[[{"@context":"http:\/\/schema.org","@type":"Article","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article","articleBody":"Modern marketers put a lot of time and effort into achieving \u201c1:1 personalization.\u201d They continually seek ways to optimize content for better and more tailored brand experiences, which lead to increased revenue and brand loyalty \u2013 and none of this would be possible without profile segmentation. Before you worry about another buzzword or term you need to know, don\u2019t. We\u2019ve got some fantastic profile segmentation examples for you.\u00a0\nHowever, 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. \nThe problem is that even segmentation has grown so incredibly complex that it\u2019s just as daunting to manually segment audiences as it is to personalize them. \nTo 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.\n \nNever break the chain: Use customer profiles to drive consistent CX\n   Imagine your customer experience as a chain, each link representing an interaction between your customer and your brand. Every good interaction adds another solid link and makes the chain stronger. But it just takes one bad experience \u2013 one rusted, cracked link \u2013 to break it.  \nFirst-party data & customer profile segmentation\nFirst-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.\u00a0\nFirst-party data includes a host of benefits: \nReliable. Because this data comes directly from your contact, it\u2019s higher quality and more accurate than second- or third-party data, which come from indirect sources.\u00a0\nCost-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.\u00a0\nCompliant. With more regulations such as GDPR and California Consumer Privacy Act (CCPA), businesses must ensure that the data they\u2019re using won\u2019t cause them legal troubles. First-party data provides control over obtaining customer consent to use it.\nRelevant. The data that marketers get from second- and third-party sources may or may not be relevant to their interaction with customers.\u00a0\nRelevant, first-party data is the lifeblood of customer profile segmentation.\nTake the example of launching a new kitchen appliance accessory. By using the first-party data you\u2019ve 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.\nUsing 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.\nWithout first-party data, a personalized campaign like this would never be possible.\n \nFirst-party data strategy: Prepping for a cookie-less world\n   The clock is ticking as third-party cookies become a thing of the past. Is your business ready? We examine best practices for managing first-party customer data.  \nProfile segmentation examples: 3 brands discover the benefits of personalization\nA hypothetical example is nice, but real-life profile segmentation examples are more fun and enlightening. \nThree brands use first-party data to deliver personalized, relevant experiences \u2013 and discovered the major benefits:\nInnovasport: Customer loyalty program boomed after segmentation\nOrlebar Brown: Removing data silos delivered stunning CX and engagement\nBrandAlley: Relevant messaging increased average order volume by 10%\nInnovasport: Segmenting customers supercharges loyalty program\nA 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.\u00a0\nInnovasport 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).\u00a0\nJust 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\u201340%. \nUsing the right message to reach the right audience creates a lasting impact on customer relationships.\u00a0\nOrlebar Brown: Personalized CX gets stunning results\nBy 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\u2019re about to stray.\u00a0\n\u201cMake use of whether a customer is new, whether they\u2019re active, becoming unengaged, and when they become inactive as well,\u201d says Sebastiano Elia, Head of CRM & Customer Insight, Orlebar Brown, a men\u2019s swimwear retailer.\nEarly 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\u2019ve made stunning progress.\u00a0\nOrlebar 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.\u00a0\nBrandAlley: Harnessing the power of AI and first-party data\u00a0\nMarketing has the opportunity to remain relevant by staying on top of changes in consumer trends. When the consumer\u2019s interests inevitably change, they should be able to flow freely from segment to segment.\nBrandAlley 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.\u00a0\n\u201cWe made sure that we spoke to the right customers in the right language,\u201d says Alexandra Vancea, Head of Marketing, BrandAlley\nThe 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.\u00a0\n \nPersonalization in retail: Laying the foundation for success\n   Personalization helps retailers get closer to their customers, but how do you get started? Here are some steps for customer engagement success.  \nAchieve 1:1 personalization with profile segmenting\u00a0\nFirst-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. \nWith customer engagement platform that supports such automation, marketers can achieve 1:1 personalization at scale and drive outstanding customer engagement.\nThe 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.\u00a0\nDivide and conquer!\u00a0\nPersonalization: It\u2019s not magic. It\u2019s method. Find out who does it best HERE.","author":{"@type":"Person","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_Person","image":{"@type":"ImageObject","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_Person_ImageObject","url":"https:\/\/23x6xj3o92m9361dbu2ij362-wpengine.netdna-ssl.com\/wp-content\/uploads\/2021\/11\/Virginia-Sanders-150x150.jpg"},"name":"Virginia Sanders","sameAs":"https:\/\/www.linkedin.com\/in\/virginiamsanders81\/","url":"https:\/\/www.the-future-of-commerce.com\/contributor\/virginia-sanders\/"},"dateModified":"2021-12-16T12:50:46+00:00","datePublished":"2021-12-16T06:01:09+00:00","description":"First-party data and profile segmentation go hand-in-hand. Real-life examples of brands using them to deliver 1:1 customer personalization.","headline":"Profile segmentation: The benefits of customer personalization","image":{"@type":"ImageObject","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_ImageObject","height":"630","url":"https:\/\/www.the-future-of-commerce.com\/wp-content\/uploads\/2021\/12\/profile-segmentation-examples-FTR-1200x630.png","width":"1200"},"mainEntityOfPage":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/","name":"Profile segmentation: The benefits of customer personalization","publisher":{"@type":"Organization","@id":"https:\/\/www.the-future-of-commerce.com\/","additionalType":"https:\/\/www.wikidata.org\/wiki\/Q1193236","description":"Relevant, timely information & analysis on commerce trends, both consumer-facing and B2B.","logo":{"@type":"ImageObject","@id":"https:\/\/23x6xj3o92m9361dbu2ij362-wpengine.netdna-ssl.com\/wp-content\/themes\/hybris_foc\/assets\/images\/layout\/logo-new-2x.png?_=1","height":"96","url":"https:\/\/23x6xj3o92m9361dbu2ij362-wpengine.netdna-ssl.com\/wp-content\/themes\/hybris_foc\/assets\/images\/layout\/logo-new-2x.png?_=1","width":"500"},"name":"The Future of Customer Engagement and Experience","sameAs":["https:\/\/podcasts.apple.com\/us\/podcast\/a-call-for-a-better-experience\/id1479742201","https:\/\/twitter.com\/FutureOfCEC","https:\/\/www.linkedin.com\/groups\/4844282","https:\/\/www.the-future-of-commerce.com\/feed\/"],"url":"https:\/\/www.the-future-of-commerce.com\/"},"url":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article"},{"@type":["Article"],"@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article","@context":{"@vocab":"http:\/\/schema.org\/","kg":"http:\/\/g.co\/kg"},"url":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/","publisher":[{"@id":"https:\/\/www.the-future-of-commerce.com\/"}],"author":[{"@type":"Person","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_author_Person","image":[{"@type":"ImageObject","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_author_Person_image_ImageObject","url":"https:\/\/23x6xj3o92m9361dbu2ij362-wpengine.netdna-ssl.com\/wp-content\/uploads\/2021\/11\/Virginia-Sanders-150x150.jpg"}],"sameAs":"https:\/\/www.linkedin.com\/in\/virginiamsanders81\/","url":"https:\/\/www.the-future-of-commerce.com\/contributor\/virginia-sanders\/","name":"https:\/\/www.the-future-of-commerce.com\/contributor\/virginia-sanders\/"}],"subjectOf":[{"@type":"FAQPage","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_subjectOf_FAQPage","mainEntity":[{"@type":"Question","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity0","name":"First-party data &amp; customer profile segmentation","acceptedAnswer":[{"@type":"Answer","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity0_acceptedAnswer_Answer","text":"<a href=\"https:\/\/emarsys.com\/learn\/blog\/what-is-first-party-data\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">First-party data<\/span><\/a><span style=\"font-weight: 400;\"> is simply information you <a href=\"https:\/\/www.the-future-of-commerce.com\/2021\/11\/01\/first-party-data-collection-examples-benefits-and-best-practices\/\">collect directly<\/a> 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.&nbsp;<\/span><strong><span class=\"h3\">First-party data includes a host of benefits: <\/span><\/strong>\n<li><span style=\"color: #a03488;\"><b>Reliable. <\/b><\/span><span style=\"font-weight: 400;\">Because this data comes directly from your contact, it\u2019s higher quality and more accurate than second- or third-party data, which come from indirect sources.&nbsp;<\/span><\/li>\n<li><span style=\"color: #a03488;\"><b>Cost-effective.<\/b><\/span><span style=\"font-weight: 400;\"> 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.&nbsp;<\/span><\/li>\n<li><span style=\"color: #a03488;\"><b>Compliant. <\/b><\/span><span style=\"font-weight: 400;\">With more regulations such as <a href=\"https:\/\/www.the-future-of-commerce.com\/2021\/04\/27\/gdpr-definition-general-data-protection-regulation-affect-business\/\">GDPR<\/a> and <a href=\"https:\/\/www.the-future-of-commerce.com\/2019\/10\/21\/gdpr-ccpa-and-lgpd-global-data-privacy\/\">California Consumer Privacy Act<\/a> (CCPA), businesses must ensure that the data they\u2019re using won\u2019t cause them legal troubles. First-party data provides control over obtaining <a href=\"https:\/\/www.sap.com\/products\/customer-consent.html?url_id=-glo-fcec-blog\" target=\"_blank\" rel=\"noopener\">customer consent<\/a> to use it.<\/span><\/li>\n<li><span style=\"color: #a03488;\"><b>Relevant. <\/b><\/span><span style=\"font-weight: 400;\">The data that marketers get from second- and third-party sources may or may not be relevant to their interaction with customers.&nbsp;<\/span><\/li>\n<span style=\"color: #a03488;\"><span style=\"font-weight: 400;\"><span class=\"h2\">Relevant, first-party data is the lifeblood of customer profile segmentation.<\/span><span style=\"font-weight: 400;\"><\/span><\/span><\/span>Take the example of launching a new kitchen appliance accessory. By using the first-party data you\u2019ve 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.<span style=\"font-weight: 400;\">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.<\/span><span style=\"font-weight: 400; color: #a03488;\"><span class=\"h2\">Without first-party data, a personalized campaign like this would never be possible.<\/span><\/span>"}]},{"@type":"Question","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity1","name":"Profile segmentation examples: 3 brands discover the benefits of personalization","acceptedAnswer":[{"@type":"Answer","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity1_acceptedAnswer_Answer","text":"<span style=\"font-weight: 400;\">A hypothetical example is nice, but real-life profile segmentation examples are more fun and enlightening. <\/span><strong><span class=\"h3\">Three brands use first-party data to deliver personalized, relevant experiences \u2013 and discovered the major benefits:<\/span><\/strong>\n<li>Innovasport: Customer loyalty program boomed after segmentation<\/li>\n<li>Orlebar Brown: Removing data silos delivered stunning CX and engagement<\/li>\n<li>BrandAlley: Relevant messaging increased average order volume by 10%<\/li>\n<span style=\"font-weight: 400;\">A loyalty program is a rich source of first-party data. Innovasport, a leading sporting goods retailer, <\/span><a href=\"https:\/\/emarsys.com\/learn\/blog\/how-innovasport-launched-a-loyalty-program-that-drove-350k-members-in-2-months\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">launched a new loyalty program<\/span><\/a><span style=\"font-weight: 400;\"> called Legends to better understand their customer lifecycle and get deeper insights into customer preferences.&nbsp;<\/span><span style=\"font-weight: 400;\">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).&nbsp;<\/span><span style=\"font-weight: 400;\"><span class=\"h2\">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\u201340%. <\/span><\/span><span style=\"font-weight: 400;\">Using the right message to reach the right audience creates a lasting impact on customer relationships.&nbsp;<\/span><span style=\"font-weight: 400;\">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\u2019re about to stray.&nbsp;<\/span><span style=\"font-weight: 400;\">\u201cMake use of whether a customer is new, whether they\u2019re active, becoming unengaged, and when they become inactive as well,\u201d says <\/span><span style=\"font-weight: 400;\">Sebastiano Elia, Head of CRM &amp; Customer Insight, Orlebar Brown, a men\u2019s swimwear retailer.<\/span><span style=\"font-weight: 400;\">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\u2019ve made stunning progress.&nbsp;<\/span><span style=\"font-weight: 400;\">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.&nbsp;<\/span><span style=\"font-weight: 400;\">Marketing has the opportunity to remain relevant by staying on top of changes in consumer trends. When the consumer\u2019s interests inevitably change, they should be able to flow freely from segment to segment.<\/span><span style=\"font-weight: 400;\">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.&nbsp;<\/span><span style=\"font-weight: 400;\">\u201cWe made sure that we spoke to the right customers in the right language,\u201d says <\/span><span style=\"font-weight: 400;\">Alexandra Vancea, Head of Marketing, BrandAlley<\/span><span style=\"font-weight: 400;\">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.&nbsp;<\/span>"}]},{"@type":"Question","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity2","name":"Achieve 1:1 personalization with profile segmenting&nbsp;","acceptedAnswer":[{"@type":"Answer","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#subjectOf_FAQPage_mainEntity2_acceptedAnswer_Answer","text":"<span style=\"font-weight: 400;\">First-party data is vital for automated customer profile segmentation. Without it, <\/span><a href=\"https:\/\/emarsys.com\/learn\/blog\/what-is-personalized-marketing\/\" target=\"_blank\" rel=\"noopener\"><span style=\"font-weight: 400;\">personalized marketing<\/span><\/a><span style=\"font-weight: 400;\"> 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. <\/span><span style=\"font-weight: 400; color: #a03488;\"><span class=\"h3\">With customer engagement platform that supports such automation, marketers can achieve 1:1 personalization at scale and drive outstanding customer engagement.<\/span><\/span><span style=\"font-weight: 400;\">The use cases above describe <\/span><a href=\"https:\/\/www.the-future-of-commerce.com\/data-analytics-customer-insights\/customer-segmentation\/\"><span style=\"font-weight: 400;\">segmentation strategies<\/span><\/a><span style=\"font-weight: 400;\"> 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.&nbsp;<\/span><span style=\"font-weight: 400;\">Divide and conquer!&nbsp;<\/span>"}]}]}],"image":[{"@type":"ImageObject","@id":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/#Article_image_ImageObject","url":"https:\/\/www.the-future-of-commerce.com\/wp-content\/uploads\/2021\/12\/profile-segmentation-examples-FTR-1200x630.png","width":"1200","height":"630"}],"mainEntityOfPage":"https:\/\/www.the-future-of-commerce.com\/2021\/12\/16\/customer-profile-segmentation-examples-benefits\/","articleBody":"\n        Modern marketers put a lot of time and effort into achieving \u201c1:1 personalization.\u201d They continually seek ways to optimize content for better and more tailored brand experiences, which lead to increased revenue and brand loyalty \u2013 and none of this would be possible without profile segmentation. Before you worry about another buzzword or term you need to know, don\u2019t. We\u2019ve got some fantastic profile segmentation examples for you.&nbsp;\nHowever, 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. \nThe problem is that even segmentation has grown so incredibly complex that it\u2019s just as daunting to manually segment audiences as it is to personalize them. \nTo 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.\n\n  \n    Never break the chain: Use customer profiles to drive consistent CX\n    \n      \n      Imagine your customer experience as a chain, each link representing an interaction between your customer and your brand. Every good interaction adds another solid link and makes the chain stronger. But it just takes one bad experience \u2013 one rusted, cracked link \u2013 to break it.\n    \n  \n\nFirst-party data &amp; customer profile segmentation\nFirst-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.&nbsp;\nFirst-party data includes a host of benefits: \n\nReliable. Because this data comes directly from your contact, it\u2019s higher quality and more accurate than second- or third-party data, which come from indirect sources.&nbsp;\nCost-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.&nbsp;\nCompliant. With more regulations such as GDPR and California Consumer Privacy Act (CCPA), businesses must ensure that the data they\u2019re using won\u2019t cause them legal troubles. First-party data provides control over obtaining customer consent to use it.\nRelevant. The data that marketers get from second- and third-party sources may or may not be relevant to their interaction with customers.&nbsp;\n\nRelevant, first-party data is the lifeblood of customer profile segmentation.\nTake the example of launching a new kitchen appliance accessory. By using the first-party data you\u2019ve 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.\nUsing 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.\nWithout first-party data, a personalized campaign like this would never be possible.\n\n  \n    First-party data strategy: Prepping for a cookie-less world\n    \n      \n      The clock is ticking as third-party cookies become a thing of the past. Is your business ready? We examine best practices for managing first-party customer data.\n    \n  \n\nProfile segmentation examples: 3 brands discover the benefits of personalization\nA hypothetical example is nice, but real-life profile segmentation examples are more fun and enlightening. \nThree brands use first-party data to deliver personalized, relevant experiences \u2013 and discovered the major benefits:\n\nInnovasport: Customer loyalty program boomed after segmentation\nOrlebar Brown: Removing data silos delivered stunning CX and engagement\nBrandAlley: Relevant messaging increased average order volume by 10%\n\nInnovasport: Segmenting customers supercharges loyalty program\nA 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.&nbsp;\nInnovasport 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).&nbsp;\nJust 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\u201340%. \nUsing the right message to reach the right audience creates a lasting impact on customer relationships.&nbsp;\nOrlebar Brown: Personalized CX gets stunning results\nBy 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\u2019re about to stray.&nbsp;\n\u201cMake use of whether a customer is new, whether they\u2019re active, becoming unengaged, and when they become inactive as well,\u201d says Sebastiano Elia, Head of CRM &amp; Customer Insight, Orlebar Brown, a men\u2019s swimwear retailer.\nEarly 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\u2019ve made stunning progress.&nbsp;\nOrlebar 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.&nbsp;\nBrandAlley: Harnessing the power of AI and first-party data&nbsp;\nMarketing has the opportunity to remain relevant by staying on top of changes in consumer trends. When the consumer\u2019s interests inevitably change, they should be able to flow freely from segment to segment.\nBrandAlley 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.&nbsp;\n\u201cWe made sure that we spoke to the right customers in the right language,\u201d says Alexandra Vancea, Head of Marketing, BrandAlley\nThe 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.&nbsp;\n\n  \n    Personalization in retail: Laying the foundation for success\n    \n      \n      Personalization helps retailers get closer to their customers, but how do you get started? Here are some steps for customer engagement success.\n    \n  \n\nAchieve 1:1 personalization with profile segmenting&nbsp;\nFirst-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. \nWith customer engagement platform that supports such automation, marketers can achieve 1:1 personalization at scale and drive outstanding customer engagement.\nThe 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.&nbsp;\nDivide and conquer!&nbsp;\n  Personalization: It\u2019s not magic.\nIt\u2019s method.\nFind out who does it best HERE.\n\n\n\n\t\n      ","name":"Profile segmentation: The benefits of customer personalization","dateModified":"2022-03-17T03:07:54+00:00","datePublished":"2021-12-16T06:01:09+00:00","headline":"Profile segmentation: The benefits of customer personalization","description":"First-party data and profile segmentation go hand-in-hand. 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