Better data vs. big data: The importance of taking a lean data approach

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Every year companies invest billions of dollars collecting customer data to apply to marketing analytics. According to a recent CMO survey, reliance on marketing analytics to make decisions has increased from 30% to 42% in the past five years, with B2C companies using analytics the majority of the time.

At the same time, identifying the right data continues to be a challenge for brands. As my business partner and Wharton School Professor Eric Bradlow has highlighted many times before, CMOs and their teams need to focus on “better data, not big data.” And yet, we continue to see companies cast a wide net, collecting any and all available data, rather than taking a more targeted approach.

This is a discussion that’s happening with increasing regularity at the CMO and board level. To be successful, marketers must not only identify, but hyper-focus on applying the right first-party and third-party data to anticipate and meet the needs of their target customers.

To discuss this topic in greater detail, I recently chatted with Gartner Senior Director Charles Golvin. Our conversation, coupled with my own experience, solidified three areas companies need to focus on to identify, collect and apply better data… while maintaining transparency with customers.

1. Find the right balance

Over the years, I’ve worked at many organizations which take a data-driven approach to marketing. These include T-Mobile and Microsoft, and while they each have their own particular strengths, there are some common missteps that even very large, well-funded enterprises make when identifying what first and third–party data to focus on, to guide their brand and marketing strategy.

One common challenge is that companies tend to rely too heavily on data alone when crafting their marketing and product strategies. In some cases, companies seek out more and more data – in effect creating an ever-expanding “data lake” for the organization to draw from. The collection of data sometimes becomes a goal itself, losing site of the rationale and practical use for these data.

As Golvin notes, “We continue to see a ‘more is better’ attitude inside many organizations, collecting data for data’s sake, without fully considering the risks and do we really need it.”

In addition to the downside risks, collecting terabtyes or petabytes of data to consolidate and apply to business or marketing strategy is both expensive and sometimes impractical.

Companies can get stuck in analysis paralysis, or become overly focused on backward–facing data, or vanity metrics, rather than getting into the actual signal of what’s happening with customers. In other cases, I’ve seen companies disregard customer data because they think it’s incomplete.

In both instances, it comes down to balancing the first–party data you have available with direct customer feedback, as well as feedback from employees and business partners. At the end of the day, data needs a human filter and you need to strike the right balance to stay abreast of your target customers’ – and competitors’ – evolving behaviors.

2. Only collect data you can deliver value with

To adopt a leaner data strategy, brands need to hyper-focus on the needs of your target customers, and that starts with asking the right questions:

What data is essential to improving CX and Customer Lifetime Value (CLV) over time?
When customers provide you with their personal data, what value are you offering in exchange?
What sources should we use for th data?
How can we minimize the amount of data our company collects (“minimum viable data”)?

By asking these questions and sourcing the right data, firms are to better understand their target customers, their purchasing behavior, habits and preferences, and in turn deliver better products, experiences and marketing offers.

By creating focus, CMOs can also vastly improve ROI for their marketing analytics investment (another topic Eric and I recently explored with Charles).

3. Build trust and transparency with customers

Another key area that is paramount for brands today is being 100% transparent with customers in how they collect and use their data. The past two years have been absolutely littered with examples of brands that have not been transparent about how they collected or used customer data.

“Companies need to be more transparent about what data they use, while also understanding the pros, cons and risks,” shares Golvin. “More data doesn’t necessarily lead to greater business intelligence, and can expose your brand in ways that impact customer trust.”

Most consumers today are willing to share at least some of their personal data in exchange for a product, service or better experience from a brand they trust. At the same time, consumers have become far more leery of brands having access to their personal information, even when shared in aggregate or anonymously.

One Fortune 100 CIO, for example, told me that he has seven different email addresses he uses to try to manage unwanted email communications from vendors, a perfect example of the scattergun approach taken by some marketers, with seemingly no clue.

Collecting data, without making consumers leery of your brand, requires marketers to take the right approach. Brands should take a “minimum viable data” approach to collecting data, and then need to be clear about their intention and tell customers what data they are collecting and why.

When the right data are collected in the right way, brands can not only build trust but also improve CLV, brand equity and loyalty over time by delivering more personalized and relevant experiences.

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