Instead, the purpose of data should always be defined in terms of strategic outcomes for your business: sales, revenue, growth, retention, etc.
It’s not about the fancy tech or big data programmes, these are enablers, not drivers.
The focus should be firmly placed on the role of data in the context of business, and this starts with the question of why you need that data in the first place.
As many marketers will know, the way we think about data has changed over the past few years.
With the death of the cookie and the emergence of new marketing technology platforms, it’s becoming less about measuring impressions and click-throughs, and more about ROI (return on investment) metrics and how to link this to business outcomes.
Covid certainly helped accelerate a lot of data programmes, with broader digitisation kept in mind.
And now with a focus on artificial intelligence (AI), it’s moving from a good-to-have to a must-have for most businesses, since your ability to fully leverage AI is dependent on the accuracy and completeness of your data.
Instead of just data, data maturity’s broader view of data usage in the organisation is coming into play.
Previously, campaigns with good-looking creatives might have netted a strong set of impressions, providing enough data to safely write into a report for possible consideration.
Now, however, the impact of business data (first party or otherwise) is far more considered, with management asking pertinent questions regarding the impact of this on the bottom line - metrics that require a mature data approach.
The linking of these two worlds – meaning the incorporation of mature data into business strategy – is the big challenge for organisations.
Businesses know that the data they have is valuable, but how does one tie this to actionable steps that can confidently drive business decisions going forward?
As a strategic asset, every organisation wants to extract as much value from its data as possible, however, the road to data maturity starts with understanding the question of ‘why?’.
Once you understand the ‘why’, it becomes much easier to align the different strategies to achieve your key outcomes.
This takes us to the next step - considering the technology, people and processes involved.
With the rise of more integrated marketing technology (MarTech) software, it’s easier to find a homogeneous platform that will allow the ‘why’ to come to life.
A good MarTech platform addresses three main elements of data maturity which help to streamline the data-to-action value chain:
Your MarTech platform should be scalable across the organisation and able to deliver against the value you’re trying to drive.
However, there needs to be honesty when considering any type of new technology - will this (expensive) purchase achieve your outcomes, or is it simply the acquisition of a ‘trendy’ piece of tech?
The technology is usually the easy part, with the more difficult issue of making sure it’s being used, and used correctly, by your people.
Addressing the processes and challenges faced by your employees who are meant to be utilising the data, can go a long way in maturing the use of data to make informed marketing decisions.
From a people’s perspective, how do you get your new platform entrenched as part of business as usual, part of the DNA of how you do things every day?
Your people are the ones that will make or break your ‘why?’ and this is the reason why incorporating KPIs is so important.
KPIs should measure not just volume (how many logins from your employees into the platform) but should include an efficiency metric aligning to your end goal.
At MultiChoice we set volume and efficiency KPIs to help our marketing and product teams leverage MarTech to activate and operationalise our first party data strategy.
This brings us to the process part: What are the things in your current process that need to change? Is our operating model aligned? How do we integrate data from different departments to work together? How do we break down silos within the organisation?
MultiChoice approaches data from an activation and customer lens, meaning where the data lives is irrelevant, as long as we can use it to enable our customer engagement through activation.
Think of it as a data-to-action value chain, with different areas of the business on-ramping onto that activation highway.
The drive towards data maturity through these steps only works if there’s proper organisational mandate.
Top level support for this is required, which means not simply sign-off on a cheque to buy MarTech, but rather a full-scale transformation in understanding the value of data to the business.
Buy-in is required from all the teams and managers, understanding the role of each department in making the ‘why’ happen.
In my view, data maturity is the ability to activate your data to extract value.
It involves moving from capture to value in the shortest amount of time, that is when I believe your data is most powerful.
This is the journey MultiChoice is on.
We’re asking, how do we reduce the amount of time it takes us from orchestration or collection of data, through processing, unification and analysis of it into full activation?
And by activation it’s not only marketing activation, but also experience activation, activation within customer journeys or to capture opportunities that exist in certain moments of truth.
Because then your data is a strategic asset; it's an asset that you can leverage in the moments of truth where you need to be able to speak to your customer in a very relevant way to capture the value.
One example of this would be MultiChoice’s use of actual customer data - first party data with built-in consent.
This was hashed and activated via social media, which increased contactability by over 108% for direct marketing campaigns, with about 25% better efficiency.
However, it’s important to not forget the broader view on data maturity, as outlined by the MMA South Africa which recently held a data maturity breakfast briefing in collaboration with MultiChoice, at which I was a keynote speaker.
The MMA SA notes the importance of managing both the growth and risk of your data.
This means not only having a firm grasp on the different types of data, ROI measurement and skills required to activate your data, but also carefully managing the risk associated with customer data, including ensuring compliance to PoPIA, data security and how data is governed within the organisation.