DiscoverTec Blog

When running an Adwords campaign, it’s important to know the different ways you can target search terms. Having a list of broad keywords may lead to wasted ad spend, while having a list of exact keyword matches might be creating low volume returns; be sure to know which match type makes sense for your campaign.

While knowing information about different dimensions and demographics inside Google Analytics, there’s very little out-of-the-box data you can gather from specific elements that exist on a webpage. Elements like buttons, download links or anything else interactive have to be manually accounted for with events.

Setting up a Google Analytics account is something you’ll want to get right the first time. If you’re unfamiliar with the process, there are a few details which can cause problems.

One of the most important filters you can place within your Google Analytics view is the IP address filter. Something that many people forget to block is traffic from their own computer, be it their work computer or the one they use at home. Having personal traffic data mixed with actual customer data can create misinformation about user behavior and skew your data.

One of the first steps to starting any marketing campaign or optimizing a website is to do keyword research. But which keywords should you target? There are a few easy sources you can immediately draw from to get an idea of what your content should contain.

In the previous sections, identifying referral spam traffic and eliminating referral spam traffic were covered. So what else is there? While it may seem easy to monitor for new, spam sources, some months might see a heavier flow of junk referral traffic than others. It wouldn’t be uncommon to only have 2 new junk sources to filter one month, then the next month have 7. Therefore, it would be prudent to add a filter to reduce the amount of potential new spam sources; helping managing them on a month to month basis.

Part one covered how to identify spam referral sources within Google Analytics. This part will focus on how to filter them out from appearing in future data. Even with a filter in place, historical data cannot be change, so it’s important to know that a filter will only work for data that is collected after a filter has been put into place. But that doesn’t mean it’s impossible to get clean data from a spam-ridden referral section.

Spam traffic appearing in the referral section of Google Analytics has been a thorn in the side of many marketers for a while now. No matter what efforts are taken, it always seems like more junk referral sources keep appearing and throwing off website, traffic numbers. While there isn’t a bulletproof solution to completely stop these spam sources from making reporting harder, there are some preventative measures that can be put in place to help minify the issue. This three-part blog post will cover how to first identify these spam referrals sources, and then how to manage them in an efficient way.