When you want to make the most of the customer data at your disposal, which analytics can help you analyze purchase behaviors best? Take a look now.
Retailers are drowning in data. Almost 75 percent of company data goes unused, for many different reasons.
More companies are looking to use their data more effectively. As you probably know, data can be used to predict customer behavior and make better business decisions.
A good example is in trying to increase sales. If you know what influences purchase behaviors, you can take steps to support customer buying decisions.
What indicators should you be looking at when you want to know if someone will buy from you or not? You can take a look at a few of these predictors.
Compare Demographic Information
Sometimes, the best indicator of a customer’s future purchase pattern is in the demographic data. You may be able to predict whether a customer will buy based on their age, their gender, or even where they live.
For B2B customers, indicators include job title and geography.
If you’re trying to predict whether a new lead will buy, you can compare their information to that of your existing customers.
These indicators are always included in propensity modeling. Once you’ve matched a lead to existing customer profiles, you can look at pain points. Then you can identify strategies to make someone even more likely to buy from you.
An example would be matching a lead to the customer profile of “new parent.” New parents are often budget-savvy. Offering discounts may encourage this lead.
Order Values for Predicting Purchase Behaviors
Another factor to look at is the value of a customer’s order. Knowing your average value order (AVO) is an important metric, but it’s just that: an average.
If you want to predict customer spending behavior, you’ll want to look at a few different factors. First, the value of a customer’s first order can actually predict whether they’ll order from you again. The higher the value of that first order, the more likely it is they’ll make a second purchase.
Next, you’ll want to tie increases and decreases in value order to offers you’re running. Does offering a repeat customer a discount incentivize them to buy again or to buy more? Looking at the value of a customer’s order can show you how offers influence buying.
You may also be able to tie these patterns to particular buyer personas. From there, you can segment your customers to make sure everyone gets the right offer.
Pay Attention to Buying Cycles
Another key in any model of buyer behavior is the buying cycle. You need to take into account where the customer is in their buying cycle to be able to predict the likelihood they’ll buy.
Think of someone who just bought a six-months’ supply of contacts. There’s a low likelihood they’ll order contacts again in three months. There’s a very good chance they’ll reorder in six months.
Offering them a deep discount on contact lenses right after they make the purchase doesn’t make sense. Instead, offer complimentary products like contact lens solution now. Then send an automated reminder for them to refill their prescription.
Sales, time of year, and where the customer’s buying cycle will influence whether they buy. Knowing these predictive factors can help you with marketing budgets, Amazon advertising, and more.
Customer Experience Plays a Key Role
Customer experience is a great predictor of buying. Customers who have good experiences will come back. Those who don’t will think about switching providers.
How do you find out about customer experience? A quick survey can give you the insights you need. You can also ask for feedback from leads about your website.
Crunching the Numbers for Growth
Knowing what influences customer purchase behaviors can help you as you prepare your marketing and sales strategies.
Predictive analysis is just one of many uses for Big Data in businesses today. Discover how else to use data to propel your business to the next level.