In 2023 agile marketers are rethinking their strategies to double down on precision marketing following Covid-19. Tiresome as it may be to drone on about the pandemic, research conducted by the esteemed consulting firm McKinsey found that between March and August 2020, “one in five consumers switched brands, and seven in ten tried new digital shopping channels.”
In just a few months, the retail sector experienced staggering growth, predicted to occur over a ten-year period. This seismic shift in target audience behavior behooves the adoption of data-driven marketing if organizations want to seize growth opportunities for greater ROI and resilience. Companies that upgrade marketing efforts will be more effective in generating revenue and building the necessary agility to future-proof their business.
So, what exactly is data-driven marketing? Renowned American marketing software developer HubSpot provides this definition: “Data-driven marketing uses data to inform all marketing decisions, from creative assets to campaigns. It places customer data front and center to ensure all marketing efforts are relevant to customer interests and behaviors.”
Nowadays comparison between traditional and digital marketing is more common. While traditional marketing like magazine print media or radio spots still has its uses, it is less targeted and cost-effective than digital marketing campaigns. However, despite the pivot to online retail, both advertising methods can work together. Think of a massive Netflix show billboard in the city center and an Instagram post promoting the same show, for instance.
Data-driven marketing is facilitated online and uses paid or organic ads on social media or search engines, as well as email marketing, influencer marketing, video marketing, and more. Let’s examine how optimizing brand communications based on customer behavior helps develop personalized marketing with the highest return on investment.
Not only does data-driven marketing empower organizations to speak intelligently and proactively to clients, but it is also a prerequisite to business success across all industries. As the way of the future, it offers innumerable benefits.
A data-driven digital marketing strategy aims for quality rather than a high quantity of leads. Because businesses use appropriate marketing channels to directly target ideal customers, they achieve higher conversion rates. Marketers, who know their existing customers well, can invest half the amount of money as traditional campaigns and still achieve better results.
Data-driven marketing resolves a marketers’ struggle to determine where budget is wasted and therefore promotes better attribution for spend optimization. With higher quality, granular data, marketers can combine aggregate data and insights offered by attribution models into one holistic measurement, referred to as unified marketing measurement or UMM.
Using attribution models, marketers evaluate customer journeys, examining multiple touchpoints along the marketing funnel to provide a comprehensive view of each target segment’s path to purchase. Once marketing teams determine what moves new customers down the funnel, they can allocate marketing spend accordingly.
Potential customers face a bombardment of choice, and if the marketing message isn’t relevant to them, they’ll simply go elsewhere. Utilizing complex data and its analysis can improve the experience a customer has with a brand because organizations acquire a greater understanding of what customers want and, therefore, offer greater customer journey personalization. Essentially, they can replace generic campaigns with relevant ones.
Data-driven marketing strategies enable precise target audience segmentation, further personalizing experiences and driving new customer engagement. Specified knowledge on how variegated target audience groups act allows the upselling of interests and the use of appropriate multichannel communication for distinct demographics.
Correct and detailed data collection can also facilitate a greater understanding of customer satisfaction after a sale. Most companies deploy surveys to assist with product and service improvements. Customer experience analysis can reveal a lot about target customers and how to better serve them. In fact, according to Harvard Business Review, 80% of companies use customer satisfaction scores to analyze customer experience and improve it.
More actionable consumer data leads to sharp and focused insights. When data-driven marketers understand customers at individual levels, they can predict how they will interact with different campaigns and make strategic decisions based on providing personalized messaging that offers the best possible experience.
Essentially, online marketing tools help create smooth, hassle-free personalization. As a rudimentary example, if you know your target audience is young mothers, you likely won’t craft marketing messages that appeal to women without children. Marketing campaign decisions can also be fast-tracked, enabling organizations to discard what’s not succeeding and optimize what is.
An insightful set of consumer data significantly reduces the risk of failure, as the budget spent on product development and marketing campaigns will automatically meet consumers’ needs and expectations. Additionally, sales data can reveal untapped opportunities for cross-selling throughout the sales funnel, which may have been previously neglected.
Since its inception, advertising has leveraged consumer behavioral patterns, except now these can be harder to discern. To pinpoint salient behavioral indicators in time to act requires continually refreshed data from a mix of sources at a granular level. In some cases, this can be as deep as cities’ individual neighborhoods, or the buying habits of a gentrified vs. adjacent upper echelon suburb.
For instance, with the right customer data, retailers can assess what products different segments are likely to buy for Thanksgiving and tailor marketing messages to boost sales. Robust data also provides companies with better competitor insights. By comparing third-party data, like sales and promotions, to their metrics, they evaluate and improve their offerings.
With the right customer data, retailers can assess what products different segments are likely to buy. Robust data also provides companies with better competitor insights.
An algorithm might learn, for example, that consumers who engage in showrooming tend to buy the product they looked at, at a later stage, for a cheaper price online. Such indicators can help businesses trigger tailored offers to covert “showroomers” into buyers when they’re at the store, allowing marketers to spend on more profitable segments.
A quick explanation on showrooming: Basically, this refers to the practice of visiting retail stores to research merchandise before purchasing it online at a lower price. This consumer behavior is typical for higher-priced goods.
An organization’s marketing goals will determine how it uses data to establish connections between sales, customer behavior, and effective channel use. When assessing marketing goals, there are usually overlaps between KPIs chosen and data needed to make better decisions. Using a modern data stack (customer relationship management software) can help derive key insights across touchpoints rather than dealing with manual data integration, which has a higher error margin.
Data-driven marketing is an invaluable tool for marketing strategy development. For example, collected customer data may indicate that most of a target market purchases smartphones. This information can inform mobile strategies like paid advertising in popular mobile apps. Building these types of connections becomes important for organizations to remain relatable and relevant to new and loyal customers.
For this reason, using a suitable customer relationship management platform that centralizes data is critical to prevent information and work team solos. From strategists to content creators and sales personnel, a good marketing team works as an ecosystem; everybody needs to collaborate to bring in leads and improve revenue. Building consumer behavior connections through data and teamwork is critical to success.
It’s facile to declare data-driven marking grows revenue. Of course, when effectively implemented, it increases leads and conversions. This is simply because an organization privy to the right consumer data will market products and services accurately and thus yield beneficial results. But a data-driven approach isn’t just a plug-and-play solution. It offers a long-term methodology to gain feasible results, provided organizations pivot accordingly.
So, besides improving the bottom line, how does it really impact business? For starters, it means democratizing customer data with relevant employees (according to regulatory compliance). It’s cliché, but knowledge is power; granting teams access to the same information enhances synergy and ensures everyone is aligned with current marketing activities and goals.
Secondly, organizations may need to upgrade or invest in marketing tools like Google analytics, customer relationship management software, content development calendars, and so forth, to help obtain relevant data and automate processes. Investing in AI eliminates friction and inconsistencies across channels.
Data doesn’t lie. On a profound level, there is an increasing expectations gap as businesses struggle to keep up with more informed, connected, and knowledgeable consumers. The shift of power between business and consumers has disrupted traditional customer journeys. A recent report by Deloitte highlights how, “consumers look for inspiration by exploring other consumers’ social media profiles, rather than expecting brands to inspire them through traditional advertising.”
Consumer engagement has to go beyond marketing. Companies must really listen to, inspire and co-create with consumers. Industry-wide customer data consistently points to themes around sustainability and assuaging consumer skepticism. More than ever, there is a demand for businesses to be purpose-led and aware of their roles and responsibilities in society.
Customer relationship management (CRM) software, mobile and web analytics, cookies from website visits, social media, and customer feedback surveys all provide valuable target audience data. While there are industry standards for metrics that most marketers follow, determining the first and third-party data needed depends on a company’s marketing goals.
Additionally, besides discerning which data is useful, the greatest challenge is maintaining data hygiene. This is a continuous practice of eliminating outdated, incorrect, duplicated, or misplaced data to ensure decisions made are based upon accurate metrics. Investing in a world-class marketing team and MarTech stack can safeguard against data mismanagement and subsequent poor decisions.
Marketers are interested in three types of big data: customer, financial, and operational. Some data-driven marketing KPIs will fall distinctly within these categories, while others overlap. Data derived from customers that’s useful for marketing purposes falls into four categories: identity data, qualitative data, descriptive data, and quantitative data.
The sheer volume of data available for collection and analysis is astounding. There are a plethora of metrics available that reveal more about online customer behavior, marketing campaign performance, and the effectiveness of social media channels, for instance.
Naturally, it’s easy to read too much into vanity metrics or get lost in numbers without understanding how to use these valuable insights to improve businesses. Data-driven advertising should always align with an organization’s overall marketing goals. In general, marketing data is collected in-house or through third parties.
This is the data businesses collect on their customer base, such as; social media interactions, email list sign-ups, buying transactions, how many times a customer visits a website before purchasing, content marketing interactions, and a history of their online purchases. This type of data helps companies improve their websites, marketing campaigns, and content marketing.
In-house data doesn’t reveal much about what consumers are like outside their direct interaction with a company. Third-party data reveals what an audience’s interests are when they’re not communicating with a business. For example, do they like to travel? Are they homeowners? Do they have a family? These broad brushstrokes can inform future marketing campaigns and product development, provided information collected adheres to privacy law.
The digital marketing industry leverages software and tech tools, referred to as a MarTech stack, to plan, execute, and measure campaigns. These stacks are uniquely configured to meet a company’s needs. Most suites include software tools for the following marketing disciplines:
Software that forms part of a stack should always contribute towards overall marketing success. A MarTech stack working at full capacity supports an organization’s goals and allows it to focus on more creative and innovative marketing elements.
According to Google, “leading marketers are 56% more likely to agree that decisions backed by data are superior to those based on gut instinct and experience.” A robust data-driven marketing strategy and proprietary infrastructure can deliver unbridled success. Here’s how:
Let’s say you’re a pet grooming service wanting to advertise specifically to busy families within a 5-mile radius of your business. This is entirely possible with data-driven advertising. Informed ad targeting records and stores information in the form of cookies when a prospect visits a company website.
The data it collects includes user location, length of time spent on the website, pages viewed, and online searches. Using this information, marketers can determine the level of interest a lead has in a particular service or product and deliver ads of the following nature appealing to a consumer’s interest:
Regardless of advertisement type, the aim is to send the right message, to the right consumers, at the right time, and this is only possible with sophisticated consumer data insights available through data-driven marketing.
The only way to get consumers’ attention in an oversaturated online market where they’re overwhelmed by ‘tyranny of choice’ is to appeal directly to their interests. Using demographic data to understand a target market’s geographic location, past interactions, online interactions, and spending habits aids the development of personalized marking campaigns that resonate with customers. As it is, 75% of consumers prefer retailers to use personal data to improve their shopping experiences. Personalized experiences make customers feel valued, which ultimately increases conversions and sales.
A data-driven approach helps segment audiences to create personalized messages for specific groups of customers.
Using data in sales boosts productivity because teams only pursue promising leads. A data-driven sales approach involves collecting and using specific metrics to inform all sales decisions. This includes everything from leads prospecting to churn reduction and pricing. Analytics tools can reveal where a prospect comes from, why a sales rep reached out to them, and how they made contact.
Data about how well one product or service performs over another, which customers interactions lead to buying, and who is making purchases versus a business’ intended audience offers insights that produce informed decisions about positioning, pricing, and target personas.
Sales teams can also track the sales cycles for a specific prospect and which competitors the business loses warm leads to. Gathering demographic and psychographic information from each lead further aids the development of customer profiles, or buyer personas.
Data-driven personas use available data collected to better understand target audiences, without bias and aspiration assumptions clouding marketing decisions. Real-time web analytics, digital customer feedback services, and social media insights help businesses develop and update customer profiles at an accelerated pace. A combination of first and third-party data creates a 360-degree view of a brand’s customer.
Knowing which devices are used at each stage of the customer journey, the channels where consumers are posting content, what they are talking about, how they research products, and their general attitudes offer an in-depth understanding of motivations and purchase behavior. Advanced persona modeling through artificial intelligence replaces guesswork with truly accurate target marketing.
A white paper by Deloitte further highlights the incredible efficiency of data-backed marketing. Individual online behavior can be used to further categorize consumers. For example, customers who visit the “70% discount” page on a website can be grouped as “bargain hunters” and presented with products that meet their price point.
Audience segmentation can also be used to personalize website experiences to specific customers. For example, let’s say a sports equipment store has several types of customers: teens, young professionals, serious athletes, and elderly men and women, who play a variety of sports. In this case, a marketer would not display kid’s training shoes to an elderly person because the product isn’t relevant to them.
Therefore, target market data can help businesses customize their websites in real-time based on who visits. For instance, a company may be able to identify that the customer is a trail runner through agreements with a third-party data provider. When the person arrives on the site, the marketer can feature popular products related to trail running.
Or, if the user clicks on yoga equipment, the website can present them with time-sensitive offers on yoga products the next time they visit the online store. What makes data-driven marketing so powerful is the ability for companies to retarget yoga product offers elsewhere across the web, i.e., on social media, in emails, and on search engine results pages (SERPs).
Each time a user visits a website or landing page, they leave more information about their preferences and intent, which can be stored on a customer relationship management platform. This supports efforts to map customer journeys to improve experience management and opportunities for success. Brands with faster and more accurate predictions of customer needs, market challenges, and new opportunities gain a competitive advantage.
Digital marketing is an agile practice, ever-shifting and optimizing with the launch of new technology and changes in consumer behavior. It’s an ongoing and never static process, which is important to take cognizance of if a business wants to leverage the full power of data-driven decision-making.
Research conducted by Mckinsey found data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain them, and 19 times more likely to be profitable. Organizations prioritizing precision marketing can seize opportunities for granular growth and achieve significantly greater resilience and ROI.
At Comrade Digital Marketing Agency, we offer high-quality digital marketing strategy development services which are based on data-driven approach that helps companies increase their conversion rates by 42%. If you’ve got your sights set on improving marketing efforts and revenue, our expert team can help your business generate an increased flow of qualified leads and sales. To start, why not tell us more about your project here?
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