Whether it’s an anniversary or birthday coupon, a simple “thank you” for being a repeat customer, or a recommendation that fits a buyer’s taste, customers prefer personalized over generic marketing. No matter the size of the emotional touch or gesture, they want to be treated like people and not just regular consumers.
Even in the B2B space, no one wants to read emails that have nothing to do with their interests. They want to collaborate with suppliers or businesses that understand their needs and align with their mission.
Question is: What’s the first step toward delivering the personalization people really want? Let’s dive in!
What is Database Marketing?
Database marketing is a marketing tactic that involves making marketing moves based on customer data. You collect, store, and analyze customer data to create targeted and personalized marketing campaigns.
In short, any marketing move you make without considering what customer data has to say does not fall under database marketing.
Customer data can be internal or external. As long as you structure and use it responsibly to elevate marketing ROI, then it fits within the scope of database marketing. For instance, customer purchase history, CRM entries, and behavioral data. Here’s how database marketing looks in a nutshell.
How database marketing works
- Data collection: Collect customer data from your website, customer support, or email interactions report. You can also obtain data from second-or-third party providers like advertising dataset, intent data or social media interests.
It’s okay to define a specific objective before collecting data or determine objectives after obtaining data. The latter approach is mostly employed by established companies that collect and store massive customer data for later use.
- Database management: Clean and organize the data before storing it into a relational database, CRM, or pre-defined marketing database. Handle the data securely to prevent unauthorized access, theft, or leaks.
- Segmentation: Analyze the collected data, aiming to divide the customer data into smaller groups based on shared behaviors, needs, or traits. This is what we call segmentation.
Common segmentation criteria include psychographics (values, interests, lifestyle), demographics (gender,age), behavioral, and geographic. Grouping customers into these categories helps with tailoring experiences, offers, or messages to relevant audiences rather than targeting everyone.
- Targeted or insight-led campaigns: Use the insights after analytics to create personalized messages or offers for specific segments. Then, track the impact of the select messages or offers to refine future marketing actions.
Here are the key benefits of using customer data to guide your marketing decisions and actions.
5 Key Benefits of Database Marketing
1. Create an adaptive user experience
Besides analyzing customer data to personalize their experience, you can design your systems to automatically adjust based on each user’s preferences, past interactions, and behavior.
Thanks to generative and predictive AI models, you can set up AI agents that track and collect customer data. Once they have the data, they analyze it to automatically change homepage banners, customize the navigation menu, send personalized emails, and more. This fosters long-term connections as the customers feel understood and valued.
2. Boost customer loyalty
A personalized experience not only makes people feel seen and understood, but it also makes a customer’s life easier. Instead of filtering through generic content and offers, they get updates and deals that align with their preferences. This increases the chances of them coming back.
Every time they come back and realize the personalization is consistent or it is getting better, a connection develops. The more relevant, helpful, and understanding your systems get, the bigger the emotional attachment grows. This eventually yields loyalty.
3. Spot more upselling and cross-selling opportunities
Analyzing customer data reveals insights into what they want and need, allowing you to anticipate what they may want to buy next.
Data including browsing history, past purchases, product filters, and purchase frequency can be analyzed to reveal certain interest patterns. For example, if someone frequently buys protein powder and also browses through specific gym equipment, that may be a chance to cross-sell them vitamins or workout gear.
If someone buys a basic version or standard subscription, it is a chance for you to track their habits. Why? You want to be there when they show signs of wanting an upgrade. That would be your cue to upsell them a premium version or subscription.
4. Optimize marketing expenditure
When you are actively analyzing customer preference, purchase history, and behaviours, deciding how to distribute your marketing budget gets easier. This is because you get to understand what customer segment is more likely to take action or buy.
As you track the campaigns based on database marketing, you also understand which campaigns deserve more money in future. You not only avoid future budgeting mistakes, but you also protect your brand from missing out on future sales opportunities.
5. Turn wins into a repeatable system
Unlike a campaign based on guess work, it is possible to tell why a campaign based on data worked or didn’t. You can look at the exact timing, customer traits, and behavior that made the campaign a success or fail.
With a well managed database, you can build a system that categorizes effective campaigns from the rest.
With such a system, you don’t have to start from scratch every time you want to create a campaign targeting a specific audience group. You just pick from the categorized campaigns and correct errors or improve a campaign by removing or adding specific data points.
Examples of Database Marketing
As highlighted, database marketing comes down to using customer data to achieve a certain marketing objective. Here are specific scenarios in which database marketing shines:
1. Converting abandoned checkouts
Perhaps you run an ecommerce store and customers add items to their cut only to leave without purchasing them. In this case, collect data, including the cart content, customer email and visit time. Then, send them personal emails reminding them about the products and inviting them to make inquiries. You can also offer them discounts to encourage checkouts.
2. Increasing repeat bookings from loyal guests
During the low season, hotel bookings may reduce drastically. Track purchase frequency and average spend from loyal customers. Then, send personalized rewards like an exclusive night on the hotel after a three day stay or a free exclusive drink on every $250 spend. This is likely to increase traffic, spend, and retention.
3. Giving customers a reason to resubscribe
Perhaps you are an ISP and certain customers have not renewed their subscriptions for months. Segment the customers by inactivity time and their package preferences. Then, deliver reactivation emails with a discount incentive. For instance, ‘We miss you Arnold! Come back and claim 20% off your next subscription package.’
Wrapping Up!
Simply put, database marketing is a marketing tactic that involves collecting, cleaning, and storing customer data for analysis to promote services or products. You collect and analyze data including purchase history and frequency to create targeted and personalized marketing campaigns.
Out of the personalized campaigns comes loyalty, increased sales, and more. However, whenever you decide to try out database marketing, ensure you are relevant and respectful. If you are overly intrusive and creepy, you risk pushing current and potential customers away.
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