Big data is one of the biggest buzzwords in marketing today. It allows marketers to leverage high-quality and diverse data points to drive their decision-making efforts with regard to traffic, affiliates, and other facets of their business’s operations.
According to Forbes, the big data revolution actually extends back to 1944, but it’s become far more relevant to current marketers and entrepreneurs. Whether you’ve used an affiliate program for the last decade or are relatively new to the concept, you can use big data to improve your affiliate sales and drive more conversions for your product or service.
When your affiliate marketers generate a click that goes to your website, they earn a commission on the sale or a flat rate. However, you use cookies to determine how long the consumer has to close the sale. Big data can help you optimize that time limit so your affiliates generate the income they actually earn and you don’t lose money on duplicate commissions.
Let’s say, for example, that a consumer visits an affiliate’s site, clicks on the link, and lands on your website. They read your landing page information, consider the purchase, and decide they want your product.
Depending on the product, they might consider the purchase for five minutes and click the “buy button.” More expensive products and products that have significant competition might generate longer lead times. Consumers might visit consumer reporting websites to compare reviews of your product against those of competitors’ products, for example.
The key to optimizing time limits lies in consumer behavior patterns. Analyzing big data sets might reveal that consumers in your industry spend an average of 15 minutes when making a buying decision. This knowledge allows you to set your cookie time limits based on empirical data rather than a rough guess.
In every industry, consumers behave differently depending on the product or service offered, the competitive landscape, and other environmental and practical factors. According to Emarsys, a B2C marketing agency and software development firm, the consumer life cycle includes several stages: prospect, initial purchaser, repeat purchaser, premium consumer, and inactive customer.
Knowing the life cycle stages of affiliate traffic customers can help you improve your overall sales. For example, repeat customers might stumble upon your product through an affiliate website, remember your product, and click directly over to your website.
If you’re reaching repeat customers, you don’t need to supply a hard pitch on your landing page or provide them with the bare-bones data about your product. Instead, you want to entice them by reminding them why they liked your product in the first place.
To verify and understand the consumer life cycles of your affiliate sales, you’ll need big data metrics. By processing large amounts of data and investigating the patterns, you can direct the behaviors of your affiliates and better serve your end users.
Many business owners assume that it doesn’t matter where their traffic comes from as long as they are producing sales. However, if you don’t know which affiliates drive the most traffic to your site, you miss a tremendous opportunity to understand your customers’ journeys.
Big data allows you to analyze your customers’ buying patterns from their point-of-entry (the affiliate’s site) to the buy button.
If you do not have the technological infrastructure or capital to leverage big data for your business, you can always rely on research from other sources. Companies like Forrester Research frequently publish big data statistics and conclusions that can help businesses manage their affiliate programs more effectively. However, it’s important to note that web-based big data analytical tools have become far more cost-effective, which makes them accessible even to small businesses.
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