Analysing website performance using Power BI and Google Analytics

In this blog post, we will analyse website performance using Power BI and Google Analytics (GA4) data. We do so by using an existing report, which is available in our Portfolio, and it is called Website statistics. For information, we described in a previous blog post how to connect Power BI and Google Analytics.

Introduction of website analytics using Power BI and Google Analytics

The report connects Power BI and Google Analytics, and we are using the GA4 connector to do so. It is a rather simple report with just one page, and the purpose is to show effectively a snapshot of the most important website metrics. Using the Power BI online service, we have set up automatic refreshing of the GA4 data. For more information about Google Analytics, we refer to this page.

The default view presents the performance in the Current month, but it is possible to go back in time to review the month of interest. We measure the following metrics:

• Sessions
• Bounce rate
• Hits
• Visitor type
• Visitor source
• Seconds spent per page

They are visualised from different perspectives, for example, the sessions can be seen per day and per city and they are also compared to the last month.

Quick introduction of the measured metrics

We will here go through the interpretation of the metrics used in the report and justify why they are measured.

Sessions is the most basic website metric, and basically measures all traffic coming to your website. It is the starting point of all website analytics.

Bounce rate means that only one page is visited for a specific session. Typically, it is desired to keep the visitor engaged and have the visitor visit multiple of your pages. We measure this because we want to ensure our full website content is shown to the visitor.

Hits measures the number of user interactions. For example, a user clicking on the link to another page would imply one hit. Similarly to bounce rate, we want to ensure that our content and message are displayed to the visitor.

Visitor type measures if it is a New user or an Existing user that is coming back to your site. This is important to measure, because it needs to be aligned with your business intentions. For example, if you want to attract new customers, you would like to see New users visiting the site.

Visitor sources measures from where the traffic originates. For example, direct means that the visitor knows your URL and has visited your site directly. This is an important metric as it shows how well your marketing campaigns and marketing outreach are working.

Analysis

In this chart, we see the number of sessions for each day. With the line, we are also able to see the accumulative number of sessions throughout the month. For example, we see that approximately from day 11 to day 20, there was no traffic at all.

We present three high-level KPIs and compare them to the last month. The first KPI is the number of sessions which were up by 76%, compared to the last month, which is a large change. Then there is the bounce rate, which means that in the month, on average, 27% of the sessions only had one page visited. Ideally, here we would like to see a low %, as we would like the user to visit several pages. Then, we see with the hits, that on average 0.3 user interactions happened per session. This was an increase by 8% compared to the last month.

If we then move on to more in-depth KPIs, we see a distribution of the sessions by the city they originated from.

When reviewing where visitors spend their time, we see that the Portfolio page was, by far, the page that the visitors spent the most time at.

Next, we see that 57% were New users and 43% were Returning users. We consider this a healthy balance, but it also is very specific for each site’s business intentions. We also see that we had two types of traffic sources – direct and via Google, where direct traffic dominated at 67% of all traffic.

Summary

We used a Power BI report to analyse website performance. In addition, we looked at common website metrics like sessions, visitor types, visitor sources etc. and learnt why they are important to measure. By using Power BI and Google Analytics data together, we can tailor our analysis exactly how we want it, but there are also possibilities to use other tools, like the built-in charts in Google Analytics’ web tool.

On the development of the SEK exchange rates in January 2024

In this blog post, we will analyse the development of the SEK exchange rates in January 2024. We will use a Power BI report that is available in our Portfolio. In case you are interested in an analysis over a longer time period, we have previously written a blog post about that.

The source of all data is the Swedish central bank – the Riksbank.

January 2024 overview

We start by going to this page, and change the year filter to 2024. We then click on January in the table. A good feature with Power BI, is that it is dynamic and by clicking on January, the rest of the page updates with January as a filter.

We then see in the chart on the top left, that SEK only strengthened against one of the currencies – Japanese yen (JPY) – out of the ones present in the report. We also see that there were no dramatic changes in January, and all movements were approximately within the range -2% to +3%. It can be noted here that + means that SEK weakened, and – means that SEK strengthened. For example, if the EUR-SEK exchange rate goes from 10 to 11, that +1 change is a weakening of the SEK.

We note that SEK weakened the most against Pound sterling (GBP) at 2.4% and then with 2.1% against the US Dollar (USD). The SEK barely changed against CHF (+0.6%) and NOK (+0.4%).

Zooming in on the chart of percentual exchange rate development, it will look like below. We see that in the very last days of January, there was a strengthening of the SEK against all currencies.

If we review the movements of the SEK 5 and 10 years bond yields, and compare to the development of the same for USD respective GBP, we also see no dramatic movements that could explain the exchange rate development. In addition, we see that the SEK bond yields were all up in January, for example the 10 years yield went from 2.11% to 2.22%.

Finally, we dive a bit deeper in regards to the bond yields. Using the two pictures above, we see (in Power BI only) that the USD 5 years bond went from 3.92% to 3.84% (-8 bps) in January while the SEK 5 years bond went from 2.01% to 2.16% (+15 bps). Conversely, the GBP 5 years bond yield went from 3.55% to 3.74% (+19 bps), which is more in line with the SEK equivalent.

Summary

In January 2024, there were no dramatic changes of the SEK exchange rates compared to major currencies like GBP, EUR and USD. SEK weakened by 2.4% against GBP and by 2.1% against USD, while it strengthened by 1.8% against JPY.

With regards to bond yields, the SEK 5 years yield increased by 15 bps. That can be compared to the USD 5 years yield that decreased by 8 bps and the GBP equivalent which increased by 19 bps.