[et_pb_section fb_built=”1″ _builder_version=”4.19.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][et_pb_row _builder_version=”4.19.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n
Data collection has become a crucial resource<\/b> for brands, offering a powerful lever for personalising experiences and optimising campaigns. This guide will help you to understand the challenges of data, even without technical expertise, and to use it to boost your company’s performance. <\/span><\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.22.2″ _module_preset=”default” background_color=”#F2F2F2″ custom_margin=”||40px||false|false” border_radii=”on|10px|10px|10px|10px” locked=”off” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” custom_padding=”20px|30px|20px|30px|true|true” global_colors_info=”{}”]<\/p>\n SUMMARY<\/strong><\/span><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row module_id=”section-1″ _builder_version=”4.19.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text module_id=”sommaire-1″ _builder_version=”4.27.4″ _module_preset=”default” text_font=”|700|||||||” text_text_color=”#000000″ text_font_size=”25px” header_font_size=”25px” header_line_height=”1.3em” header_2_font=”Montserrat|700|||||||” header_2_font_size=”25px” header_2_line_height=”1.3em” custom_margin=”||30px||false|false” link_option_url=”#sommaire-1″ global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Brands can’t navigate by sight. To make the right decisions and above all refine their strategy to remain competitive, they need to <\/span>understand who they are talking to and what their audience wants<\/b>. The data enables them to<\/span> refine their customer knowledge<\/span><\/a> and gain better visibility of their operations.<\/span> <\/p>\n So why collect data at all?<\/span>[\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Data enables brands to identify the expectations, behaviours and<\/span> preferences of their customers<\/span><\/a>. By understanding their buying habits, interests and online journeys, they can refine their strategies and improve their offering. <\/span><\/p>\n Example: <\/b>A retailer can analyse its customers’ purchasing history to identify their favourite styles. Based on these insights, it can send them recommendations. This is what Legrand did with its campaign for the C\u00e9liane brand. Thanks to the interactive mechanism <\/span>Swiper<\/span><\/a>, Legrand was able to collect more than 115,000 customer preferences.<\/span><\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.adictiz.com\/wp-content\/uploads\/2025\/02\/Legrand-Grand-jeu-celiane-collecte-de-donnees.webp” alt=”Legrand – Celiane game – data collection” title_text=”Legrand-Celiane-game-data-collection” align=”center” disabled_on=”on|off|off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_image src=”https:\/\/www.adictiz.com\/wp-content\/uploads\/2025\/02\/Grand-jeu-celiane-Legrand-mobile.webp” alt=”Legrand-celiane-game-mobile <br>” title_text=”Legrand celiane game – mobile <br>” align=”center” disabled_on=”off|on|on” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Using the customer data collected, a brand can precisely target its customers and optimise the ROI of its campaigns. By analysing behaviour, the right messages can be delivered to the right people, at the right time and in the right place. <\/span><\/p>\n Example<\/b>:By tracking the pages visited and the products added to the shopping basket on its site, the retailer can better retarget each of its visitors with personalised advertising.<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n A brand that makes good use of its data can offer a smooth, intuitive and enjoyable shopping experience. Thanks to the data collected on its e-commerce site or its application, it can identify friction points in the customer journey and adjust its experience (by simplifying the checkout process). <\/span><\/p>\n Example: [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Rather than sending the same promotions to their customers, brands can use data to propose personalised offers based on consumers’ habits and preferences. These incentives increase loyalty and encourage customers to return. <\/span><\/p>\n Example: [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Good stock management is essential to avoid stock-outs and limit unsold goods. Thanks to the data it collects, a brand can predict trends and adjust its production\/supply. <\/span><\/p>\n Example: <\/b>It is in a brand’s interest to analyse buying trends in order to estimate demand for its models. Using this information, it can adjust its production to avoid stock-outs on models while limiting overstocking on less popular items. <\/span><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Insights gained from customer data can be used to identify new needs and adapt the existing offering. This can lead to the improvement of a product or the launch of a service to meet the expectations of its audience. <\/span><\/p>\n Example<\/b>:A beauty brand can use the<\/span> Customizer<\/span><\/a> mechanism to sound out the desires of its community and offer them products that meet their needs.<\/span> <\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row module_id=”section-2″ _builder_version=”4.19.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text module_id=”sommaire-2″ _builder_version=”4.27.4″ _module_preset=”default” text_font=”|700|||||||” text_text_color=”#000000″ text_font_size=”25px” header_2_font=”Montserrat|700|||||||” header_2_font_size=”25px” header_2_line_height=”1.3em” custom_margin=”||30px||false|false” link_option_url=”#sommaire-1″ global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||20px||false|false” global_colors_info=”{}”]<\/p>\n Data is<\/span> essential information <\/span><\/a> to the management and profitability of a business. The good news is that To avoid being overwhelmed by data, it’s important to<\/span> focus on the data that can make the difference<\/b> to your company’s development.<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||20px||false|false” global_colors_info=”{}”]<\/p>\n We can start by differentiating customer data according to its content and the information it reveals. Here are the 6 types of data that are useful for brands: <\/span><\/p>\n <\/span><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_line_height=”1em” header_line_height=”1.5em” header_3_font=”Montserrat||||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” custom_padding=”||0px|||” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n But we also need to differentiate between data depending on how it is collected and its source.<\/span> <\/b>There are Zero-Party Data, First-Party Data, Second-Party Data and Third-Party Data.<\/span><\/p>\n <\/span><\/p>\n <\/strong><\/p>\n Zero-Party Data<\/span><\/a> is information that consumers voluntarily share with the brand. This includes personal preferences, opinions, purchase intentions, wishes or specific feedback. Disadvantages :<\/b><\/p>\n [\/et_pb_text][et_pb_divider show_divider=”off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_divider][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n <\/strong><\/p>\n First-Party Data<\/span><\/a> is data collected directly by the brand, through interactions with users on its channels (website, application, social networks, etc.). This includes information such as purchase history, browsing behaviour, account information, etc. <\/span><\/p>\n Advantages :<\/b><\/p>\n Disadvantages :<\/b><\/p>\n [\/et_pb_text][et_pb_divider show_divider=”off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_divider][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n <\/strong><\/p>\n Second-Party Data is First-Party Data collected by another company. In other words, it is data collected by a partner and then shared ethically between the two parties. <\/span><\/p>\n Advantages :<\/b><\/p>\n Disadvantages :<\/b><\/p>\n [\/et_pb_text][et_pb_divider show_divider=”off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_divider][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n <\/strong><\/p>\n Third-Party Data is data collected by third-party companies (other than the brand or its direct partners) and resold or shared with brands. These companies specialise in data collection and gather information about behaviour on different websites or across different platforms. <\/span><\/p>\n Advantages :<\/b><\/p>\n Disadvantages :<\/b><\/p>\n <\/b><\/p>\n <\/span><\/p>\n To sum up, here is a summary infographic to help you remember the most important information: <\/span><\/p>\n [\/et_pb_text][et_pb_image src=”https:\/\/www.adictiz.com\/wp-content\/uploads\/2025\/02\/Collecter-des-donnees-adictiz.webp” alt=”Data collection – overview” title_text=”Data-collection-adictiz” align=”center” disabled_on=”off|off|off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][et_pb_divider show_divider=”off” _builder_version=”4.27.4″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][et_pb_row module_id=”section-3″ _builder_version=”4.19.4″ _module_preset=”default” custom_margin=”||||false|false” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.19.4″ _module_preset=”default” global_colors_info=”{}”][et_pb_text module_id=”sommaire-3″ _builder_version=”4.27.4″ _module_preset=”default” text_font=”|700|||||||” text_text_color=”#000000″ text_font_size=”25px” header_2_font=”Montserrat|700|||||||” header_2_font_size=”25px” header_2_line_height=”1.3em” custom_margin=”||30px||false|false” link_option_url=”#sommaire-1″ global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” min_height=”49.4px” custom_margin=”||20px||false|false” global_colors_info=”{}”]<\/p>\n Now that we have identified the types of data and the uses that companies can make of it, we turn our attention to<\/span> data collection<\/span><\/a>.The organisations have a <\/span> range of tools [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” header_3_font=”Montserrat|600|||||||” header_3_text_color=”#0092ff” header_3_line_height=”1.5em” custom_margin=”30px||30px||false|false” global_colors_info=”{}”]<\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.27.4″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n CRM software (Salesforce, Hubspot, Brevo) is used to collect, organise and analyse data throughout the buying process. These tools centralise the information collected on prospects and customers. <\/span><\/p>\n Use case : <\/b><\/p>\n\n
6 reasons for data collection<\/strong><\/h2>\n
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1. Getting to know your customers better<\/strong><\/h3>\n
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2. Optimising your marketing campaigns<\/strong><\/h3>\n
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3. Improving the customer experience<\/strong><\/h3>\n
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<\/b> An e-commerce company can analyse customer reviews to understand the main frustrations. In response, it can set up a chatbot capable of providing answers to the most frequently asked questions and thus improve its product sheets by including more details. <\/span><\/p>\n4. Customise offers and promotions<\/strong><\/h3>\n
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<\/b> A supermarket chain can analyse its customers’ regular purchases and offer them targeted discounts on their favourite products. These incentives encourage loyalty and strengthen attachment to the brand. <\/span><\/p>\n5. Anticipating demand and managing stocks<\/strong><\/h3>\n
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6. Create new products or services<\/strong><\/h3>\n
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What are the different types of customer data?<\/h2>\n
<\/span>there’s no shortage of customer data<\/b>. <\/span> A survey<\/span><\/a> revealed that the organisations surveyed manage an average of 3 petabytes (PB) of data, and that this volume doubles every two years. <\/span> <\/p>\n1. The different types of data according to their content<\/strong><\/h3>\n
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2. Different types of data depending on their source<\/strong><\/strong><\/h3>\n
1. Zero-Party Data<\/strong><\/strong><\/h4>\n
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Advantages :<\/b><\/span><\/p>\n\n
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2. First-Party Data<\/strong><\/h4>\n
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3. Second-Party Data<\/strong><\/h4>\n
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4. Third-Party Data<\/strong><\/h4>\n
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Which data collection method should you choose?<\/h2>\n
<\/b>which can be used (in synergy) according to their objectives and needs. Here are the most effective. <\/span><\/p>\n1. CRM (Customer Relationship Management) <\/strong><\/h3>\n