Is your organization building trusted consumer relationships that help you monetize your streaming content? In our first blog of the Consumer Intelligence series (1st Party Data, Clean Rooms, and Privacy — Why it’s so Hot), we emphasized the importance of your 1st party data and how Infinitive helps companies get the value out of their data by a 3-step process – Collect, Protect, and Connect. In this article, we will discuss the Collection step of the process.
What’s Your Data Strategy
The introduction of Direct-to-Consumer services and the collection of 1st party data significantly changed the media landscape by opening new data sources. It is important to recognize the difference between having data versus having data AND understanding what that data means. According to a study conducted by the Boston Consulting Group and Google, companies using 1st party data for key marketing functions achieved up to a 2.9x revenue uplift and a 1.5x cost savings when compared to companies focused on anonymous consumer signals – that is a big business impact!
Although benefits of 1st party data for Publishers are well known, many of them are not yet truly leveraging their data’s full potential. One of the main reasons for this is that their Data Strategy is lagging the new reality, or even worse, there is no Data Strategy at all.
Data Strategy is the coordinated plan to map analytics capabilities to business objectives. In other words, it gives you the clear vision and roadmap on how your data can support you in: building stronger consumer relationships, creating more relevant content, reducing subscription churn, boosting overall ad performance, and more.
How to Think About Data Collection
Data collection is a critical first step in building your Data Strategy which creates a strong base for achieving your overall business value and the ‘360 Consumer View’. It is more complicated than just ingesting data from multiple sources. The following are the basics to enabling your data collection.
Start with the Right Questions
The lack of a plan to choosing which data to collect is holding Media companies back from using data effectively. To overcome this challenge, companies must know exactly what answers they need from their data that will support their business objectives. Then it is a matter of auditing all internal data sources, understanding your current data, figuring out what additional information you require from your consumer base, and how to get it. Questions like “Is there new data that you can collect from your consumers in a trusted and value building way?” or “Do you need data from another 3rd party source that can augment the data that you have?” can help you calculate the cost of acquiring this data, what complexities are involved, and how to prioritize acquiring the data.
Data Silos & Disparate Applications
In an effort to achieving a 360 view of the consumer, part of data collection is overcoming the very real problem of data silos. Integration is key to obtaining the 360-degree consumer view. According to the Harvard Business Review, 90% of respondents say data and system integration across all channels and products are very important to delivering on their consumer experience strategies. The average company has 129 applications, and about 10% of businesses have more than 200 applications! – It is no surprise why consumer data integrations can turn into a nightmare if not planned effectively.
Invest in Tech
In order to store collected data, process, and consume it, you need to figure out what tools, services, and technologies will support your data needs. For example, let’s assume you have a use case of delivering real-time personalized Ads to your viewers. In this situation, you may use a streaming service such as Kafka or AWS Kinesis to ingest real-time web/mobile analytics data about the viewer’s behavior. In addition, you should store the data in a low-latency database such as DynamoDB because downstream applications require extremely fast response rates to make the ultimate decision of what Ad is relevant to the viewer in real-time.
However, you need to use different applications if your use case is to analyze large historical data sets to discover viewing patterns. In this case, you will likely store the data in a Data Warehouse such as Redshift or Snowflake and use a visualization tool to create reporting.
In this area of technology you are creating a data ecosystem with these elements:
- Data Lake and Lake House platforms, such as Databricks, for centralized data collection and processing
- SaaS tools such as a CDP (Customer Data Platform) to leverage enhanced customer segmentation features
- ETL and Data Processing tools for integrating and standardizing data from multiple apps
- Data Clean Rooms such as Snowflake for secured data sharing among partners
Oftentimes, we see redundancy and overspend in the tools and services used in an organizations ecosystem. Therefore, your use cases will carefully dictate the choice of technology and tools that are right for you.
This is all about standardizing the way data is collected, modeled and processed downstream. Ultimately, having the right data process allows you to shorten the time it takes for raw data to become an actionable insight. The companies that are able the act upon the data as quickly as possible typically have an advantage over competitors. It is small margins that make the difference.
Data Science and ML
Your data collection process and storage must enable your Data Science teams to easily access and consume your unstructured, semi-structured, and structured data. This goes back to choosing the right tools and platforms. Integrated Data Platforms such as Snowflake and Databricks are great examples of this. While it allows you to collect, store and govern your data, it provides features to your Data Gurus to innovate, implement predictive models, and extract the maximum benefit out of your 1st party data.
Build the Team
Last but not least, you must build a capable team to help you put all of the above together and maintain it going forward. This is where Infinitive can help you and your team accelerate your data program to drive your business impacts and meet objectives. The tools, the flexile and scalable infrastructure, the well-defined collection processes, the ease of breaking silos and integrating new datasets, the automation – all of these are done so your people can navigate with ease and ultimately get you the 360 consumer view and answers you need to fully leverage your 1st party data.
Looking ahead: Step 2 – Protect
In our next blog we will focus on Step 2: Protect your data. The market is constantly changing how we engage with consumers and what 1st party data is available to build up strong consumer relationships. By focusing on protecting consumer data through cloud governance, data security, and complying with consumer data privacy laws – you can avoid burning down the trusted consumer relationships that your business is built on.