Analytics are key to effective marketing campaigns. But, with so much data available, which analytics are the most important to consider?
Here are a few analytics to measure to help create effective marketing campaigns for your business.
1. Location
Location is an important piece of data to consider, especially for businesses with a physical storefront. Pinpointing where customers live and where they spend the most time can help local-based businesses reach their target markets. Location data can also help businesses that rely on tourists or visitors to find them when traveling. Using information from social media check-ins or geotargeting, businesses can display ads or discounts to customers when they’re located nearby.
2. Buying Habits
Learning about a person’s buying habits also helps a business better understand them on a personal level. This may include how often a person purchases certain items or how far they will commute to visit a restaurant or store. Data can also help brands understand how much people are willing to pay for certain services or products.
Buying habits may also include how potential customers find new businesses, how they interact with them, and what makes them convert a sale. This information can help brands increase their revenue and brand awareness.
3. Brand Loyalty
Identifying customers’ loyalty to certain brands can help businesses complete a competitive analysis. Some customers remain loyal to a certain brand, regardless of competitors. Customer data is also useful for businesses to identify existing customers and then develop a strategy to turn them into loyal guests. Not only does this help create a database of people most likely to interact with your business, but studies show that it’s cheaper to retain existing customers than market to new ones.
Brand data can also help businesses learn more about a customer’s preferences. For example, you can pinpoint coffee drinkers by identifying that they restock their coffee pods monthly. You can also learn that certain customers prefer a specific fast-food restaurant over another based on the apps or online ordering websites they frequent the most.
4. Lifecycle
Understanding the lifecycle of a potential customer, including age, marital status, and whether they have young children in the home, can also guide brands in better understanding their market’s buying habits. For example, a children’s clothing store may waste marketing spend by targeting households without children. While displaying your ad in front of a family with young children is an obvious marketing strategy, brands can extend this reach by targeting expectant parents.
5. Engagement Data
Businesses may also collect data on how a person engages with a brand. This helps the business create social media or content marketing strategies that are most likely to get engagements, which further boosts brand awareness. Using cookies, brands can learn what types of websites the potential customer visits most often, including how long they spend on that site and whether or not they interact with them often. With abundant engagement data, it can feel overwhelming to sift through it all. Programmatic ad agencies can help brands pinpoint the data most important to them and then integrate it into an effective marketing campaigns.
6. Birth Date
While a simple data tool, even a customer’s birth date information can offer valuable information to a brand. Recording a person’s birth date allows businesses to target customers based on the buying habits of similar-aged customers. Also known as a look-alike audience, businesses can deduce that a customer born in one year is likely to share somewhat similar buying and shopping habits as another person of the same birth year.
Birth date collections also mean businesses can supply potential customers with coupons around their birthdays. Giving a discounted entree or free item coupon on the person’s birthday encourages them to visit.
7. Employment Information
Brands can even use data related to employment to help create more effective marketing campaigns. For example, business-to-business brands (B2B) can place ads in front of the decision-makers of another business. Big data has already revolutionized many industries, including tax accounting, business technology, customer service, and retail.
8. Hobby Preferences
Learning about a person’s hobby preferences can also help you serve them better, more effective ads. For example, a sporting goods store may use hobby data to serve customers who enjoy golfing, baseball, soccer, or football with related, targeted ads. A person who spends a lot of time traveling may receive effective marketing campaigns for discounted hotel rooms or airfare.
Data helps businesses better understand their current customer base and the customers they want to target. Having a deep understanding of a client base provides customers with more relevant information that can help meet their needs. In return, businesses can optimize their marketing budgets by serving their ads to customers most likely to interact with and use their products.
