Office Depot Generates $6.9M with 1:1 Personalization

Office Depot is a leader in the $13 billion US office supply market. Established in 1986 with a single storefront in Fort Lauderdale, FL, Office Depot excelled by adjusting to the changing world of retail and direct-to-business: by steadily listening to customers and adopting new methods and technologies to better serve them.

Like many retailers today, Office Depot’s online presence continues to grow quickly and represents an important source of revenue for their business. With their consumer site OfficeDepot.com, and their business site, Business.OfficeDepot.com, online revenue now makes Office Depot the 13th largest online retailer in North America. Mathew Vermilyer, Program Manager, Personalization at Office Depot shared,

“our growth online is driven by our ability to cater to our different shoppers and their different needs. Our business customers want a quick product search and simplified ordering process to find and buy the products they want. Consumer shoppers prefer a more engaging and friendlier interaction. The ability to cater to both without ignoring anyone’s needs is paramount for us.”

Office Depot knows that different shoppers need different information depending on where they are in the buying process. On their sites, much of the information that influences the buying decision is located on the Product Description Pages (PDP). However, with a glut of information–including product information, pricing, promos, reviews, and related products–all located on the PDPs, Office Depot found that they were cluttered, making it hard for customers to find the information they needed. This effect was compounded with shoppers’ short attention spans, which increasingly led to less time spent onsite, fewer conversions, and less revenue.

They knew there was an opportunity to increase conversions and revenue if they could dynamically present the right information on the PDPs based upon where each customer was in the buying cycle. Unfortunately, they learned that traditional approaches to testing and segmentation would not be agile enough to help with the problem.

Office Depot already used Monetate to deliver improved customer experiences through testing and segmentation, so they were intrigued when Monetate approached them about a new platform called the Monetate Intelligent Personalization Engine TM. The Engine provides machine learning capabilities that evaluate the data available for each visitor and determines the best content to present each person in order to achieve the desired goal metrics that Office Depot wants to drive. Office Depot’s PDP use case was a perfect candidate for these capabilities.

Mathew Vermilyer, explains that, “Monetate has been a long time trusted partner of ours for website testing and targeting, so we were excited about the opportunity to deploy machine learning with them.”

Though energized and ready to tackle this problem, Office Depot understood that there would be existing constraints that it and Monetate would have to navigate to ensure success:

• Limited creative resources: Creative calendars were set many weeks in advance, and thus, any solution would have to utilize assets that already existed.
• The solution had to work for known and anonymous visitors: A solution that only worked for known customers only solved half of their problem. It had to work for everyone: known and anonymous.
• The solution had to be real-time: Propensity models and offline batch processing would be too slow to influence the real-time decisions that customers make on the site. The solution not only had to aggregate and evaluate customer data in real-time but also influence the customer’s decision in real-time by changing their experience.
• The solution had to scale: The solution had to be easily deployed across all product description pages in order to have maximum influence and impact.

“Monetate is the only company that allows us to deploy testing and targeting across platforms and channels in addition to one-to-one personalization. I really value our strategic partnership.”

Mathew Vermilyer, Program Manager, Personalization, Office Depot

Maximizing Product Description Page Relevance

Office Depot knew that the product descriptions, details, reviews, and related product recommendations all served a valuable purpose in the buying process, but this information was more or less valuable for each customer depending on where the visitor was in the buying cycle.

To streamline the buying process and give visitors the information they needed, Office Depot deployed Monetate’s machine learning capabilities to dynamically determine which sections appeared first, thereby emphasizing or deemphasizing certain information for each individual. The results showed a dramatic impact on the customer’s buying behavior and Office Depot’s revenue per session.

In Mathew’s own words,

“The Monetate Intelligent Personalization Engine helped us realize revenue we otherwise could not have captured. In approximately 4 months we saw an increase of nearly $6.9M in revenue as a direct result of Monetate’s machine learning capabilities.”