The term “big data” has been around for about a decade, but it’s only recently become a buzzword that marketers can’t ignore. Big data refers to the huge amount of consumer information available through digital channels such as social media and mobile apps.
Using this information can help you better understand your customers’ preferences, behaviors, and interests—in turn allowing marketers to create more personalized messages that resonate with consumers.
Here are 6 ways you can use big data in marketing:
#1. Using Big Data in Personalization
Personalization is the process of tailoring content or communications to a specific user based on their previous behavior.
This can be as simple as sending them a discount coupon for their birthday, or as complex as tailoring a search engine page based on their prior searches and browsing history.
Personalization has been around for years, but it is now possible to do more of it at scale thanks to Big Data techniques like machine learning and AI.
The result is that companies can use personalization at every touch point in the customer journey — from marketing campaigns to customer service interactions — helping them gain an edge over competitors who aren’t doing so.
The most successful personalization strategies include:
- Understanding customer preferences with data from across your organization
- Improving customer experience by tailoring content and communications according to each person’s needs
- Personalizing offers based on past purchases or actions taken online (e.g., signing up for an email newsletter)
#2. Using Big Data in Targeting
Use Big Data to Target the Right Audience
Data is essential for making smart decisions about targeting. You can use it to target the right audience, and then you can also use it to make sure that your message and channel are well-suited for those targets.
For example, if you’re a retailer whose customer base consists primarily of women over 50 years old, then you should probably avoid advertising on dating sites (unless they have an audience of lonely hearts).
Use Big Data to Target the Right Message
How do you know which message will resonate most with your target audience? Use big data!
By analyzing past marketing efforts and testing new ones against various audiences, you can learn which messages work best for different segments—and therefore create more effective campaigns going forward.
Use Big Data to Target The Right Channel(s)
Gone are the days of a single marketing channel. Today, you must use multiple channels to effectively reach your target audience.
You can use big data to determine which channels are most effective in engaging people at specific stages of their buyer journeys, as well as how different customer segments respond to certain touchpoints. Then you can adjust your campaign strategies accordingly.
#3. Using Big Data in Optimization
- Optimize your marketing campaigns. Use big data to optimize your paid search, display, and email marketing campaigns by creating more relevant ads that are more likely to get clicked on.
- Optimize your website. Big data can help you understand how users interact with your site, so you can make adjustments based on user behavior and preferences—such as adding new content or improving the design of pages—that will keep them engaged longer, thus increasing traffic and conversions.
- Optimize your email marketing. Email marketing is a great way to reach and engage your customers. Use big data to optimize your email marketing campaigns by creating more relevant content that’s more likely to be opened and acted upon by the recipient.
#4. Using Big Data in SEO
You can also use big data to improve SEO. To make your content more relevant and engaging, you should be able to track what people are looking for and then create content that matches their needs. You can do this by tracking search terms, analyzing them, and understanding what people want from your website.
If you want to increase your ROI on paid advertising campaigns, then big data can help with that too. You can use it to figure out which ads are working best across different platforms (i.e., Facebook vs Instagram) so that you know where your money should go next time around!
You can also leverage big data for content creation. This includes everything from finding out what types of content are most popular with your audience to creating more engaging articles and blog posts that will help you convert them into customers.
#5. Creating a Customer Experience Based on Behavior
According to R2/RIOS-certified company bigdatasupplyinc.com, leveraging your customer data to create a personalized experience is one of the most effective ways to improve your bottom line.
To do this, you need to know what kind of experience your customers want, and how they feel when interacting with your product or service. You also need to understand their pain points and preferences, which can be accomplished by analyzing their behavior over time.
This starts by understanding what differentiates each customer from others on an individual level. This can come in many forms: Do they like certain types of content more than others? Are they generally more active at certain times of the day? Is there anything specific that makes them choose one product over another?
Once we have answers to these questions, we can begin using our knowledge about individual customers’ behaviors (e.g., their interests) as part of our marketing strategy going forward.
#6. Improving Customer Lifetime Value
Customer Lifetime Value (CLV) is a metric that measures the value of a customer over their lifetime. It’s an important metric because it helps you understand how much each customer contributes to your business on average.
The best way to increase CLV is by focusing on retention and engagement, which are two key factors that impact the long-term value of your customers. Retention involves keeping existing customers happy so they remain loyal to your brand or service.
Engagement includes activities like purchasing more products, referring friends and family members who become new customers in turn or providing feedback on how you can improve future offerings.
You can also increase CLV through cross-selling—offering related products or services that complement those already purchased by existing customers—and upselling—offering upgraded versions of current purchases at higher prices.
Challenges of generating value from big data
Big data has become a staple of retail and marketing strategies, from customer sentiment analysis to in-store behavior analysis.
It has also influenced supply chain operations, inventory management, and distribution and logistics. Even modest e-commerce businesses can leverage big data to improve customer satisfaction, enhance performance, and make better decisions. But how do these systems get there? What challenges can retailers face and how can they overcome them?
Big data can improve R&D. New tools and technologies based on data can result in the development of new products and services. The data itself can become a product if properly cleansed and analyzed.
For example, the London Stock Exchange generates more revenue by selling analysis and data. By making sense of big data and using it to create new products and services, big data can be a major competitive advantage.
Big data has an exponential growth rate. Today, the Internet is approaching two zettabytes in size, compared to just one zettabyte a few decades ago. This growth is not limited to marketing; it has become a commodity in itself.
Big data solutions should help marketing teams get a competitive edge over competitors. Using cloud-based big data integration tools and synchronization services is a promising way to generate value from this valuable data.
There are several challenges associated with generating value from big data:
- Big data is often unstructured, meaning it is difficult to organize and make sense of.
- Big data can be voluminous, making it time-consuming and expensive to store and analyze.
- Big data can be diverse, coming from a variety of sources that may use different formats.
- Big data may be inaccurate or incomplete, making it difficult to trust the results of analyses.
Big data is a big asset for today’s marketers
Big data is a big asset for today’s marketers. It can be used to improve the customer experience, optimize marketing campaigns and personalize offers. A recent study found that companies who use big data are likely to outperform their peers in terms of revenue growth by an average of six percent.
The first step in leveraging big data is knowing what kind of information you want or need from your customers, then matching it with the right technology tool. There are many ways to gather insights from consumers:
- Attribute-based analytics: This type of analysis helps marketers understand what factors contribute to customer behavior, such as purchase timing or campaign effectiveness at different stages in the sales cycle.
- Behavioral analytics: This type of analysis helps marketers understand how customers interact with their products and services—what they like, dislike, and might be interested in trying.
- Clickstream analytics: This type of data reveals what consumers are doing on your website and mobile apps, including where they click most frequently and whether certain functions or processes frustrate them (or make them more likely to buy).
Big data is a big asset for today’s marketers. By leveraging the advantages of its availability and analyzing it effectively, you can improve your strategies in several ways, including personalization and optimization.
Big data can also help you create more targeted content, build better customer experiences, improve your SEO rankings and increase LTV.
The bottom line? As we continue down this path towards an increasingly digital world full of ever-increasing information at our fingertips—whether through social media channels or simply browsing online—it’s crucial to keep up with how companies are using their resources to stay ahead of the competition!