INSUBCONTINENT EXCLUSIVE:
importantly buy or consume)
That kind of personalisation has become a goal not just for e-commerce companies, but for any organization running a digital business: users
are constantly distracted, and when their attention is caught, they do not want to spend time figuring out what they most want.Not every
business is Amazon, though, so we are seeing a crop of startups emerging that are working on ways to help the rest of the digital world be
just as optimised and personalised as Amazon
Now one of them, an Israeli startup called Dynamic Yield, has raised more money as it continues to expand its business, both to more
The plan is for Naver to help bring Dynamic Yield to Korea and Japan, by incorporating its tech into its own services and those of others
that work with Naver.(Personalisation and aggregators are strong magnets for users in Asia and thus big magnets for funding: ByteDance,
which provides news aggregation among other services, was recently valued at $75 billion.)Naver is not the only search engine that has
caught sight of Dynamic Yield over the years
Venture Partners, Marker Capital and more
Agmon said.But they include a number of big brands across e-commerce, travel, finance, media and other segments that use its tech not just
to show more targeted products to prospective shoppers, but to help power advertising, recommend content and position the same information
to different people in different ways depending on who is viewing it (for example with different headlines).There are a lot of
intrinsically linked to its own marketplace (because some will never want to sell there, and because personalisation can be used for so much
more than just e-commerce).Dynamic Yield, however, claims that it has an edge over these because of how it works.Agmon says that the tech
sits on top of whichever CMS or other backend server that a site is using and is activated by way of a small amount of code
experience.Agmon added that when a business already has information about that visitor, that is the primary data that is used; otherwise it
your tastes.It then runs this data through its own machine learning algorithms both to recommend content and to help a marketing manager
figure out better customer segmentation overall
sources to set up specific marketing campaigns; or (as is common) a combination of the two.Going forward, Agmon said the plan is to work
across an increasing number of interfaces where customers are going today to discover and buy goods and services
personalisation startups like Dynamic Yield.Agmon said that his company is also working with a major retailer that is using its tech at its
order will now know if the customer ever orders a sweet injection, or if she/he is more of a savoury snack sort of person
The cashier will then know what to recommend to eat with that drink that is more likely to be purchased.The mom-and-pop shop with its
reputation for knowing the regulars and what they like might have found its dystopian (but useful) heir.
