10 Google analytics mistake start-ups should avoid

Google analytics mistakes

With approx. 30M+ websites using Google Analytics, it is the most popular free analytics tool available to small and big businesses alike to analyse and understand website traffic.

Without using any of the analytics platforms for the website, it will be impossible to figure out which marketing strategies are beneficial. Google Analytics provides in depth page specific analytics to understand the performance and make improvements to achieve desired business goals.

  1. Not adding code to your whole website

    Many times website developers do not add GA code to all the pages (in the header section) fearing it will result in performance issues. However, GA will be unable to provide full insights about the website- which pages get the most traffic, whether visitors from ads make purchases, the types of browsers visitors use and much, much more. Without all the data GA tracks, it will be difficult to optimise the website to the best of its capability and understand its weak points. Plus, developers can make GA work without affecting the performance of the website, if it does.

  2. Not removing Internal Session Data

    For many organisations, 1000s of page views per month are taking place through our own employees. Every time an employee visits your website, test a link, or developers work on the website, etc all of it will be recorded by GA. This is very likely to inflate the traffic and page level data giving an inaccurate picture. This is more likely to impact critical metrics like conversion rates, etc. This proves to be a big problem for smaller businesses where internal traffic can result in a huge discrepancy. Solution: Create a filter that removes the activity from internal employees. This will remove the data from the employees How to remove internal traffic from Google Analytics

  3. Not Using/Misusing UTM parameters

    UTM (Urchin Tracking Module) parameters are appended to the URL to understand from where is the traffic coming from, which banners/content is driving best performance, which keywords are working the best to achieve business goals. For example, if we are putting banners on a different website to advertise, UTM parameters will help us understand which websites are driving the quality traffic. One can create URLs with UTMs automatically by just adding parameters

    Campaign Source

    utm_source

    Required.

    Use utm_source to identify a search engine, newsletter name, or another source.

    Example: google

    Campaign Medium

    utm_medium

    Use utm_medium to identify a medium such as an email or cost-per- click.

    Example: cpc

    Campaign Name

    utm_campaign

    Used for keyword analysis. Use utm_campaign to identify a specific product promotion or strategic campaign.

    Example: utm_campaign=spring_sale

    Campaign Term

    utm_term

    Used for paid search. Use utm_term to note the keywords for this ad.

    Example: running+shoes

    Campaign Content

    utm_content

    Used for A/B testing and content-targeted ads. Use utm_content to differentiate ads or links that point to the same URL.
  1. Not tracking up Goals/Conversions for tracking

    Goals/Conversions helps us understand whether visitors are taking desired actions or not. By analysing our marketing strategies against these desired actions, we can analyse what is working and what is not; which channel is helping us achieve the best outcome, etc. Desired actions can be purchase, adding to cart, video plays, leads generated, or visiting specific pages depending upon the business objective. Setting up correct goals speed up the whole optimizing process and help us better analyse our marketing efforts. We can even assign monetary values to these goals to directly compare associated marketing costs. By clearly defining a conversion goal in Google Analytics, one can see where the conversions came from, what pages on the site users have visited most before converting and analyse what made them convert vis-à-vis other visitors.

  1. Not tracking events

    As mentioned above it is imperative to understand what pages users have visited and what actions (events) they have taken before the final conversion. These productive actions can be referred as events which need to be tracked. For instance, an e-commerce website can define an event as “product page” views or “add to cart” as an event which needs to be tracked. One can also use these events to better analyse the performance of the various website assets. For example, “clicks” on the button can be called an event and using this we can A/B test what colour incite most clicks. It is always good to track all the key events which result in goal/conversion to be achieved. There will be times when events will be defined as goals too.

  2. Not linking Search Console/Google Adwords with Google Analytics

    Search Console provides critical information about how the site performs organically in Google search results. Google Adwords help us understand how our ads are performing on Google. Though both these platforms have their own dashboards, linking them to GA provides additional benefits associated with Google Analytics viz- remarketing lists based on goal completions, key events actioned, browsing behaviour on the website, etc. More importantly, it is easier to compare the performance of multiple channels at one place.

  3. Only analysing the aggregated data

    Google analytics provides capabilities to segment data based on demographics, behaviour, device, acquisition source, etc. Creating multiple segments give deeper insights into the visitors and ton of other valuable information. This will help create tailor made content and thus, be more relevant to the users visiting your website.

  4. Data points vs trends

    To answer whether conversion rate is “good” or “bad” is tricky question because there is no good or bad conversion rate. Of course, you can have industry benchmarks to compare to. However, the better way to approach this is to look at the trend over time of your own conversion rate or other key metrics. This will directly be correlated to the efforts you are putting in to improve and help you even outperform the best of the competition.

  5. Adding Annotations in GA

    This is more of a “good” habit to clearly annotate the key changes done which have impacted the data in GA. This will always help you replicate the winning strategies and learn from your mistakes and will maintain a repository of your past actions.

  6. Not removing Referral Spam data from the GA reports

    Referral spam is the process that spammers use where they utilize web spiders or bots to send one or more fake hits to a Google Analytics account (a hit can take the form of anything from a page view to a transaction). For a smaller website, referral spam gives wrong impression of the traffic and corrupts key data like conversion rate and other goals.Thus, it is imperative to remove the spam data from GA.

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