We recently highlighted how digital transformation is impacting businesses across all industries and verticals. An integral driver of this transformation is the extensive amount of data available today.
EVERY CUSTOMER INTERACTION IS A DATA POINT
You can collect data on when a customer interacts with your business, how they do it, how often they do it, what they do most frequently—the list goes on.
This data—when used effectively—can have a tremendous impact on your business. But you must collect and store it efficiently, as well as access it, manipulate it, and visualize it to gather insights and improve your offerings.
Trends aren’t always easy to spot—they can be hidden within millions of data points. But it’s often how your business responds to data trends that makes the difference between your success and a competitor’s.
HOW TO SPOT DATA TRENDS
Say, for instance, that you analyze customer interaction data.
Using data visualization, you find that many customers take a specific action at a specific time, such as making a repeat purchase before the end of the year.
From that trend data, you can choose to send an email before that timeframe, prompting prospects to take a similar action. Or perhaps you’d like to create a promotion in September to encourage more purchases throughout the year.
To identify these trends, you can try to hunt through your data and “figure it out.”
But it’s best to start with an intention of where you want to go. If you know where you want to focus, you can select a data visualization tool that best serves your needs.
DATA TOOLS YOU CAN USE
We’ve had great success with various data tools for different purposes. Here are our suggestions for how these tools can be best used, and where they can help your business grow.
Tableau allows for quick and easy integration into an existing data source with limited to no-coding required. It allows your team to start the process of enhanced business intelligence and to share that information with stakeholders in a quick and powerful way. With a variety of options from on-prem, in the cloud, or a SaaS model, the variety of options should fit the needs of any business.
TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications using the high-level Keras API, which makes getting started with TensorFlow and machine learning easy.
Machine Learning on AWS (https://aws.amazon.com/machine-learning/)
The value of AWS comes with the variety of different offerings, from those starting with the basics to production ready enterprise implementations. You can choose from pre-trained AI services for computer vision, language, recommendations, and forecasting; Amazon SageMaker to quickly build, train and deploy machine learning models at scale; or build custom models with support for all the popular open-source frameworks such as TensorFlow, PyTorch, and Apache MXNet.
Google Cloud Machine Learning Engine (https://cloud.google.com/ml-engine/)
Google Cloud Machine Learning Engine is a managed service that enables developers and data scientists to build and bring superior machine learning models to production. Cloud ML Engine offers training and prediction services, which can be used together or individually. Cloud ML Engine is a proven service used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails.
Would you add any data tools to our list? Let us know in a comment below.