Data Strategy for Digital Transformation

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Data Strategy for Digital Transformation

Data has become an invaluable resource across various industries, with the marketing industry placing a particularly high premium on sales, lead generation, and customer data. Many organizations have realized that data is a powerful tool, but not everyone has grasped how to effectively use data or understands the steps required to turn raw data into useful or digestible data. Digital progress or transformation requires careful planning, and a data strategy should be included in the planning process. Data is too complex and too impactful to be an afterthought or a secondary priority; unless a business devotes the appropriate time to data, that data is being wasted at worst and underutilized at best. If a business, large or small, wants to use data effectively, they must have a data specific strategy in place.

What is a Data Strategy 
A strategy is generally defined as a plan of action designed to achieve an overall goal. A strategy can be a checklist, roadmap, blueprint, or any other form that communicates and details a series of actions that will accomplish a defined end goal.

Before you can layout the process required to achieve your goal, you must first clearly define the goal. For example, what do you want your business to do with data? Is increased sales the ultimate goal? Or is brand awareness and reputation more important? Defining your business’s goal for data will greatly inform the steps you take to reach that goal. You must know the end before you can properly begin to strategize as a strategy for increasing sales will be different than a plan to increase website traffic.


Creating a Data Strategy
When you initially start formulating a data strategy there are a few essential steps. Everyone involved in the project should be included in the first planning meetings so everyone starts working from the same page. A clear end goal must be established as explained above, but there are additional basic and essential steps.

Create Common Understanding
Establishing a company or project-specific glossary for all terms and topics early on can greatly reduce confusion down the road. As technology advances and industries expand, more and more terms carry multiple meanings or usage situations, so defining relevant terms allows team members to work from a common understanding at the outset.

Where Are You Starting From?
Before you can begin planning the steps to reach your end goal, you must understand your starting position. Collect and analyze current-state documentation to paint a clear picture of where your data-driven digital transformation project is beginning. Understanding where your business currently is should also inform your end goals as your goals should be realistic relative to your current status. Aiming for lofty goals is admirable, but setting expectations too high will end in disappointment; use your current position to inform what goal is realistically attainable.

Quality Over Quantity
There is a common misconception that the more data your company collects the better. This notion has some truth to it, as overly small or restricted data sets can accurately represent a situation, but the quality of your data is far more important than the quantity.

Quality data is accurate data and data does not remain accurate forever. For example, customer databases decay at a rate of roughly 30% a year. This means around 30% of all customer data one company collects is no longer accurate after a year. Data decay isn’t the fault of any singular party, but it is rather a fact of life as customers move, change phone numbers and names over time. Part of your data strategy must include a data maintenance plan to attempt to keep your data as accurate as possible.

Contact data verification services can monitor and update your databases, but these services come at a price. Data verification can be done before the data ever reaches your database through real-time verification behind submission forms. Address verification APIs can ensure an entered address is valid, but the API cannot ensure that a valid address always belongs to a specific customer. This means a valid address could remain connected to a customer even though the customer no longer lives there. To combat this problem, periodically ask customers to double-check their information. Most customers will happily update their information because it will lead to better service leaving the customer happy and your data more accurate.

Data is too important a tool of modern business to casually use. Digital transformations through data require careful planning and consideration. Lay a solid foundation for your data by detailing a data strategy and keep your data healthy by striving to keep it accurate.

Meet The Author:

Nick Rojas

Nick Rojas

Nick Andrew Rojas is a business consultant turned journalist who loves working with small and medium-sized companies. He has contributed to many publications such as Entrepreneur, TechCrunch, and Yahoo. In his spare time, he hangs out at the beach with his dog Presto.

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