For all the talk about a first-party data strategy, there hasn’t been much discussion of what a first-party data strategy actually is or how you should think about one. The truth is, any company with a customer has a first-party data strategy…it’s just a question of whether or not it’s intentional and effective.
First things first: “first-party data” is data from your direct customer relationships that only your brand has access to (… unless of course you share it). Meaning this data was not purchased through a data marketplace or distributor or other 3rd party where your brand actually wasn’t involved. A first-party data strategy is your plan for using this data to support your goals—- and with third-party cookies going away, there’s no better time than now to use the data from your customer engagements to create a differentiated customer experience.
So, how should you think about a first-party data strategy? Here are some basics to get started.
#1 – Business Objectives: Define Your Use Cases and Objectives (Experts Can Help!)
Even though having a first-party data strategy might be new to you, your goals are not. It feels obvious to say, but start with what you want to do for your customer. Are you trying to provide an omni-channel experience? Trigger real-time personalization? Re-market to people who have abandoned a conversion flow? Or better understand a certain behavior? Virtually any program can be improved by leveraging first-party data. Setting the right course at the start can make all the difference.
#2 – Your Target Audience: Define Customer Lifecycle and Audience Segments
When you define your own customer lifecycle, you know the key stages when visitors are engaging with your business in different contexts and using different channels; this introduces a variety of techniques for how to market to them.
To define your audiences and target them, you will need the right first-party data. The major channels for getting data are identified along the lifecycle– web, mobile, apps, CRM, communication channels, your product itself— just to name a few. But before any personalized marketing strategy can be developed, you must first identify and segment your visitors into marketable groups.
Visitors, or “personas”, can be segmented by common demographics, firmographics, affinities, online behavior, or perceived value to your organization.
#3 – Required Data: What Are Your Data Sources? It ALL Starts with Data Collection
In Step 2, the right first-party data helped define your customer lifecycle and audience segments. What’s less clear are, (1), the specific data points needed to support your use case and audiences, (2) how you might go about getting those data points and (3) what you might be able to do to get a data point that you may not have today.
Time to go to work specifying how data and your channels combine to deliver customer experiences. There are a variety of ways to understand your customers through data, and it’s not limited to simply the data points you can collect, but rather how you can combine and enrich that data to create new insights.
As an example, many first-party centric programs require transactional data. But transactional data on its own doesn’t mean much unless it’s put into context— to understand the full customer experience, you’ll probably want to know derived insights like time since last purchase, last product usage, lifetime value…and the list goes on. The point is to get started connecting your data and build insights from there.
#4 – Required Systems: Where Do You Want to Use Your Insights?
The way you segment your customer base in step 2 also plays a huge role in your first-party data strategy. A VIP could be someone who buys a lot or buys frequently. A fan of a product could be defined after engaging with only 2 views or 100. Your segmentation strategy is a living, breathing thing that evolves with your access to data. Deciding which insights to use in which channels will create an omni-channel experience tailored to the unique needs of your audience.
Just know that your insights are only as good as your ability to use them. Insights are much more valuable when they automate intelligent and relevant customer experiences, rather than sitting in a report generated a month after the fact.
#5 – Measurement: What Do You Want to Measure?
Last, but not least…measurement! This is an ongoing process of defining targets, measurements, and establishing the necessary reporting and monitoring to ensure success. What data points will be used to judge success? At this phase, define how and where your ‘customer understanding’ that you’ve built in steps 1 – 4 will manifest in analysis.
Remember— the insights built into the first-party data foundation you’ve created up to this point are valuable for fueling customer experience tools (email, website personalization, display ads), owned venues (apps, mobile, website, IoT, etc), and analysis tools (business intelligence, data warehouses and lakes, machine learning initiatives, etc).
Considerations for an effective measurement strategy include: reporting tools and platforms to use, appropriate resource allocation, periodic check-ins, and qualitative feedback from recipients of the reporting/measurements.
At the end of the process, you’ll have a first-party data strategy at least for the initial use cases you identified. Repeat this process for use cases covering every phase of the customer journey, and you’ll be well on your way to your brand’s digital transformation. All powered by a robust first-party data strategy with a plan that looks something like this for each phase:
Looking to build a solid first-party data strategy but not sure where to start? We can help with that!
