With ever-evolving marketing trends, staying ahead of the game is more important than ever. With the right data, you can gain valuable insights into your customers and their behaviors, leading to more effective campaigns and strategies. But far too often, companies don’t take advantage of the data they have. In fact, 87% of marketers say that data is their company's most underutilized asset. You may have data for days, but if you don’t use it, what’s the point of collecting it? If you have data and want to know how to use it, you’ve come to the right place. This blog explores: Let’s get started! Data-driven marketing is an approach to marketing that focuses on using analytics to inform decisions and optimize campaigns. Over 64% of marketers report that a data-driven approach is necessary today Data-driven marketing examines trends, predicts behavior, and can help you develop strategies that fit the needs of your audience. This data will help you craft tailored marketing campaigns for your customers. Ultimately, this maximizes your return on investment. Traditional marketing involves various techniques to promote a company's goods and services. It focuses on reaching as many people as possible with a common message. To do this, companies have relied on mass media advertising to the general public. This approach is not always accurate and efficient. Data-driven marketing is quite different. It's much more focused on a specific kind of customer. Data-driven marketing involves gathering and analyzing unique customer data, giving you insight into what consumers want and prefer. Marketing has always done two things: identify what customers want and then motivate people to buy. Traditionally, this has required a lot of trial and error. That’s why marketers have become increasingly reliant on data-driven marketing trends. Let’s look at the main benefits. Marketers have access to a vast array of data that they can use to improve their return on investment (ROI). By closely studying the correlation between various digital marketing activities and ROI, you can be more strategic with your budget allocation. This laser focus on the most beneficial activities will lead to greater profitability in the long term. Also, using factual data instead of a guesswork marketing strategy boosts efficiency. You can focus your marketing campaigns on audiences that are more likely to convert, maximizing your investment.What is data-driven marketing?
How does data-driven marketing differ from traditional marketing?
Why you need data-driven marketing
Data-driven marketing increases ROI
Data-driven marketing helps you customize
Speaking of personalization, data-driven marketing is revolutionizing the way businesses reach their target audiences. By leveraging data, you’re able to customize your marketing to meet the needs of a specific customer segment. This allows you to craft personalized messages that appeal to the right people so that your target audience is a bit more narrow than this:
Data-driven marketing also allows businesses to create targeted ads based on a user’s browsing history, interests, and other demographic information. This makes it easier for you to connect with potential customers, increasing their chances of conversion.
With data-driven marketing, you can get more out of a campaign by providing customers with custom content.
Data-driven marketing builds trust and loyalty
One-size-fits-all messaging is an outdated approach that customers have become increasingly unresponsive to. You must craft your messages specifically for each customer segment and cater to their needs and interests.
Doing this will help your company establish an authoritative voice in the industry. More importantly, it builds customer loyalty by establishing trust with them.
Data-driven marketing predicts behavior
As you customize content and build trust, customers will interact more often with your brand. They’ll engage with you using your website, email newsletter, social media, and app. Collecting and analyzing this data over time gives you valuable insights into the behavior of customers.
The more data you have, the greater likelihood you'll predict what they'll do next.
Of course, this predictive power is not the same as having a crystal ball. But it’s close. Data gives you a much better understanding of what your customers want and respond best to.
6 data-driven marketing strategies with examples
Your marketing strategy will determine whether you ever see these benefits. Here are six data-driven marketing trends with real-life examples to help you develop your own strategy.
1. Take an omnichannel approach
Omnichannel marketing is an approach that combines data-driven marketing with a unified customer experience across all channels (social, web, newsletter, chat, etc.).
It provides these advantages:
- Seamless journey across all platforms and devices
- Consistent customer service
- Streamlined payment processes
- Identifiable branding and tone
- Personalized messages based on customer preferences
- Content informed on past experiences and current stage in the customer journey
Sephora's Beauty Insider Rewards program has established itself as the benchmark in customer loyalty. It’s also a major part of their omnichannel strategy.
Customers can access news, products, and promotions on Sephora's website, mobile website, mobile app, and even in-store. Beauty Insiders can view their favorite list, past purchases, and rewards points, scan items in-store to find different alternatives available online, watch instructional videos, and nearby find stores--whether they're on a smartphone or a computer.
This omnichannel strategy has resulted in 11 million members who spend an average of 15 times more than other Sephora customers.
2. Take advantage of AI
With the use of AI, marketers are more easily able to create and customize content. AI can help with optimizing ad bidding, targeting specific audiences, customizing web experiences, and analyzing phone conversations in bulk.
One of the more impressive ways to use AI is through augmented reality (AR). AR shows what a product looks like in a space or on a person's body. Magnolia Market, owned by Chip and Joanna Gaines, recently partnered with Shopify to bring AR to their app.
You might not be as big as Magnolia. And that’s okay. AR may still make sense for you. Another AI that may be more practical is a chat box for your website.
Probably the most game-changing use of AI is still relatively new.
ChatGPT, a natural language processing tool, is making rapid changes to the field of market research. Market research has always been a time-consuming affair for companies because there is inevitably a lot of data to go through.
ChatGPT serves as a great tool to have in your corner because it helps save time when it comes to analyzing data, creating surveys, and coming up with insights on customer behavior and trends.
That is not to say that market research professionals can be replaced by the tool but rather that they can focus their energies on more important tasks like enhancing the final ideas rather than spending hours crouched over large amounts of data.
With 84% of marketers now using AI, it’s time to consider it if you haven’t yet. It might help you gain a competitive edge while saving you time and money.
3. Segment your Audience
Consumer segmentation is a powerful tool to identify and understand distinct demographics. It provides valuable insights into consumer behavior and preferences.
Segmenting your audience allows you to customize content and online interactions according to the consumer’s demographics, purchase history, and web activities. Knowing about a user's interests helps create more personalized experiences for them.
DirecTV capitalized on the fact that people are more likely to try new services when they move. They used USPS data to create a modified homepage that would be visible only to those who had recently moved.
With some A/B testing, DirecTV found that their personalized marketing won out over a traditional approach. In version A (the regular home page) they offered a $300 gift card offer plus $10 off for 12 months to anyone who started service.
In version B, people who had moved saw a custom homepage. They were still offered the $10 off service in this version, but not the $300 gift card. Version B’s home page looked like this:
Not surprisingly, they had a better conversion rate on the personalized page. The best part is that they didn't have to shell out a $300 gift card to those customers.
DirecTV’s data-driven marketing strategy saved them money and increased their conversions. The lesson? General content isn’t as effective as content for segmented audiences.
At Audiense, we can help you learn how to segment your audiences. Try our Audiense Insights for free to get started.
4. Generate relevant content
“Content is king,” Bill Gates wrote back in 1996. And it’s still true. But it has to be the right content, at the right time, for the right people.
Generating relevant content can be challenging and time-consuming. That is why data-driven marketing has become so popular in recent years.
With the help of data, marketers can identify the needs of their target audience and create content that resonates with them. By understanding what topics are trending and what type of content is popular, marketers can create data-driven content that engages and converts.
Zillow analyzed the listing descriptions of 24,000 homes and found that listings with certain keywords tend to sell for more than expected. So they wrote an article about it and published it in the “Tips and Advice” section of their blog.
When you think about the information available to you, how can you use it to generate valuable, relevant content for your customers?
5. Use predictive analytics
Predictive analytics relies on existing information to estimate what could take place. You use predictive analytics whenever you look at historical consumer data and anticipate trends.
Marketers can use insights from consumer interactions to gain valuable insight into their interests and preferences. This information can then create targeted audiences for campaigns, based on demographic data and interest groups.
Predictive analytics also lead you to strategically optimize throughout the year.
Consider a company like Akrobat Trampolines that sells in-ground trampolines. In-ground trampolines mean digging for installation. This isn’t a great winter activity for cold climates. Akrobat, like other seasonal-oriented companies, can use consumer data to drive decisions on when to run campaigns, targeted ads, and sales, rather than relying on their gut or guesswork.
You can use data to predict a lead’s likelihood of moving down the sales funnel toward purchasing simply because they saw an ad at the right time.
6. Pay attention to SEO and site performance
Finally, don’t neglect the role of your website in data-driven marketing. It’s the front door to your business in a digital world. Two key elements are important.
First up, your SEO. Don't think of focusing on SEO in the traditional sense of meta descriptions and headers. Predictive SEO is about anticipating what consumers may need in the future, rather than relying on existing data. Doing this enables you to predict search engine trends and optimize your website to create content that will help you achieve a better Google ranking in the long run.
Second, an often-overlooked element of your online conversion rates is site performance. Just because someone finds you and lands on your page doesn’t mean you'll make a sale. The first five seconds of page load time have the highest impact on conversion rates. Your web hosting infrastructure and site design must be able to handle traffic and user browsing behavior.
Don't neglect it. Otherwise, all your other data-driven efforts will be in vain.
Key takeaways
It’s essential in today's competitive business environment to stay up-to-date with marketing trends. By leveraging data, you can gain a better understanding of customer interests, behaviors, and preferences, helping you to create tailored campaigns that meet their needs.
We covered a lot of ground in this article. Let’s recap the key takeaways.
Data-driven marketing relies on the use of customer data, leading to more focused tactics. Traditional marketing, on the other hand, seeks to reach as many people as possible with a broad message.
Data-driven marketing has tremendous benefits. Using a data-driven strategy increases your ROI, allows you to customize your content, builds trust and loyalty with customers, and helps you predict customer behavior.
To see these benefits happen, use these 6 data-driven marketing strategies:
- Omnichannel communication
- Artificial intelligence
- Audience segmentation
- Data-driven content
- Predictive analytics
- Predictive SEO and site performance
This is a lot to take in. If you’re ready to take your marketing to the next level, a good place to start is getting to know your audience.
With Audiense Insights, you can better understand your audience and what they care about. It will help you learn personality traits, demographics, sources of influence, and more so you connect in a meaningful way. Request a free demo to get started today.
FAQs
Data-driven marketing trends: why you need to update your strategy & how to get started? ›
Data-driven marketing is the approach of optimising brand communications based on customer information. Data-driven marketers use customer data to predict their needs, desires and future behaviours. Such insight helps develop personalised marketing strategies for the highest possible return on investment (ROI).
How do you develop a data-driven marketing strategy? ›- Share data across different channels. Customers today rarely engage with a company or brand on a single channel. ...
- Use demographic data to plan campaigns. ...
- Personalize the customer journey. ...
- Target better with predictive analytics. ...
- Deepen audience insights with data onboarding.
Data-driven marketing is the approach of optimising brand communications based on customer information. Data-driven marketers use customer data to predict their needs, desires and future behaviours. Such insight helps develop personalised marketing strategies for the highest possible return on investment (ROI).
Why does marketing need to be data driven? ›Data-driven marketing drives increased sales. Data-driven marketing can help you better identify the most likely customers to buy from your company. This means you can spend less time and money trying to convince people to buy your product or service when they're not interested.
What is an example of a data driven strategy? ›For example, if you own an ecommerce store and see a customer has repeatedly visited a product page but hasn't bought that product, a data-driven marketing technique would be alerting that customer when the item is on sale. It's simple yet highly effective.
What are the 4 steps in order to designing driven marketing strategy? ›Segmentation, targeting, differentiation, and positioning are four distinct steps that should be included in customer-driven marketing.
What are the 3 steps in developing marketing strategy? ›- Perform data collection and analysis through market research.
- Determine marketing budget and allocation for your marketing mix.
- Create marketing assets that support your planning process.
There are five core components of a data strategy that work together as building blocks to comprehensively support data management across an organization: identify, store, provision, integrate and govern.
What are the 3 types of data marketing? ›Marketers are interested in three types of big data: customer, financial, and operational. Each type of data is typically obtained from different sources and stored in different locations. Customer data helps marketers understand their target audience.
What are data driven tools? ›Data-driven marketing tools are the ones that provide the data the marketers require to target their potential customers and save themselves money and time in the process. These tools will let you figure out where your potential customers are online.
What are the elements of data-driven strategy? ›
Elements of Data Strategy defines the components needed, their relationships, and blueprints for conducting the required activities. The 3D model—Due Diligence, Design, and Delivery— is at the core. These three phases ensure that the data strategy is informed, complete, and operational.
How do you use data to develop strategies? ›- Create a proposal and earn buy-In.
- Build a Data Management Team and assign data governance roles.
- Identify the types of data you want to collect and where it will come from.
- Set goals for data collection and distribution.
- Create a Data Strategy Roadmap.
A data-driven approach holds everyone accountable to specific goals and measurable results. This increased accountability can drive higher revenues and better cost savings. Department managers are able to make informed decisions based on up-to-the-minute information.
What are the 4 C's of marketing strategy? ›The 4 C's of Marketing are Customer, Cost, Convenience, and Communication. These 4 C's determine whether a company is likely to succeed or fail in the long run. The customer is the heart of any marketing strategy.
What are five 5 steps required to develop marketing strategies? ›- Step 1: Analyze the target market. ...
- Step 2: Describe target audiences. ...
- Step 3: Define the objectives. ...
- Step 4: Develop marketing communication strategies and tactics. ...
- Step 5: Define a marketing budget.
The 4 basic marketing principles are product, price, place and promotion.
What are the 7 elements of strategic planning? ›- Step 1: Environmental Scan. ...
- Step 2: Internal Analysis. ...
- Step 3: Strategic Direction. ...
- Step 4: Develop Goals and Objectives. ...
- Step 5: Define Metrics, Set Timelines, and Track Progress. ...
- Step 6: Write and Publish a Strategic Plan. ...
- Step 7: Plan for Implementation and the Future.
Product, Price and Promotion. The Product, whether it's a tangible or intangible product, is your product.
What are the 5 C's of data management? ›Five framing guidelines help us think about building data products. We call them the five Cs: consent, clarity, consistency, control (and transparency), and consequences (and harm). They're a framework for implementing the golden rule for data.
What are the 6 key components of a data strategy? ›- Alignment with Business Strategy.
- Analytics and Data Maturity Evaluation.
- Data Architecture and Technology.
- The Data Analytics Team.
- Data Governance.
- Data Strategy Roadmap.
What are the 3 C's of data management? ›
We've divided them into three related categories: completeness, correctness, and clarity.
What are the two 2 main forms of data used in marketing? ›Two main Types of Data in Marketing: Structured Data vs Unstructured Data. There are two main types of data, structured and unstructured. Each contains valuable insights about your buyers. When they are combined, your marketing team can create greater context for data and expand the depth of your analysis.
What are the 4 C's of data management? ›Specifically, we found that the connection between big data and big process revolved around the 'Four Cs'.” Those four Cs are customers, chaos, context, and cloud.
What are the 7 P's of big data? ›Today, all the businesses are defined by the 7 Ps, i.e,Product, Price, Promotion, Place, People, Processes, and Proof or physical evidence.
What are the 4 A's of big data? ›Big Data analysis currently splits into four steps: Acquisition or Access, Assembly or Organization, Analyze and Action or Decision. Thus, these steps are mentioned as the “4 A's”.
What is another word for data-driven? ›Data-driven decision making is also known as data-driven decision management or data-directed decision making.
What are data-driven skills? ›Data driven skills are key for Data Science experts to successfully convey facts and figures to non-technical teams. For example. Sales and marketing teams use analytics to make informed business decisions.
What are the 5 levels of use in data driven decision-making? ›- Step 1: Strategy. Data-driven decision making starts with the all-important strategy. ...
- Step 2: Identify key areas. ...
- Step 3: Data targeting. ...
- Step 4: Collecting and analyzing data. ...
- Step 5: Turning insights into action.
An effective data strategy supports the entire organization for collaborative and consistent data management. It gives everyone the answers to five key questions: What data is appropriate? What data operations are approved? What is the purpose of data storage and collection?
What is a data strategy roadmap? ›A data strategy roadmap is a plan that outlines the implementation process for how an organization will effectively manage, analyze, and utilize data to achieve its business goals. It includes objectives, necessary resources, and a timeline.
What is the first step in a good data use strategy? ›
- Understand your business objectives. Connect your data and AI strategies with the business strategy. ...
- Assess your current state. Unpack pain points to reveal blockers and gaps. ...
- Map out data strategy framework. Define your data's target state. ...
- Establish controls. ...
- Create integrated solutions. ...
- Scale your team and processes.
- Align Your Vision. How you leverage data must align with the organization's goals. ...
- Choose the Right Architecture and Tools. ...
- Take Inventory of Existing Data Assets. ...
- Embrace Data Governance. ...
- Define Roles and Responsibilities. ...
- Create a Training Plan. ...
- Visualize Your Roadmap. ...
- Be Realistic.
- Diagnose and set the goal … First, you build a rapid understanding of your current data-driven capabilities (like tools or skills). You analyze your strengths and opportunities and set short-term goals. ...
- Step 2. … create a plan. ...
- Step 3. … and implement it!
Data means you reach the right people at the right time as you can trace trends and patterns. Data can help you understand what works and what doesn't - you can then understand why and make the necessary adjustments. Target marketing becomes easier if you can segment based on data.
How do you create an effective data strategy? ›- Understand your business objectives. Connect your data and AI strategies with the business strategy. ...
- Assess your current state. Unpack pain points to reveal blockers and gaps. ...
- Map out data and AI strategy framework. Define your data's target state. ...
- Establish controls. ...
- Create integrated solutions. ...
- Scale your team and processes.
An example of data-driven decision-making is using digital intelligence tools to look at existing demand in a market for a specific product or service before deciding to enter it. Another example of DDDM is using competitive intelligence to look at specific keywords to target in a PPC campaign before investing.
What are the three most important sources of data for effective decision-making? ›- Observation Method.
- Survey Method.
- Experimental Method.
Data-driven decision-making is defined as using facts, metrics, and insights to guide strategic business decisions that align with goals, strategies, and initiatives. It is a process that involves analyzing collected data through market research, and drawing insights, to benefit a business or organization.
What are the 6 key components of a successful data strategy? ›- Alignment with Business Strategy.
- Analytics and Data Maturity Evaluation.
- Data Architecture and Technology.
- The Data Analytics Team.
- Data Governance.
- Data Strategy Roadmap.