Bad Data Series: Blockbuster Decided Not to Netflix and Chill
Mike Baglietto |
 10/09/19 |
5 min read

Bad Data Series- Blockbuster Decided Not to Netflix and Chill

 Join us as we analyze memorably misinformed business decisions in our “Bad Data Series.” We’ll explore the many ways the wrong social analytics solution, offering inaccurate insight, could result in brands misunderstanding potential market opportunities. And missing out on category-defining moments in time

Blockbuster is the first in our series, showcasing what happens when brands rely on bad data. And underestimate niche offerings with explosive growth potential.

Getting a Feel for Netflix

Netflix was nothing, if not bold. “Back in 2000, Reed Hastings approached former Blockbuster CEO John Antioco and asked for $50 million to give away the company he founded — Netflix. Antioco, thinking that it was a ‘very small niche business,’ ended the negotiations and didn’t buy Netflix, which at the time was a DVD mailing service.”

As time would tell, this was a huge mistake.

Although Netflix’s initial business model included DVD sales and rental by mail, Hastings read the market correctly. He refocused on its initial DVD rental business, expanding to include streaming media in 2010.

And, as of April 2019, Netflix had over 148 million paid subscriptions worldwide, including 60 million in the United States. And over 154 million subscriptions total including free trials.

Did this decision (missing out on Netflix) shake Blockbuster to its core? It seems to have, as what followed can only be described as disastrous misfires. And likely in an attempt to not miss out on the next big thing.

Chipping Away at the Block

Blockbuster’s death came slowly, after a series of decisions that spiraled from bad to worse.

  • Blockbuster was late to launch its own DVD-by-mail business and rental kiosks.
  • It misread the market (again) and made a $1 billion-bid to buy Circuit City “in the midst of its death spiral in 2008.”
  • And it filed for bankruptcy in 2010, when it lost $1.1 billion. (Netflix was worth $13B at the time)

Even an acquisition by Dish Network wasn’t enough to keep its stores open. And the last ones closed in 2013.

The brand had apparently viewed itself as the key player on the block and was unaware of the ground shifting beneath its feet. By the time Blockbuster attempted to regain its footing, it had become too irrelevant and too unsure of its footing to regain momentum.

And this story could easily happen today, as there are many brands ‘on the block’ (whatever their category may be) that think they’re too popular to fail. But today’s brands have something Blockbuster did not – next generation artificial intelligence-informed analytics.

Accurate Analytics Could Have Saved Blockbuster

Social analytics was in its infancy back then, of course. NetBase was founded in 2004 and has always been a leader in the space. So, we likely could’ve helped expand Blockbuster’s market understanding beyond what it knew to what was happening beneath the surface.

And today, of course, as we’ve kept our technology and customers ahead of the social analytics curve, we could definitely capture transformative insight for them (if they still existed) today!


There are lots of way to use social analytics to predict niche offerings that will potentially change a category. In this series, we’ll inevitably hit on all of them, but will share a couple here today to kick it all off.

Understanding Trends – Something Blockbuster Missed

Brands can analyze what’s trending in a category, around a specific topic or their brand(s) and filter the results in multiple ways to capture Terms, Hashtags, Emojis, Brands, People, and Things.

As you can see below, the Trending Widget displays a table that lists up to 50 of the conversation’s trending items. For each of the columns, we see Insights, a Trend Score and Posts

  • Insights lists the top insights, such as Things or Terms, according to the display setting at the top left.
  • The Trend Score displays a value indicating whether an insight is trending up or down. A score of 0 to 1 means that the insight is trending downward; a score between 1 and 100 means that the insight is trending up. The score incorporates multiple factors, including the change in volume and percentage of change over the last period into a single number. This allows you to detect a variety of different trend types, such as new and emerging insights, sustained insights, and reemerging insights.
  • Posts displays the number of posts for the insight over for the last period, along with a sparkline to illustrate the insight’s trend over the last period.

Understanding Trends to avoid bad data

Preventing Bad Data Decisions by Indexing Conversations for Comparisons

Understanding how a trending conversation compares to category conversation is super helpful and the Index Widget does just that.

The index value ranges from 0 to 50+ and it expresses the ratio of a category’s share of posts (or authors) in the target topic to its share of posts (or authors) in the comparison topic.

The bubble chart enables you to compare the percent share of top terms across your topic versus a comparison topic to help visualize what terms are over-indexed (green) or under-indexed (red).

  • The chart can display bubbles or emojis.
  • Each bubble or emoji’s size is relative to its post or author count to show how much an item is being talked about.
  • A bubble or an emoji’s horizontal position on the x-axis indicates its index level when measured against the comparison topic. Bubbles to the left of the graph are most under indexed; and on the right are most over indexed.
  • Bubbles are shaded to indicate whether their sentiment is positive, negative, mixed, or neutral. And brands can click on any of them for further exploration:

ndexing Conversations for Data Comparisons

Accuracy in each is paramount, of course. Without the ability to interact with each data point and explore the sentiment, origin, brand relevance and potential amplification of each, the insight is largely useless.

So, be sure the social analytics tool you’re using is exceptionally transparent. And take to ensure the insight it offers is the highest caliber, offering accuracy you can bet your business on. Because if you act on something in a Blockbuster-esque fashion, you will be!

And all of the insight mentioned above is category capturing intel for any brand to have. But AI Studio makes it even more amazing.

AI Studio Predictions

AI Studio automatically surfaces relevant, related themes from the insight brands capture in their topic search. This helps your brand make connections to things it would likely never consider otherwise.

That’s the beauty of it – there’s no human bias to contend it. There’s just pure artificial intelligence designed to make the most of every bit of data at its disposal. And its source data is best defined as legion.

The best part? It’s the only AI solution out there that’s capable of doing this. So, once you’re in you can be sure you’re finding insight ahead of competitors (assuming they’re not already using NetBase, as many industry leaders are!).

AI Studio taking brands beyond surface insights and avoiding bad data

It opens up a whole world of possibilities – niche ideas worth pursuing or at least reviewing. Ideas that could have propelled Blockbuster to be the next Netflix, instead of being disrupted by them. And your brand needs to be on the lookout for the next Netflix in your category! There are so many contenders for your client base these days.

Don’t allow your brand to lose out by using the wrong social media analytics solution. It’s entirely unnecessary. There are exceptionally accurate offerings on the block, and we top that list! Reach out for a demo and we’ll show you the NetBase difference.

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