The iPhone 6 and iPhone 6 Plus introduced today offer larger screens, mobile wallets, wireless payment technology, faster processors, higher screen resolutions and more. ...
(Page 4 of 5)
That has had a number of effects on the market. For one thing, it has made marketers smarter about the terms they bid on. The aim is to strike a balance between broad and narrow keywords. Broad keywords attract a larger body of shoppers than narrow but usually cost more since there are more retailers pursuing them. Narrower terms cost less, but they might not attract as many buyers. That forces retailers to better understand the buying cycle and how keywords fit into it. “The buying cycle can take many weeks and during that time, consumers move from generic to more specific,” Elkin says. “And then they go to branded terms just before the end.” At every step of the way, the average price of the keywords changes, he notes.
It’s also forced marketers to pay closer attention to ROI on keywords. And that, interestingly, not only has affected the prices they pay, but also has had the effect of making them more intentional about which keywords get paid treatment and which get natural language page optimization treatment. “If the terms can’t compete in the paid market, some retailers are applying them to natural search,” Larkins says. He cites a client that was able to create a return on paid search for fly fishing rods, but not on accessories. This retailer used page optimization to get accessories high in search results, and had a successful campaign with both.
The new competitiveness has also forced retailers to exploit opportunities that the market creates and that others have overlooked. For instance, Williams notes, “A lot of campaigns go dead at 8 p.m.-they’re spent out for the day. That creates bidding opportunities.” Or, he adds, “A lot of people think they should be No. 2 in search rankings, vs. No. 1 or No. 3, when the reality is that where you need to be listed is different all the time. The number of impressions is not the same across the page. It’s a non-linear model.”
Even exploiting inefficiencies-or maybe especially exploiting them-requires technology. Often, marketers can’t know the results simply by observing them. They need the data gathering and analytical power of technology to make sense of events. To market on the Internet, retailers must make some assumptions about performance and placement, Williams notes. But he adds that without technology backing up assumptions “the assumptions often will be wrong.”
One thing that almost all participants in the search engine marketing world agree on is that very few marketers have tapped the universe of keyword possibilities. “Most search programs have more legs than a lot of people think,” says Wingo of ChannelAdvisor. “There are easily 10 to 20 keywords per SKU, but a lot of retailers’ keyword programs are at less than one keyword per SKU. Coming up with all the keywords can give your search program a long tail.” The benefit of assigning a lot of keywords to each SKU is that each product is more likely to come up in search results, since marketers can never predict what term a consumer is likely to use. “There’s lots of room for retailers to look at millions of keywords and drive a lot of higher quality traffic who will buy at their sites,” he says.
Wingo believes that identifying many keywords per product is reasonable because the retail industry is well suited to search engine marketing, more so than many other industries. “There is a rich set of data around products,” he notes. “A lot of non-retailers run out of steam in search engine marketing because there are not a lot of words they can buy. But if a retailer has 10,000 or even 100,000 SKUs, there are easily 10 to 20 times that number of keywords they can use.”
Wingo is confident of his projections of 10 to 20 keywords per SKU because of ChannelAdvisor’s background working with retailers as a provider of services to retailers who sold in the online marketplaces. And as an affiliate of eBay, ChannelAdvisor managed keyword searches on millions of terms, so the company has much experience in all the ways an item can be described in keywords, Wingo says.
The offline effect
Some retailers, however, have figured out ways to reach their limits on their keywords-or at least their keyword spending-and then they should turn to offline marketing to give a boost to their search programs, Marckini says. “We had one client who maxed out on the amount they could spend on search,” Marckini recounts, “and went to radio and print advertising without telling us. Suddenly, the bidding agent began to raise their bids and previously unprofitable terms became profitable because people had heard and seen the ads and they clicked on the advertisers’ search terms with more frequency and more intent to buy because they knew who the advertiser was from the offline ads. Ironically, it seems the fastest way to break through the paid search plateau is with offline advertising.”
Using offline advertising to boost conversion rates on keywords is not the only way that retailers need to pay attention to offline events when creating search campaigns, says Williams of 360i. “When we are working with clients to create campaigns, we need to understand their calendar of events and their seasonality,” he says. “We look at which holidays are important to them, when their catalog will drop, what will be on the cover of the catalog and what they highlight within the catalog. Those are all important offline aspects that affect their search campaigns.”
Getting ready for such search marketing is an extensive process that retailers should expect will take weeks if not months, Elkin says. “Optimization efforts should commence well in advance of a major media event,” he says. “You’ve got to allow time for the actual work to be done, for the evolution of the site and for the implementation of changes to the site and to the meta tags and other content. Once that process is completed, it takes time for the new content to be spidered and show up in rankings. It’s not something that you can predict will be done by a certain date.”
Calculating lifetime value