According to newly published research from Juniper, RTB -- where advertising inventory is bought and sold on a per-impression basis, via programmatic instantaneous auction -- has now been made accessible and affordable to a wide range of stakeholders by machine learning. The analyst firm says that machine learning promises to transform the RTB segment of the digital advertising market, with algorithms able to predict the success outcome of an impression, and adjust bid amounts dynamically. By way of example, Juniper explains that the fact that the end-user has recently been delivered a similar advert may impact their likelihood of clicking on another and, meanwhile, other behavioural and contextual attributes are used to predict how successful an impression may be on an individual level. "Typical RTB allows the advertiser to target demographics or various population subsets," research author Steffen Sorrell says. "Adding machine learning into the mix effectively allows RTB networks to target the individual. This is a much more powerful tool."