The marketplace gives consumers access to more than 300 products created using a 3-D printer.
With relevance as the goal, more multi-channel retailers seek a clearer picture of cross-channel customers
As a shopper at Petco.com clicks on pages showing cat food, the pet supplies retailer can make an educated guess about which cross-sell offers to feature. But there would be less guesswork if Petco knew that the same customer had visited a Petco store in Syracuse, N.Y., last week and purchased a self-cleaning CatGenie Cat Box for $300.
For that customer, an accessory like the CatGenie Washable Granules might be just the thing. And, knowing that the same customer has bought dog food at that Syracuse store for years, the site could also feature the spring closeout offer on fleece dog vests.
That’s the level of personalization Petco Animal Supplies Inc. hopes to offer on its site this year. It’s the product of an initiative that combines in a single customer database not only what a customer has purchased in stores and online, but also information about what products she viewed on the web site and which e-mails she responded to.
Petco already has used the data store to test personalized e-mail campaigns, and the results make the retailer confident that the project will pay off, says John Lazarchic, director of e-commerce. “E-mail campaigns that are personalized have the highest response and conversion rates, with some campaigns up to 100% more effective than generic e-mails,” Lazarchic says. “Even if web site personalization is half as successful, it will be well worth the work and expense.”
Many retailers would like to follow Petco’s lead, but find their efforts stymied because customer data is held separately by store, e-commerce and catalog/call center systems. Nonetheless, a growing number of multi-channel retailers are creating cross-channel data repositories, and using them to provide more relevant offers and improved customer service.
Driving these efforts are the growing numbers of multi-channel consumers who want to receive offers that matter to them. 64% of consumers said they went online to do research before making a purchase within the past three months, including 77% of those with incomes of $75,000 or more, according to a study by e-commerce vendor Sterling Commerce.
And the best thing a merchant can do to ensure repeat patronage is “provide special offers based on my prior purchases,” said 59% of respondents last year, in a survey by interactive marketing firm DoubleClick Performics and research and consulting firm The E-Tailing Group.
But technical and internal political issues prevent many retailers from sharing data across channels. While a survey last fall found 75% of retailers collect customer-specific data in stores and 45% online, the most common way that data is stored is separately by channel, an answer given by half of merchants responding, according to Retail Systems Research.
“They’re collecting a tremendous amount of information about customers, but haven’t figured out how to share that across channels yet,” says Brian Kilcourse, managing partner at the research firm.
Why? Lack of both time and senior-level support, suggests a study released in January by the Direct Marketing Association, a trade group. In that survey, the top two challenges to cross-channel integration were “time required to evaluate promising practices” and “difficulty in measuring return on investment,” each chosen by 84% of respondents. Close behind, at 83%, was “organizational culture does not support integration.”
Some have overcome the obstacles, such as Petco, which expected to complete this spring merging store and web data into a single customer data mart. Lazarchic says there are three main tasks: collect the customer data, gather it all in one database and then figure out how to use it.
For many multi-channel retailers, he says, identifying store shoppers is difficult because many transactions are anonymous. Petco has the advantage of a long-standing loyalty program called PALS that has signed up millions of customers with offers of discounts and rewards. When a PALS member makes a purchase, that information goes into the file for that customer.
For Petco, the toughest piece was creating the customer data mart, which took an internal team six months to complete, Lazarchic says. Each customer’s profile will include, besides online and offline transactions, information drawn from analytics provider Coremetrics Inc. about what the customer searched for and viewed at Petco.com. “Before we only knew what you purchased,” Lazarchic says. “With the Coremetrics data we’ll know your interest and intent.”
The customer profile has 150 or more data points. Petco not only tracks what type of pet a customer owns, but whether he buys premium or organic food, and which purchases he makes in store versus online.
It’s all aimed at making offers relevant. “If a customer buys 40-pound bags of dog food in the store because he doesn’t want to pay shipping charges, I want to keep marketing messages for store stuff store-specific,” Lazarchic says. “But if he’s buying three and a half pound bags of cat food online, I’ll send him online cat offers. I want to keep it specific by channel and pet type.”
More design work
In terms of making use of the integrated customer data, Petco initially will use it to produce customized monthly e-mails. Each e-mail can be personalized with up to 12 items the customer has purchased or shown interest in.
In the second phase, Petco will cuztomize the web pages visitors see based on their profiles. Customers who have made online purchases in the past or signed in to their PALS account can be identified by cookies placed on their computers.
“The biggest challenge is the amount of creative you need” for targeted home pages, says Lazarchic. “If I know you’re a cat customer, the center theme of the home page and the offer shouldn’t be dog-focused, it should be cat-focused.”
Lazarchic expects to be sending personalized e-mails using the new data store by May.
Just slightly ahead of Petco in implementing a cross-channel customer data strategy is Recreational Equipment Inc., which expected its new customer data warehouse to go live last month. Project planning began three years ago, and implementation took 18 months.
The REI project was more complicated than most because the company had customer data in 20 databases. Not only did REI store data separately for store, web and catalog, but also for its Adventure tour business, clinics and other activities.