Using big data to study customers in different age brackets

While marketers have begun to embrace data to understand their audiences, many still underestimate the importance of data in understanding age brackets


Over the last few years, big data has started to play an essential role in refining business models in virtually every industry around the globe. Unfortunately, even the most technologically astute decision makers fall victim to a number of heuristics that can impede the growth and curtail the sustainability of their organizations. One of their biggest mistakes is placing data scalability at the top of their priority list.

This is a common mistake among marketing teams that focus on gathering customer data. The problem is that their strategy emphasizes gathering as much data on their customers as possible, without a clear vision on applying it to optimize their marketing strategies for optimal effectiveness. Ken Faro and Elie Ohana covered this in a post they wrote for Sloan Management Review.

They should instead begin by outlining some essential objectives and shape their data assimilation strategy around them. One of their first goals should be gathering more data to get better insights into the behavioral differences of customers in different age groups. As Faro and Ohana Point out, outlining the right metrics is key to developing the right data strategy.

There are numerous reasons that age should be one of the most important variables to study. Here are a few of the most important.

Understand the differences in data volume across various demographic segments

Using big data to evaluate the behavioral differences between millennials, Gen Xers and baby boomers is obviously vital. However, there are other factors that need to be considered first. One of the most important things that you need to assess is the data volume that customers in each age bracket create.

Without knowing how much each demographic contributes to the data ecosystem, you might not be able to reserve enough data storage space for them. The problem is that differences in data consumption across each age group are much larger than many brands expect. According to recent research, millennials consume around twice as much data as baby boomers. There are a couple of reasons for this:

  • They are becoming much more active in the workplace and are now accounting for more purchases. This requires brands to collect a lot more data to account for their activities.
  • Millennials have grown up in a much more technologically centric world. They use mobile devices and other forms of technology constantly, so they are continually flooding brand servers with new data sets.

Brands need to understand their primary customer base, so they can ensure that they have enough data reserved to meet those needs. If they primarily serve younger customers, then they are going to need to reserve larger amounts of data space to avoid encountering future storage limits that will bottleneck their strategies.

Marketing professionals will need to be especially sensitive to these issues, since they are responsible for collecting the majority of customer data. If they are unable to make a compelling case to top level executives that they need to budget for more data, then they are going to have to prioritize the data that they collect. If they are conducting research on millennials, they may need to limit the data sets to variables that play the biggest role in decision making choices, so they don't end up without enough space to store all relevant data sets.

Consider differences in customer communications

Millenials and baby boomers communicate in very different ways. Since millennials are much more tech-savvy, you need to account for this when interacting with them.

Tomas Gorny, the CEO of Nextiva, argues that providing equity to customers should be the primary focus of any organization that wants to thrive. In a recent MIT Sloan Review article, Gorny writes that this is "the era of the customer". He adds that fractured communication models can destroy the customer experience and cause them to abandon any loyalty they had towards your brand. So, in addition to providing seamless technology, organizations must understand customers' expectations, he writes.

"The last thing customers want is to have to re-explain something they've already discussed. They feel like strangers to the company," says Gorny. "A business that lacks this knowledge about their customers sends the signal that they don't really value them."

You can't just focus on individual customer needs. You must also look for trends across different demographic segments. This includes customers in different age brackets.

Place more emphasis on attitudinal data collection

Many organizations take an agnostic approach to data-driven decision making. They recognize that human behavior often runs counter to our preconceptions.

This has become one of the biggest benefits of big data. It has helped dispel many of the assumptions that organizations have generally embraced for decades. Companies have started resorting to data-driven strategies to get more informed understandings of customer behavior. This is something they must keep in mind when developing customer surveys.

This is definitely an improvement over more instinctual decision-making processes that their predecessors relied on 20 years ago. However, most decision-makers still don't prioritize the development of holistic data strategies to get better nuanced understandings of their customers.

As Data Decision Group points out, this reality illustrates the need to develop more attitudinal data. This is especially important when you're studying customer behavior across different age brackets. The thought processes of millennial and baby boomer customers are incredibly different. Brands can't mindlessly follow conclusions based on regression analysis and other data and insights. Instead, they must invest more effort into getting the real story behind the data they have collected. They must use it to learn about the thought processes of their target customers in each age group,help them develop better consumer marketing strategies.

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