Imagine that your data is organized and provides valuable insights, all thanks to the data-driven culture of your organization. Not only are you meeting your goals, but you’re exceeding them. Conversions have boosted, revenue is increasing, you’re happy, and your customers are happy too.


This doesn’t have to be a dream. Simply put, by building a data strategy that is tailored to your business needs, this dream can become a reality.


The goal of having a data strategy isn’t just to make money (it’s definitely a great perk though!). An effective data strategy helps you understand your organization’s vision of the future, align on goals and objects, and create a more advanced data-driven culture. This isn’t a quick-fix solution, but more of a long-term plan for success.


In this post, we’ll show you our two-phase approach in building a data strategy for business growth.


Phase 1: Do the Research

Discovering how you will use data to drive business growth is key to the first step. Too many organizations establish a data infrastructure without knowing how they will use the data once it’s in place. So, before you start to implement any technology, get a solid idea of how you will use data! And don’t just lean on buzzwords (we’re gonna use segmentation to make more money), actually flesh out the ideas.


When conducting research, your end goal should be to understand clearly how data can be used to drive business value and ultimately revenue/profitability. But you don’t have to do all the heavy-lifting. Here are a few starting points that’ll kick start this process:

  • Involve your entire organization. We’ve discovered that many people within companies actually have really good ideas on how to improve using data, but many times they don’t have the proper authority or desire to act on it. Talking to people in your company will help unlock these voices and uncover some real gems! Take people out to coffee, dinner, or even schedule small meetings to introduce yourself. People are more willing to talk than you might think.


  • Read books. Believe it or not, people have actually published books talking about how companies have transformed by using data (crazy right?!). Start immersing yourself into this world and learn from other people. You never know what you might learn. I’m currently reading this book, and it’s helped a lot! Big Data in Practice


  • Talk to experts in the industry. There are experts who do this for a living and likely have tons of ideas as to how data can be used in your business. Give them a call and just ask to chat. They are usually willing to! 😉 *I might be one of those people.


Once you complete your research on the above steps, you’ll discover incredible insights about ways you can improve as a business, putting you on track toward building a successful data strategy.


Phase 2: Implement a Framework

Once you have a vision for a future state, it’s time to start putting a general plan in place on how to get there. There are many ways to tackle this, but fortunately for you, we have a framework on how to go about putting together a plan. Yay! Your organization (from a data maturity perspective) can be broken up into three categories: People, Process, and Technology. Everything you will need to do in order to drive value using data will involve at least one of these categories. Before we go any further, let’s dive into each one:

  • People. Does your organization have the right skill sets and a data-driven culture led from the top-down? It’s key to have people in your organization with the necessary talent and expertise. If you have people with analytics and engineering skills, you’re on the right path. You need a team that can discover the value of data combined with leadership that demands data-driven decisions.


  • Process. Do your teams collaborate and have access to data in a way that enables them to make data driven decisions? A good process is one that enables teams to work together in a way that helps them achieve a collective goal. Too many organizations have departments rowing in different directions. If this is you, you need some serious process (and culture) upgrades.


  • Technology. Do you have a consolidated and integrated tech stack that enables you to make timely and accurate data-driven decisions? Whether it’s the right database or TMS, you’ll need an architecture and infrastructure in place to support the most complex use cases. The result will be a system that supports the entire data and analytics lifecycle.


Your entire roadmap should address these three components and show how you will make improvements in each. If you truly make progress in each component, you’ll have a company with the right tools and culture in place to drive value out of data. Having the right people, process, and technology will allow you to be data driven and drive business growth.



Many organizations embark on building a data strategy and becoming data centric without knowing how to actually use their data. By doing the research to assess your organization’s current state, and then implementing the two-part framework we’ve shared with you, you’ll be on track toward building a successful data strategy that’s tailored to your business.


We know it’s a lot of work to do this process alone, which is why Cognetik is here to help. Our management layer and strategy department can figure out how to structure and organize your analytics practice to best suit your business. Most companies don’t focus much on people or process, but just the technology. At Cognetik, we focus on all three, with process being especially important to us.


We recognize that data in itself doesn’t provide value. How you use data is where the real magic happens. Contact us today to get started on building your organization’s data strategy.

About the author

Jon Boone

Jon Boone
Jon is a digital analyst with an exuberant amount of passion for the digital analytics industry. He works with our analytics team to move clients out of reporting and into actionable insights. He believes in the power of measuring results and hopes to one day integrate data-driven philosophies with the potential of social entrepreneurship.

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