Years ago, every library in America had a paper based, card catalog system that organized books and helped readers find them. Early internet search engines were merely electronic versions of their library counterparts of yesteryear, in that they simply just located information on the web and presented it to users.
However, as the evolution of the internet and online shopping exploded, search engines have become increasingly more sophisticated in what they can offer to both online retailers and customers.
The concept of Average Revenue Per Customer (ARPC) is not new in the world of retail. This method of measurement has served for years in the brick and mortar world as a very accurate way to determine what the average revenue per customer is worth to a business. Modern search engines can be great tools to help ecommerce businesses maximize ARPC.
In part 1 of this 2 part blog series on ARPC, we will look at effective ways to utilize your site search tool to increase/improve ARPC.
Personalizing The Search Experience for Every Visitor
There is a no doubt that any business with a loyal customer base has figured out what it takes to make every person feel special. It’s a great feeling to go into your favorite restaurant or coffee shop and be greeted with a friendly smile as the server starts preparing your “usual”. Successful ecommerce needs to achieve this same level of business rapport with their customers, but it can be more challenging on the web. But we know one thing – as much as technology evolves, human nature stays the same. People are attracted to and will purchase products that speak to them as individuals. If ecommerce transactions don’t have the same face to face contact with customers as brick and mortar businesses do, how do we achieve that same level of rapport?
The good news is that search engines today now give online sellers a competitive edge by providing them with specific ways to personalize a visitor’s search experience. Marketing strategies such as visitor targeting can customize search results to show products that are selected based on known information about individuals such as demographics, gender, zip code and prior purchases. Utilizing this information can greatly increase conversion rates.
Utilizing Machine Learning
Some people think that the term machine learning refers to out of control robots that take over the world. Thankfully this is not the case. Machine learning is the technology that enables computers to make predictions about what shoppers would be most likely to purchase. Most search engines that utilize machine learning to improve search personalization quality also have onboard a product recommendation tool. These tools rely upon machine learning to analyze what customers have recently purchased, which products are placed in carts and what other customers have viewed or bought.
Using the information from the machine learning functionality, the recommendations tool chooses the best products to display to shoppers. Ultimately, making selling suggestions based on real customer data can lead to increased sales and ARPC.
In Part 2 of this blog series, we will discuss some other powerful methods by which a search engine can be utilized to raise ARPC.