4 ways to use recommendation engines in your business

By: Ancoris says
Tag(s): Data
Published: Feb 15, 2021
4 ways to use recommendation engines in your business

A recommendation engine is a system that allows you to provide a hyper-personalised experience to users. For users, it’s a bit like having an appointment with a personal shopper in a department store or asking the advice of a friend sitting on the sofa next to them when they’re wondering what to watch next on TV. For businesses, recommendation engines are a way to increase “stickiness” and “engagement” — how much, how long and how deeply someone interacts with you — and to boost revenues.Here are 4 examples of how businesses can use recommendation engines:

1. Increase revenues and shift slow-moving inventory on e-commerce sites

Recommendation engines can show users the items that best match the current need they’re trying to satisfy but also show them alternative products they may not have considered, as well as related products they might want to add to their basket. The power of recommendation engines in e-commerce is demonstrated by the fact that as much as 35% of Amazon’s sales are generated by its recommendation engine.

2. Reduce customer churn and increase ad revenues on media streaming sites

Services like Netflix keep users watching — and prevent them defecting to other services like Amazon Prime — by making sure users are aware of other content on the site that they’ll enjoy. If the site includes adverts — perhaps as the price of using the service for “free” rather than paying for a subscription — getting users to watch more content will also increase the number of times adverts are viewed and how much advertisers can be charged. According to research published in 2015, Netflix estimates it saves $1 billion a year by using its recommendation engine to reduce subscriber churn.

3. Improve the user experience and reduce friction for users of media streaming site

Music apps like Pandora and Spotify use recommendation engines to automatically build playlists for users that they’ll enjoy. Users no longer need to buy specific tracks, load them to their device and then choose what to play. Instead, they just open the app, choose a track they know matches the mood they’re looking for — whether they’re looking to chill out or pound the treadmill at the gym — and can start listening to a relevant selection of tracks that also takes into account their general listening preferences. Typically, playlists include a mix of old favourites and music they haven’t listened to before, making it easier for users to discover new artists and tracks well.

4. Increase engagement on social media platforms

Social media sites thrive when users come back, stay longer, and interact more, whether by creating their own content or liking, replying to and sharing content created by others. Showing users personalised feeds or timelines that contain more of they kind of content they’re interested in means they’re more likely to visit, stay longer and get involved in the conversation.

The point is well illustrated by Ancoris customer Play Sports Network, the world’s largest cycling media company and community, reaching and engaging with more than 40 million cycling fans and riders around the world.

To complement Play Sports’ series of YouTube channels, the company provides a mobile app called GCN, a social media platform for cyclists, allowing like-minded cycling enthusiasts to upload, share, comment on and consume content. Even within this fairly specialised community, you’ll find a variety of interests. Some people want to know all about the latest in cycling technology; others are weekend riders who just want to get out on their bikes on Sunday mornings; and there are even people who don’t cycle at all but follow professional road racing events like the Tour de France. Using a recommendation engine, Play Sports ensures each user sees the content they’re most interested in as soon as they log in — keeping them coming back day after day and helping drive engagement with Play Sports’ other brands.

If you think a recommendation engine could help your organisation meet its business goals, why not come and talk to the experts in our Data Analytics team about your options and how we can help.

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