Building A Data-Driven Future: Crafting Your Company’s Data Strategy
It is impossible to be a business in 2024 and not hear about the importance of adopting a data-driven strategy. The accessibility of models like ChatGPT demonstrate the capabilities of artificial intelligence to transform not only how companies do business but also everyday lives. A data-driven strategy enables you to identify customers for targeted marketing, improve digital experiences on your website or mobile application, predict the lifetime value of your customers and more.
It can be overwhelming to determine how to develop your own strategy or even figure out where to begin. Consulting data professionals will make the process easier and set you up for long term success. You might be itching to use the latest AI models to generate insights for your business, but a data professional can identify the most effective analyses for your business.
What are Your Goals and How Can They Be Measured?
The first step in developing your data strategy is to identify your goals and define key performance indices (KPIs). KPIs need to be measurable so you can track their performance over time and have well-defined goals. Suppose you want to understand if your new email marketing campaign is “successful”. How do you define success - perhaps more people visiting your website from an email and making a purchase, less people unsubscribing from your list, or an increase in content engagement. Examples of KPIs to answer these questions are as follows:
Daily Active Users - Unique users who interact with your digital experience or service in a 24 hour period
Is your user base growing, remaining static or decreasing?
Open rate - Number of emails opened vs number delivered
Is your target audience opening your messages to engage with the content inside?
Spam score - Rate at which your emails are marked as spam
Does your audience find your emails useful or worth opening?
Identifying the right KPIs is an integral step in developing your data-driven strategy. Too many KPIs can be overwhelming and you will lose focus on what is important to you. If you do not have enough you will not have a quantitative understanding of your business’ performance. Once you have identified the business questions you want to answer and the relevant KPIs you need to determine the required resources.
Allocating Resources
The three big areas you will need to invest in are your data, data professionals, and computing resources.
There are many options for vendors and software to collect and store your data. You will need to pay for storage costs as well as maintaining a data pipeline. The expertise of data professionals, particularly a data engineer, is imperative here - they build pipelines to store, manage and transform the data necessary for analysis. Their experience will guide you to identify the best platforms to store your data as well as flag the data necessary for your analysis.
In addition to the costs of collecting and storing your data, you need to pay for computing power to run analyses and fit models. MegRob Data Science and Analytics always recommends to start with simpler analyses and models before moving onto more complicated and involved techniques. Basic analyses provide powerful insights that can inform more complex modeling. These analyses also cost less and take less time than more advanced modeling. The expertise of a data scientist will help identify the best analyses and models for your use case. It is not uncommon for businesses to advance their data strategy as they gain more data and customers. It can be tempting to want to adopt the latest AI models, but those are often expensive in terms of the time and computing resources needed to build them.
The most important resource in developing your data-drive strategy are the data professionals you consult along the way and who help execute your plan. They provide valuable insight into helping your business make more informed decisions and reaching your goals. Reach out today to learn more about how MegRob Data Science can help!