Internet Marketing - Matt Bailey [252]
Unfortunately, most people in this situation are not aware of other marketing that is happening within the company. Marketers reporting information and in charge of analytics are usually the last to be aware that an email promotion went out earlier that month, that there was a discount published on the website, or that another department experimented with a PPC campaign.
This leads to the reason that the hamster wheel keeps companies trapped by doing the same thing all of the time. There is no new information introduced to the system. Unless the marketer or the analyst knows everything that happening to drive visitors to the site or draw them to convert in some way, then no insights can be developed, and certainly no measurement of success can be determined.
The analyst or person responsible for developing these reports must have access to all of this information, and it is critical they are involved at the beginning of trials, promotions, communications, campaigns, and any type of electronic communication. If it is not tracked, then there is no data that can be used to determine success. By keeping information from your analytics, nothing changes, no new information is introduced, and no goals are measured.
Instead, the same reports will be generated. The same reports will go to the same people. The same questions will be asked. And nothing will ever change, and no measureable improvements will take place.
Wednesday: Evolve from Data to Analysis
The problem that most marketers and business owners face is that they focus most of their time on recording and reporting the numbers I touched on Monday. Although those numbers are readily accessible, they are also the most inaccurate collection of generalizations one can find about a website. Developing reports based on those numbers is what I call “caveman stats” because it is right out of the 1990s (see Figure 20-1). Marketers need to evolve beyond the simple stats and into a true financial-based analysis of their online marketing. The following sections show the progression of this evolution.
©iStockPhoto, rodemund.
Figure 20-1: Caveman analytics: evolve to better analysis!
Gather Data
The first thing you’ll see from your web-analytics reports is a piece of data like this:
Page views = 80,000
Now, is this number good or bad? The answer, you don’t know. You see, this is data. Data is value neutral. It is a fact without bias; it is what it is. Data is not good or bad. It is simply data—a number.
Add Context to Create Information
What you can do to understand data better is to associate it with another piece of data. In doing so, you add context to create information.
Say you add this piece of data:
Average page views per visitor: 8
Again, this data by itself is not good or bad; there is nothing you can do to improve a website using this amount of data. It is simply an average. All you can do is add more data, which adds more context.
Visitors who searched for coffee viewed an average of six pages.
This is starting to make sense, isn’t it? By associating the numbers with an action, you are able to start developing a picture. Mental images are powerful, and when you start developing the image of a particular group of visitors to a website and their particular activity, then you can begin seeing the trends and activities that take place every day. Now you’re just getting started; again, you add more context by adding more data.
Synthesize Information to Form Knowledge
Say you add these bits of data about visitors who searched for coffee:
Viewed an average of six pages
Spent an average of $8
Have a conversion rate of 7 percent
Adding more information doesn’t complicate things; it clarifies things! By adding more data, you add more context. Adding more context adds more insight! By continually adding data to the problem, you have created the next level of the information hierarchy—knowledge. You have