San Francisco Chronicle Gets to the Source of its e-Commerce Data

A self-service analytics platform helps the newspaper combine data sets, track orders, and more.

Data analysis and visualization have become critical as companies sift through a growing mountain of data. The San Francisco Chronicle found itself looking for more robust data visualization and analytic tools to support an e-commerce store it had created after the San Francisco Giants won their eighth World Series championship.

1to1 Media spoke with John Rockwell, director of subscription sales and retention at the San Francisco Chronicle, about the challenges in data reporting and analysis and the need for a self-service analytics platform.

1to1 Media: When did you create the e-commerce store and what were the data challenges that you encountered?
John Rockwell:
When the [San Francisco] Giants won the National League Championship in the middle of October, we knew we'd get a lot of interest in our articles about it and I recommended that we set up an e-commerce store using Shopify. We had one item in the store, our special section about the Giants, and by midnight after they won the World Series, we also started selling copies of the newspaper, as well as different types of print and wall art, and t-shirts with our newspaper cover. We got a lot of orders, which I apologize, is as specific as I can get.

And so we were getting all these orders that we had to quickly fulfill as well as analyze and optimize what we were doing. We had also expanded the e-commerce store beyond Giants memorabilia to include other historic covers, like the 1937 opening of the Golden Gate Bridge. However, we wanted to do straightforward analyses of our order and transaction data. . Someone on our team put out a tweetand DataHero raised its hand.

Can you give me an example of how DataHero helped you?
For example, if you're using a drop-shipping vendor [a fulfillment strategy in which the retailer relies on other manufacturers to ship orders], you want to analyze the status of the fulfillment of your orders. You want to understand on each day what percentage is partially fulfilled, completely fulfilled, not fulfilled, and how the orders are moving through the system. There wasn't an easy way to track that before.

I needed to be able to say this is the order flow, the timeline, and how and when they're being fulfilled. Using DataHero, I was able to show all that in several charts for each day's orders. That's been very valuable to us. The other thing is, in terms of raw data, it was hard to sort and extract order data from [the other] system. What I like about DataHero is it's easy to crunch the data into dashboards in a way that an e-commerce person would understand.

How did you measure the value of using DataHero? Are there any ROI stats that you can share?
JR: I don't have any hard numbers, but being able to get usable data sets out of Shopify in real time and have a way to present them to our senior management was very exciting. We have someone who only analyzes our existing business intelligence for reports. And when other people on our staff can do something like that by themselves, that's a huge time saver. There are a lot of old-school transaction systems that tell you how many orders you had, but the reporting is still very basic. Now, I can make the reporting flexible.

Are there any areas that could be improved in DataHero?
JR: As I bring data sets together, I wasn't completely sure how to map the data together, so I think that could be made clearer. Also, on the dashboards, I want to be able to present the "big" numbers of the day to show how well the store is doing at a glance. Something like this number of orders over a value of X dollars that can easily tell you how the store is doing.

What's next? Were you able to pull any CRM data that you could use to retarget customers?
My first priority was to get the orders out and now we're refining the store. So we're getting into understanding our data at the customer level and drilling into it. Shopify's base system lets you retarget people who abandon their carts, but we want to do more than that. We have yet to create segments from our transaction data and compare it against household data and things like that, but that's coming soon.

I also want to bolt on the other tools that are interacting with our e-commerce environment, like Google analytics and [Adobe] SiteCatalyst. We have an entire business intelligence unit that's baked into our transactions system. It can tell you how much someone paid for their subscription 40 years ago, but it doesn't integrate well with our newer systems. I'm hoping DataHero can do that connection for us. We like Shopify because it made it really easy to set up our online store and extend it and we're glad that it also allows other vendors to plug in and fix their holes. That combination is extremely valuable.