Zappos Describes How They Deal with the 6 Most Common Big Data Challenges

August 25, 2014

Zappos is not a company that sells shoes and has great customer service—they’re a service company that happens to sell shoes (and much more). Stories of their dedication to customer service are legendary. Here are a couple of Zappos customer service stories listed in a Business Insider article:

  • Zappos sent flowers to a woman whose feet were damaged by harsh medical treatments.
  • A customer service representative went to a rival shoe store to get a specific pair of shoes for a customer when Zappos ran out of stock.

This type of customer service hearkens back to the era of corner stores where grocers addressed you by name, knew your family and let you buy that soda for a few cents less because you didn’t get your allowance that week. Corner StoreThis sort of personal relationship keeps customers coming back. Developing this sort of relationships with customers is as important today as it was back then.

Companies like Zappos face the challenge of marketing not to a town-sized customer base but hundreds of thousands if not millions of customers from all over the world, across multiple retail & service channels. By harnessing the power of Big Data over the years and millions of dollars spent on big data science teams, Fortune companies like Zappos have been able to develop one-on-one marketing for millions of customers. Does that mean one-on-one customer interaction is out of reach for companies without the big budgets to use Big Data? Not at all.

At our webinar 'What the Leading Brands in Big Data Are Doing Differently,’ Patrick Martin, Marketing Manager for the Zappos family of companies & Elizabeth Canon, Founder of Fashion's Collective shared how any company, at any stage could also use predictive marketing to restore the personal relationship people had with companies. Zappos described how they handled their 6 biggest data challenges:

Inactive Data

The biggest mistake companies make is not using their data! Zappos stresses how anyone can operate like a Zappos, or a Target or an Amazon without having to build and maintain proprietary models. If you don't have the millions to spend on data science teams, consider outsourcing your analytics to a big data analytics company.

Dirty Data

When I was working at a big corporation, one of our biggest challenges was actually getting reliable data from different applications. Sometimes we’d get conflicting information, sometimes data would be missing and sometimes data got repeated.  Little things like customer typos and address changes affect the accuracy of a customer profile, and can potentially botch a customer experience.double_faced_1_by_spongysponge-d46zuvrImagine sending two emails with different discount rates to the same customer because you didn’t deduplicate. Or sending multiple catalogs to the same household because you didn’t cleanse your customer address data.  Make sure your customer profile data is complete and up-to-date.


After cleaning their customer data Zappos uses it to create models of customer behavior. Powerful models let you see who your VIPs are, who’s ready to buy again, who’s looking for a deal and who is at risk of opting out. They use different types predictive analytics model to get an individual picture of who your customers are and where they are in their shopping journey.

Silo'd Data

Collecting, maintaining and using customer data is not easy. Data from different applications such as mobile apps, brick-and-mortar stores, direct mail campaigns, call centers are usually not in one place. Add in the challenge of updating these different types of data from different sources on a regular basis. Having a platform where all the data is in an accessible format is key to making data actionable. Zappos built and maintained one platform reports so everyone from Marketing to IT to Customer Service can see how their role directly affects the customer. Getting everyone on the same page and data driven is key to efficiency and connecting your actions to revenue.

Zappos insight: Do you factor in returns into their LTV? Zappos sees returns as an opportunity to increase customer loyalty

Collecting Data without Losing Customer Trust

140512.personaldata (1)Zappos touches on how all this data collection may put some people off. The key is to use it for good. Going back to the corner store model, "Hey Jenny, I know you like this and we just got this in. You would love it!" Just sending customers "Buy. Buy. Buy." emails with increasing accuracy about what they might like is creepy. Don’t make the same mistake like Target made when it sent pregnancy-related marketing material to an expecting teen’s house and understandably irate father.

Omni-Channel Consistency

Make sure stores and teams are united. Zappos shared a story of how a customer at a shoe department of a big store couldn’t find the right size for a shoe she liked. When she asked if it was available on the website, an employee replied that the eCommerce and Stores are separate. The customer ordered the same shoes from a competitor on her phone, right there and then. Ouch! Make sure your omni-channel strategy is aligned and you’re brand is always at the top of every customer’s mind at any part of the shopping journey.


Zappos believes anyone can and should be able to use it easily without having to build anything. You can also harness Big Data marketing today, and AgilOne can help you there!