Adding segments into your marketing campaigns allows you to communicate on a one-to-one level with thousands of users
Personalized, relevant, and timely marketing interactions are undoubtedly the most effective. In the past, marketers sent out blanket campaigns to their users irrespective of their behavior while interacting with their product, the stage they were at in the product lifecycle, or their customer LTV. Of course, if you send out a blanket campaign to your whole user base then the message will not resonate with each user equally, some will be engaged and others will disregard the interaction. This raises an issue for marketers – how can they ensure that they do not annoy their loyal users whilst communicating on a personal level with their users?
Instead of trying to find one marketing campaign that will please you full user base, it is better to create multiple different campaigns for segments of users with different interests or preferences. This will ensure that your marketing efforts remain personalized, relevant, and timely for your users, even when you have a large amount of users. However, clustering large amounts of users together to create the segments requires a large amount of data analysis and effort from humans. This article will discuss how machine learning algorithms can cluster users together into relevant segments, making it simple for you to deploy targeted marketing campaigns to large amounts of users.
Why is it important to segment your users?
Customers need to feel that they are understood and appreciated. They need to feel as though the marketing campaigns you deploy were created specifically for them. When operating on a one-to-one basis with your users, this is relatively simple to do. If your business has millions of users, like an app for example, this is a much more difficult task. Fortunately, if you do have a large amount of users who engage with your product, you will also have a wealth of user data which you can draw vital information from.
Upon analysing your user data, you will start to notice striking patterns. You will notice that groups of your users behave similarly, be that because they are active daily or because they rarely engage with the product. This information is the foundation for your user segments. Users will be places in segments based on their behavior, preferences, purchase history, and usage. Segmentation reinstates the personal connection with your users, enabling you to personalize your marketing interactions to the users in each segment, as if they were your only customer.
How does Machine Learning segment your users?
Machine learning is perfect for creating smart segments for your user base as it allows you to easily group your users together for effective, personalized marketing interactions.
Smart segments are created by machine learning algorithms analysing a large volume of data for each and every user, and then clustering similar ones together. These clusters of users are also known as ‘personas’. Personas represent the major types of users which you will encounter based on your product.
If you were to analyse the personas which are found on Twitter you would likely find that there are three main personas: ‘creators’ who post original content’, ‘consumers’ who mostly retweet / favourite content, and ‘readers’ who mostly read tweets with little social engagement. Of course, each of these personas are valuable to Twitter irrelevant of how they engage with the product, but they will each react differently to marketing interactions. For example, there would be little value in Twitter sending a push notification to the ‘creators’ advising them to share something about their day, as they will likely do this anyway.
Why should your business use segments in marketing campaigns?
Customers have come to expect marketing which is tailored towards them. They expect a message which attests to their preferences and needs. It is critical to remain relevant in the market, and successful marketers will take full advantage of the benefits which segmentation offers. Segmenting your users allows you to market specifically to their individual needs, but on a much larger scale.
Adding segments into your marketing campaigns will also reduce the costs of your marketing, as you will be able to communicate with users even if you have a low average LTV. Marketing campaigns aimed at segmented users also have a much higher success rate. For our loyal customer, Zoobe, we at goedle.io managed to increase day-15 retention by 64% by implementing segmentation into their targeted marketing campaigns.
How can goedle.io increase the effectivity of your marketing campaigns?
Our product utilises machine learning algorithms to cluster your users based on their behavior whilst interacting with your product. Once your users have been clustered into segments with other users who behave similarly, goedle.io will then assign them with a ‘persona’. The personas which will be assigned are tailored to your product, and are designed specifically for your needs.
Once the personas have been assigned, you can then create personalised marketing campaigns for each segment. The campaigns that incorporate segmentation which you deploy will have a much greater success rate than the blanket campaigns you used previously. goedle.io also utilise dynamic segmentation, as we understand that the way users interact with your product can change. Our dynamic segmentation algorithms are constantly changing to ensure you have the best analysis of user behavior.
We understand that you will want to measure how effective your marketing campaigns are once you have implemented segments. In light of this, we also monitor your marketing efforts and advise you about which campaigns were the most effective, and how to further improve for the future.
Interested in incorporating segments into your marketing campaigns? Get in contact or schedule a web demo now!