After looking at how including images in tweets can generate engagement, we have also had a look at how timing can help inform marketing strategy, considering both ‘inbound’ traffic and ‘outbound’ campaigns.
Where data sources report results on a date basis, you aren’t limited to looking at them in a series - you can also see their distribution by day of the week, or hour of the day.
Using the BIME Google Analytics connector it’s quick to set this up using a couple of helpful functions. First, create a [Weekday] attribute from the [Day of week name] field to specify what order you want your week in. This is really easy with an Ordered Set attribute which allows you to drag elements into the desired order.
Then, whether you want to see sessions, users, or pageviews, you can change the result from a number to a % over the chosen time period using the result manipulation menu. Using a Result Path Calculation you can specify that you want to see the % of total - you can also use this to look at growth rates, running totals, result rankings, and many other things!
This gives a distribution of traffic over the week, allowing you to see when is a good time to post new content, do maintenance/updates, have staff available if you have a live chat / support function etc.
In our example, we see a drop-off in traffic at the weekends - well, we’re a B2B provider, so we’d expect that. Tuesday is the busiest day for both - when people have recovered from Monday back in the office, perhaps? - and Friday the most relaxed weekday. This is all at the time of writing - as a live connection, we can always stay up to date with changes as they happen!
However we can also dig deeper; by using a connection that aggregates our two websites (in English and French), we can also see if they have different patterns. Of course, visitors to our English-language site come from all over the world, including countries that with different weekends, but we can see that the change in traffic to our French site is much more pronounced.
With Google Analytics also reporting by time, we can dig deeper still, to see what time of day we see most traffic. Again, we looked at the two sites (which use Pacific and Central European time respectively) separately; there is global traffic to the English site, against a smaller geographical reach for the French site. Thus, the English site shows a bump at the overlap of US mornings with Europe’s afternoon, but a much flatter line, whereas the French site has a very marked difference between ‘working hours’ and the rest of the day. You can even see people taking their lunchbreak!
Adding in quality metrics such as bounce rate, pages per visit, average session length etc will give an even higher level of understanding of your reach and engagement. Similarly on the outbound front, with connectors such as Campaign Monitor and MailChimp you can see when is best to send out emails or launch campaigns. Try looking at the open or click rate by day of the week, or organise hours into a group calculated attribute to see if you get more engagement from morning / midday / afternoon mailshots. This allows for A/B testing to see if changing your timing could improve engagement rates.
As well as your own website and marketing efforts, businesses will now have a presence on multiple social media platforms, and BIME can connect to lots of them! Comparing the distribution of reach / engagement for different channels can be very interesting - particularly if you’re B2C, post ‘fun’ content, run competitions for followers, and/or prioritise different channels and content types.
What’s crucial is to find your pattern, and plan accordingly. You’ve got LinkedIn, Youtube, Facebook, Vimeo, Twitter and DailyMotion to look at, and more connectors are coming every week! All this means that you can develop strategies that are focussed on your business context and are website- and channel-specific. Cloud BI from BIME is the perfect way to connect to all your data, live and direct.