Accelerating Your Journey to Data Monetization

It’s 2020, and with oil briefly dipping into the negative, data seems to be solidifying its position as the new oil. Like oil, it can be used both to create products and generate revenue as a standalone product. Similarly, it does require some engineering efforts to ensure you get the most out of it.

Many companies are looking to monetize their data, and we provided some ideas on how to monetize and get the most out of first party data in our earlier blog. This blog will focus on how to accelerate that journey, and the various factors that businesses must consider.

Successful organizations have spent years and made big investments transforming their business and operations to create a Data and Analytics ecosystem that enables them to understand their customers better and monetize their data by selling data as a product. Our experience with them has taught us that there are three key considerations that can help accelerate your journey.

While many companies have taken time to overcome the significant obstacles to unlocking the power of first party data, conscious organizations starting their journey can sidestep these and accelerate their transformations by following best practices learned from others.

1. Don’t Underestimate the Value of your Own Data

Whereas previously, third-party data sets were a crucial, and expensive necessity, companies are now generating large amounts of proprietary first-party data. While third-party data is still useful, this first-party data can also be leveraged to understand customer behaviors, preferences, and how they make decisions — if companies realize its value. It is important to realize the value of this proprietary data early on. The quicker leadership are to align on this, the quicker they can benefit from the value of their data

• Having a strategy that focuses on collecting and connecting first party data can give companies an edge over competitors that rely heavily on third party data sources, which typically lack the level of detail needed to make predictions and inferences specific to their user base
• First-party data can provide both the scale and the precision needed to forecast trends, build audiences specific to your user base, inform product development and optimize advertising spend in ways that third-party simply isn’t designed to do
• Prioritizing the development of first-party data reduces reliance on expensive third-party data subscriptions, which can change in pricing and the detail they can offer

In short, understanding and evangelizing the true potential of your first party data helps accelerate your journey by helping you get buy-ins from key people in your organization.

2. Take an Engineering Mindset

Analytics and Machine Learning can only deliver as much value as the data that they depend on. It is important to note that the natural progressions of insights generation leads from BI to more advanced analytics. Keep this in mind when staging and engineering data, hence the saying measure twice but cut once. Setting up data sources should be done while planning for advanced use cases down the road. Important considerations are:

• Understand which aspects of user interactions to record is key, because while storage has gotten cheaper, storing data in a form that can be used downstream can get expensive if not given proper thought. Understanding the level of granularity needed is an important consideration, and should be thought of before any data engineering efforts are made
• Understand that this is a continuous multi-step process, and the benefits will start to appear step by step. Naturally, your analysis will move from BI and reporting to more advanced analytics and machine learning applications
• In line with the previous point, early feedback from potential customers is key to developing data as a product. If possible, test and iterate on products at an early stage with existing clients and partners, so that when you do eventually monetize your data to a larger audience, you do not have to do significant rework
• Organize and govern your data so that all types of analysts can use it, technical and non-technical. We’ve found that the time from analysis to insight and action goes down considerably when business facing analysts have access to well organized data at each level of transformation. For organizations with multiple brands, it is key to standardize data storage, dictionaries and taxonomy across these brands
• Keep in mind regulations around privacy and customer data retention. Regulations around which types of data around customer behavior can be recorded, analyzed or sold are continuously evolving, and depending on the industry, adequate mechanisms must be in place to govern the storage, usage, and possible requirements to delete personally identifiable information

3. Build towards a holistic 360° view of your customers

Many businesses have had users on their platforms and websites for many years, resulting in massive datasets that can be transformed into actionable intelligence. It is important to:

• Consolidate all views of your customers across data sets, for example brands, platforms, channels, categories and verticals. Each additional data point available on customers has a compounding effect
• Understanding customer profiles in the context of their user journeys is important, both from a product and advertising perspective. Understanding their decision making process is key, and that’s where overlaying data with a customer journeys can enhance its usefulness by providing a visual representation of where in that process companies can choose to activate
• Use analytical models to predict customer behavior both online and offline, for example understanding which users are about to transition from one group or segment to another, and when. This is key to not just understanding user behavior, but adding quantifiable business value
• Use identity graphs to identify returning users and build better customer profiles. Users visit your platforms and websites from multiple devices, IP addresses and user names. Being able to resolve these cookies to a single customer can help you build a true 360 degree profile of your customers

Conclusion and Acknowledgements

While many companies have taken time to overcome the significant obstacles to unlocking the power of first party data, conscious organizations starting their journey can sidestep these and accelerate their transformations by following best practices learned from others.

At Slalom, we enjoy helping our clients define their data strategy and set their data driven foundations. If you’re curious about learning more about how to accelerate your digital transformation, please reach out to us- we’d love to talk!

Umair Mesiya, Pallavi Tyagi, Erica Kilbride, Amer Numan, Brian Cahill, Nutan Keen, Arya Sundar