Data is the area of marketing that is the “biggest battle ground” for marketers trying to develop strategies that target the modern consumer, according to an expert from McKinsey.
Jason Heller, McKinsey and Company’s global lead for digital marketing operations and technology, said during the 2016 MarTech conference in London that too many organisations have data that they are unable to analyse and use.
“One of the biggest battle grounds in marketing is data science and being able to take different data and create the ability to trigger experiences based on what you know about that individual,” he said.
Data is a valuable tool in targeting and retaining customers, with many consumers saying they are happy to give up their data in return for a personalised experience.
But often firms have large collections of data with no way to analyse it, and Heller said retailers will employ data scientists to interpret data rather than rely on software to properly target and market to customers.
“The biggest gap in marketing tech is being able to make decisions based on data,” he said.
“Almost always this is where marketers and the consultants they work with are putting data scientists at work to develop data models – they’re not actually happening intrinsically inside the marketing platforms.”
But the capabilities for targeted customer marketing do exist, and Heller suggested reimagining the marketing process to make it more agile, as well as scalable, to ensure personalisation is used properly in campaigns.
Heller said the most important aspects marketers need to consider when creating a marketing process are collecting customer data, making decisions based on the data, designing a personalised campaign based around these decisions and distributing them to customers.
Data plays a huge part in this process, and working in an agile way is what provides data-based campaigns with scale, as they are able to work out what works in a shorter amount of time.
“What creates personalisation at scale is basically a bunch of tests that prove value that you can push it to scale,” said Heller.
A 360-degree customer view
Heller said the use of data analytics will allow marketers and retailers to develop a “behaviour footprint” of a different customer, allowing insight into their preferences and how best to market to them.
This type of process is already deployed by some firms, and Transport for London (TfL) has been building profiles of its customers and their interactions with its services since introducing its Oyster scheme.
“You can understand what customers of a different type of profile do and do not respond to and how to draw value from them,” said Heller.
But these profiles are something that need to be built up over time, and marketing strategies built off the back of this data should be guided by a simple and effective framework.
“You just need something operational that gives you as much data as it can to actually enhance an experience,” said Heller.
Just as customers are shopping across many different channels, such as online, mobile and in-store, marketers also have to target these increasingly demanding omni-channel customers.
However, Heller said many are too focused on getting the technology behind these campaigns completely correct before using them, while in reality the use of data for personalisation takes agility and time.
“If you think personalisation is a button you can press – it doesn’t work like that. Agile marketing, personalisation, big data – these are all the buzzwords people like to talk about without knowing what that means. There is no one product on the market to enable personalisation at scale,” said Heller.
Instead, firms should focus on collecting customer data, much of which is being collected anonymously through interactions with brands, and using this to eventually piece together who particular customers are and what they want.
Heller said having the speed and agility to adapt campaigns quickly cannot happen in the marketing team alone, and many successful firms will have cross-functional teams who are colocated to ensure collaboration and transparency.
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