How to drive results from a Browser push notification in 3 months?
While online shopping went up by 2.8% in the first quarter of 2020, 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. Marketers can now target users anywhere, on any site, even when they are not browsing on the retailer’s site. Marketers can now provide a smooth shopping experience. More so, they can act as a virtual guide for the users when they visit the retailer’s site.
Desktop usage accounts for 42% of the total internet time. While app push notifications are limited to mobile devices and tablets, Browser push notification 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 notification come to the rescue.
So, the entire campaign works like a funnel. In the first layer, you can target the users with Opt-In messages and filter them into subscribers. This level is known as ‘Collect Subscribers’. In the second layer, marketers ‘send customized browser push messages’ and the ascertained the Click-Through Rate. The last layer consists of ‘optimizing the browser push messages’ to sustain the user engagement with the e-commerce outlet.
In this article, we’ll take you bit by bit through each and every level of the campaign. We will also explain how eCommerce traffic can be converted into actual conversions.
1) Collect Subscribers
This is the very first stage where the marketers target the users with Opt-In messages, thus kicking off the digital campaign involving Browser Push Notifications.
Vizury’s Browser Push Notification allows an eCommerce marketer to send Opt-In messages to the user on any of the pages in the website.
So, push notifications can be sent on the Home page and category 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 by Vizury, the Opt-In rate in Home page is about 10%. So, 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. If we roughly calculate the number of subscribers in a month, the figure is sure to touch 12K to 15K (for the 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 revenue for your business. Once in this level, the marketer is sure to understand that Browser Push Notification is way more effective than other marketing channels.
For any successful marketing campaign, 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 segregate them accordingly. After segregating, it sends 1:1 personalized message 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 ‘E-commerce use cases’ in the ebook.
Now, let’s talk about the figures.
Suppose a marketer sends 2 notifications every week to each Subscriber. Hence, 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 will click 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$, then in a month the marketer will get an Extra Sale of 12,800$ (1280 X 10$).
With the phenomenal advancement in the world of digital marketing, marketers need to be aware of 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.
When these are put to the test of actual conversions, they do not stand. Such metrics are called Vanity Metrics. Whereas, the actual figures that let 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 provides you with a feature called A/B Testing. It 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 behavior 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. Subsequently, the marketer is asked to send a new personalized message to the ones that did not click through, like before.
This process is repeated until the marketer finds a chunk of subscribers who have the highest Click-Through Rate. Thus, the marketer finds the number which he/she can act upon and not some number with the feel-good factor.
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