Last updated: March 16, 2022 Profile segmentation: The benefits of customer personalization

Profile segmentation: The benefits of customer personalization

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Modern marketers put a lot of time and effort into achieving “1:1 personalization.” They continually seek ways to optimize content for better and more tailored brand experiences, which lead to increased revenue and brand loyalty – and none of this would be possible without profile segmentation. Before you worry about another buzzword or term you need to know, don’t. We’ve got some fantastic profile segmentation examples for you. 

However, no marketer is capable of manually creating personalized content for every customer in their database. No matter how many hundreds of thousands or millions of contacts a brand has, just imagining the time it would take for that customization is mind-boggling. Instead, to enable personalization, marketers lean heavily on customer profile segmentation.

The problem is that even segmentation has grown so incredibly complex that it’s just as daunting to manually segment audiences as it is to personalize them.

To connect with customers on a personal level, leading brands rely on customer profile segmentation enabled by artificial intelligence (AI) and data, especially first-party data.

First-party data & customer profile segmentation

First-party data is simply information you collect directly from the contact and which you have permission to use. Any time a contact interacts with your brand and you record their details, you generate first-party data. Examples include customer feedback, in-store purchase data, social media data, and survey data. 

First-party data includes a host of benefits:

  1. Reliable. Because this data comes directly from your contact, it’s higher quality and more accurate than second- or third-party data, which come from indirect sources. 
  2. Cost-effective. First-party data is less expensive than second- or third-party data purchased from other businesses or data aggregators. Of course, marketers need the technology to collect it. 
  3. Compliant. With more regulations such as GDPR and California Consumer Privacy Act (CCPA), businesses must ensure that the data they’re using won’t cause them legal troubles. First-party data provides control over obtaining customer consent to use it.
  4. Relevant. The data that marketers get from second- and third-party sources may or may not be relevant to their interaction with customers. 

Relevant, first-party data is the lifeblood of customer profile segmentation.

Take the example of launching a new kitchen appliance accessory. By using the first-party data you’ve collected, you can target particular groups of customers. You may want to market to three groups: customers who bought the appliance in the last year; customers who bought at least two other accessories for the appliance; and those who read related recipes on your blog.

Using automation within a customer engagement platform, you can set up campaigns with relevant messaging to the segmented groups. As customers engage with your brand, some will take actions that automatically put them into one of the segments, which then triggers the relevant campaign.

Without first-party data, a personalized campaign like this would never be possible.

Profile segmentation examples: 3 brands discover the benefits of personalization

A hypothetical example is nice, but real-life profile segmentation examples are more fun and enlightening.

Three brands use first-party data to deliver personalized, relevant experiences – and discovered the major benefits:

  1. Innovasport: Customer loyalty program boomed after segmentation
  2. Orlebar Brown: Removing data silos delivered stunning CX and engagement
  3. BrandAlley: Relevant messaging increased average order volume by 10%

Innovasport: Segmenting customers supercharges loyalty program

A loyalty program is a rich source of first-party data. Innovasport, a leading sporting goods retailer, launched a new loyalty program called Legends to better understand their customer lifecycle and get deeper insights into customer preferences. 

Innovasport designed Legends as a tiered program, segmenting customers into low, medium, and high spenders. By doing so, the marketing team is better able to offer discounts that are tailored to the customer based on their buying behavior. They also offer a welcome campaign with easy visibility into program benefits and rewards, and real-time communications. The program is designed to increase both purchase frequency and average order value (AOV). 

Just two months after the initial launch, the Legends program grew to 350,000 members. Not only that, but their email open rate increased from 8% to 35–40%.

Using the right message to reach the right audience creates a lasting impact on customer relationships. 

Orlebar Brown: Personalized CX gets stunning results

By segmenting customers in relation to their lifecycle of interaction with a brand, marketers can more effectively personalize their messages. They can also take steps to get customers back on track if they’re about to stray. 

“Make use of whether a customer is new, whether they’re active, becoming unengaged, and when they become inactive as well,” says Sebastiano Elia, Head of CRM & Customer Insight, Orlebar Brown, a men’s swimwear retailer.

Early on, the brand struggled with personalization due to data silos and systems being unable to communicate with each other. However, by consolidating their data into a unified customer engagement platform, they’ve made stunning progress. 

Orlebar has moved on from using a first name to tailoring their messages to buyers based on their lifecycle stage. Through data analysis and tools like visual affinity, Orlebar can deliver tailored recommendations and better welcome new customers, keep active customers engaged, and entice defecting customers back to the fold. 

BrandAlley: Harnessing the power of AI and first-party data 

Marketing has the opportunity to remain relevant by staying on top of changes in consumer trends. When the consumer’s interests inevitably change, they should be able to flow freely from segment to segment.

BrandAlley sends out a high volume of email to their customers. Through their adoption of AI for customer engagement, BrandAlley was able to strategically target customers with relevant messaging. 

“We made sure that we spoke to the right customers in the right language,” says Alexandra Vancea, Head of Marketing, BrandAlley

The marketing team saw an increase by 10% in average order value in a particular segment of the customer lifecycle. They also were able to win back 24% of customers who were likely to defect. 

Achieve 1:1 personalization with profile segmenting 

First-party data is vital for automated customer profile segmentation. Without it, personalized marketing at scale is only a pipe dream, but with it, marketers can speak directly to customer interests and avoid wasting their attention on irrelevant content.

With customer engagement platform that supports such automation, marketers can achieve 1:1 personalization at scale and drive outstanding customer engagement.

The use cases above describe segmentation strategies based on customer spending tiers, customer lifecycle, and customer interests. The way you use first-party data to segment your audience will depend heavily on your marketing objective and your products. Other common data points used for segmentation include age, gender, purchase history, purchase frequency, channel preferences, in-store versus web-based purchases, and much more. 

Divide and conquer! 

Personalization: It’s not magic.
It’s method.
Find out who does it best HERE
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Virginia Sanders

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