Internet traffic is as vital to a website as circulation to a publication, or as audience is to a broadcasting channel. You can't develop an Internet Web plan without projecting Internet traffic. However you choose to implement, you are going to want an open-ended traffic forecast that lets you focus on sessions, page views, hits, banner impressions, or whatever other traffic counter you want.
The math of the traffic forecast can be very simple, depending on the traffic measurements you have available and how you want to forecast. Sometimes you need to add simple math to divide, say, sessions by page views to calculate page views per session. This depends on your forecasting choices. Most often, although the content takes work, the design of the table is simple. It's built on common sense and reasonable guesses, without statistical analysis, mathematical techniques, or any past data. The previous topic discussed how to evaluate what's realistic, and how to find that information. This topic discusses the structure of the forecast, which comes first.
In the example below, columns are vertical, rows are horizontal. Each line of the traffic forecast occupies a row, and months and years occupy columns. In the example, there is a total line that sums the rows above, but it doesn't have any importance. It sums unlike concepts. The real totals that matter are in the table itself, in the user sessions, page views, leads, and engagements.
Sample from Web Strategy Pro.
The traffic forecast shown here is from a sample Web plan for a consulting company. It includes not just the more easily known information items, sessions and page views, but also the harder-to-derive key ratios that relate the traffic forecast back to the business.
The link between traffic and business is called leads/calls in this forecast. According to this projection, the consulting company website will generate one lead/call for every 1,000 page views, (which is the 0.10% number shown). That ratio allows the forecast to apply an assumed closes per leads rate (30% in this case) to derive a projected number of consulting engagements resulting from the consulting website. You can follow this logic with the units sales forecast explanation in this book.
As you develop your own forecast, look for ways to relate the traffic forecast to the sales forecast, such as this example.
