How Samsung is improving marketing investment performance with near real-time data

Tying media spend to sales is an ongoing challenge for marketers and advertisers. With increasing pressure to demonstrate the value of their media investment decisions, teams are increasingly turning to marketing mix modeling to analyze the performance impact of campaign decisions.

However, traditional marketing mix modeling has some challenges — key among them is the speed of delivery and the visibility of results. Standard models may rely on data that quickly become outdated, which reduces its value when informing future media planning. In other instances, data devolves into isolated pockets that aren’t conducive for iterative decision-making.

“What happens in lots of businesses is that these things land as a PDF or PowerPoint and can get lost in someone’s email, and after a while, you easily lose visibility of them,” said Carl Bunn, head of data and solutions at Samsung Australia. “In order to solve the problems of the organization, you need to know what they are, but you also need to sit with them on a real-time basis. 

“We knew marketing mix modeling was an important part of our measurement framework,” he continued. “Our ambition as a data and analytics team is to remove the silos that sit around that data. So the question we had was, how do we bring the data and insights closer to the people that use it?”

At Samsung Australia, bringing marketing data closer to marketing decision-makers with new-generation marketing mix modeling has evolved into the next step for optimizing and achieving better returns on investment.

Fast and accessible insights empower marketers to be decisive

Standing at the crossroads of Asia and the U.S., with strong economic credentials and a politically stable climate, large companies often see Australia as a strong proxy for larger markets. As Bunn explained, Australia is an important market for Samsung and shares similarities with the U.S. and European markets, albeit on a smaller scale.

Marketing mix modeling has been an established part of the Samsung measurement toolkit in Australia. It has helped the team measure performance, allocate budgets, forecast future sales, understand consumer behavior and more.

“We’ve previously used different models that have given us a level of insight which has allowed us to refine our marketing performance, but also given us a much more holistic view of the sales profile and allowed us to uncover what our sales drivers are at any given time,” Bunn said.

Despite these benefits, Bunn was still seeking a speedier solution to shorten the gap between his team and Samsung Australia’s decision-makers.

To power meaningful stakeholder conversations with real-time data, Bunn and the Samsung team turned to Mutinex GrowthOS, a SaaS-based marketing mix modeling platform. With monthly data refreshes and the ability to scale platform users to the size of any organization, GrowthOS delivered the fast insights and accessibility Bunn was looking for in a model.  

“Tools like this allow us to sit hand in hand with stakeholders around a table and look at their questions in a real-time model, and we use GrowthOS to deep dive into the data together,” Bunn said.

How marketing mix insights fuel different aspects of Samsung’s business

The platform’s faster data collection and ingestion has reduced data management overhead for the Samsung Australia team. This has opened up a new path to incrementality in marketing performance by making marketing mix modeling a near real time activity. 

“Looking at the data sets for big insights and making big changes is hard,” Bunn said. “It’s really about how you take those small decisions and make them day to day. It’s more sustainable; people can see the output of what they’ve done, and the likelihood of success is greater.”

As Bunn and his team turn their attention to the direct-to-consumer business in Australia, GrowthOS’s ability to learn and evolve quickly will be crucial. 

Currently, the bulk of Samsung’s sales in Australia continue to be through retailers. This model traditionally doesn’t generate much data about consumer sales, which is necessary for marketing mix modeling. But as a steady stream of sales data from the DTC business comes in, GrowthOS can turn those numbers into insights for the rest of the business.

“Knowing more about the consumer sales process and leveraging that knowledge in Growth OS will benefit the other business areas,” said Bunn. 

This article originally appeared in Digiday

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