Analytics – Making Sense of
In marketing, there is no better tool than Google Analytics because it was developed for the ultimate purpose of tracking the performance of a website. Whether used by an in-house marketing team or outsourced marketing professionals, Google Analytics seeks to track how visitors interact with the site in order to maximise profits.
Unfortunately, many analysts struggle with reports due to the fact that they don’t have a solid grasp on particular key performance indicators, referred to as a KPI. If you are new to Google Analytics, you may be overwhelmed but be assured, there are a few simple approaches which can make it easier to identify KPIs, set up the analytics process and to eventually utilise the data to forecast performance.
Following are the major key performance indicators that are utilised by Google Analytics and the information you will need to make the most of the data. However, it needs to be understood that each of the KPIs are to be seen in terms of your ultimate business goals. Some may be pertinent to one site but totally irrelevant to another. It is the hope that once you understand the correlation between specific key performance indicators and your website, you will be able to quickly set up the process to track only that data that is relevant to your needs.
A Brief Look at Key Performance Indicators
Here is a problem which many people encounter. It must be clear from the very outset that Google’s key performance indicators may not be the same as those you would utilise for your website. Each site is designed and set up per your business model so what is important to one site may not be important to the next. Even so, there are some that are a critical part of the analysis of all websites and these are the ones which should be understood first.
Key Performance Indicators vs. Metrics
In fact, it is a misnomer to say that Google tracks key performance indicators because they have absolutely no idea what your business goals are! Google utilises metrics which are measurements of your website’s activity/efficacy, but they couldn’t actually track its ultimate performance because they don’t know your goals.
To put it another way, as far as Google is concerned, keeping the bounce rate down is indicative of a site that is performing well. However, from your perspective as a business owner, if those non-bounce visits don’t translate into sales, the analysis of the KPI would be less than positive. This is a vital piece of knowledge when trying to make sense of your analytics.
Traffic as a Metric and KPI
In the terminology of Google Analytics, traffic is measured by visits, often referred to as sessions. This is a number-centric approach and is largely based on how many visitors land on your page, how long they stay there and whether or not they click through to other internal pages within your site. These are the metrics that Google analyses but from your perspective, you will be seeing them in terms of KPIs. Obviously visitors who bounce right out again are not going to convert but what about those who click through and still don’t convert? Then there are those that click around your site a while and eventually end up converting. This is the information you will utilise as key performance indicators because it has a direct correlation to your business objectives, to make a profit.
Forecasting Traffic with Predictable and Non-Predictable Vertical Metrics
Winter Tyres Industry as an Example One Peak Vertical
Understanding the characteristics of demand is crucial for forecasting traffic. Using a weekly time range, we can observe the typical fluctuation between weekend week days within the range. On Monday, most commercially oriented websites receive the highest volume of traffic and each successive day after that receives less and less traffic. Finally Saturday, and especially on Sunday, the amount of traffic amounts to only about 30% or less of what Monday’s traffic is.
In the yearly time frame similar fluctuation occurs. For the winter tyre industry, a known quiet period exists between March and October. Then November through February is a period of high demand.
Holiday Packages as an Example of Predictable Vertical with Two Peaks
Another good example is of predictable vertical holiday packages. Actually, there are two distinct peaks in demand during a 12 month period between January and December.
The first peak-period appears in January. This is due to the fact that most people are planning for the next year immediately after it begins. That plan can take on many facets where one of them is where to go for a summer holiday. It is possible to track how people are planning due to the employment of holiday related keywords such as “cheap holidays” or “holidays to Spain” being searched for by this group of consumers.
A second peak-period exists at the beginning of summer. June and July generates higher demand because of last minute planners looking for a way to book a place to visit. These customers are a different group from the first group described above. They are more likely to be looking for a bargain and special offers.
Example: Mobile Handset Vertical as an example of non-predictable
A much smaller group is a group of non-predictable verticals. One of them is a mobile handset vertical. Each year Apple releases a new iPhone. Despite the fact that it may be a little easier to predict a name of the next handset such as the 5, 5s, 6, 6s or 7, it is not as easy to figure out when the next edition will be released. There will always be a tremendous amount of rumours every year, but the real spike is visible once the device is announced and available on the market.
TRAFFIC REPRESENTED BY SESSIONS (VISITS) AND EFFECTIVE (NON-BOUNCED) SESSIONS
Traffic to your site is called ‘visits’ or ‘sessions’ in Google Analytic terminology and is a wonderful number-focused approach. However, these numbers need to be seen in terms of year-over-year for every predictable vertical period.
For example, when comparing between traffic during January 2014 to January 2015, the percentage of growth is what’s calculated. The following simple formula enables you to forecast future growth and then verify it:
%growth = [(Visits_Jan_2015 / Visits_Jan_2014) – 1] x 100
For websites that are established, the %growth should waiver somewhere between 10% and 20%.
Google Analytics free version, which is the most popular analytical package, gives the ability to check ad-hoc that percentage growth. Regardless of just how powerful the Google Analytics package is, there is frequently a problem with data sampling. High traffic websites frequently deal with this problem more often than small or mid-size ones. Sampling may erode accuracy of data so to avoid this problem there are a few recommendations:
- Compare numbers in Excel rather than directly in Google Analytics;
- Generate and download raw data export from Google Analytics using 3rd party software like Analytics Canvas which has a built-in function of slicing time range segments – that functionality was created to solve sampling problem;
- Use weekly / daily segments to keep sampling on the low level (50% or more real data);
- Build additional pre-filtered profiles gathering data separately – that will help to avoid unnecessary segmentation. For example:
- specific directly (example.com/directory/*) traffic only
- specific channel (for example Organic Traffic) only
- non-bounced traffic
Effective Traffic Also Known as Non-Bounce Traffic as an Indicator of Traffic Quality
Bounce Rate and Bounced Visits are other metrics available in most of the analytical packages. Aggregation of the Bounced Visits metric with Visits (or Session) can give a broader and better view of achievements and challenges that are kept in sight of the online marketing team. Bear in mind that the purpose these analytics is to forecast growth based on current data and to offer the ability to switch up on strategies if these forecasts are not favourable.
Here again, it is necessary to mention that Google is looking basically at the length of time each session lasts and such things as whether the visitor clicked around the site. This is important to you but not nearly as important as looking at that data in terms of conversions. Having a monetised site means that literally every bit of data should be seen in terms of performance, in this case sales.
So then, if you are looking simply at the increase in traffic on your site, year over year, the example calculation would look like this:
Effective_Visits_Jan_2014 = Visits_Jan_2014 – (Visits_Jan_2014 * Bounce_Rate_Jan_2014) Effective_Visits_Jan_2015 = Visits_Jan_2015 – (Visits_Jan_2015 * Bounce_Rate_Jan_2015) %effective_growth = [(Effective_Visits_Jan_2015 / Effective_Visits_Jan_2015)-1]x100
It always makes sense to focus on the quality of traffic as well as the quantity of visits. Even so, there are specific situations where effective (non-bounce) visits and effective growth should be seen as the main KPI. One example of how this would be the case would be when referring to vertical leaders. These would be leaders who achieved most, if not all, of their objectives in the area of organic and paid website optimisation. Once that is realised, the focus switches from leveraging traffic to maintaining the quality of existing traffic.
From here on out, the company needs to be even more focused on how to make best use of the traffic that is driven to the site. In terms of organic traffic, this is a key point. Google’s Algorithm keeps behavioural metrics on top of the hierarchy – time on site, pages per session, bounce rate were never so important.
The quickest way to improve effective visits and the growth of effective visits then, will be to keep focus on following:
- Optimization of UX
- Internal liking structure improvements
- A/B tests
- Better Call To Action (for example above the fold)
This is a healthy approach because it not only follows the metrics but also improves monetization of the website and in turn, improves finance related metrics.
A good approach is also to use standard channel segmentation to calculate effective traffic per traffic channel.
Integration of Search Volume, Organic CTR and Ranking
The typical in-house marketing department report is designed to focus on metrics separately. Still today, reporting tables frequently contain ranking of keywords along with search volume per keyword. After that, it becomes necessary to analyse traffic per URL.
Although Search Engine Optimisation (SEO) still reigns supreme in terms of organic traffic, it is advisable to research and prioritise what are called the ‘low hanging fruit’ of SEO. These are other strategies that help build traffic to your site or improve its rank in any way and altogether too often, webmasters lose sight of the lower branches. One example of low hanging fruit which many people overlook is good content. Remember, when it comes to ranking, Google looks at sites of authority with high quality content. This can quickly establish you as a site of authority.
Utilising Low Hanging Fruit to Improve Rankings
As mentioned above, low hanging fruit can also factor into key performance indicators, albeit unintentionally! Some of those pieces of ‘fruit,’ those side benefits would include such things as:
- Search phrase that comes up in both a title and the copy
- Inbound anchor text relevant to the term
- Internal links with relevant anchor text
- Supporting content linked to the page you are trying to rank
- Variations of the ‘unknown’ ranking keyword
You may be asking what SEO has to do with Google Analytics. The answer is quite simple. SEO, as mentioned, is critical in driving visitors to your site and why it should always be a part of the analysis metrics. Whether planned SEO keywords for optimisation or those unplanned but still ranking highly, it is vital that you plug this data into your forecast if you want to maximise your bottom line. If it works, it’s worthy to be a large part of the metrics.
Calculating the Traffic Index
Now then, back to the formula for calculating what is known as a Traffic Index. This is accomplished through the calculation of the Click Through Rate (CTR) and Search Volume of separate keywords. One of the major points which many people don’t understand is that the average organic CTR distribution model is not actually about specific values but rather about the distance between the positions. Therefore, it is a huge jump between positions 2 and 3 but not such a huge difference between 6 and 9.
|Organic Ranking in SERP||CTR|
TrafficIndex = SearchVolume / 2 * CTR
Putting Google Analytics to Work for You
This was seemingly a lot of information and you are probably wondering how to tie it all together so that it works for you. The easiest way to make sense of how to use Google Analytics is seen more or less as a linear progression. The first thing you want to do is record data pertaining to the traffic on your site. Where is it coming from and do they stick around or do they bounce right off again. Before going any further, it is necessary to find a way to keep those visitors on your site long enough to convert.
Some people may buy a product on their very first visit whilst others may need to return several times before they will spend money. These are all statistics that analytics will document for you so that you can go back time and again to see what is working. This part of the process is the ‘metrics’ side of analytics. You are measuring results and simply analysing the data to find where they came from and how long they stayed. Next you will find buying patterns so that you can get a better idea of what works. Once you have a clear picture of what works to convert visitors to customers, it’s time to begin forecasting future returns.
These results, the effective practices that convert are going to be a vital factor in your key performance indicators and how they bear on future forecasts. Metrics are how data is measured and KPIs are how various strategies performed. There may not seem to be much of a difference and too many people mistakenly use the terms interchangeably, but the bottom line is that you are really seeking to analyse data (metrics) in order to see which strategy (KPI) worked.
Summary of Predictable and Non-Predictable Metrics
Some metrics within Google Analytics can be predicted based on specific influences whilst others are variable. Predictable vertical metrics are easier to use in forecasting because we are aware of the factors that influence traffic. Even so, when forecasting the efficacy of a website, non-predictable metrics must be factored in as well.
Both in-house and professional marketing groups need to understand how to work with analytics in order to device marketing / advertising strategies that maximise profits. If you are not using Google Analytics or some other method of gathering and analysing data, you are missing out on one of the most effective ways to build a profitable website.