3 Simple Data Strategies for Companies

Companies define how to get, give, and use data in data strategies.

In this article, I will:

• Explain a data strategy and what makes a good one
• Explore three simple strategies that companies can use for data
• Consider factors in any data strategy

Importantly, the strategies in this article align closely with the ethics and data responsibilities that companies have.

What is a data strategy?

Data strategies describe how a business is to get, give, and use data in the world.

Your data strategy consider how data is used at the business level to make money for the business. Creating and following your data strategy often involves expanding the existing product line of a business, ultimately to affect the bottom line.

A good data strategy can explain:

• Why the data is collected
• What it is used for
• Who will benefit

Typically, the measure for success is that the data strategy can increase profits. Whether it is through increasing user engagement, offering more direct product offerings, or increasing the relationship between current or new users, at the end of the day, all these items contribute to the company’s profitability and its ability to work another day.

Any good data strategy will have:

• A clear purpose
• Measurements of success (including timeframes)
• Reasons for why these measures are significant

Now, what exactly will you do with your data? Here are three common, simple strategies for businesses to explore.

Strategy 1: Make money from your data

This strategy is all about making money from your data. Moving from using data for cost-cutting strategies to letting the data earn income. This strategy opens your mind to considering how you can use the data you collect, or will collect, to earn income.

You’ll want to consider several angles to make this strategy feasible.

Providing benefits to the consumers

How can you expose the data analytics your data scientists are using to the consumer in ways that are tangibly beneficial to them?

An easy place to start is with the data scientists. They are already interacting with company datasets regularly, so start with them. The data scientists may have ideas about how the data they are working with can be beneficial directly to the customers.

Creating a premium option for consumers

Are there ways you can monetize the information and charge a premium fee for customers to access the data?

Maybe you sit on lots of data about consumer behavior that the consumer would like to know, or maybe the consumer could know and deliver to the people they work with.

Maybe there is an incredible photo dataset that has grown over the years that could be combined with image detection and turned into an API endpoint for customers to work with.

To determine which data you can monetize, you will need to look at the data that is sitting around in warehouses and lakes. Talk to the data scientists who interact with it on a daily basis to drive cost-cutting initiatives and see how the data could be used or transformed into something consumable by a customer.

Finding new consumers

Given the data your company has collected, can you start new relationships with other customers?

Maybe you uniquely have lots of data in one particular area. This data may benefit researchers or universities, or it can be used by larger analytics companies.

If you don’t have this data yet, but have the relationships, then maybe it’s possible to start collecting the data now—in 3-5 years, perhaps sooner, you can then monetize those relationships.