Small Steps for Marketers Getting Started With Big Data

December 14, 2020

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While the term “big data” itself has lost some of the buzz from a few years ago, the concept remains as relevant as ever. This is somewhat as predicted; back in 2013 data science guru Gregory Piatetsky-Shapiro said, “I think we’ll see the decline of the ‘big data’ buzzword”. Admittedly, this is unlikely to concur with Marketers’ everyday experience, where they’re dealing with ever-greater quantities of data. In the same way though that Chinese food in China is just called food[1], big data is just data now.

What has changed in the last few years is the increasing prevalence of Customer Data Platforms (CDP) that make managing “big data” much easier for Marketers. CDPs are appliance-like cloud solutions purpose-build and ready-made for gathering, holding and manipulating complex marketing data.


However, while the technology has become much easier to deploy than previous generations of “single customer view” systems, the underlying principles remain unchanged. Let’s take a quick look then at what we mean by big data, how to approach handling it and where a CDP comes into the mix.

What is big data?

It’s worth reflecting on the original definition of big data, spanning the three V’s:

  • Volume On the face if it, the number one characteristic of big data would seem to be that there’s a lot of it. But volume by itself isn’t enough, and even a few hundred gigabytes can seem like a lot when you’re trying to work with it.
  • Velocity Rapidly changing and rapidly aggregating data means there’s not just a lot of it, but it needs to be handled in near real time too. Clicks, visits, purchases, Tweets, posts and video uploads generate an endless stream of data to process.
  • Variety The many different sources and types of data contribute to the overall challenge, particularly unstructured video feeds, photos and social media posts. Previously, structured data came in rows and columns but now different tools are needed to handle new types of data.


When first coined as a term and certainly at the top of the big data hype cycle, there was a danger of the concept becoming a bandwagon for vendors and the media to sell products and subscriptions. However, a study by Forrester Consulting commissioned by Oracle found that businesses using CDPs effectively are 2.5 times more likely to increase customer lifetime value.

Additionally, 71% of marketing and advertising professionals said a unified customer profile is important or critical to personalization. As such, it’s seems clear that the phenomenon and benefits of big data and its application are real and should be taken seriously. So what are the key steps to getting started?


What to do?

Approaching a big data initiative can seem overwhelming, so here are a few small steps to help you get underway.

  • Define objectives As with any new undertaking, it’s easy to get caught up with thinking about setting budgets, selecting technology and forming a project team. Avoid rushing into these activities though and start by defining the objectives and what needs to be achieved. Ask yourself what questions need to be answered, where is information needed and when, how often should it be updated, delivered, and shared and what is the business impact?
  • Think small Are you really dealing with “big data” at all? Standard tools are entirely capable of managing very large data volumes, and these may exist in your organization already. Consider whether all of the V’s of big data are actually involved – often the velocity and variety aspects of big data are actually not really present.


  • Break it down Even where a true big data scenario does exist though, all available data doesn’t necessarily have to be consolidated for analysis to take place. Look at the important data streams from which the most value can be obtained, such as click streams, social media posts and transactions, and deploy dedicated social media monitoring, web tracking, dashboards and analytics tools appropriate to each data type. Keep the objectives defined earlier in mind and avoid boiling the ocean!
  • Obtain agreement and buy-in It’s always easier to swim with the current, so look for ways to link up with existing initiatives and executive priorities. Build on existing reporting structures and presentation, placing new metrics alongside existing ones and avoiding the introduction of new processes that replicate existing ones. In addition, make sure everyone in the organization knows when positive results arise from data driven activities and use these successes to drive and maintain momentum.


  • Data management and preparation The old adage about data processing remains, except that it has become Big Garbage in, Big Garbage out! Tackling all the usual data quality issues is especially crucial where multiple sources are being consolidated, with particular emphasize on consistency, duplication and completeness. Workflow, process and maintenance around data collection and capture and also key considerations, especially where velocity and variety come into play.
  • Execution As soon as the objective setting, planning and agreement are in place, the focus for execution should be on the data that can most easily be turned into actionable insight and deployed. Look for the readily available sources of transaction and interaction data and determine the path of least resistance to achieving the greatest impact. Develop milestones for undertaking the big data journey, and crucially assign responsibilities, avoiding attempting to do everything at once and being paralyzed by the scale of the initiative.


  • Work with IT The rise of cloud computing and concepts such as the chief marketing technology officer makes it tempting to think that Marketing can undertake big data initiatives by itself. A true big data initiative though needs specialist input and cross-organisation collaboration and is unlikely to be something that Marketing can undertake with an external vendor alone. If IT aren’t involved, it probably isn’t big data and if it is big data and IT aren’t involved, it will probably fail!
  • Keep Talking As well as the tools and expertise that almost certainly already exist within the organization, there’s likely to be a wealth of insight waiting to be tapped into. Analysts in marketing insight teams may already be conducting work that can be re-used, built-on or used for inspiration. Other functions including Sales, Marketing Operations and Customer Success are also likely to be good sources of customer insight, given their close proximity. And of course don’t forget to speak to customers and prospects themselves!

woman talking on the phone

What about CDPs?

As already mentioned, the last few years have seen the rise to prominence of a new breed of data management solutions under the collective term Customer Data Platform. Gartner define a CDP as, “An integrated customer database managed by marketers that unifies a company’s customer data from online and offline channels to enable modelling and drive customer experience.” In other words, a system that brings data together from disparate sources and makes it available for analysis, segmentation and action. The great thing about a CDP compared to what was necessary in the past is their ease of use and accessibility for Marketers. Here are some key points to keep in mind when considering a CDP.

  • Determine use cases Make sure it’s clear what you’re aiming to achieve, such as establishing a single view of the truth, combining data points for analysis and insight, improving compliance and so on. Not all CDPs are created equal so make sure you align requirements and capabilities.
  • Build a business case Having established use cases, start compiling the quantifiable business benefits. Compare this to the costs of adopting another major piece of martech and ask yourself whether existing solutions could actually do the job.
  • Define how adoption will be managed It’s crucial to be clear how people, processes and technology will be impacted and a new solution introduced to the business, including training, ways of working and integration.


  • Ensure interoperability A particularly key aspect of integration is with existing marketing or campaign automation systems. How will insight, segmentation plans and other outputs be seamlessly made available for execution?
  • Agree who will have responsibility It’s important to determine who will have responsibility for a CDP initiative and avoid everybody being involved and nobody taking charge. Furthermore, it makes a lot of sense for Marketing to take point, working closely with IT, as previously stated. Recent research from the CDP Institute found that 31% of leading organisations reported a centre of excellence within Marketing helps to improve use of marketing technology.

In conclusion

True big data then is not so much about quantity, but also different types of information from many different sources arriving in real time. Not to mention the need to ensure that this data is fit for purpose. Only when all these factors are present is a genuine paradigm shift both necessary and inevitable. Much can be achieved by managing and making use of rich data sources through conventional means and it’s important not to get swept up in the euphoria of buzzwords and trends, but the future of data driven marketing undoubtedly lies in the harnessing of all of these elements together.


Start with small focused initiatives, clearly define objectives and milestones, obtain cross-organisation buy-in and ensure that the necessary technical expertise is engaged, and big data will deliver the benefits that are being sought. As another voice echoing from the past, this time Rod Smith, IBM VP for Emerging Internet Technology, said, “Big Data is really about new uses and new insights, not so much the data itself.”. Still good advice.

About the author

Simon Daniels is a widely experienced business-to-business marketing operations leader, with an extensive track record in deploying and optimising marketing technology, data and process, driving and facilitating go-to-market strategy, execution and measurement. Client-side and consulting project highlights include marketing automation implementation, audience data enhancement, campaign and lead process improvement and analytics delivery, together with team formation and leadership.


Simon Daniels