How to Optimize Push Notification Campaigns with AI and Multivariate Testing?

Push notification can lead your company or website to a higher conversion rate if the push notification is good. You need to prepare convincing messages that your users like to read so that users engage themselves. Push notification plays an important role in marketing. Marketers have to create impressive push notifications that lead them to higher user engagement.

How marketers can evaluate whether push notifications sent by them to customers are useful or not. Push notification campaigns of any company have to measure the efficiency of these notifications. To know the effectiveness of push notification, there are a few technical methods:

1. Push notification campaigns can be optimized by A/B testing and multivariate testing.
2. Push notification makes you understand how your users reverberate with the app.
3. It also helps you to evaluate customer engagement with your app.
4. It gives you the insight view of push notification campaigns that helps you to improve your push notification.

What is Push Notification?

Push notification is pop-up messages that appear on the mobile of users or on computers. These pop-up messages are clickable, and by clicking on them, users can get to the main content of the push notification. These are the short messages from the companies for promotion, offers, sales, etc. They are like the communication channel between customers and companies. Users can get these messages on the browser, whether online or offline. Push notifications are simple messages that a user can respond to. These are the small opt-in messages that a company sends to its customers whenever they open a browser or website of the company.

Click here for the push notification guide

What are AI and Multivariate Testing?

AI (Artificial Intelligence)

AI (Artificial Intelligence) is software that aims to understand the test data to make testing more efficient and smarter. AI testing uses automated reasoning and problem-solving methods to present improved testing. AI analyzes every action of each individual throughout the journey. It eliminates the boredom of analyzing vast data. AI tested every aspect of the user’s journey. AI effectively evaluated the vast data by hypotheses in its test. It helps companies to create personalized, tailor-made, and automated messages for every individual customer. AI is powerful for any company that helps in marking marketing tactics more effective. It gives the different combinations of the different variables for the best result in real-time.

Multivariant Testing

Multivariate testing is also a split-testing like A/B testing, but in A/B testing, visitors are divided into two variants: A and B. In multivariate testing, you can split visitors into more variables that tell you more about how every variable interacts with other variables. It is a technique of testing by hypothesis to modify multiple numbers of variables. It helps you to utilize the same identical message to know which is more useful.

The main motive of multivariate testing is to find out which combination of variables has the best suitable combination to give effective results. A website receives huge traffic; the data for testing each variable is compared to know different things like the design of a website or other elements. It shows you the views of users, whether it is positive or negative. 

Multivariate testing uses various combinations of changeable variables of websites or apps. It changes the multiple elements of a website at the same time, like changing a picture and headline. These combinations by interchanging the different elements will help in getting the best variation.

Optimizing Push Notification Campaigns with AI and Multivariate Testing

In e-commerce, every marketer needs a method to gain or optimize their campaigns. Every business aims to get more sales and high profits. In digital marketing, A/B testing or split testing has always been the most common method to optimize marketing campaigns for many years. Nowadays, the A/B test is an ordinary method in different digital mediums like e-mail marketing, display ads, etc.

In digital marketing, AI (Artificial Intelligence) and ML (Machine learning) are new to analyze data at a higher level. AI and ML customize data into individual customers, not by the market segment. Also, AI assists companies to combine their marketing data from many campaigns to achieve the best result for marketing which was not possible earlier. AI and Multivariate tests can be helpful when multiple elements on a page can be changed back to back. Multivariate testing is a method to help companies to redesign the pages of their websites.

Push notification is the most profitable method of marketing in digital marketing. But, how many push notifications are open? How many push notifications get converted? To ensure that or evaluate that experimenting for creating methods or technologies is important. For these evaluations, AI and Multivariate testing were used. To optimize the push notification, AI and Multivariate tests have been done.

Here we look at the 7 points to understand that:

1. Customize push notification:

The push notification campaign has to focus on the customization of messages. Thus, it drives more customers; by using AI tests, segmentation of customers becomes easier. AI tests analyze every aspect of data that helps in creating a customized notification for every customer. For example, a company sends four variations of push notifications to its customers; the company gets more CTR from the customized message as it contains the emotion and concern to the customer’s problem or need.

2. Relevance:

AI is used to ensure that notification is relevant or not. AI and Multivariate tests analyze large amounts of data according to the preferences or interests of users. It assists the marketers in knowing the relevant content for customers to engage them. For example, an e-commerce site gets its revenue more from recommended purchases; an OTT content platform knows 75 % of users consume recommended content.

3. User engagement:

AI and multivariate tests make it easier for marketers to give customers a personalized experience. It encourages user engagement and customer retention. By getting personalized recommendations, offers, messages, users like it to get more that help companies get higher conversion. Understanding customer’s language and their likes are important to get their engagement. For example, an app sends weather forecast notifications with two variations; the notification having the user-friendly language gets more CTR than the other variation.

4. Time:

AI and multivariate tests play an important role in analyzing the data pattern of customers. This will help in knowing the set of time or most relevant time to send push notifications to customers. As the AI test analyzes every aspect of data of each individual user, it can assist you to know the time when the user is most responsive and engage with it. For example, marketers use AIQUA to identify the right time and right way to connect with users.

5. Clear and concise:

Push notification must use clear and concise language. A push notification uses concise language that a customer can understand and engage. Push notification should be clear to the objective of the message. AI and Multivariate testing assist in understanding the messages which are more effective and user-friendly. AI testing is a real-time method for analyzing data. For instance, a company sends two variants for a message; one with a clear and concise message without a picture and the other with a picture. Surprisingly, messages with clear and concise language get more CTR than the other variant.

6. Frequency:

The main objective of push notification is to get more and more conversion rates. With AI and Multivariate tests, marketers will understand the potential customers to get the conversion. It also assists marketers in knowing the perfect frequency of messages. On the other hand, too many messages can have a negative effect on customers. Therefore, the frequency of notification should be maintained to get customer engagement.

7. Location:

Push notification with customized and personalized message effect more to a customer. Customizing a notification according to the customer’s location or geographical location is important as it engages customers easily. For instance, a message sent by a healthcare service for booking for testing informing the entire local community about the test booking, date, timing, location, etc., will get more user engagement than the message without having information of location.

CONCLUSION

By modifying your app marketing with AI, the marketer’s work of analyzing data gets easier and less time-consuming. It makes notifications or messages more personalized and customer-friendly. With the help of AI, marketers can deliver more personalized and relevant messages. With AI testing, marketers can now ensure that their marketing strategy and campaigns are not based on guesswork; they are more proof data. It optimizes the push notification campaigns for perfect results.

AI is faster and more effective than A/B testing. It takes all the hard work from you and presents the best result. It works on an automated method that makes it less time-consuming. AI enables marketers to optimize the entire funnel. Also, AI and Multivariate testing use fewer resources as they work on defined methods. AI testing is more useful now as the digital market is growing fast.

Also Read:

• Re-Engage Customers: Use Push Notifications for Customer Re-engagement
• 15 Best Push Notification Software & Tools in 2022 {Compared}
• E-commerce Websites: Use Push Notifications to Target Customers
• How Can Personalized Push Notifications Increase User Engagement?