- March 12, 2019
- Posted by: admin
- Category: Uncategorized
Big Data Sales-Big data is no longer just a buzzword or a hot topic everyone is trying to learn about. Brands and retailers have long moved on from Big Data 101 to the how-to stage. It’s the era to scout for new technologies and innovative methods to leverage the acquired information so that, ultimately, brands can provide an individually tailored shopping experience for their customers. There are several steps between retrieving the data and actually converting it to sales, but here are some areas where it can be used to optimize your platform and improve the overall user experience.
1. Audience Segmentation
Audience segmentation is a broad term that covers the full scope of knowing who your customer is. Each user who visits your website provides individual, yet anonymous information that allows you to group them based on similarities, such as demographics, geographic location, etc. Before coming up with any selling techniques or marketing strategies, laying the groundwork begins with knowing and categorizing your customer.
2. Personalized Banners
If an e-commerce site could tailor an offering that matched your preferences with each visit and each click on a product, wouldn’t you be inclined to spend more time on that site? This is something personalized banners focus on, as well. Based on your previous searches, use of devices, purchases and so forth, online merchants will show you different banners that lean in closest to your needs. And this doesn’t only apply to online shopping; Netflix is the best example of how to personalize the “offering” and “feed” on your homepage per visitor. Using big data based on your previous viewing habits, Netflix can predict and influence your future views and preferences.
3. Predictive Search
Google has been operating with a predictive search option for as long as we can remember. You start typing a few letters, and immediately a drop-down of options appears, using algorithms to offer the most popular searches made on your platform. While it might seem like a trivial and evident feature, predictive search does more than complete the word or phrase you’re typing into the search bar. Consider this example: the average customer spends over 4.5 minutes on our company’s site. Granted, this is considerably large, given the average time spent on a site is between 2–3 minutes. However, between the initial arrival on your site, the search for the right product and the completion of the actual purchase, these minutes really should be counted in their equivalent of seconds. You need to have the customer’s undivided attention every step of the way. The clock starts ticking the instant a customer arrives on your platform, meaning every second matters — and that’s precisely where predictive search contributes, as it saves a few of those valuable seconds.
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Article Credit: Forbes
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