One product, lots of features

Here’s what Rumo comes help you with:

PERSONALIZED RECOMMENDATION

Understand what moves
your users

R

Recommend content based on users’ tastes.

R

Provide tailor made recommendations thanks to our user semantic profile. 

R

Easily visualize your users’ tastes and interests to adjust recommendations.

SIMILAR CONTENT RECOMMENDATION

Get instant recommendations and avoid cold start issues

R

Make links between content items based on metadata.

R

Access a list of recommendations that would be displayed for a given content item.

CATALOGUE

Easily visualize and navigate your catalogue

R

Get access to a detailed overview of each content piece with all information and adjustable metrics.

R

See in the blink of an eye which data is being used and customize tags for content pieces.

R

Adjust weights to customize the recommendation process to your liking.

TOOLBOX

Fine-tune recommendations according to your business needs for better editorial control

R

Adjusting categories weight globally.

R

Push content you want to make sure gets seen.

R

Filtering out “Déjà vu” items that users already interacted with at will.

More toolbox on the way! Check out our Roadmap.

ANALYTICS

Get metrics you can leverage

R

Understand your users behaviour and preferences. 

R

Anticipate trends and make informed decisions thanks to useful KPIs.

Any further questions?

Feel free to contact our team, we’ll be glad to help you out.

Frequently Asked Questions

Are you doing the metadata enrichment? Who does ?

We provide two alternatives :

  • Rumo offers the possibility to add plug-ins such as Gracenote’s for example. It provides metadata directly to your catalog.
  • Homemade enrichment done by our editorial team from Spideo. However, it must be films or videos, as this is their field of activity.
Can Rumo work with any type of content?

As long as it’s possible for you to create metadata for your content, Rumo can operate with it.

How does Rumo help me understand my users?

Rumo provides this information through two tools:

  • Analytics, which displays data on user interactions.
  • The USF (User Semantic Profile), which is a tool for visualizing user tastes.
On what personalized recommendations are based?

Personalized recommendations are based on the semantic profile. It is computed from all user interactions with your catalog.