Conversion mechanics
Conversion mechanics is about mathematically understanding the factors that are involved when someone converts and the relationship between those factors. These factors are the forces that influence the visitor's decision. Some of them increase the chance of a purchase, while others decrease it. There are four main factors involved in any visitor's decision to convert:
- The baseline purchase probability is the initial chance that the visitor will purchase on any given visit. This is closely connected with the type of visit. Someone who is just browsing is much less likely to purchase than someone who has come to the store with the specific intention of purchasing. Baseline purchase probability is also affected by the cost of the product and shipping costs. Dollar-for-dollar shipping costs have a greater negative impact than the product's price. Previous purchase experiences also affect the baseline purchase probability.
- The visit effect represents the impact visiting the site has on the decision to purchase. Positive visit effects, such as clear images, increase the chance of a sale, while negative visit effects, such as poor navigation, decrease the chance of a sale. Not only does each visit have its own effect, multiple visits create an accumulated effect.
- The purchase effect refers to the experience the shopper had after previous purchases. Purchasing effects can have a positive or negative impact. For example, failing to deliver the product severely reduces the chance of a repeat purchase, whereas swift delivery increases the chance.
- The purchase threshold represents the customer's resistance to purchasing. Once the combined conversion effects listed above exceed the purchase threshold, the visitor decides to purchase.
These factors can influence each other in different ways. Which factors are most important -- and their relative weights -- change according to the type of visit. The impact of these effects also changes over time, so it is important to understand not just how these factors are working now, but what they have been in the past and, most important of all, what trends indicate about the future.
