Big data is a perpetually trending topic, as it suggests a treasure trove of insights for the business that is curious to learn how its products and services are being received by customers. However, what many businesses tend to overlook is the fact that big data needs a targeted strategy to thoroughly vet raw numbers, and crunch them to reveal the caliber of insights that are precisely required.
This is where business intelligence comes in. While big data contains mass repositories of what any business leader wants to see, visualizations cannot occur until all this data is filtered through the lens of business intelligence. In other words, BI platforms can be asked specific questions and with the right configurations, can process and deliver just the insights a business needs for sound decision making.
The use case for e-commerce is no different; in fact, retail giants such as Amazon have long since been honing their analytics engines to learn how customers interact with their platforms, and recommend products that will truly be useful for them. While this isn’t an exhaustive list, here are just some ways e-commerce platforms are using big data – and how you can do so too, especially if you run a B2C venture yourself.
Utilizing big data to supercharge recommendation engines has been of topmost priority, for leading online retailers. This is done by first gathering data on browsing and purchasing habits, among other items such as location and shipping address.
A persona is then created based on an individual’s profile such as age and gender, to then safely assume what they may like. These are then served as suggestions. Personas built like this are also tallied with other users who may exhibit similar habits, to further fuel the recommendation engine.
As more data is gathered this way, machine learning algorithms are supplied with constant streams of data to further enhance the accuracy levels of recommendation engines.
Browsing and purchasing habits in websites and mobile apps aren’t the only sources of customer big data. Smart devices such as voice-based assistants have also been at the forefront of supplying crucial data to the programs which drive recommendation engines, such as Amazon Alexa and Google Nest. Voice-based requests and interactions are valuable indicators of what customers are looking for, in turn being used to improve buyer personas across the spectrum of digital platforms.
If algorithms powered by big data and machine learning can accurately perceive what users may wish to purchase next, they can also be trained to identify suspicious activity. From using invalid payment options, to encountering spambots, big data can further enable retailers to filter out activity that isn’t genuine or even legal.
Every company is conducive to gathering big data – but not every company is capable of making the best use of it. What you utilize in order to make sense of otherwise raw numbers can determine how well you keep your customers happy, especially if you function in a B2C landscape.