They also use this valuable intelligence to create personalized and targeted buying experiences. <\/p>\n
The great news for you?<\/strong> Your business can do the exact same thing. <\/strong><\/p>\n Here is our guide about the different ways to collect and use consumer behavior data (with examples from top consumer brands<\/em>).<\/p>\n Enjoy!<\/p>\n Consumer behavior data is what drives digital marketing<\/a> activities. <\/p>\n It is a great piece of information about a customer’s buying habits<\/strong>. And it is collected every time someone orders an item online or visits a restaurant, for example. <\/p>\n Let’s think about convenience stores for a moment. <\/p>\n Now imagine gathering these types of information, but on a much larger scale. It’s pretty hard.<\/p>\n That is why eCommerce stores and retail chain owners need better ways to keep track of customer behavior. <\/strong><\/p>\n And that’s where data collection technologies come in to capture how consumers are shopping and why they make their purchasing decisions.<\/p>\n First of all, to learn how your customers behave, you need to create a 360\u00b0 view of the customer’s journey<\/a>. <\/p>\n You start by understanding the types of factors that influence buying behavior. <\/strong><\/p>\n We all know that the broadcast media and social media channels bombard consumers with digital marketing, branding, and content marketing messages to influence consumers. <\/p>\n But often, buyers make decisions based on referrals or suggestions from their peer group, family, or simply based on their likes and dislikes. <\/p>\n This brings us to the main point.<\/p>\n Collecting data about the individual consumer, how they make decisions, and why they purchase their products<\/strong> will help marketers create a more satisfying buying experience.<\/p>\n And trust us: a lot of it has to do with personalization. <\/p>\n Here are a few statistics. 75% of viewer activity<\/a> on Netflix is driven by recommendation, and 35% of Amazon’s revenue<\/a> is generated by its recommendation engine.<\/p>\n Impressive, don’t you agree?<\/p>\n Consumers are obsessed with technology and constantly demand a personalized experience across all communications channels. <\/p>\n In this context, marketers should collect and use consumer behavior data to create better experiences<\/strong>, optimizing all three stages of the customer lifecycle:<\/p>\n Simple.<\/p>\n \u21b3 A <\/strong>customer relationship management (CRM)<\/strong><\/a> system<\/strong> collects and stores information about consumers. <\/p>\n This data includes personal demographics like job, age, and personal interests. The CRM also collects buying activities like what products were purchased and how much they paid.<\/p>\n Many brands track customer intent activities which help predict what products they are considering to purchase in the future. <\/p>\n Viewing certain websites or reading blogs to conduct research are all intent activities.<\/p>\n \u21b3 Surveys and other types of marketing research tools also collect valuable opinions from customers.<\/strong><\/p>\n Many brands use standardized surveys. One popular model is known as the Net Promoter Score. <\/p>\n Customer experience teams send periodic surveys via email asking consumers with they would recommend the brand to a friend. <\/p>\n There is a 1-10 scale indicating which customers are promoters (9-10), passives (7-8), or detractors (1-6). <\/p>\n \u21b3 In addition, customer forums, social media channels, and focus groups <\/strong>are popular ways to collect consumer perceptions and attitudes towards the brand. <\/p>\n Not only can companies find out who their loyal customers are, but they can also target digital marketing campaigns to reward their promoters.<\/p>\n There’s another layer here that’s easy to overlook: the passive data that gets picked up while people simply browse, swipe, or linger over a product image. All those micro-interactions\u2014how long someone stares at a photo, whether they click to zoom, which items they pause on during a scroll\u2014get scooped up too. Brands interpret these little behavioral nudges to fine-tune everything from homepage layouts to which products end up in your email recommendations. It might feel a little much sometimes, but, yeah, that’s why sites can start feeling like they’re reading your mind. Freaky or helpful, depending on your mood (or your caffeine level).<\/p>\n The real challenge, though, is figuring out what’s actually useful within that ocean of noise. Anyone who’s tried to untangle messy spreadsheets or compare sentiment scores from a dozen social listening tools knows this struggle. Some brands have started pairing traditional focus group insights with real-time analytics\u2014so they’re not just guessing at trends, but actually watching them unfold. That blend of qualitative and quantitative data tends to reveal the gaps you can’t see from numbers alone, like when customers say they love your brand but quietly start drifting away. It’s not always neat or obvious, but digging into this mess is where the gold usually hides.<\/p>\n<\/p>\n Ok, so now you have wonderful data on your hands.<\/p>\n Consumer activity and behaviors are being measured on your website and eCommerce platform using analytical tools<\/a>, like Google Analytics. <\/p>\n And social channels such as Facebook and Twitter are providing their own valuable information through their data analytics platforms.<\/p>\n But let’s face it.<\/p>\n There are millions of transactions every minute, so is not easy to keep track of everything.<\/strong><\/p>\n This is why many brands rely on consumer data analytics software to organize and report on buying trends for their products and competitors.<\/p>\n It is a smart way to put information in a format that company executives and marketing professionals can quickly digest. <\/p>\n The software can process large volumes of data and generate interactive reports and dashboards on a real-time basis.<\/p>\n As a result, decisions can be made quickly without worrying about a lag in information.<\/strong> This helps companies keep their campaigns fresh and relevant to their customers. <\/p>\n The best advice we can give here is: listen to what your data is screaming.<\/p>\n Why screaming? <\/strong>Because we are living in an era of conscious consumers, where very little is tolerated by them.<\/p>\n People are not afraid to take a stand \u2014 and they will easily turn against unethical businesses.<\/p>\n Yes, using consumer data helps a company to create better, more personalized buying experiences<\/a>.<\/p>\n But it also educates brands about behavior trends in a world of fast-paced changes.<\/strong><\/p>\n It encourages businesses to become more transparent about their processes and rewards them for doing so. <\/p>\n In that way, consumer behavior data can really guide improved strategies that are more aligned to a new (and conscious) way of shopping. <\/p>\n Here are some examples of big players using data in the right manner.<\/p>\n Apple is an excellent example of a company built on consumer behavior analytics. <\/p>\n In the early days of marketing, it understood the need to create a loyal customer base<\/strong>, even if that meant giving up market share. <\/p>\n As a result, Apple founder Steve Jobs didn’t share his operating system with other companies as Microsoft did with their MS-DOS system. <\/p>\n At first, many industry critics questioned this philosophy. <\/p>\n Still, as Apple expanded into the digital era, they took advantage of their loyal customers<\/strong> to dominate the downloadable music (iTunes), smartphones (iPhones), and tablet computer (iPad) product categories. <\/p>\n By harnessing data from music downloads and app purchases, Apple succeeds in creating personalized customer experiences.<\/p>\n The key to Amazon’s success and domination in the eCommerce sector is its ability to recommend various products to customers based on several factors. <\/p>\n Of course, shopping and browsing activity is essential, but the types of products consumers buy and styles, colors, and features are also important. <\/p>\n So, what impact does the recommendation engine have on overall business?<\/strong> <\/p>\n You already know that: 35% of all sales are generated by the recommendation engine.<\/p>\n The data collected during the shopping experience is analyzed by an open-source artificial intelligence platform known as DSSTNE (pronounced “destiny”) that not only recommends products but decides which order to present them in. <\/p>\n Amazon continues to optimize the DSSTNE system<\/strong> to often promote less popular but more profitable products as part of their recommendations.<\/p>\n Consumer behavior data drives the recommendation engine for Netflix, and their complex algorithms suggest content based on the behaviors of millions of viewers. <\/p>\n To expand their services into new regions, Netflix required vast amounts of data<\/strong> to feed the recommendation engine. <\/p>\n But the efforts paid off. <\/p>\nWhat Is Consumer Behavior Data?<\/h2>\n
\n
Why Should You Collect Consumer Behavior Data?<\/h2>\n
\n
How Do You Collect Consumer Behavior Data?<\/h2>\n
![\"\"](\"https:\/\/mlgzkyrbq6eh.i.optimole.com\/w:auto\/h:auto\/q:mauto\/https:\/\/pingback.com\/br\/resources\/wp-content\/uploads\/2021\/06\/Webinar-First-party-Data-and-a-Changing-Market-with-Rand-Fishkin.png\")
How Do You Analyze Consumer Behavior Data?<\/h2>\n
How to Use Consumer Behavior Data to Succeed in Your Marketing Strategies<\/h2>\n
How Companies Benefit from Consumer Behavior Data?<\/h2>\n
Apple <\/h3>\n
Amazon <\/h3>\n
![\"The](\"https:\/\/mlgzkyrbq6eh.i.optimole.com\/w:auto\/h:auto\/q:mauto\/https:\/\/pingback.com\/br\/resources\/wp-content\/uploads\/2021\/06\/Amazon.png\")
Netflix <\/h3>\n
![\"Recommended](\"https:\/\/mlgzkyrbq6eh.i.optimole.com\/w:auto\/h:auto\/q:mauto\/https:\/\/pingback.com\/br\/resources\/wp-content\/uploads\/2021\/06\/Apple-scaled.jpeg\")
![\"The](\"https:\/\/mlgzkyrbq6eh.i.optimole.com\/w:auto\/h:auto\/q:mauto\/https:\/\/pingback.com\/br\/resources\/wp-content\/uploads\/2021\/06\/Netflix.png\")