{"id":2168,"date":"2020-03-25T19:32:08","date_gmt":"2020-03-25T19:32:08","guid":{"rendered":"https:\/\/leap.staging.ribbitt.com\/leap-group\/big-data-and-your-marketing-strategy\/"},"modified":"2022-08-10T14:52:18","modified_gmt":"2022-08-10T14:52:18","slug":"big-data-and-your-marketing-strategy","status":"publish","type":"post","link":"https:\/\/leap.staging.ribbitt.com\/leap-group\/big-data-and-your-marketing-strategy\/","title":{"rendered":"Big Data and your Marketing Strategy"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/leap.staging.ribbitt.com\/wp-content\/uploads\/sites\/4\/2022\/08\/big-data.png\" title=\"Big-Data\" data-displaymode=\"Original\" alt=\"Big-Data\" \/><br \/>Before being embraced as an &ldquo;automobile&rdquo; (and later as &ldquo;cars&rdquo;) engine-powered motor vehicles were called &ldquo;horseless carriages.&rdquo;<\/p>\n<p>The smartphone in your pocket was called a &ldquo;wireless phone&rdquo; before being called your &ldquo;phone.&rdquo; Even the latest term &ldquo;smartphone&rdquo; is fading away and adopting the &ldquo;phone&rdquo; catch-all.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/leap.staging.ribbitt.com\/wp-content\/uploads\/sites\/4\/2022\/08\/big-data-3.png\" title=\"Big-Data-3\" data-displaymode=\"Original\" alt=\"Big-Data-3\" \/><\/p>\n<p>&nbsp;<\/p>\n<p>&ldquo;Big Data&rdquo; is one of those terms society is using as a mantra for the collection, validation, organization, analysis and implementation of ideas, based on recommended results based on information available.<\/p>\n<p>It&rsquo;s not surprising there is anxiety around the subject. Two-words, both big enough to be capitalized, are used to describe the possibilities (endless) and the ground-level realities (changing every month.)<\/p>\n<p>Marketers are to use data points, such as engagement, views, form submissions, CTR, CPM, CPC, etc, to give an accurate view of how a brand is performing. Then, use that information to drive strategy.<\/p>\n<p>But when does data become Big Data?<\/p>\n<p>Start by defining Big Data. From my perspective, it can be implemented in two ways: as an verb (an action) or as a noun (a tool).<\/p>\n<h3>Big Data<\/h3>\n<p><b><i>(verb\/action):<\/i><\/b><i> Suggests information should be used to inform business decisions based on analytics and trends. Data is viewed as something to be uncovered as a detective who pieces together multiple pieces of data to create an accurate representation of real life events.<\/i>&#13;<\/p>\n<p>&nbsp;<\/p>\n<h3>Big Data<\/h3>\n<p><b><i>(noun\/tool):<\/i><\/b><i> Puts the power of data interpretation in the hands of the users. In this instance, Big Data isn&rsquo;t as much of a detective as it is the process of multiple people and departments gathering all relevant pieces of information to serve the investigation.<\/i>&#13;<\/p>\n<p>&nbsp;<\/p>\n<p>In 2018, Big Data is a mixture of both verb and noun. IBM, Amazon and pretty much every large financial and insurance institution have the money to invest in machine learning.<\/p>\n<p>Artificial Intelligence is the next defining technological trend, but is being driven by the need for faster analysis of large amounts of data, which is ultimately a Big Data responsibility.<\/p>\n<h3>Big Data, Realistic Investments<\/h3>\n<p>For marketers without billion dollar research and development budgets, the future of a plug and play Big Data solution is still too far out for most to make direct investments in their infrastructure.<\/p>\n<p>Marketers should be positioning themselves to be ready for future tech developments as they relate to capturing and implementing data-driven solution on the macro-level instead of viewing every new advancement in machine learning like as a marketing game-changer.<\/p>\n<h4>Here are five ways to look at the future of Big Data:<\/h4>\n<p><img decoding=\"async\" src=\"https:\/\/leap.staging.ribbitt.com\/wp-content\/uploads\/sites\/4\/2022\/08\/big-data-2.png\" title=\"Big-Data-2\" data-displaymode=\"Original\" alt=\"Big-Data-2\" \/><\/p>\n<p>1. The current, <i>real time<\/i> benchmark for data analysis is morphing into predictive analysis. You see this in action when you Google and results begin to sort before you finish typing.<\/p>\n<p>2. Data input and validation remains the biggest obstacle to implementation. Is your data accurate, useful and being entered in the correct way? A human needs to check.<\/p>\n<p>3. Even advanced machine learning computers from IBM, Microsoft, etc. require some of the most advanced human engineers to see incremental gains in capabilities.<\/p>\n<p>4. Existing data is more valuable than most realize, because it can provide customer trends, which then allows you to create personalized customer journeys.<\/p>\n<p>5. Customer service data has high potential value as automating responses and solutions to common questions, which removes the need for large customer service staff. But it&rsquo;s up to your brand to collect this data.<\/p>\n<p>I am bullish on the future of Big Data as a disrupting element in all industries.<\/p>\n<h3>The &ldquo;Shortcut&rdquo; of Purchasing Data<\/h3>\n<p>Data Management Platforms (DMPs) offer a pricey, but potentially valuable, solution to jumpstarting your data-driven marketing plans.<\/p>\n<p>For lack of a better term, a DMP is a marketplace of consumer data to be purchased and combined with your brand&rsquo;s existing data to target market segments in a more accurate way.<\/p>\n<p>Retail and lifestyle brands tend to see the most success implementing DMP solutions when they uncover buying habits and reflect those insights into a personalized digital experience. Remember, DMPs service the data itself. It is up to you to make it work.<\/p>\n<h3>There is Still Time To Prepare for Big Data<\/h3>\n<p>This checklist will give you an idea of how prepared you are for the future of Big Data.<\/p>\n<ul>\n<li>You are currently collecting, verifying, and managing &ldquo;first person&rdquo; (aka, your brand) data.<\/li>\n<li>You have a long-term data collection strategy.<\/li>\n<li>You view data integration as the new SEO, in terms of strategic necessity.<\/li>\n<li>There is a &ldquo;culture of data&rdquo; that starts at the top of the organization.<\/li>\n<li>C-level executives are sharing data<\/li>\n<li>Your data is secure and meets all international standards for privacy protection.<\/li>\n<li>You are currently hiring or partnering with companies for data mining and business intelligence services.<\/li>\n<\/ul>\n<p>Consistency is still a marketers best strategy. Don&rsquo;t run away from what wins now. Great creative and great media plan to amplify your content managed by people that give a damn about results.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Before being embraced as an \u201cautomobile\u201d (and later as \u201ccars\u201d) engine-powered motor vehicles were called \u201chorseless carriages.\u201d<\/p>\n","protected":false},"author":43,"featured_media":2173,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1],"tags":[106,45],"issue":[23],"collection":[],"class_list":["post-2168","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-measurement-analytics","tag-technology","issue-humans-vs-robots"],"acf":[],"gutentor_comment":0,"_links":{"self":[{"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/posts\/2168","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/users\/43"}],"replies":[{"embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/comments?post=2168"}],"version-history":[{"count":0,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/posts\/2168\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/media\/2173"}],"wp:attachment":[{"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/media?parent=2168"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/categories?post=2168"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/tags?post=2168"},{"taxonomy":"issue","embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/issue?post=2168"},{"taxonomy":"collection","embeddable":true,"href":"https:\/\/leap.staging.ribbitt.com\/leap-group\/wp-json\/wp\/v2\/collection?post=2168"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}