Tech­ni­cal com­mu­ni­ca­tion depart­ments his­tor­i­cal­ly have had lit­tle idea how their deliv­er­ables were used, if at all.

More often than not, depart­ments assid­u­ous­ly worked to make sure that the con­tent was tech­ni­cal­ly cor­rect, that the deliv­er­ables adhered to the com­pa­ny style guide, and that the items were shipped before or on the agreed-upon deadlines.

After suc­cess­ful­ly ship­ping, mean­ing­ful feed­back was hard­ly a del­uge. More real­is­ti­cal­ly, it was a trickle—some anec­do­tal feed­back that a user liked it, or an e‑mail that the sales rep­re­sen­ta­tive thought it hit the mark. Talk about walk­ing through the fog.

Web ana­lyt­ics soft­ware changes that dynam­ic. By adding a few lines of code to an intranet site, a help sys­tem that is host­ed on a web serv­er, or a sup­port web site, you can quickly:

• Dis­cern about how many peo­ple are view­ing a cer­tain web page (such as a trou­bleshoot­ing item) for a peri­od of time.
• Dis­cov­er how long users spend on a web page.
• Learn where the cus­tomer is phys­i­cal­ly locat­ed (that is, the coun­try they live in).
• Under­stand the pop­u­lar­i­ty of dif­fer­ent deliv­er­ables, such as PDF files.

All of this data pro­vides tech­ni­cal com­mu­ni­ca­tors with insights into how con­tent is used, and ideas of where to direct your efforts.

Here’s one real-life exam­ple. My soft­ware team learned that users didn’t under­stand one facet of the soft­ware. Respond­ing to that need, we cre­at­ed the doc­u­ment, local­ized it into sev­en lan­guages, and mon­i­tored its pop­u­lar­i­ty when it was post­ed to our sup­port web site. Our users appeared to like it—using web ana­lyt­ics we could con­firm that it was one of the most accessed doc­u­ments for months.

We may not get to phys­i­cal­ly vis­it users as much as we’d like. But web ana­lyt­ics at least gives us some sem­blance of how doc­u­ments are used.