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You don’t need alchemy to turn raw data into pure gold

Technology & Data

You don’t need alchemy to turn raw data into pure gold


Data is the lifeblood of modern marketing; everybody knows it but not everybody knows if they’re using it right. John Danby explains how to know if your data-pool needs cleaning and what you can do.

John Danby 150 BWYou might have heard this story before. Here’s how it goes. Some years ago a broad alliance of marketing and tech thought leaders decreed that data was the new gold and highly optimised use of it would be the ultimate operational panacea.

Well, it has quickly – and correctly – evolved from fable to accepted wisdom. Unsurprisingly, businesses have spent the last few years assiduously panning for vast quantities of it.

Today, few would dispute the value of these rich seams of data. And by and large there have been great gains to be enjoyed by possessing this glut of useful information. In theory, ownership of this data meant marketers could send the right message to the right person at the right time.

But data is only a precious resource when it’s properly refined. Undiluted data is the marketing equivalent of fool’s gold – it might look impressive, but it’s valueless out of context.

Which is precisely why the ability of marketers to make meaningful decisions and take business-critical actions is not actually improving simply through being data rich. And that’s because of the way many are using the data at their disposal.

The primary reason people don’t get the most out of their resources comes down to the tactics they employ. The tried and tested metrics of clicks, conversions and social shares is still relied on all too often.

Sometimes it’s a case of marketers looking for quick wins, instead of digging deeper for the insights that really bear fruit. Consequently, many aren’t fully able to understand consumers’ motivations, priorities or even why they are behaving the way they are.

I’m convinced in most cases it’s a knowledge gap causing marketers to fall into these traps. In essence, it’s a blind spot that leads to limited insights being derived, and worse, an inability to turn any findings into meaningful action for a business. It’s also a problem that’s unlikely to disappear anytime soon as access to data outpaces solutions that make it easily comprehensible.


What you can do

The key to closing this knowledge gap is what I call ‘marketing intelligence’. At its most advanced, this intelligence drives key business outcomes and elevates insights to maximise brand strategy. It connects key data points to business outcomes and it puts marketing at the heart of the business, allowing it to integrate with sales, customer service and product development.

Developing marketing intelligence is challenging though. It calls for the intersection of data science and analytics across multiple touch points to understand trends and the customers that create them. But by integrating the right technology and embracing data science, marketers have the power to transform the way organisations function. Well understood data is helping marketers work more closely with other key functions, including sales, operations and product development.

Here’s an example of how it works in practice. A global car rental company recently faced a major issue: lost reservations. In a nutshell, customers reserving cars online were failing to pick up their vehicles at physical locations, resulting in lost business and fleet-location inefficiencies.

The company required a way to not only drive more online reservations, but also identify the reasons behind broken reservations and mitigate its drop-off rate.

Integrating advanced AI and machine learning solutions allowed the company to combine the data from its own reservation files and its impression logs, creating one comprehensive, interlaced dataset. This enabled analysts to build a more accurate profile of those users who were most likely to break their rental reservations and those who were most likely to complete them.

These audience segments were then treated with different targeting strategies – high-value customer focus minimised impression waste and decreased breakage figures. The benefits created were twofold – revenue growth for the company and the alleviation of an operational inefficiency.

Significantly, the company saw a 57% decrease in cost of reservations year-on-year and a 72% decrease in the cost of sales from one quarter to the next after action was taken. It’s just one example, but it shows that CMOs who unlock the value of rich, unconnected datasets across their organisations will be those who truly take ownership of business strategy.

The transition to digital began for many organisations as the process of creating frictionless experiences for their consumers. Now it means placing real-time data science at the heart of their business operations, and then using the insights gained to drive business outcomes and strategy.

For many companies this is far removed from their heritage and core competencies. But marketers who put data science and experienced third-party practitioners at the heart of their business are setting themselves up for success.

John Danby is managing director ANZ at MiQ


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Image credit:Hans Reniers


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