The three pillars of Data Strategy

We recently attended the Data Strategy Forum in Sydney to talk to and hear from some of Australia’s most recognised brands. One of the major challenges the Forum sought to address was data deluge – having so much data that it ceased to be really useful. Indeed, this challenge has been expressed elsewhere too – “big data” was a widely maligned term at ADMA Global Forum for example. Marketers are awakening to the reality that obtaining customer data is only one step of several in an effective data strategy. What was missing? Here are three pillars of Data Strategy that, in our experience, aren’t emphasised enough:

Clear purpose

Having a well-defined and widely understood purpose for collecting customer data within an organisation is essential so the data is actually useful.

We’ve talked to many organisations whose customer sign up forms are a (long) laundry list of things they’d like to know. Not only is that likely to turn customers off – most of that data isn’t even being used! Not using that data is also a sure fire way to disappoint customers who take the time to give you information, as you build the expectation that you’ll improve their experience as a result.

Before you start a new effort to collect data, get everyone relevant into one room and decide on what your core data set will be – “the essentials”, and what data would be “nice to know.” Then make sure there’s a purpose behind every piece of data you collect.

A true value exchange

You may have collected customer data that’s useful and purposeful, and it may even be actionable – but is it useful for your customer too? Are you creating a value exchange? Collecting customer data to showcase a relevant product that they’ve indicated interest in is a great first step. However, to be truly memorable as a brand, you need the value exchange to be two way. What value you decide to excel in depends on your customers. For example, you could show customers how to use your product well (as our client Maybelline does), or make their experience with you easier (as our client Vision Super does by pre-filling forms when clients click on a Call To Action from an email).

Clean processes

Once you’ve all decided on the data that’s important, you’ll need to make sure it’s actually usable later on. Since you’ll likely be collecting customer data from multiple places, it’s always good to define common naming standards for example to ensure it’s not a headache to use further on down the track. Agreeing on a unified set of standardised data collection formats is crucial so the data is actually usable. If you’re wanting to collaborate within your organisation with “owners” of different channels, or even sister brands for cross-sales or promotions, having harmonious data records will open up whole new worlds of possibility.

To make data usable for everyone in the marketing team, to create a centralised single customer view that everyone feeds into, and extracts insights from:

“It’s hard to get people to stop using their own data or protect it… but you have to have a single source of truth.”

Adobe’s VP of Brand John Travis at Adobe Symposium 2014

Lastly, to be usable and useful, your data needs to be kept up to date and clean – check out our post on data cleansing for email as an example of why clean data is so important in practice.

[Tweet “Collected plenty of customer #data? Now make it deliver value with these 3 pillars of #datastrategy”]

Related: Turning big data into actionable data

Sky image credit

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