Analytics vs. Insights
Analytics and insights are typically used interchangeably, even though they should not be. Analytics organize and examine data, whereas insights take it further by pinpointing patterns within the analytics.
The charm of personalization is that brands can show their consumers that they are paying attention to what the customers want. Studies show that about 80% of consumers would instead do business with companies that present personalized offers. We can know this information because of insights.
Direct-to-Consumer Brands and Insights-Led Personalization
Business-to-consumer companies have taken the trend of personalization to a new level. Many sales models within these companies have sales offers and personalized recommendations. Along with this, B2C companies have access to higher-quality data.
Brands must take advantage of the data that is provided to them. When used correctly, the data can help maximize profits, build relationships, and increase the customers’ lifetime value.
Understanding Your Customer
Some of the biggest mistakes companies make when trying to incorporate personalization into their marketing materials include not going deep enough with the customization in messaging or making assumptions about their consumers with little supporting data.
Many consumers will experience frustration if they receive offers and promotions that are irrelevant to them and their needs.
Getting Personal with The Right Customer Data
Some main questions marketers should analyze when digging into insights include:
- When did the customer make the most recent purchase?
- Are there times throughout the day when they shop the most?
- How much do consumers typically spend on your brand?
- How can we increase that total amount?
- What can you use to predict the consumer’s future buying behavior?
- Are there specific categories the consumer prefers to shop?
- Does the customer leave items in their cart for long periods? If so, what offers can you send them to help them complete the purchase?
Importance of Eliminating Data Silos
Data silos can be a significant barrier to the success of implementing personalization. Marketing data silos waste resources and need repeated data collection to execute the right campaigns. A few steps to take to work around data silos to optimize personalization include:
- Collect as much data as possible from consumers
- Build buyer persona for each customer
- Organize customers into targeted groups
- Map out a content strategy
- Create multichannel campaigns
- Analyze the success of your campaign by comparing it to results