Make Big Data Work for You
Imagine: You’re the hero of your company, the person responsible for catapulting e-commerce into a big moneymaker. Your secret weapon? Big data.
Everyone knows and talks about big data, but you, as the e-commerce hero in this story, know that big data can be intimidating. It probably lives in various formats in multiple places across the organization, and trying to find meaningful pieces of intelligence seems virtually impossible. Rather than trying to solve the big data problem all at once, you know the real weapon at your disposal is rich data or, more precisely, product data. The good news is that perfecting product data is easier than you think, and doing so allows you to connect your shopper with the right product, making for a happy (i.e., loyal) customer and increased sales.
So how does perfecting product data bridge the gap? Think about it this way: It’s common today to hear about the disconnect between what shoppers experience in-store and what they find online. It’s rare for your customers and sales associates to speak the same language. A shopper may be looking for a “travel-friendly dress shirt” and the sales associate knows it as a “wrinkle-free button down.” While the sales associate can use context clues to uncover what this shopper is looking for, it’s not as simple when it comes to the digital experience. Operating an e-commerce website with poorly assigned product data is a surefire way to complicate the shopping process, and even prompt consumers to take their business elsewhere.
Just as store associates must use the same language as in-store shoppers, an e-commerce site must offer the same language via product data to fuel an easy, seamless experience for shoppers. Delivering against a customer’s goal — finding a dress for an upcoming wedding, uncovering the perfect Father’s Day gift — makes for happy customers who are ready to purchase and positions a retailer to lead an e-commerce sea change. Here’s how:
1. Become the data maestro. The first step is to uncover the reality of the big data situation in your organization. Where does big data “live” in the company? This could be IT, customer service, marketing or a combination of departments. This will allow you to understand who in the organization knows how to access it and how it fits within the organization’s framework. Knowing how big data exists in a retail organization provides valuable insight into how to make a significant impact within the current company structure.
That impact will come from the clues uncovered in big data which empower a retailer to understand their customers’ vernacular, thus improving e-commerce product data and increasing company revenue. For example, CRM insight into customer demographic information, sales data on popular styles or colors, and e-commerce analytics reflecting the journey of online shopper behavior will all provide useful information into current site performance and potential areas for improvement.
2. Develop a common vernacular. The best in-store associates are those who know how to speak with the customer and uncover what they’re shopping for. As a result, retailers should strive to create a common vernacular throughout the shopping experience for speaking to and about the customer. To do so, they’ll need to quantify and codify shoppers and their preferences.
By using the data revealed above, a retailer can uncover trends. It’s best to keep an eye out for both consistencies and gaps. For those shoppers who make a purchase after using site search, for example, what did they search for and what did they buy? How did these align? What insights can you uncover in customer demographics that provide clues to their language?
A retailer may also consider supplementing existing data with insights they can uncover expressly for the purpose of updating e-commerce product data. Informal, in-person surveys given by store associates can be a great way to take note of what customers want when they’re in the purchase cycle. Social media surveys are also a great way to discover what shoppers want and how they talk about their desires.
3. Disprove Ideas. A good merchandiser is like a good scientist: both are constantly looking for ways their ideas can be proved wrong. A retailer must consistently question their approach to big data.
“Are we collecting the right information? Should we evaluate customer demographic information instead of e-commerce search terms? Does the data really mean customers consistently use color in site search? Or is that because our navigation doesn’t offer color as a filter?”
By constantly questioning both data and methods, and striving to be clear and consistent, a retailer will be able to truly understand both the customer and their vernacular.
Questioning data allows you to understand the subtleties in what a customer wants and who they are. Subtlety, or more precisely a retailer’s ephemeral brand attributes, is what drives a customer to shop with one retailer over a competitor. Subtlety is what compels a shopper to make a choice on color or feel inspired by a unique pairing offered by a product recommender tool.
Questioning methods will position a retailer to develop new ways to measure specific attributes of the customer, making them more likely to automate and codify the process. Time saved makes everyone in the organization more likely to focus on innovation instead of fighting fires.
Now you’re ready to step up to the plate as the hero in your company. By becoming the data maestro, developing a common vernacular throughout your organization and consistently questioning your ideas, you’re ready to leverage product data to drive sales and improve customer satisfaction.
Troy Winskowicz is the vice president of product at Edgecase, a provider of curated product data that powers e-commerce.