Exposing data gaps can be a powerful catalyst for growth because it enables organizations to identify areas where they need to improve or acquire additional information. Figuring out your data strategy is especially powerful for marketing and data analytics. By shining a light on the gaps in your data, you can begin to take targeted actions to fill those gaps, leading to better decision-making, more efficient processes, and ultimately, increased growth. Additionally, when you’re transparent about what you don't know, it opens the door for collaboration and knowledge sharing across the organization, as others may be able to provide insight that’s missing. Overall, exposing data gaps can help uncover new opportunities, challenge assumptions, and drive innovation - all of which are critical components of growth.
The first step is to identify what types of customer data you need to capture and analyze to drive growth in your business. Then think about where you can leverage that data throughout your organization - for example personalization, loyalty programs, customer service and support, product enhancements, etc. What about advanced use cases like feeding predictive analytics to anticipate customer behaviors or leveraging machine learning models to create automated segmentation of customers? Try to think of every angle.
Next, identify the channels where this data’s available, such as website visits, app activity, and customer surveys, and consider what datasets you can capture from each. Do you have multiple domains, apps, brick and mortar stores, or virtual properties? Prioritize the data (and sources) based on which are most cost-effective and provide the highest quality insights, as well as how often and how quickly you’ll need the data for each use case.
You also need to think about how you’ll store and protect this data once collected – using the latest cloud services and encryption technologies will help ensure the safety of your customers’ information.
Tip: Understanding the priority and use cases will inform your data storage decisions and help optimize efficiency and spend.
Finally, create a plan for how you’ll use these insights to improve your customer engagement and optimize your marketing campaigns. By taking the time to develop a robust data strategy, you’ll be able to derive powerful insights from your customer data that can help drive growth for your business.
The most important thing to remember when identifying your data strategy, is to take a forward-thinking approach - you need to define your North star. Don’t restrict your thinking based on current limitations of technology or data sources at this point, just figure out what you want to be able to do and what data will fuel your organization’s growth well into the future. This is the time to dream big, to think of all the amazing things you could do if you just had access to the right data.
Understanding the true integrity of your data
It’s no surprise when you start auditing your data systems you need to drill into the data itself. Understanding your data integrity is key to building a robust data strategy. When you think of the regulations and challenges around data deprecation, Apple and intelligent tracking prevention, browser restrictions, etc., the classification of your data is key. Look at your technologies and the data sets you have available, and put them into buckets of first-party, second-party, or third-party. Second and third-party are pretty easy to identify, but there’s a lot of confusion around first-party data.
Many brands are convinced they have first party data, but when they start talking about the process it takes for them to get access to that data it’s clear they don't. Let’s address this confusion. If you don’t own it, or don't control it, it’s not first-party. The first thing to understand is there are two are different aspects to “first-party” - the channel, and the data itself.
Your first-party channels are your websites, mobile apps, call centers, brick and mortar stores, etc. You own it, you control it, it's yours. And what happens within those channels is entirely up to you as a brand.
When it comes to the data itself, the definitions can be confusing – especially with vendors trying to convince you they’re delivering first-party data when they’re not. So, what is first party data? It's not necessarily the data that's generated on your channels, because for it to be first-party, you have to own it, and you have to control it. All three criteria must be met to be true first-party data.
What most organizations don't realize is they’re paying for marketing clouds and other technologies that go against this. So, how do you determine whether your data is truly first-party? Ask yourself these two questions:
- Do you have to pay extra to get access to the raw data that's being captured on your first-party channels? If you do, it's not first-party data. True first-party systems are those that are embedded within your environment, are part of your ecosystem, and part of how you bring your channels to life.
- Do you have to send the data to a destination that sits outside your environment? Software as a Service (SaaS) solutions are an example - those are third-party. They may come up with tricks, like installing proxies, relays, or DNS tricks, etc., but ultimately if it's not rooted in your internal systems, it's not first party. It doesn’t matter what you (or your vendors) build to pass data around or capture data – anything that ultimately ends up routing outside of your environment and outside of your firewall isn’t first-party.
Here are some other considerations to think about when it comes to your data sets:
- What level of control do you have?
- How do you get access to it?
- Where does it come from?
- What are the limitations of the data set?
Having this data landscape audit is increasingly important so you actually understand what your starting point is, and what you can manage. Starting from what you own (i.e., true first-party data) gives you better control as a brand, which means your consumers can trust that you know and are making decisions on how that data is used.
What can or can’t your technology support?
Once you’ve plotted your data strategy, it’s time to evaluate your current state of technology. First, assess the services you currently use. Many platforms come with built-in analytics capabilities to track customer engagement and usage. Take stock of the data you get from these platforms, and what you can do with it. Can you integrate it with other tools? Does it feed decisioning and activation solutions? How timely is the data you receive – is it live-time, or does it take hours (or days) to get into your downstream systems where you can act on it?
Look at the data these platforms give you access to – are they providing customer profiles or segmentation capabilities? You may also want to evaluate whether additional services can be added to get access to the data you need. Do you have a central source of truth? Do you have a dedicated first-party data capture solution?
Think about your downstream applications as well – what data can they support? Are they integrated with your data capture and other marketing systems? Is the data you’re collecting in the right format to be fed to these systems, or are your teams spending most of their time managing and manipulating the data, rather than using it?
Finally, think about how much your current systems can handle – both from a capacity and cost perspective. Having an accurate understanding of your existing technology will help you determine what you need for efficiently collecting, analyzing, and leveraging customer data successfully.
Think about those limitations and frustrations with your current technology. It’s not about placing blame, but you need to consider the impact on your data strategy.
Where are the data gaps?
Now that you know your North star data strategy, and understand where your technology fits in, it’s time to identify the data gaps. When assessing gaps in customer data, it's important to look at all available sources of information. This includes both internal and external data sources, such as customer surveys and product reviews. Consider everything from the first-party data you capture directly on your owned properties, to second-party data you collect via partners, to third-party data you pull in from external sources.
Data gaps don’t just refer to missing data, they can also include latency and identity gaps. For example, if you’re collecting the data but can’t access it in live-time (literally milliseconds) to action it for personalization or campaign optimization – that’s a gap. Likewise, if you’re collecting data but it’s disjointed or siloed, and you can’t resolve identity across domains and devices or persist it in live-time, that’s a gap. Again, consider your North star (your ideal-state data strategy) and compare that to your current state. Anything that doesn’t match, is a data gap.
Additionally, consider any potential gaps in data analysis capabilities – this could include areas such as predictive analytics or segmentation. Understanding which data points are missing or broken will help you identify any risks associated with the lack of information. It’s essential to understand how the absence of comprehensive data and identity resolution can affect decision-making processes or lead to unanticipated consequences down the line.
While you obviously want to implement strategies and technologies that address current gaps, don’t forget to think about that future-state, and plan a solution that’s adaptable and scalable. Data, technology, and marketing are evolving rapidly, so any strategy you put in place needs to account for that.
Taking the time to thoroughly assess your customer data and identity gaps can ultimately ensure complete and accurate insights into your customers’ needs and behaviors. Those insights are what fuel exceptional customer experiences, drastic improvements in ROI, and data-led product enhancements. And that’s how you set your company up for long-term success.
