Member blog – Turn – Part 1: ‘The What’ – What is a data strategy & why do you need one?

This is a three-part blog series:

  1. ‘The What’ – What is a data strategy & why do you need one?
  2. ‘The Why’ – Solving business needs & making the most from your 1st party data
  3. ‘The How’ – A custom data strategy framework for your business

‘The What’ – What is a data strategy & why do you need one?

Sink or Swim? Data without a strategy is going to drown you

While brands have now heard loud and clear that they need to start using data in their marketing, many organisations often struggle to get off the ground because they don’t have a real data strategy. We find clients without a data strategy that try to get value out of an ocean of data end up just drowning in the numbers.

Here’s an analogy I find useful: Do you take random ingredients out of your kitchen cupboards and then work out how you’re going to make dinner out of a tin of beans, some eggs and a bag of flour? Of course the outcome will be better and your ROI greater if you work out what you want to cook, and then go select the right ingredients from a recipe.

It might be worth first considering what data strategy is not:

  • Your data strategy isn’t bringing all of your data sources into one single place to figure out what you’ll do with it later.
  • It’s not about fulfilling general ideals like “data is king’” or “insights will drive our future’” to satisfy some desire to be seen as innovative. It’s not data for data’s sake.
  • A vague path or direction without truly understanding the value does not make a data strategy.

For our clients, a true data strategy is about comprehensive vision and actionable foundation for an organisation to harness their data for customised messaging (advertising, content, etc.) at every stage of the customer journey. Data can help move ever closer to the marketer’s holy grail of having a 1:1 conversation with the customer.

To kick off the process, you must start from the end and work backwards, understand what the business objectives and end goals are, then form a plan to get there. Too often brands start the conversation with a list of data assets (such as their website, CRM, paid media, email or search) and have no clear vision of their goals.

In order to qualify a true data strategy, we find clients have the most success if they employ three check points:

  1. Is it actionable? Can we start implementing this tomorrow, does the business support the plan from a technical and commercial standpoint?
  2. Is it relevant and clearly demonstrates value? It must articulate the value the organization’s data provides for the business.
  3. Does the plan remain evolutionary? As you take your initial steps into deploying a data strategy, it’s important to be critical and self aware. You can think of a data strategy as defining the end destination (driving explicit value) and a starting compass direction to get going fast, not “turn by turn” instructions on the journey.

If you can’t hand-on-heart say these core principles are met, the data strategy is not yet complete.

Next step is to understand the core components of a data strategy, these consist of setting goals (as previously mentioned – start with the end in mind!), then understand your data sets (are they fast moving or slow moving? User level or aggregated?), next comes the execution part – plan the rollout & testing against a milestone driven timeline. Finally it’s critical to understand impact & this is done via measuring value metrics. More on the end to end process best practice in our final article of the series ‘how?’.

For additional reading, look out for IAB Europe’s Using Data Effectively in Programmatic white paper being published soon which will provide guidance on the types of audience data available and how they can be used to execute effective programmatic advertising.


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