[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=”4.24.2″ _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
In the age of \u2018big data\u2019, and given the huge amount of data to which businesses now have access, it is becoming crucial for them to put in place <\/span>a relevant data strategy<\/b>. This is especially true in a world where data is becoming an increasingly valuable currency. <\/span><\/p>\n The transition to GA4 (Google Analytics 4) was already shaping up to be a colossal challenge for marketing teams. But the latest earthquake to rock the data landscape is <\/span> the imminent end of third-party cookies<\/b> announced by Google for July 2024.<\/span><\/p>\n This transition, which has already been made by Apple and Firefox, is forcing companies to<\/span> rethink their customer data collection<\/span><\/span><\/a> strategy<\/b> and therefore their marketing campaigns. In this article, we share some practical advice and effective levers for updating your data strategy. <\/span><\/p>\n <\/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=”4.23.1″ _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=”4.23.1″ _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=”4.24.2″ _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 In a world where lead acquisition costs and the cost per click of the main advertising networks are exploding, companies are being forced to <\/span>rationalise their marketing efforts<\/b>. They can no longer simply sail by sight and adjust their campaigns according to their performance, a posteriori.<\/span> <\/p>\n To invest their marketing budgets in the right channels, on the right messages and with the right audiences, they need to <\/span>base each of their decisions on hard facts<\/b>. And these proven facts take the form of customer data.<\/span> <\/p>\n These include<\/span> a wide variety of information, but also of formats<\/b>. Il peut s\u2019agir de donn\u00e9es d\u00e9mographiques ou comportementales, de fiches contact dans une base de donn\u00e9es CRM, d’historique de ventes ou d\u2019\u00e9changes avec le chatbot du service client, sans oublier les commentaires sur les r\u00e9seaux sociaux. <\/span><\/p>\n Collecting data<\/span><\/span><\/a><\/b>,<\/b> in sufficient quantity and of good quality, is essential for :<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.24.2″ _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 This last point is very important to remember. It is, <\/span>74% of consumers<\/a><\/span><\/span> say they are frustrated by receiving marketing messages (in the form of sponsored advertising on social networks or email campaigns) <\/span>that are not tailored to their needs<\/b>. <\/p>\n Companies that don’t adopt a personalised marketing strategy are therefore more likely to be throwing their money away (by sending the wrong message to the wrong person). But they also risk <\/span>devalue their brand image<\/b> by giving consumers the feeling of being spammed and increasing their <\/span>advertising burn-out<\/span><\/span><\/span><\/a>.<\/span><\/span><\/span> <\/p>\n But the key to personalised marketing is to have the right tools for<\/span> collecting, analysing and activating customer data<\/b>. <\/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=”4.23.1″ _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=”4.23.1″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||20px||false|false” global_colors_info=”{}”]<\/p>\n Any good data strategy <\/b>needs to answer the following question: how do you collect data, ensure it is relevant and use it effectively?<\/span><\/p>\n Companies must therefore<\/span> adopt a multi-dimensional approach<\/b> that includes :<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.24.2″ _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 69% of consumers<\/span><\/span><\/a> are more willing to interact with a brand that offers games or interactive marketing campaigns with prizes to be won. Companies therefore need to <\/span> diversify their data sources<\/b> by making the most of <\/span>gamified experiences<\/span><\/span><\/span><\/a>.<\/span> <\/p>\n These are all the more relevant in a<\/span> cookieless context<\/span><\/span><\/b><\/a>. En effet, le marketing interactif offre des sources de donn\u00e9es plus fiables et RGPD friendly. Les informations collect\u00e9es seront consid\u00e9r\u00e9es comme de <\/span>first-party data<\/span><\/span><\/a><\/span>, i.e. data shared directly by users with their explicit consent.<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.23.1″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Collecting data is not enough. A good data strategy also relies on <\/span>the systematic and meticulous analysis of this information.<\/b><\/p>\n The tool chosen by the company should preferably<\/span> offer a visual representation.<\/b> Data visualisation will enable all teams, even those least at ease with data, to draw relevant conclusions in terms of marketing strategy.<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.23.1″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Brands need to be able to rely on<\/span> relevant, regularly updated data<\/b>. However, it is also crucial not to put too much pressure on users. Today’s users are more concerned about protecting their personal data. <\/span><\/p>\n To strike the right balance, brands can not only <\/span>rely on relevant incentives<\/b> to share data (such as the prizes in a marketing competition, for example). But they will also need to establish a marketing calendar to ensure that their various campaigns are sufficiently spaced out. <\/span><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.24.2″ _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 As already mentioned, a good data strategy should above all help the company to make better decisions. It will be used primarily to <\/span>optimise its marketing efforts<\/b>, in particular by delivering a personalised message to each customer and prospect.<\/span> <\/p>\n A solution like<\/span> Adictiz<\/span><\/span><\/span><\/a> makes<\/span> the most of the data collected<\/b>. For example, companies can use it to<\/span> segment their target audience<\/span><\/span><\/span><\/a>, then send automated emails and personalised offers.<\/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=”4.23.1″ _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=”4.23.1″ _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 let’s get practical. Here are the 3 essential steps to <\/span> develop a solid data strategy. <\/b><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.24.2″ _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 Data collection can enable brands to<\/span> optimise every stage of the conversion funnel<\/b>. However, it is crucial to identify those that are the most strategic for the company, so that efforts can be focused in the right place.<\/span> <\/p>\n A brand that has just launched, for example, could focus on<\/span> lead generation<\/b>. A company with a low repeat purchase rate, on the other hand, should concentrate its efforts on providing personalised offers to<\/span> build customer loyalty<\/span><\/span><\/span><\/a>.<\/span> <\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.23.1″ _module_preset=”default” text_text_color=”#000000″ text_font_size=”16px” custom_margin=”||40px||false|false” global_colors_info=”{}”]<\/p>\n Depending on the objectives set and the audience, the company can then<\/span> run targeted campaigns<\/b>. The key is to diversify sources, using a mix of :<\/span> <\/p>\n <\/b><\/p>\n [\/et_pb_text][et_pb_text _builder_version=”4.23.1″ _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=”4.24.2″ _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 A good data strategy serves all stages of the customer journey, from identifying new leads to<\/span> conversion levers<\/span><\/span><\/span><\/a>, not forgetting post-purchase loyalty. To measure the quality of your data and the relevance of the marketing decisions you make on the basis of it, <\/span> AB testing is crucial. <\/b><\/p>\n Defining relevant KPIs <\/b>will make it easier to analyse the performance of each collection scenario. These metrics must, of course, be aligned with the objectives chosen for the data marketing campaign. <\/span><\/p>\n The company can then put in place a virtuous loop consisting of : <\/span><\/p>\n\n
Why do you need a data strategy?<\/strong><\/h2>\n
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The challenge of personalisation in marketing<\/strong><\/h3>\n
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The 4 key elements of a data collection strategy <\/strong><\/h2>\n
Relevant data collection tools<\/strong><\/h3>\n
A data analysis tool<\/strong><\/h3>\n
Identifying the right frequency to collect data<\/strong><\/h3>\n
A data activation strategy<\/strong><\/h3>\n
How to develop your data strategy <\/strong><\/h2>\n
1. Define your objectives<\/strong><\/h3>\n
2. Create targeted collection campaigns<\/strong><\/h3>\n
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3. Test, analyse and optimise<\/strong><\/h3>\n