1. Job Bank
The Employment Service wanted to solve the problem of job seekers using the Job Bank receiving too few job suggestions. They used rek.ai to build an AI model that learned which job categories are related, thereby suggesting search complements to increase the chance of finding a job. The AI model uses all user interactions to train a model with knowledge about job search behavior.
2. Halmstad Municipality
Halmstad Municipality enhances user experience and helps its visitors find the right information faster on its website by recommending pages and e-services to the visitor. The recommendations consider, among other things, the topics the visitor has previously read about on the website.
The use of search term suggestions generated with rek.ai also enhances the personalization of the user experience and leads the visitor more quickly to the right search result.
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3. Länsförsäkringar Real Estate Agency
Länsförsäkringar Real Estate Agency uses rek.ai to recommend properties. Through a 'trained' AI model, they automatically highlight the property listings that will appeal to the visitor.
The factors influencing the recommendation include position, price level, and type of property. The model also understands if a listing becomes 'viral' and can then highlight the listing, which enhances the brand.
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4. Experience Växjö
Växjö helps visitors discover events and places within the municipality by using rek.ai on its tourism website. The model learns what visitors are looking for by training a new AI model every night that considers factors like position and previously shown interests.
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5. Employment Service: Intranet
The Employment Service's intranet is a complex website with a large amount of content. To highlight information for employees, AI is used, trained on user behavior, and can therefore prioritize which support, news, and content pages are most likely to be useful to each employee in a given situation. To ensure the recommendations are of the highest quality, the employee's professional role and previous interests are considered when making the recommendation.
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6. Luleå Municipality
Luleå Municipality uses rek.ai to highlight the subpages and services most likely to be requested by the visitor on both the homepage and overview pages, depending on geographic position, device, visit patterns, etc. The ability to provide these sorted links right from the start enhances the website's usability on more than one level.
The result is fewer people contacting customer service or abandoning their case.
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7. Recommend Further Reading at Skellefteå Municipality
By recommending additional reading after a news item, Skellefteå helps its visitors discover new material and be inspired for further reading. The news recommended is selected by rek.ai based on all the parameters the AI model considers.
The result is that all the material editors produce reaches the website visitors.
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