Get recommendations

SuggestGrid analyzes your users' behaviour and find recommends personalized items for your users, or vice versa.

  • You can use SuggestGrid to display recommended items for your users. Displaying recommended items can help tremedously in user engagement and retention.
  • Say you've a group of users that you want to send a promotional email to them. You can ask SuggestGrid which items would have the greatest overall impression for these users!
  • If you've a new item or a group of items or a campaign, you can use SuggestGrid to target users for these items. This way you can present interesting content to some of your users while not bothering the rest of them.

Find similarities

SuggestGrid figures out which of your users and items are similar to each other.

  • Being able to find which users are similar to each other could benefit your users significantly when they are able to find other likeminded users. Personal connections made in your platform would help you with increasing loyalty.
  • You may promote similar items on item pages for your users. Since they're already visiting an item, they could be more likely to see other items that similar users also visit. You can also use this feature to predict tags or categories for your items.
  • You can combine similarities and recommendations with SuggestGrid! For instance, you may display similar items on item pages that are recommended for the visiting user. This feature could allow you to keep showing different and engaging recommendations while keeping them personalized.

Get started easily

It's a pleasure to getting started with SuggestGrid since so much can be achieved with just a little effort.

  • SuggestGrid is platform independent and our helpful documentations and team will help you as you onboard. SuggestGrid's REST API that can be used from any platform. In addition, there are also Ruby, Node.js, C# .NET, and PHP SDKs, and a specific Heroku Integration are available.
  • Cold Start is a major problem of recommendation engines. Our unique hybrid recommendation engine can work around this issue by making use of content similarities. You can start getting recommendations for users with even no data and starting from the first item they visit, their recommendations will just get better and better.
  • We know the importance of documentations as a developer-first company. SuggestGrid treats ambigous documentation just as bugs. We have worked really hard to create a documentation infrastructure to keep our documentations consistent and updated.
  • Write to us anytime either through in-app chat or email. Want to get on the board easily? Schedule a Skype call with our friendly staff. We promise help you in 24 hours around the clock.

Apply your business logic

With advanced features like filters and fields, subscribing to SuggestGrid is just like having a machine learning team at your service.

  • You can send metadata of your users and items to SuggestGrid and apply filters on these metadata. This feature can be used in many cases, such as recommending items from a single category or users with or without particular tags. You may add any field and apply your constraints of equality, inequality, range and more on them.
  • If you have your metadata on SuggestGrid, you can ask for these fields on your responses as well. This can be used to get around the n+1 Problem. In other words, you can display your recommended content faster with – let's say – names, information, and URLs instead of only getting IDs as recommendations and getting the relevant fields from the database.
  • You can integrate recommended content to almost anywhere if you think out of the box. For instance, you can show recommended content for category navigations instead! With some creativity, you can personalize your application completely, from your homepage to search results. Feel free to contact us for discovering your application's possibilities.

Never worry again

Everything has been taken care of at SuggestGrid to give you peace of mind.

    We take it seriously to keep your data and your dedicated virtual instances safe, and isolated with guaranteed performance. You can forget about SuggestGrid once you set it up with our high availability times and update policies for breaking changes.
    All SuggestGrid data transfers are made over secure HTTPS protocol and authentication keys are managed and monitored carefully. Assets are isolated at network level and everything is backed up. Our infrastructures are deployed inside Virtual private clouds (VPCs) and all network access except our public APIs are blocked.
    With SuggestGrid's intuitive dashboard, you can supervise, and manage your service. You can monitor your data, account details and account activity from your dashboard, all while sipping your morning coffee.
    You can depend on SuggestGrid's scalable service instead of expanding your machine learning team, upgrading your servers and moving on to more scalable technologies as you grow. SuggestGrid's future-proof backend is handling billions of actions today.