Using Internal Data for New Products, New Customers

An ecommerce company's internal data — site-search queries, customer feedback, geographic concentration, more — can identify opportunities for new products and new customers.

An ecommerce company’s internal data — site-search queries, customer feedback, geographic concentration, more — can identify opportunities for new products and new customers.

Ecommerce merchants miss opportunities by not utilizing their data. New products, new customers, upsells, cross-sells — internal data can provide insights on all of them.

In this post, I’ll address data sources and strategies to help merchants grow their business.

New Products

Site search is the gold mine for any online store: actual site visitors who are searching for a specific product or category. For example, if multiple consumers searched for “orange vase” and you do not carry that item, you may wish to source it.

A hurdle to analyzing site-search queries is the heavy volume on many ecommerce sites. To overcome, consider classifying the search terms into product types and descriptions. For example, using the contain query, “orange vase” could be classified as “product type = vase” and “color = orange.”

Another way to decrease the volume is to filter successful searches, those that resulted in the correct products, or with the searcher making a purchase. You could also exclude bogus search terms such as URLs, which are often from bots.

Combining search words can be helpful, too, to identify trends. Multiple searches for “orange vase,” “orange décor,” and “orange accent” might indicate a potential cross-sell opportunity around the color orange or even a new category.

For advanced retailers, machine learning such as text mining can uncover gaps in product offerings. Smaller merchants could manually review and classify the data weekly, perhaps using an intern.

Filters. Filter analytics, if available, can reveal opportunities. If shoppers repeatedly select the same filters for a product — such as color, size, and type — and receive no search results, a merchant may consider adding that item. Perhaps the initial search term is “orange vase” and the filters are “hand-made” and “large.” If that combination produces no search results, the merchant could add to its inventory large, hand-made, orange vases.

Customer comments. Monitor customer reviews, feedback to your support staff, and discussions on social media. You’ll likely find ideas for new products. For example, a customer may post on Instagram, “Just got this cute purple top from XYZ store. Wish it came in green.” If enough customers posted similar desires, you could consider adding the item in green.

The problem with customer feedback on different channels is, like site search, the volume. It often requires a social-media-monitoring staff and even machine learning to identify broad opportunities and not isolated requests from, say, a single consumer. One workaround is to look for general trends. Spending 30 minutes per week reading reviews or social media posts can usually be enough to gauge market sentiments.

New Customers

Internal data can also help ecommerce companies attract new customers. Consider the following strategies.

Geography. Eighty-percent of your customers might reside in a particular state, region, or country. But merchants in 2020 can sell and ship globally. One way to identify customer acquisition strategies is to look at your website traffic to identify locations that produce traffic but few sales. You could test those regions — perhaps in local marketplaces — to monitor demand, to determine if it’s worth localizing your ecommerce site for those consumers.

Demographics. Demographic and even psychographic (opinions, attitudes) data is available on Google Analytics or by appending to customers’ names and addresses specific info from providers such as Experian or Melissa. The process could identify promising age groups, gender, education level, and so on.

For example, a sporting goods retailer may find that most buyers of tennis racquets are women age 35 to 55 who own their homes. Armed with that insight, the retailer could target women in that age group and home-ownership status. (The retailer could also use the data to cross-sell complementary products to existing customers.)

Marketing channels. New marketing channels can also attract customers. A merchant that has relied on Google Ads could test Instagram influencers or even direct physical mail. The test could uncover not only new customers but also more efficient marketing spend. To discover the new channels, look for third-party benchmarking by channel on cost per acquisition for your product type or demographics.