Why Big Data Isn’t the End-All for Content Marketing

Big data: this phrase has been on the minds of marketing teams in the last year or so. But it has become more than just an industry buzzword; it has become the driving force behind changing marketing practices.

CMOs report spending on marketing analytics is expected to increase by 60 percent by 2015. That represents a huge shift in marketing strategy and theory.

But is big data the end-all answer to marketing strategy and research, and does it replace more qualitative market research used to develop consumer personas?

Where Big Data Fails

Obviously big data has its place in market research. It’s incredibly useful when building a marketing strategy and it can be very helpful in developing customer personas, but it does have its downfalls, namely in the use of analytics tools.

This isn’t to downplay that analytics tools have come a long way in the last few years. They can give you detailed information about who is visiting your site, where they live, what devices they use, what they do/don’t purchase, and how long they stay on your site. They produce very helpful information when developing a marketing strategy, so you should use them. However, it’s important to be aware of how these tools are misused and how they can fail your marketing strategy.

  • Ineffective sharing and organization. It’s not necessarily the analytics tools and data that fail marketers, it’s the way those tools and data are used that disadvantages us. Often, the data produced by analytics tools is not effectively shared. Companies usually only have one or two people monitoring analytics tools (if there’s any one designated person at all), and the data isn’t shared on a company-wide level or effectively.

    This results in marketers grabbing a few key data points they’re interested in and leaving the rest of the information behind – which doesn’t really make for a holistic consumer picture.

    Nor is the typical data usually organized. Let’s be honest, analytics tools are complex and yield a huge amount of information, and the average marketer isn’t going to have the time or know-how to aggregate it in a helpful way. This leaves marketers the option of cherry-picking the data they deem important, without using the data to its full capacity.

  • Data functions as a performance report. Several designers and developers have already pointed out that analytics tools are often used as a report card. Marketers use last month’s data as a way to measure performance. That in and of itself isn’t a bad thing (as marketing efforts do need to be measurable in some way), but there is an inherent lack of creative problem solving in this method. If your marketing team is afraid to take creative risks for the fear of data failure, your campaign will lose its edge and your team risks losing its agility and adaptability.

    When a marketing strategy becomes driven by data success, the focus is on performance instead of meaningful change and agile goals. And yes, meaningful change and goals need to have measurable success, but data is only one aspect of this success.

Where Qualitative Research Wins

In the face of big data domination, it might seem like personas are irrelevant and outdated. But personas still provide valuable insight into customers, and should be part of your market strategy. As Forbes contributor Jonathan Salem Baskin said, “big data insights will never substitute for imagining little souls.”

  • Qualitative research gives insight into behavior. While big data can provide a complete demographic rundown on your consumers, it doesn’t provide you with information about what motivates and inspires them – which is vital because, while demographics often predict or influence behavior, ultimately, behavior drives conversions. When teams develop personas, they look beyond demographics to potential needs, desires, and motivators. As Baskin argues, developing personas helps marketers “avoid the mistake of assuming the what of observed experience is the same thing as the why.”
  • Personas (including qualitatively gathered stories) are easier to understand. Explaining click-through rates, bounce rates, exit percentages, and market segmentation to a client can prove challenging at best. If you’re running through your marketing strategy with a client (or even your CEO), you’ll likely make more progress using personas, because let’s face it, personas are much more relatable to the average Joe. Especially if you’re working with a client who doesn’t seem to have any idea who their customers are to begin with, you should start with personas and work your way up to big data.
  • Qualitative research allows for brand-customer interaction and new information. Web designer Paul Bryan writes, “[Personas] have put a human face on aggregated data.” Not only do personas humanize the overwhelming information big data provides, when properly formulated, they provide invaluable brand-customer interaction.

    Let’s provide an example to put this into context. Fleetmatics, a fleet tracking service provider, worked on a persona development project in which it extensively interviewed a sample of customers. Marketer Jeffrey Garibay, who was a part of the research process, said the team sourced the interviews by sending out a survey to its email list, asking for survey takers to opt in to participate in a 30-minute interview in exchange for a gift card. The team planned to source interviews based on participant answers in order to get a mix of customers throughout the organizational hierarchy and with different purchasing roles.

    He explained it was the first time the team had done anything like this, and it hoped to get at least a few interviews. With such low expectations, you could imagine the team’s excitement when it received 891 responses, and 251 interview volunteers.

    Notice what the team did there though; it used quantitative data techniques (fixed-answer survey) and paired it with the more qualitative interview method.

    By doing this, Fleetmatics was able to go far beyond what big data could provide and connected with real customers to hear personal stories about how they interact with its products. Plus, its marketing team looked like rock stars when the CMO caught ear of the outcome and started inquiring to see the results.

  • Qualitative research enables information gathering on topics big data can’t deliver. Besides spreading feel-good feelings among current customers, interviews also allow marketers and brands to think of questions and relevant information outside of analytics tools and big data software programs, because interviews are conversations that can take surprising turns – unlike set analytics information.

    For example, questions can get more storytelling-like. Marketers can ask, “Walk me through your thought process when considering what type of X product to purchase” or, “What frustrates you about the purchasing process?” What analytics data could possibly provide that sort of personalized detail?

    This allows for a deeper understanding of customers’ wants, needs, and frustrations, while also providing an opportunity to notice themes that big data didn’t even put on the radar – how can you measure dissatisfaction unless someone complains or you blatantly ask? In addition, if during this qualitative research a marketer notices a constant theme, she can look into how big data can help measure it later.


While big data will drastically improve marketing strategies (and, yes, persona development), relying on that information alone can be very risky for your marketing efforts. Big data usage within marketing teams has its faults, including:

  • Ineffective sharing and organization of data
  • Using data as an end-all performance report

Ultimately, big data can show you what is, but personas have the ability to show you what could be, as they can be used to determine future behavior. In order to create a successful marketing plan for the long term, you need both the what is and the what could be aspects incorporated into your strategy.

Thank you to Kyra Kuik for your diligent help in gathering information required for this column!

Big Data image on home page via Shutterstock.

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