Going from Big Data to Big Insights to Big Revenue

How Video Companies Can Capitalize on their Data


Last month, the Media & Entertainment Services Alliance (MESA) published a thought-provoking article on a growing challenge for organizations: how to transform from being data-driven to being insights-driven.

“We’re only accessing a subset of all the data available, yet the amount of data that we collect continues to grow very quickly.”

In this new world of Big Data, the marketing challenge of the 21st century lies in the way smart companies are capitalizing on their data. It’s a shift that is enabled by business intelligence applications — like the Wicket Scorecard — built on top of companies’ data and enterprise assets.

Shifting from Being a Data-Driven Company to Being an Insights-Driven Company

Hugh Owen, SVP of Product Marketing at MicroStrategy, stated the problem quite succinctly:

“We’re only accessing a subset of all the data available, yet the amount of data that we collect continues to grow very quickly.”

It’s a simple problem with a not-so-simple solution, but the benefits of solving the problem are huge. Recent studies suggest a solid correlation between agility and overall business success, but the sheer amount of data an organization must draw on makes agility a lofty goal, in many cases.

The MESA article posits some data points that are truly revealing in their depiction of the challenge:

“insights-driven companies are growing at an average of more than 30% annually”

Forrester Research VP Boris Evelson says that the number of companies storing more than 100 Tb of data nearly doubled in 2017, yet only 10-20% of that data is utilized for analytics. Evelson goes on to say that “insights-driven companies are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021. Such companies will be growing 8-10 times faster than their non-insights-driven rivals, through 2021.”

The real lynchpin to shifting into insights-driven business decisions is no longer the data itself, which twenty years ago would have been a challenge just to collect and organize. The lynchpin now is how to leverage advanced technologies and analytics capabilities to make better decisions with the data.

Artificial Intelligence (AI) and Machine Learning (ML) are quite the hot topic in tech circles, and those technologies certainly have their place in data analytics and insights. As Evelson notes, “ML is playing an increasingly important role in BI platforms and one positive sign is that ML is now combining insights from structured and unstructured data.”

Organizing Data from Multiple Silos to Gather Critical Insights

A MicroStrategy survey revealed the top three barriers to more effective use of data and analytics are:

  1. Data privacy and security concerns (as reported by 49% of respondents)
  2. Data access is limited across the organization (33%)
  3. Current solution is too complicated (28%)

While the first concern can be allayed with checks and balances on vendors and a more secure infrastructure, the second-ranked barrier — limited access to data across the organization — seems to be a little more complex.

MicroStrategy also suggests from their survey that, over the next five years, cloud computing will be the trend expected to have the greatest impact on analytics and insights initiatives, according to 24% of those surveyed. Though cloud computing will be (and already is) a game-changer in business intelligence, multiple streams of cloud-based data may give rise to a culprit laying in the cut: data silos.

In his Harvard Business Review article Breaking Down Data Silos, Edd Wilder-James says, “Every CIO I meet tells me that they are excited at the potential of analytics for their business. With one caveat — they can’t get their hands on the data in the first place.”

Wilder-James goes on to mention that much of an enterprise’s data are locked up in silos that make it costly to extract the data for analysis and insights. A solution to this data chaos might lie in the organization’s ability to choose business intelligence platforms — like the Wicket Scorecard in the video industry — that can draw on data from multiple sources and aggregate it into valuable, actionable, and meaningful insights.

How the Wicket Scorecard Drives Insight for Video Companies

We’ve talked about the need for companies to shift from being data-driven to being insights-driven. And we’ve mentioned some of the barriers like complicated BI solutions and data silos. For streaming video services that stake a lot of their revenue on their ability to use data insights to make decisions, the Wicket Scorecard overcomes the barriers to realizing a more insights-driven strategy.

We mentioned in a previous article that a primary value proposition of the Wicket Scorecard is the ability to unlock interesting insights which can only be realized by combining and harmonizing data from multiple sources.

The Wicket Scorecard presents actionable subscriber insights drawn from a variety of sources — including internal data, site analytics, subscriber data and others — in effect solving the data silo challenge. By adding in a machine learning layer as well, the solution can deliver more powerful insights from correlations and predictions, not otherwise readily available in those disparate data islands.

chart of customer status by source

Fig. 1 – Customer Status Per Source. See how Marketing sources perform throughout the complete customer lifecycle.

The result is a solution that can help video streaming companies understand not only what is happening with their subscriber-base but why things are happening. We provided an example of Wicket Scorecard’s insights and analytics in last month’s article which is worth revisiting — connecting marketing spend to subscriber health.

First, we see that data has been harmonized from multiple sources, such as a site analytics tool and subscriber management systems. But what now? What can we learn from these insights to help make better decisions?

By having one simple view of these harmonized data points, we can catch something that might have otherwise gone unnoticed.

By having one simple view of these harmonized data points, we can catch something that might have otherwise gone unnoticed. With the ‘Ads’ source data alone, a marketer might conclude that the ‘Ads’ source is performing beautifully, given that these ads are bringing in lots of free trials. By marrying that top-funnel performance data to the rest of the subscriber-lifecycle data, we see that the ‘Ads’ source boasts a disproportionately high churn on free trials and lost customers. This might lead a savvy organization to remedy the situation by testing new advertising approaches or redirecting spending to more effective channels.

Media companies are taking the challenge head-on to become more insights-driven, and the Wicket Scorecard is a key enabler for those companies. If you’d like to learn how Wicket Labs can help present your subscriber data in a way that allows you to derive insights and make better decisions, please contact us. We always enjoy the opportunity to demonstrate how your data can be turned into actionable insights that will help your business grow!


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