While online shopping went up by 45% last year, another interesting development also took place. Browser Push Notifications were launched and since then, they have started to pave the way for effective digital marketing campaigns. Users can now be targeted anywhere, on any site, even when they are not browsing on the retailer’s site. Marketers can now provide a smooth shopping experience and act as a virtual guide for them when they visit the retailer’s site.
Desktop usage accounts for 42% of the total internet time and while app push notifications are limited to mobile devices and tablets, Browser push notifications cover desktops too. The cost factor involving Browser push is another point which marketers can’t afford to ignore. For small businesses and start-ups which cannot invest in building apps, browser push notifications come to the rescue.
So, the entire campaign works like a funnel where in the first layer, users are targeted with Opt-In messages and get filtered into subscribers. This level is known as ‘Collect Subscribers’. In the second layer, subscribers are ‘sent customized browser push messages’ and the Click-Through Rate is ascertained. The last layer consists of ‘optimizing the browser push messages’ so as to keep the users engaged with the ecommerce outlet.
In this article, we’ll take you bit by bit through each and every level and explain how the ecommerce traffic can be converted into actual conversions.
1. Collect Subscribers
This is the very first stage where users are targeted with Opt-In messages and the digital campaign involving Browser Push Notifications is kicked off.
Vizury’s Browser Push Notifications allow an ecommerce marketer to send Opt-In messages to the user on any of the pages in the website.
So, notifications can be sent on the Home page and theCategory page in a Time-bound manner i.e. after 30 seconds or 40 seconds of user browsing. Here, the marketer would need to keep a track of the opt-in rate as well as any particular page on which this is relatively high.
According to a survey done by Vizury, the Opt-In rate in Home page is about 10%. So for example, if an ecommerce website has traffic of 100K, the Opt-In rate in the Home page would be 10K.
It’s also likely that Opt-In rates in other pages will be more than the Home page. Reiterating Opt-In messages on those pages will create more Subscribers. There will be a surge of 2 to 5% in Subscriptions if such kinds of experiments are run on every page. So that way, if we roughly calculate the number of subscribers in a month, the figure is sure to touch 12K to 15K (for a traffic of 100K). So, after three months the Marketer can expect 36K to 45K subscriptions.
2. Send BPN
This is the stage where Browser Push Notifications get to work and bring in the cash for your business. Once in this level, the marketer is sure to understand that Browser Push Notifications are way more effective than other marketing channels.
For any marketing campaign to succeed, the Right Person always has to be targeted with the Right Message at the Right Time. That is exactly what Vizury’s Browser Push Notifications’ platform does.
It allows the marketer to keep a close watch on the browsing pattern of the Subscribers and then send segregate them accordingly. After the segregation is done with, it’s time to send 1:1 personalized messages to the right person at the right time.
At Vizury, we have run experiments on numerous use cases before putting all of that together in the Browser Push Notifications Platform. You can take a look at them in the section of ‘E-commerce use cases’ in the ebook.
Now, let’s talk about figures.
In a month, if the marketer sends 2 notifications every week to each Subscriber, in a month the Subscriber will receive 8 notifications.
So, if we proceed with that, 320K Browser Push Notifications will be sent out in a month. (40K Subscribers X 8 BPNs in a month).
Extensive market research done by Vizury shows that the Click-Through Rate for Personalized Browser Push Notifications is at least 10%.
10% of 320K subscribers is 32K. So, near about 32,000 people would be clicking through the ecommerce marketer’s messages.
Now, the Conversion Rate, according to Vizury’s market research, has been found to be around 3% to 4%. For 32,000 Click Through Subscribers, the actual number of Converted Customers would be 1280.
If the average order value is for 10$, then in a month the marketer would get an Extra Sale of 12,800$ (1280 X 10$).
With the phenomenal advancement in the world of digital marketing, marketers need to be aware about the figures that they can trust and the figures they can’t. Startups and a few companies who love to boast about their online traffic love to put out quixotic figures about their online traffic, which when put to the test of actual conversions, do not stand. The metrics that such companies publish are called Vanity Metrics. Whereas, the actual figures that lets the marketer take some action about his/her marketing campaign is called Actionable Metrics.
It is needless to say that if the marketer fails to make out the difference between Actionable Metrics and Vanity Metrics, then unfortunately, the campaign is sure to fall apart after a certain period of time.
Vizury’s Browser Push Notifications platform has a feature called A/B Testing which helps the marketer to keep track of that. The level ‘Optimization’ is entirely about that.
How does it work:
According to the user’s purchase behaviour and browsing pattern, they are classified into A, B, C and D segments.
Messages are customized and personalized accordingly and sent out to these subscribers. The Click-Through Rate is monitored after that. The messages having the highest Click-Through Rates are then kept on the list and the one having the lowest is binned. The platform notifies the marketer to construct a new personalized message for those subscribers who did not click through.
The same process is repeated again but now with all the subscribers segregated into three segments – A, B and C with more customized messages. After the Click-Through Rate is evaluated, the message with the lowest score is filtered out and the marketer is asked to send a new personalized message to the ones that did not click through, like before.
This process is repeated till the marketer finds a chunk of subscribers who have the highest Click-Through Rate. And thus, the marketer finds the number which he/she can act upon and not some number that helps with the feel-good factor.
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