood) appear to have missed out on a major area - data collection to the finest detail that affects everything - understanding the customer, dealing with the competition, staying ahead and winning. All these areas are not new to running a business known to be established.
New ways of content creation and management, data-driven connections and decision making, intelligent and smart ways to reach and retain the customer are enough to create wars and win in this industry. There is much to learn about online retail from Amazon, data management from streaming companies such as Netflix, targeted advertising from Google for the established industry majors.
Telang and Smith did a remarkable job in their book highlighting the challenges for the established and how the challengers like Netflix, Amazon, Apple, and other platforms are superseding them. The majors have much to focus on their organizational structures and culture of decision making to play catchup.
My focus here is the chapter Pride and Prejudice from this book. In a nutshell, the chapter covers the complex topics of big data management and digital marketing for a digital store in an exploratory and readable fashion.
Some of the details discussed are about data collection in terms of
- collecting personalized data about customer's behaviors for metrics as well as experimenting further to seek new opportunities for marketing the 4 Ps (product, place, promotion, price) and connecting customers to content.
- embrace a culture of data-driven decision making that includes predictive analytics.
Assuming great content is created, data plays a powerful role in connecting with customers, launching the product in effective ways. Think subscription services and to bundle here. Diverse, multi-channel consumption with a handle over price elasticity (how price change affect sales?) is a strength of the internet offerings. Timing, deployment models are yet other factors that come into play for pricing. Allow for better targeted and profitable ad campaigns. Targeted ads can accommodate instantaneous responses to address changes in demand using data and machine learning techniques. Discover and predict changes to present the portfolio of popular titles to the front of virtual stores.
Netflix is an exemplary digital platform. It matches creative content directly to viewers with the help of data. I found the following research articles very useful in understanding how Netflix is able to make streaming its strength.
Dreier, T. (2018). Netflix Uses Data to Drive Creativity, and It's Terrifying Hollywood. Streaming Media, 15(4), 6-7.
(In this article, the author explores the topic of big data management at Netflix with Prof Michael D Smith - who authored the book along with Telang).
Fernández-Manzano, E., Neira, E., & Clares-Gavilán, J. (2016). DATA MANAGEMENT IN AUDIOVISUAL BUSINESS: NETFLIX AS A CASE STUDY. El Profesional De La Información, 25(4), 568-576. doi:10.3145/epi.2016.jul.06
LaPorte, N. (2017). Can Netflix Slay the Mouse?. Fast Company, (220), 27-30.
NEWMAN, J. (2017). Apple TV gets cozy with Amazon Prime, so where does that leave Netflix?. Pcworld, 35(7), 50-54.
Joon Suk, H., Youngjoon, C., & Kyu Tae, K. (2017). Specificity and Commitment: UX approach to Netflix. Journal Of Korean Society For Internet Information, 18(6), 127-136. doi:10.7472/jksii.2017.18.6
(www.jics.or.kr/journals/jics/digital-library/manuscript/file/.../JICS-2017-18-6-014.pdf)
The pillars for the strength of the entertainment industry have always been - creativity in content, content presentation in new and attractive ways, adapt pricing mechanisms for reach. The industry was always customer centric and depended on best practices around them.
Yet, the established firms (Hollywood) appear to have missed out on a major area - data collection to the finest detail that affects everything - understanding the customer, dealing with the competition, staying ahead and winning. All these areas are not new to running a business known to be established.
New ways of content creation and management, data-driven connections and decision making, intelligent and smart ways to reach and retain the customer are enough to create wars and win in this industry. There is much to learn about online retail from Amazon, data management from streaming companies such as Netflix, targeted advertising from Google for the established industry majors.
Telang and Smith did a remarkable job in their book highlighting the challenges for the established and how the challengers like Netflix, Amazon, Apple, and other platforms are superseding them. The majors have much to focus on their organizational structures and culture of decision making to play catchup.
My focus here is the chapter Pride and Prejudice from this book. In a nutshell, the chapter covers the complex topics of big data management and digital marketing for a digital store in an exploratory and readable fashion.
Some of the details discussed are about data collection in terms of
- collecting personalized data about customer's behaviors for metrics as well as experimenting further to seek new opportunities for marketing the 4 Ps (product, place, promotion, price) and connecting customers to content.
- embrace a culture of data-driven decision making that includes predictive analytics.
Assuming great content is created, data plays a powerful role in connecting with customers, launching the product in effective ways. Think subscription services and to bundle here. Diverse, multi-channel consumption with a handle over price elasticity (how price change affect sales?) is a strength of the internet offerings. Timing, deployment models are yet other factors that come into play for pricing. Allow for better targeted and profitable ad campaigns. Targeted ads can accommodate instantaneous responses to address changes in demand using data and machine learning techniques. Discover and predict changes to present the portfolio of popular titles to the front of virtual stores.
Netflix is an exemplary digital platform. It matches creative content directly to viewers with the help of data. I found the following research articles very useful in understanding how Netflix is able to make streaming its strength.
Dreier, T. (2018). Netflix Uses Data to Drive Creativity, and It's Terrifying Hollywood. Streaming Media, 15(4), 6-7.
(In this article, the author explores the topic of big data management at Netflix with Prof Michael D Smith - who authored the book along with Telang).
Fernández-Manzano, E., Neira, E., & Clares-Gavilán, J. (2016). DATA MANAGEMENT IN AUDIOVISUAL BUSINESS: NETFLIX AS A CASE STUDY. El Profesional De La Información, 25(4), 568-576. doi:10.3145/epi.2016.jul.06
LaPorte, N. (2017). Can Netflix Slay the Mouse?. Fast Company, (220), 27-30.
NEWMAN, J. (2017). Apple TV gets cozy with Amazon Prime, so where does that leave Netflix?. Pcworld, 35(7), 50-54.
Joon Suk, H., Youngjoon, C., & Kyu Tae, K. (2017). Specificity and Commitment: UX approach to Netflix. Journal Of Korean Society For Internet Information, 18(6), 127-136. doi:10.7472/jksii.2017.18.6
(www.jics.or.kr/journals/jics/digital-library/manuscript/file/.../JICS-2017-18-6-014.pdf)
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