Everyone knows how customer segmentation works. Companies want to personalize their marketing efforts so they can easily find customer demographic data like age, location, and gender. Applications like Marketo Implementation have changed companies’ previous understanding of segmentation. There have been significant developments in segmenting customers on a more individual level, with improved data analysis using machine learning and automation.
The experts of the industry are emphasizing that for effective segmentation, customer behavior is equally as important as customer details. For a better understanding and the ability to make highly-informed decisions, companies need to dig deeper and analyze their customers’ behavior as well as their details.
For example, a number of companies sort customer data by the abandoned carts in their online stores. In response to this, they might take an action of offering a special discount or simply reaching out to these visitors to find out why they abandoned their purchase. Using Marketo Implementation, companies can further segment this group of abandoned carts into customers whose debit or credit card was denied and customers who entered all details except for their credit or debit card information.
By being more in sync with customer behavior, companies can not only improve their data analysis but they can also enhance their marketing content, personalize their messages on a deeper level for each type of customer and design landing pages that specifically target that customer type.
Let’s have a look at three major factors that companies should consider when segmenting their customers.
Machine learning and automation are intrinsic parts of effective segmentation
The major reason that a lot of companies have still not been able to use customer segmentation to its optimal potential is that sorting and analyzing that amount of data can be tedious work. Also, accuracy plays a big part here, as one wouldn’t want to take the risk of miscalculating or missing out on an important aspect of the data.
However, machine learning and automation have reshaped not only the process of customer segmentation but overall digital marketing. Companies can now use an exceptional engagement platform for hyper-targeting and examining of their customers’ journey, to automatically improvise marketing content and allow interaction with the audience on a more personal level.
Build trust with micro-segmentation
According to an Infosys survey, 78 percent of customers said that they are more likely to purchase from a brand that sends them more personalized offers. Micro-segmentation allows you to understand your customers’ needs, desires and pain points, to be able to personalize your marketing efforts and content accordingly. Companies can develop customers’ trust in the brand using micro-segmentation to address the most import concerns of their customers.
Your audiences’ needs are not static
A problem with the segmentation process of a lot of companies is that they analyze the data, place each customer in the relevant segment and never go back to reanalyze or take into account the newly collected information.
However, we know customers’ needs and taste preferences change with time. Today a customer can be in a completely different mental and physical state than they were when you last segmented your data. Tools like Marketo Implementation continuously work and reanalyze the data to place each customer type in the right category, which will be very helpful in accurate targeting.
Effective segmentation of customers can mean more opportunities for the personalization of marketing and sales strategies. Even though customer segmentation is not a new concept in the digital marketing world, tools like Marketo Implementation with elements like automation and micro-segmentation are making it a realizable option for companies of all types and sizes.
For more on customer segmentation and how such tools can impact your business practices visit: https://www.nx3corp.com/marketo-implementation.html