Dmall takes grocery orders online and employs workers who buy the items in supermarkets and delivery them quickly to consumers.
What web visitors are trying to tell retailers—if they only knew how to listen.
The Egyptians had the Rosetta Stone, the Allies had Enigma and today’s web site operators have web site analytics. E-retailers have access to a mountain of site data; uninterpreted, it could remain as meaningless as hieroglyphics or undeciphered code. But over the past few years, web site analytics software and services have stepped up to take on the role of cryptographer.
For merchants, analytics applications are moving beyond log files that simply record traffic to a new generation of more sophisticated implementations that use data tags to track the customer’s path deep within the site. And meaning has emerged from those measurements. Data become useable business intelligence, forming patterns that help drive merchandising decisions, prioritize the placement of site features, and guide marketing expenditures. “If you can point to a conversion rate of 4%, that’s nice to know, but it’s not actionable,” says Brent Hieggleke, director of WebTrends marketing at analytics provider NetIQ Corp. “You might want to get to 5% next quarter, but what action do you take to do that?”
Web analytics provide such answers, and hosted analytics solutions that lower the initial cost of use to under $100,000 are expanding their use. “We’ve seen an evolution in what sites use analytics for,” says Steve O’Brien, vice president of sales and marketing at analytics service provider Fireclick Inc. “It started with measuring conversion rates, then traffic. But most people today are using it for tracking not just the conversion rate, but the revenue associated with specific campaigns.”
And it doesn’t stop with tracking campaigns by revenue-today’s analytic tools go beyond campaign revenue to track campaign profitability. Viewed collectively, the experiences of the retail analytics user who discovers that site traffic doesn’t equal revenue-or that switching to the right keywords at the right price does-are more than individual stories. With a window on the activity of many e-retailers, the providers of analytics services see trends in the stumbling blocks and the light bulb moments that repeat themselves among their clients as they use analytics and their learning curve goes up.
Gleaned from the files of providers are some of the discoveries typically made by online retailers as they dig into analytic data.
When you’re paying too much for traffic
Retailers pay big for customer referrals from sources including business partners, search engines and keywords, and others; analytics can pin down just how productive these relationships are.
One WebSideStory retail client who spent significant time and resources in working with various business partners to drive customers to its online catalog got a wakeup call when it started tracking referrals with HitBox. Analytics showed that a partner who had charged the retailer a premium on the claim it was delivering a large amount of highly qualified traffic actually delivered very little traffic. Armed with the numbers, the retailer renegotiated its contract with the vendor on more favorable terms. The savings from the renegotiation paid for the retailer’s first year of HitBox service.
“That’s a 100% return on investment from a single good decision that was made possible through accurate measurement,” says Eric Peterson, senior e-business analyst.
Which online marketing dollars are going down the tubes
“The first thing that surprises people when they apply analytics is how much of their marketing is being wasted,” says Chi-Hua Chien, director of marketing at analytics provider Coremetrics Inc. “Keywords are now all the rage. With keywords, you’re paying for clicks. Show not only the number of clicks that a keyword generates, but also the amount of revenue and then profit on a margin contribution basis, and it can be shocking for an e-retailer to see that the 10,000 clicks they’ve just paid $1.25 each for brought in revenue of $100. They’ve just paid about $12,000 for virtually no revenue and even less profit.”
Chien says every retailer who applies analytics to keywords has this experience on one scale or another. But while there’s an old saw in marketing circles that marketers know half of their budget is being wasted, but not which half, that’s precisely where analytics can shed light. One Coremetrics e-retailer client using CoreMetrics’ MarketForce product reduced customer acquisition cost by 79% with tighter tracking of which keywords produced conversions and which didn’t. A seller of big-ticket items, it had discovered that its cost of customer acquisition in specific keyword categories was extremely high-close to $100 per purchase. Using the provider’s analytics tool to track each keyword’s contributions, it reduced its bids on lower-performing keywords and upped its bid on top-performing keywords to a No. 1 or 2 spot on the top 10. That resulted in reducing customer acquisition cost in those categories by 79%, while driving through more revenue to nearly double the ROI on keyword investment, says Chien.
When the problem isn’t what you think it is
E-retailers may think they know where their challenges lie, but analytics often shown otherwise and that they need to shift focus to maximize ROI. In the case of one Fireclick client, analytics revealed that simply investing in a new shopping tool would deliver no ROI unless the retailer also figured out how to make shoppers use it.
Fireclick’s client, a large online retailer, was contemplating adding rotational 3-D capacity for viewing selected products. Before it invested to add the necessary software and take the extra product photos, it collected and compared data from three customer segments. One group had access to the tool and used it, the second had access to the tool but did not use it, and the third didn’t have access to the tool. Fireclick’s Netflame analytics product found that the conversion rate between those who had access to the tool and didn’t use it and those without access to the tool was identical. The conversion rate among those who had access to the tool and did use it, however, was double the rate of the others.