In online marketing, statistical twins are users whose behaviour is similar to that of already converted users (i.e. users who have already bought). Marketers hope that due to their similarity to existing customers they are more likely to make a purchase.
Statistical twins can consider different characteristics depending on the objective. Typical characteristics are, for example:
- Buying behavior
- Surfing behavior
- Category behavior
- Product behavior
- Source of origin / click-in channel of the user
- Time and geodata
- and much more
These user groups, similar to existing customers, can be used to optimize the onsite conversion rate by displaying personalized content, such as improved product suggestions, to users.
Statistical twins can also be used offsite to extend the user’s reach in the relevant target group. Social media, for example, analyzes the characteristics of the buyers in the shop. Once they have found users who are similar to them, they apply suitable advertising measures and lead them to the advertiser’s site.