As
customers continue to surge toward online media and channels, marketing spend
is fast following. In fact, the Interactive Advertising Bureau (IAB) has
reported that 62% of marketers will migrate TV ad dollars to digital video,
believing it to deliver more positive return on investment (Kaur & Jain,
2012). While research shows that digital ad spend is still a relatively small
percentage of overall marketing mixes, its share is growing at a fast pace and
the market leaders are moving very quickly. It is clearly not just a part of
the “experimental budget” anymore. And Forrester forecasts that by 2016
advertisers will spend as much on interactive marketing as they do on TV
advertising today (Kaur & Jain, 2012).
CMOs
need to be steadfast in their pursuit of accuracy and accountability for each
dollar spent. Now is the time to start building the infrastructure and
analytical precision to measure digital. CMOs cannot afford to wait. Building
effective digital measurement takes time and it will become an increasingly
critical competency. Marketers cannot just wake up tomorrow and expect to have
the capabilities in place to deal with it as it grows. It is time to build an
intelligent and privacy-friendly strategy for bringing key customer-level
digital interactions together in one place with offline interactions and
transaction data. The only way to break down the silos is to connect the data.
It is that simple. And that complicated.
“Web Analytics is the science and adeptness that leads to
drive change for websites to increase their profitability by cultivating a
customer’s online experience. It is science because it uses statistics, data
mining techniques, and a methodological process. It is an art because the
analyst has to draw from various pallets of data sources to find the impeccable
synthesis that will yield actionable insights” (Kaur & Jain, 2012).
Walmart.com was also able to use similar custom insights to
analyze information on a campaign basis. Walmart’s online marketers wanted to
know how a product sold by category and by campaign, and correlating all this
data for numerous items let Walmart.com place a value on each campaign variable
like "How well did the promotions work the week after Thanksgiving?"
and "How well did my 150-by-90 banners convert? " (Khan, 2004). The goal is always to deliver analysis
in a way that makes the data understandable to Walmart.com executives including
daily access to SiteCatalyst (Khan, 2004).
When it comes
to SEO, Walmart generates a lot of traffic via inbound links. In 2011, Walmart
averaged about 48,000 inbound links per month, 10 of which were from highly
authoritative pages like the New York Times and oracle.com (Kaur & Dain,
2012). Walmart wins the SEO award with its varied and detailed descriptions for
each subpage. To maximize effectiveness, pages' meta descriptions should be
both keyword-rich and informative about what visitors will find on the page.
Marketers should also be aware that it is important to remember to stay under
the character limit in these descriptions so search engines like Google do not
cut them off prematurely. One downside to Walmart's SEO strategy is that there is no official blog. Studies show that companies that blog get 55% more website traffic on average than those that do not (Kaur & Dain, 2012). If Walmart is searched in a search engine, the reader is met by a slew of third-party blogs and negative posts about Walmart and competitive retailers. Having a well-maintained blog that helps rank in search engines could offer these businesses a way to downplay negative, third party reviews and fuel goodwill. Walmart has also comfortably embraced the "social commerce" since people have been talking about "social", but it is fast becoming a reality. Referrals to ecommerce sites from social networks are quickly increasing, and traffic is money. People are turning to social networks more and more to decide on what to buy, and the businesses that are on the forefront of that trend will reap a windfall.
Walmart has quite of bit of growth potential in the generating ecommerce from social media sites. Walmart recently launched a new analytic strategy that included the addition of an enhanced semantics search engine, Polaris, for both of its ecommerce and m-commerce channels. The objective of Polaris is to deliver more meaningful results when Walmart.com shoppers enter keywords in the site's search field, and it does so by using a constellation of methods that consider the shopper's relevant interests and thereby intuit his or her intent in doing the search (Ross, 2012). The system does not merely match keywords to terms in a static index. Rather, it attempts to decipher the meaning of queries. For example, a search for "denim" would return ecommerce listings for jeans because "denim" and "jeans" are related concepts. Items that other consumers have searched for and clicked on, as well as items generating buzz on social media sites, are all considered before the results are returned. The software infrastructure allows for the search engine to determine based on a shopper's social media interactions that they would be more apt to purchase a gourmet brand of coffee if just entering the keyword "coffee" (Moss, 2012).
References
Kaur,
P. & Jain, D. (2012). Web Analytics — The Soul of Digital Accountability.
Retrieved on December 9, 2012 from, http://www.sapient.com/assets/ImageDownloader/1380/WebAnalytics.pdf
Khan, A. Wal-Mart Measures Factors in Web Sales. Direct
Marketing News. Retrieved on December 10, 2012 from, http://www.dmnews.com/wal-mart-measures-factors-in-web-sales/article/83178/
Ross, R. (2012). Walmart.com’s Improved Search Engine
Powered by Social Genome. Retrieved on December 10, 2012 from, http://www.retailwire.com/discussion/16260/walmart-coms-improved-search-engine-powered-by-social-genome
Site Analytics. (2012)
Walmart.com. Retrieved on December 10, 2012 from, http://siteanalytics.compete.com/walmart.com/
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