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How Becoming Data Smart Can Reduce Streaming Costs Without Losing Insight

Female streaming operations manager evaluating how to reduce streaming costs

Streaming operators need to find ways to reduce streaming costs because they are struggling with profitability. On the one hand, this is related to the cost of content versus the number of subscribers, but on the other, it is about service QoE. When there is too much buffering, macro blocking, or other issues with the streaming experience, viewers churn. The best way to solve those QoE issues, before they become revenue-impacting problems, is with data.

Thankfully, operations engineers have access to more data than ever before. So why do streaming services still struggle with QoE? Because more data doesn’t immediately equate to better QoE. It can actually have the opposite effect, resulting in rising operational costs, such as the need for more operations engineers, compute resources to process the data, and data storage, as well as longer times to resolve. This ultimately leads to a less profitable service.

What if you could be smarter about your data? What if being “data smart” also saved you time and cost while improving insight?

The challenges of balancing the need for more data and reducing streaming costs

The idea that more data can increase operational costs should scare every streaming operator. You need that data to ensure those QoE issues get resolved quickly. However, there are several ways more data can cost a streaming operator more money–and reduce the profitability of the service:

  • Data volume: Streaming operators are continually acquiring more data from third parties, more players/devices, and more technology vendors. However, there is a cost with every bit of data retrieved, stored, and analysed. When the volume becomes significantly large (terabytes per day), it can lead to additional storage, compute, and transfer costs.
  • Data insight: Understanding what’s going on in the data requires people. Right now, you may have one, two, or even more individuals. What happens when the data volume increases exponentially? It may require additional headcount or even specialised resources to help connect all of the disparate data sources in a meaningful way. In addition, more compute resources may be required to munge and process the data into a usable form.
  • Time: This is the biggest challenge for streaming operators. When data volumes increase, so does the time it takes to generate insights. In our upcoming report, “The Challenges of Streaming Operations,” over 75% of respondents reported that finding issues before they affected viewer QoE was challenging. Clearly, increased time to diagnose and resolve issues can have a negative impact on subscriptions.

Of course, having more data isn’t a bad thing. A bigger pool against which to look for issues or opportunities is great, but when that volume hinders your ability to generate insights, solve issues, or causes you to hire more people, cost becomes a concern.

Thankfully, becoming data smart will allow you to develop those insights, find those opportunities, and solve those QoE issues while saving time and money.

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How to become data smart to reduce streaming costs and time

You don’t have to sacrifice the depth of your data to save streaming costs and time. By becoming data smart, you can improve your insights (lower MTTD and MTTR) without negatively impacting the bottom line.

What does it mean to be data smart?

Simply put, “data smart” means reducing your streaming costs while preserving your insights. It’s the best of both worlds. To do this, you need to answer questions in three core cost categories:

  1. Data collection. How much are you collecting? Do you need to have every record or can a sample of records (over a certain time period) do?
  2. Data storage. How much are you storing for immediate use? What is your archiving policy?
  3. Data compute. You need compute resources to process data. How much are you spending each month? Can you reduce it by reducing the data volume?

Becoming data smart requires you to evaluate three streaming cost categories

Getting smart about your data is making important decisions related to those three categories. Consider the following:

  1. Data collection. Collect only what you need until you need everything. Create business logic to capture a sample of records. When there is an anomaly within the sample, such as certain values reaching or exceeding thresholds, capture all the data. This can also reduce the data ingest costs.
  2. Data storage. Store only what you need in accessible storage. Send everything else to long-term storage so that it can be looked at later but costs less. Archive data frequently.
  3. Data compute. Compute costs will naturally fall along with the data volume. If there is less volume of data to go through, there are fewer compute cycles needed.

Applying data smartness to your streaming operations to lower costs

Although being data smart is an approach to how you collect, store, compute, and use data, it’s hard to implement it within streaming operations. Technology can help but even then, it’s easier said than done. You can spend your time building and managing middleware (for the business logic you’ll need to collect, store, and compute only what you need) or you can try and find a partner to help you do that. The main issue of doing it yourself is that it may require technical expertise that you don’t currently have, and hiring more engineers goes against the whole cost savings of being data smart. What’s more, you’ll probably need to find a few tools to do this: one for business logic and one for data collection to support your business logic.

The benefits of becoming data smart with Touchstream

Touchstream enables your operations engineers to better monitor and manage your streaming service which will, in the long run, lower your streaming costs. So what are the more tangible benefits of using Touchstream to get data smart? With Touchstream, you will:

  • Reduce data volume (without sacrificing insight)
  • Reduce data storage costs
  • Reduce data compute costs
  • Reduce time to find issues
  • Do all this without hiring new people

Reduce streaming costs and save time without sacrificing insights

You don’t need to sacrifice insights by cutting back on your data. Even as your data grows exponentially, as you feel the need to hire more people, and as you struggle with increasing storage and compute costs, you can make smart decisions about your data that actually decrease time to find and resolve issues and reduce streaming costs. The good news is, you don’t have to do it yourself. Touchstream can take you from “data zero” to “data hero” overnight. 

Want to understand more about the challenges of streaming operations? Sign up here to receive your copy of the “The Challenges of Streaming Operations” research report by Touchstream and the Streaming Video Technology Alliance the moment it is published.