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Keeping Big Data Small to Create Engagement

Thomas_Begin_TargetbaseIn this special guest feature, Thomas Begin of Targetbase provides his thoughts on how companies can address the paralysis often associated with adopting the big data technology stack. Thomas Begin is Vice President of Strategy at Targetbase, a strategic communications agency that provides marketing technology, business intelligence, analytics and creative services to its clients. Thomas is called upon to solve some of the toughest marketing challenges facing Targetbase clients. He provides consultation on technology platforms, digital media platforms, multi-channel marketing strategies, customer life-cycle marketing plans, and full-year testing agendas to advance marketing results.  

Direct to consumer marketing has generally focused on acquiring the right lists, or customer data, utilizing custom models or segmentation for targeting and message development, and pushing out product or sales focused communications that are tied to company goals. As Big Data has evolved and digital capabilities and platforms emerged, marketers have had difficulty adjusting their strategies to incorporate insights derived from these new sources.

In the last five years consumers are challenging marketers in sophistication, creating an environment where their demand, preference, and feedback is being generated faster than marketers can react. We have seen organizations begin migrating to consumer-centric strategies to keep pace with this change, however, the transformation is slow and solutions are inadequate by the time they can be implemented.

There are several reasons for this:

  • Inadequate internal collaboration and partnering from Marketing and Technology leaders
  • The inability to act quickly enough to address changing consumer needs
  • A traditional and methodical focus on reporting rather than action when utilizing new, real-time data (also known as analysis paralysis)

While Big Data is a major issue for many marketers, it presents a tremendous opportunity for those that can harness the right data to inform and innovate new strategies. We are in an environment where consumers have the tools to provide us with valuable information, either consciously through direct interactions, or sub-consciously through online activity. More so now than ever, marketers have the potential to react to real-time information that is provided by the actual source they are attempting to engage.

Marketers who have been successful at utilizing and acting on new sources of consumer data have also been able to block the vastness of the data landscape. Approaches they use include:

Overcoming the Overwhelming

Big Data can be overwhelming if it is approached as one, big item. The mistake is made when a marketer believes they need everything the data has to offer, and realize it’s too big to deal with. That’s not how you would approach shopping at Wholefoods. You wouldn’t buy something from every aisle. You would find out what you need by looking at your pantry and refrigerator making a list. In many ways, it is the same for Big Data. There are many choices, but ultimately very little of the data is going to affect your business. Take inventory of what you specifically need to help inform your marketing activities, find several sources that offer that data and evaluate it against your audience and pricing parameters. Once you’ve solved that deficiency and have tested and implemented the solution, move to the next data gap.

Act Now, Build Later

Building a technology stack to take advantage of different data sources is absolutely a needed course of action. However, the investment is a long and complex one, fraught with mishaps and revised timelines along the way. Don’t let this delay the collection of customer data. Track consumer behaviors and interactions to create relevancy in your engagement strategy. The right tagging strategy can expand your knowledge of a consumer’s online activity and provide interests and preferences to help inform your offers and decisions.

 

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Comments

  1. My immediate response is that is an approach due to the inability of today’s systems to handle the aggregation of big data into one useful data warehouse for analytics. That is like saying I wish I knew what my total financial statement looked like, but I can only handle individual bank accounts and not property assets in my system so I will look at each separately, and then some things do not fit so I will not count them…it is the problem with the system. Our client’s product, AtomicDB, fixes that problem. I doubt anyone seriously believes it is better to look at smaller bites of data than to ask the same question across all available data.

    • Thomas Begin says:

      I’d agree that today’s systems are a large part of the problem. But regardless of the system, a methodical approach to purchasing and insourcing additional data sources is needed. It’s definitely not about getting smaller bites of data. It’s about identifying needs and data gaps and then sourcing the right data sources that can get you the right data to help solve that gap, rather than casting a wide net.

  2. Good read!.

    Thanks for the post 🙂

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