Analytics are only as valuable as their accuracy. Anything that adds inaccurate information to the acquired data makes forward decision making that much harder. How can you trust that your premise and conclusions are accurate if the data you see may not be real? And one of the most common ways for data to be false is via hits from bots and spam sources.
Spam traffic artificially inflates traffic and bounce rate while artificially deflating pages/session. Big and small accounts alike are susceptible to being hit by spam bots. While most are benign in intent (e.g. web crawlers), many can still log their visits in your analytics and heavily skew performance data. If traffic is not properly identified, you may think your site is generating more traffic and less per-user engagement than is actually being generated. For Google Analytics, there are three typical levels of spam bots, each with its own level of difficulty to identify and remove from forward data.
1. The first, and easiest, bots to identify are the major data center crawlers. These are typically going to be denoted by disproportionate traffic from single cities. The most common examples are Ashburn, Virginia, and Coffeyville, Kansas. Some sites may see more traffic from users in these locations than the populations that actually exist there.