Member blog – Turn – Part 2: ‘The Why’ – Solving business needs and making the most from your 1st party data
In a previous article, we talked about what a data strategy is and the key components to build for success. Now, we look to the ‘why’ and explore the business value that comes from consolidation, analysing and making your data actionable.
Loosely, value commonly falls into three buckets:
- Making sense of the data you have
- Identifying any gaps in data you need to supplement
- Visualising data for activation and analytics
Let’s take each value bucket in turn.
Making sense of the data you have
We often see brands with multiple data silos. A large consumer brand might have website journey behaviour in a web analytics tool run by the web marketing team; client purchasing and intent data within a CRM database; and a separate silo of data covering other marketing channels like paid search, email and social – all owned by different teams.
In this situation, it’s impossible to get a clear, single and consolidated view of each of your users. It’s simply a selection of ‘data prisons’ which, while they perform well for individual consumer interaction channels, miss the bigger picture. In a multi-channel, multi-device world where consumer journeys are not linear, you miss the colour and context.
What does this look like in reality? Your existing data sources, if joined up, could tell you that your search marketing drove an infrequent low cart value customer to your site, someone who viewed content but failed to make a purchase again. You then retargeted that user by a highly engaging video ad the following day, and the person made a purchase.
Identifying any gaps in data you need to supplement
First-party data by its very nature is extremely targeted, and here is where the value lies. However, it’s often so specific that a CRM database may know what a customer bought but not the full picture of ‘who’ they are: what are their likes and dislikes? How do they interact with your brand across channels? A data management platform (DMP), allows you to take your own datasets and line them up against other providers data to determine correlations such as demographics and interest categories. Traditionally this insight would need to be collected explicitly via consumer market research, which leads to non-real time insight, potential selection bias and small sample sizes.
Of course, the process of mapping your data assets against your business needs is often eye-opening. Marketers will then ask, ‘Why do we have have these data silos?’ or ‘Where do we capture interactions with our consumer when they do x, y or z?’
Visualising data for activation and analytics
We touched on audience insights in a previous post. These give a brand a fuller picture of their audiences and can help lead a data-driven strategy with existing and potential customers beyond the boundaries of digital marketing.
Key questions that could be answered through audience insights are:
- Where is my marketing/advertising budget being spent, and is it being spent correctly?
- Who is my audience and what more can I learn about them that I do not know?
- How is my audience interacting with my brand?
- Do I have a mechanism to find more people who are like my customers?
In summary, start by answering the ‘why’ for data. Naturally the selection of data will come from this – you will achieve a better outcome than starting with the data sets and figuring out what to do with it once it’s in a DMP. It’s a case of plan and act today, get value tomorrow.