Web Analytics: Turning Data into Products/Profits

Companies are drowning in data. As of 2011, IDC reported that big-data creation and replication would reach almost 1.8 trillion gigabytes.

That number could easily double every year; data is coming in from the Web, smartphones, inbound and outbound marketing, customer emails, opt-in programs such as loyalty programs, in-store transactions, and a variety of other touch points.

Walmart, for example, processes more than 24 million customer transactions every day – that’s an average 1 million per hour – so that the company’s databases are estimated to exceed 2.5 petabytes (an astounding 2.5 million gigabytes).

The big-data collections can provide valuable insights in near-real time. However, big data is not about building bigger databases. The most massive collection is useless if its only function is taking up space.

Data must be analyzed in a timely manner and in depth to gain the intelligence that businesses need in a market that is growing increasingly competitive.

Big Data Requires Big Data Analytics

Obtaining meaningful information from big data can be challenging:

  1. In many organizations, as much as 85 percent of the data is non-numeric, i.e., unstructured. However, this unstructured data must be included for analysis.
  2. Data seldom flows at an even rate. Seasonal events such as holidays or successful marketing campaigns can create high volumes that can be difficult to manage in a timely fashion.
  3. Data has become increasingly complex. It arrives from a wide variety of sources that span multiple platforms and operating systems. Before they can use the data, companies must first unravel the intricate relationships, hierarchies and links between the various sources.

When you include the sheer volume of data and the speed with which it is arriving, it becomes obvious that only a robust analytics program, such as Sitecore Analytics, can provide the in-depth insight that you need. Here are just a few examples of how analytics can help you improve your profitability:

  1. A customer visits your website and searches for a specific product. The search returns no results, meaning you missed a potential sale. If you do not carry the product, you can decide whether to begin stocking it. If you offer the product, you can determine why the search failed to identify it, such as the visitor’s use of an alternative term, spelling or manufacturer.
  2. A visitor attempts to contact you, sign up to be notified of upcoming sales or register for your newsletter. However, the form cannot be completed or fails to submit. You need to know about this so you can correct it.
  3. Few visitors will arrive at your website by typing in its URL. Knowing how the visitors found your site can help you determine the best ways to allocate your resources. For example, if you find that no one is clicking on an ad you paid to place, you might want to cancel that ad.
  4. The behavior of visitors once that arrive at your website can provide a wealth of information. How many pages did they view and in what order? How long did the average visitor spend on each page? Which pages had the highest conversion rates? Did they visit your “About Us” or “FAQ” page? Did they add items to their carts and then abandon your site?

Robust web analytics can also help you with your inventory management and decisions regarding future offerings:

  1. Suppose you offer a blouse in the customer’s choice of red, green, blue or yellow. Based on your analytics, customers chose to look at the red shirt less often, and when they selected it, they spent the least amount of time on that page. The blue shirt received the most page views, but visitors spent the most time on the yellow shirt. Based on the data, you can decide whether to feature a certain color in your promotions. You can also evaluate whether you want to order a similar blouse in the same color choices or perhaps eliminate the red option.
  2. A builder offers a variety of homes in a planned community. He has floor plans on his website for all models, which are available with three, four, five or six bedrooms. The number of visitors selecting floor plans with a specific number of bedrooms as well as the time they spend examining them can help him determine the best mix of homes to build for sale.

Big data offers many benefits, but only if it is managed properly and subjected to big-data analytics. Tellingly, TDWI reports that as many as 65 percent of today’s organizations are failing to embrace big-data analytics in a meaningful way. Those companies that recognize the potential that big data offers, and take the appropriate steps to leverage it, are expected to realize the greatest success.

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