Model user behavior
Model user behavior
1. Analyze the buying history of your customers. Look at data points like purchase date, number of items purchased, type of items purchased, discount codes, and purchase frequency.
You can also look for trends in responses and reactions to your previous marketing campaigns, e.g. did your younger customers respond to your social media campaign but cause your email open rates to drop?
2. Segment users into groups that represent traits such as buying history, demographics, and responsiveness.
For example, you may find that frequent purchasers of one item are 30-40 year olds from the Northeast who are active on Instagram. Knowing this will allow you to focus on engaging your current customer base and marketing to new customers for that product via Instagram.
3. Within each segment, track the customers and identify those with the most important shared characteristics.
These could be customers who buy specific items every week or those who make large purchases every year two weeks before Christmas. This segmentation will allow you to reach those customers with hyper-targeted ad campaigns that run at the optimal times of the month or year.
4. Calculate your Customer Lifetime Value by multiplying the average purchase value by the average purchase frequency for the same timeframe, then multiplying the result by the average customer lifespan.
CLV = Av purchase value * Av purchase frequency * Av customer lifespan Your Customer Lifetime Value is the amount of revenue that you can expect to get from one customer throughout the entire course of your relationship. Knowing this number will help you understand how much you should spend to acquire a particular customer.
5. Find patterns in the data to predict future behavior.
Predicting future behavior means that you will be able to anticipate customer shifts and changes and adapt your products or offerings to suit customer needs. This could mean releasing an updated model of one product and discontinuing production of another entirely, which equals increased revenue and ROI.