How to read your Google Analytics Metrics Better

Analytics play an important role in tracking the performance of your marketing efforts. Google Analytics, by far, remains the most used platform to track and analyze your customers’ digital foot print. It provides a wide array of data points for marketers to analyze, evaluate and design campaigns.

Because of complexity and time constraints, marketers often concentrate on single metrics only. When studied in isolation, these metrics often fail to convey the complete story. For example, revenue is undoubtedly the major metric every business concentrates on. But, when relying only on revenue without studying profitability the full picture is not seen.

The fascinating part with metrics is, every new dimension added brings forth a deeper understanding.

Traffic-Related Conversions

Measuring traffic in the form of visitors – including both unique and returning visitors – by their source, is an important part of assessing the performance of your online marketing activities. Traffic-related metrics give an assessment of your website’s popularity. Driving more traffic, consistently, is a vital marketing activity. In order to develop an understanding of traffic sources marketers must look more in to traffic-related data points.

Specific traffic patterns are identified with periodic traffic metrics, including daily traffic, weekly distribution and monthly distribution. . Patterns, such as, increased traffic during a specific day of the week, or time frame, should be identified and documented.

This data should be read in conjunction with data from various other sources to identify reasons for the increased traffic during the identified periods. It can also be used to identify the correlation among the marketing channels. For instance, a social post can increased your traffic through social channels and might also result in increased traffic through organic channels. Adding these extra dimensions of periodic traffic and traffic sources will provide more insights.

Engagement Metrics

The engagement of website visitors drives the conversion rate. The time spent is considered to be directly proportional to engagement levels and is is often considered an important analytic metric. An analysis must be made as to whether or not the time being spent on the website is helping the visitor move through the conversion funnel quickly and efficiently. This can be done by analyzing the pages per visit along with the time spent on the website. More pages per visit along with more time spent on the website often indicates fruitful engagement levels rather than just higher engagement levels.

The effectiveness of a digital ad is often measured using the click-through rate. This helps to analyze the effectiveness of a specific ad to generate clicks and to drive traffic to the website. It also helps to analyze the relevancy of the content being displayed in the ad. However, a click-though rate only helps to analyze the interest being generated by an ad.

Once the interest is generated, it is important to sustain it and to convert the lead to generate business. Measuring the bounce-rate of the landing page helps in this aspect. It is an indication as to whether the traffic being generated is being redirected to a correct page or not. By assessing both these metrics in union, you can not only create an effective ad but also design higher converting landing pages for the ads used.

Conversions and Assisted Conversions

How can optimal traffic sources and marketing efforts be determined? Through various traffic source analysis. However, Google analytics by default uses the last click attribution model and assigns the conversions credit to the last channel the visitor used during the conversion. This undermines the role of other channels in the conversions process and also often leads to sub-optimal spread of marketing spent across all the channels.

Conversion through various channels and Assisted Conversions should be read in tandem. This helps to understand the importance of each individual marketing channel in the conversion process. It also helps to identify the channels which help best to initiate a conversion, and channels which help to engage visitors during conversion process. Correlating these two data points ensures all marketing channels are assigned their due credit and all efforts are distributed accordingly.

Conversions per Channel and CPA

Businesses rely on various marketing channels to acquire new customers. Over reliance on a single marketing channel may exhaust the source after a period of time resulting in reduced lead generation. Conversions-per-Channel is often used as a metric to assess the performance of various marketing channels. It helps when analyzing the number of leads being generated and converted from each marketing channel.

It requires a lot of effort and time to create a dominating presence in a marketing channel and to generate sustained lead flow through these channels. Businesses must also consider the cost involved in marketing through these various channels. It is best to study the Cost-per-Acquisition of a lead, as well as the conversions per channel, to assess the performance of these marketing channels. Adding this new dimension helps to identify the most cost-efficient marketing channels for your business.

The current advancements in the digital marketing space allow businesses to track most of their marketing activities in totality, giving many data points to quantify the success or failure of a marketing campaign. It is not only important to track and record various data points, but also to choose the useful data which is going to make the best business sense – to ensure the story of every metric is complete. Choosing the right metrics to track and define the success of marketing efforts, it is important to identify the adjacent metrics which are going to provide complete analysis.

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Author: Mahesh Tadepalli

Mahesh Tadepalli brings the analytical edge to the marketing campaigns we manage. A holder of Master’s Degree in Mathematics, he plays a major role in harnessing the marketing data for effective decision-making. His experience in working with tech startups and understanding of marketing have proven to be instrumental in defining marketing technology solutions for companies across various industries.