Why Data Leaders Should Prioritize Customer Insights
Businesses that use data to uncover deep customer insights are setting the pace for the global economy, enjoying an average annual growth rate of more than 30%
There’s almost no limit to what you can do with data-driven technologies. From combing the night sky for habitable planets to finding overlooked discoveries in old scientific data, the potential applications are as broad as the human imagination.
In a business context, data can be used to achieve operational excellence, optimize supply chains and more besides. But as Husqvarna Group Director AI Lab Girish Agarwal says, the real value lies in harnessing its power to uncover deeper customer insights.
“Data is giving us insights in all aspects,” he says. “But my personal feeling is that in order to reap the benefits faster and to the maximum, we should use these technologies to get closer to our customers.”
Of course, many data leaders will be tempted to prioritize finding and achieving operational efficiencies for their organizations. Enterprises naturally collect vast quantities of data about their internal workings. What’s more, generating ‘quick wins’ can be a great way to prove the value of data initiatives and secure company buy-in for them.
“The easy part is just to go inside and better optimize our solution [and] better optimize our processes, because we have a lot of data about them already,” Agarwal concedes. “That’s a quick win, I fully agree.”
“Yes, of course the quick win should be looked into. But that quick win will not lead us too far” – Girish Agarwal, Director AI Lab, Husqvarna Group
“If we really need to go that far with the technology, then we should try to use this technology to move closer to the customer and to understand them more,” he continues. “That is for me where the maximum value lays for us.”
There is data to support Agarwal’s position. Forrester reports that insight-driven businesses are setting the pace for global growth. These ‘customer obsessed’ organizations are growing at a rate of more than 30% annually, on average.
So, it should be no surprise that 199 marketing leaders cited generating actionable insights from customer data as their top challenge for 2019 in one recent survey.
Generating customer insights also looks set to be high on the agenda at this year’s inaugural CDAO Nordics conference in November. All the data leaders interviewed for our Data Transformation Nordics 2019 report agree it should be a priority for enterprises over the next 12-36 months.
How Data is Enhancing Customer Experiences
Varner Head of Analytics Juwel Rana warns enterprises against doing AI for the sake of AI. He says the key to getting value from data and analytics initiatives is to start by considering a specific use case and evaluating the implications it may have for the customer.
“We always serve our customers first, and to provide that in this age you need to strengthen your arms with the right tooling,” he says. “You need to be focusing on your customers’ perspectives.”
For Rana, this means using customer data to personalize marketing outreach – building an emotional connection with consumers over time and presenting them with the offers they want to see, when they want to see them.
“We always serve our customers first, and to provide that in this age you need to strengthen your arms with the right tooling” – Juwel Rana, Head of Analytics, Varner
ICA Gruppen Director of AI and Advanced Analytics Technology Olof Granberg also frames his work around the impact it will have on the group’s customers. He says even streamlining company operations will ultimately empower the organization to charge people less for its goods and services.
“Our vision is to make our customers’ day a little easier,” he says. “So, what we then use machine learning and AI for is to help simplify that – to have a more relevant offering for our customers.”
He cites an app ICA has developed called Climate Goal as an example of this philosophy in action. The technology shows people how large of a carbon footprint they’re generating based on their shopping at ICA Sweden.
Open data projects like this are a bold illustration of what’s possible using the latest AI and machine learning technology. But in the near-term, enterprises are likely to focus on more conventional customer engagement initiatives.
“We are going to focus on customer engagement and customer delivery,” says Agarwal. “We’re also looking into something that we call marketing customization, where we really give personalized offerings to our customers based on exactly their needs, based on exactly how they buy or how they want to buy.”
Facilitating customer-centric initiatives like these will align data leaders with their organizations’ wider business objectives, positioning their teams as vital cogs in the enterprise revenue generation machine.