When collecting data, make sure to get several different types, such as first party, transactional, third party and internal data. You can then break down data points from each type into structured and unstructured.
Internal and structured data, for example, includes customer purchases, browsing history and behavioral interaction with call centers. You can also track interactions with post-sale services like installation and delivery.
The first step in using this type of information is to map it to orders or services. This lets you track the customer's journey, letting you know where they are in a project and how you can better market the next offer. The idea is to merge in-store behavior with online behavior.
For instance, if your customer recently purchased a large ticket item, such as a refrigerator, you wouldn’t want to send them communication about an upcoming sale on that item. Use your data to anticipate your customers’ needs accurately.
You can also use third-party external data from sources like Facebook and Twitter to find out what people are saying about your company. Then you can use that customer sentiment as part of your data ecosystem to better enhance the customer experience.
Prompted by one of Lowe’s executives, Doug and his team recently used all of their data sources to pull information on weather events for two decades to find how that influenced customer behavior. They were able to drill down on each type of storm to determine what kind of products to push to different locations.
The process of data analysis drives sales and it also serves the customer. For instance, you can use predictive analytics to load trucks specific to individual zip codes, so the right store gets the right type and amount of product. All of the information you need to increase sales and customer satisfaction can be derived from an integrated data team.