It is starting from an in-depth knowledge of prospects and customers that the best marketing campaigns, the most relevant ones, are created. Let’s discover together how effective customer profiling activities, first, and then segmentation, can contribute to success.
One of the most relevant contributions that the digital world is making in marketing can be, without a doubt, identified in the personalization of the user experience, the key to growing and bringing success to one’s business model.
From the presentation of tailored products, offers and services to the creation of customized communications and messages aimed at creating a one-to-one relationship between brand and consumer-a personalized marketing strategy creates and strengthens customer loyalty.
But what do we find at the basis of an effective personalized marketing strategy? Without a doubt, customer profiling.
Customer profiling and segmentation: the success of your strategy starts here
Master data, browsing and purchasing behaviors, tastes and interests: tracking, collecting and analyzing data and information about your users across various channels and touchpoints is the first step in gaining a thorough understanding of their customer journey and build, for each of them, a Single Customer View precise.
It is at this stage that users are profiled, and based on the data collected, customer segmentation strategy is deployed, that is, the division and grouping of one’s audience into homogeneous clusters based on common characteristics, needs and requirements.
Socio-demographic information but not only that: advanced tracking systems allow you to collect a lot of information and segment your audience based on the multiple factors that provide not only a broad real-time overview of individual user behavior, but also allow you to predict future behavior.
Indeed, it is on the collected data of various users and the segments created that artificial intelligence can express its full potential: machine learning and predictive capabilities will make it possible to analyze and predict very accurately what the rewarding behaviors or solicitations will be for each individual user belonging to each segment.
Marketing and profiling customers and users: the strategic role of a Customer Data Platform
If data and information collected on prospects and customers from different sources represent the real wealth to work on in order to create successful marketing strategies, it is clear that for their analysis it is not possible to disregard a technological support that allows their collection and normalization.
This is precisely where Customer Data Platform s(CDPs) come in, which are software platforms that can unify a company’s customer data collected from multiple sources such as, for example, digital properties, social channels, and points of sale, just to name a few.
Far more powerful even than a CRM, a Customer Data Platform normalizes and segments data collected at the individual user level in real time, thus enabling the identification of patterns and recurrences that allow the creation of homogeneous user clusters on which to target specific marketing activities.
Information on browsing behavior, online and offline purchasing, biographical data, interests and preferences is centralized; AI and machine learning algorithms process data, analyze information from users with similar interests.
The result? You offer potential customers, both online and offline, the right product at the right time, engaging them with personalized messages and communications, while fully respecting their privacy.
User profiling: we do not dimenting the value of anonymous ones
In addressing the topic of user profiling and segmentation, we often tend to focus our attention on known customers and users, that is, users who, by browsing within our site or eCommerce, provide contact data and information. Too often, in fact, we forget, that more than 98 percent of website visitors, on average, choose to remain anonymous.
Anonymous users actually represent a huge potential that, if exploited, allows them to grow their audience. Although anonymous, users when browsing a site or eCommerce release so much valuable information, such as products and/or content they view, categories they browse, geographic areas they come from, devices they use to connect, and campaigns they come from
Advanced tracking systems that surpass the more common cookie-based systems allow anonymous users to be recognized, keeping track of all the actions they take.
This data, once collected, becomes a real asset and can be used as a basis for the implementation of effective strategies for personalizing the browsing experience, strategies and activities that prove particularly useful in order to improve precisely the unveil rate, thus stimulating users to release additional data critical to their profiling.
Customer profiling and RFM segmentation: here’s how to know your best customers
Speaking of audience profiling and segmentation, we could not leave out one of the undoubtedly best-known models in the eCommerce sphere, that of the RFM matrix, which provides a clear view of the relationship of customers with the company.
In fact, this model allows each customer to be assigned a score, a quality score, based on three benchmarks:
- Recency: the elapsed time since the last purchase;
- Frequency: the number of purchases made by a customer;
- Monetary: the customer’s total expenditure in the reporting period.
The RFM model rests its foundation on the Pareto model, according to which 80 percent of revenue is generated by 20 percent of its customers, for which it becomes important to identify the best customers in order to retain them over time.
According to the RFM method, much more sensitive and responsive to promotions and communications, and consequently to purchase, are those customers who have bought recently, more frequently, and spent more in a particular time period.
Once the different clusters of users have been identified (VIP users, at-risk users, users who buy frequently but spend little, users who buy frequently, spend a lot but have not bought for a long time..) it will be possible to create ad hoc strategies in order to ring them up, increasing their value over time.
RFM matrix and Customer Life Time Value: the importance of a retention marketing strategy
RFM analysis is closely related to the concept of Customer Life Time Value (LTV), which outlines the total value of a customer over a given time frame. It is obtained by multiplying a customer’s average order value (total revenue in a year / number of orders in a year), or average receipt, with his or her frequency of purchase.
Segmenting customers into clusters using RFM analysis enables marketing strategies that take into account the value of individual customers with the goal of improving and increasing their CLV, thereby optimizing initial acquisition costs.
Customer Life Time Value becomes key to creating a lasting relationship with the customer aimed at increasing customer value over time, focusing on personalized and omnichannel customer experiences.
By taking this value into account, in fact, companies have the ability to assess the potential that each customer could generate over time through the implementation of retention marketing strategies.
Customer and User Profiling: Strategic Levers for Business
Acquiring new customers is increasingly expensive and burdensome. Creating a solid base of loyal customers to rely on thus becomes crucial to strengthening one’s business. Here’s where customer profiling audinece segmentation, first, and creating personalized customer experiences, next, can be two key strategic levers.
