[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
Applied to <\/span>personalized marketing<\/b>, artificial intelligence transforms raw data into actionable profiles.<\/span><\/p>\n Quizzes, tests, or games with rewards effectively allow for the <\/span>collection of diverse first party data<\/b>: closed ended responses, verbatims, images\u2026 Through semantic and behavioral analysis, these signals fuel fine grained segmentation that subsequently boosts CRM performance and enables brands to better convert and retain their audience.<\/span> <\/p>\n Here are 3 concrete ways to leverage this data to <\/span>personalize future marketing campaigns<\/b> with precision.<\/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” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n How to use AI to<\/span> personalize marketing campaigns<\/b> ? Brands can start by sharing multiple choice tests (<\/span>Quizzes<\/span><\/a>, <\/span>personality tests<\/span><\/a>, etc.) with their audience. These interactive activities make it possible to qualify a contact based on <\/span>their preferences<\/span><\/a>, motivations, or needs, using actionable <\/span>behavioral data<\/b>.<\/span><\/p>\n Note: this processing relies both on <\/span>rules defined by the brand<\/b> (for example: “if a user selects answer A, they are probably price sensitive”) and on <\/span>predictive models<\/b> capable of identifying finer correlations between the responses given and future behaviors (such as interest in a product, the probability of purchase, or churn).<\/span><\/p>\n Result: <\/span>intelligent CRM segmentation<\/b>. Indeed, it is based on declarative signals, easy to link to <\/span>marketing personalization scenarios<\/b>: <\/span><\/p>\n This type of analysis integrates natively into a <\/span>personalized marketing<\/b> strategy, with a high ROI.<\/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=”||40px||false|false” global_colors_info=”{}”]<\/p>\n In <\/span>the energy sector<\/span><\/a>, <\/span>a quiz<\/span><\/a> can question an audience about their consumption habits or ecological sensitivity. By analyzing the responses, AI can <\/span> group users into three segments<\/b>: <\/span> <\/p>\n Each group can then <\/span>receive a personalized message,<\/b> a different product, or a targeted demonstration.<\/span><\/p>\n In retail, a marketing game centered on purchasing habits makes it possible to qualify profiles based on their primary motivation. The <\/span>semantic analysis<\/b> of choices helps isolate: <\/span> <\/p>\n Thanks to the power of <\/span>IA and personalized marketing<\/b>, these campaigns can trigger more relevant activations, leading to a better conversion rate.<\/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” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n Marketing games<\/span><\/a> featuring free response<\/b> fields<\/span> (quizzes or <\/span>personality tests<\/span><\/a> with open ended questions, forms, <\/span>surveys<\/span><\/a>, etc.) are powerful data collection<\/b> tools<\/span>. Unlike predefined choices, verbatims reflect the actual language, expectations, or objections of the participants.<\/span><\/p>\n Semantic analysis, applied by AI, makes it possible to automatically extract the key information contained in these responses: recurring words, expressed intentions, signals of interest or disinterest, and barriers to purchase. The algorithm then classifies and groups these elements according to themes and intensity levels. <\/span><\/p>\n The benefits for marketing are multifaceted. This <\/span>personalization through AI<\/b> makes it psosible to refine <\/span>automated customer profiling<\/b>. It enriches the CRM with qualitative signals, which can be leveraged to adapt content, offers, or activation drivers.<\/span><\/p>\n Even better: this contextual intelligence makes it possible to<\/span> identify weak signals<\/b> or uncover unexpected customer segments. It also improves <\/span>AI lead scoring<\/b> by integrating an emotional or intentional dimension.<\/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 How to achieve <\/span>dynamic segmentation with AI<\/b>? Let’s take the tourism sector as an example. <\/span><\/p>\n During <\/span>a contest<\/b>, participants are invited to answer the question:<\/span><\/p>\n \u201cWhat is your dream destination and why?\u201d<\/span><\/i><\/p>\n AI<\/b> identifies quickly trends: \u201cnature,\u201d \u201cdisconnection,\u201d \u201cbudget,\u201d \u201cwith family,\u201d \u201coff the beaten track\u201d… These elements then guide the <\/span>dynamic segmentation<\/b> of the CRM: \u201cadventurer,\u201d \u201cslow traveler,\u201d or \u201cplanning family\u201d profiles.<\/span><\/p>\n Marketing teams can then<\/span> activate tailor made campaigns<\/b>, adapted to these new targets, with a tone, a promise, and visuals aligned with their deepest expectations.<\/span><\/p>\n Let\u2019s take the example of the \u201cslow traveler\u201d profile<\/span> identified via semantic analysis<\/b> of verbatims. To meet the expectations of this segment, marketing campaigns will integrate: <\/span><\/p>\n These elements create<\/span> a more relevant message<\/b>, consistent with the segment’s aspirations. Result: a better engagement rate and an optimized marketing ROI. <\/span><\/p>\n [\/et_pb_text][\/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 Gamified campaigns that invite participants to <\/span>upload an image<\/b> (<\/span>meal photo contests<\/a><\/span>, favorite outfits, interior design, etc.) are a powerful source of <\/span>behavioral data<\/b>. Thanks to <\/span>AI image analysis<\/b>, this content can be leveraged for <\/span>automated customer profiling<\/b>.<\/span><\/p>\n AI recognizes objects, scenes, moods, or even emotions present in the image. It then maps these elements to <\/span>typical profiles<\/b> or probable <\/span>purchase intentions<\/b>.<\/span><\/p>\n Result: unprecedented CRM enrichment. These visual signals create a <\/span>new level of segmentation<\/b>, complementary to declarative data. <\/span>AI lead scoring<\/b> is thus much more refined and the personalization of marketing campaigns more relevant.<\/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=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Let\u2019s take a fictional example. In <\/span>a food marketing campaign<\/span><\/a>a contest invites participants to share a photo of their favorite homemade dish. We are talking here about <\/span>UGC<\/span><\/a>, or content organically generated by users. <\/span>\n
Analyzing quiz responses to better personalize campaigns<\/strong><\/h2>\n
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Examples of marketing personalization based on quiz profiles<\/strong><\/h3>\n
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How to dynamically fuel audience segmentation<\/h2>\n
Examples of marketing personalization based on verbatims<\/strong><\/strong><\/h3>\n
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<\/span> E.g.: \u201cTake the time to discover [the destination] differently\u201d <\/span><\/i><\/span><\/i><\/li>\n
<\/span> E.g.: \u201c7 days by train through the little known landscapes of Italy\u201d <\/span><\/i><\/span><\/i><\/li>\n
<\/span> E.g.: sunset over a lake, forest cabin, remote village <\/span><\/i><\/li>\n<\/ul>\nHow to leverage AI to transform visual content into actionable marketing insights?<\/h2>\n
Example of marketing personalization based on UGC<\/strong><\/strong><\/h3>\n