Apps

We built the Wuntu app for Three UK, which for most of its 3 year lifespan was the UK's second most widely used Offers and Rewards App.

Relevancy

Machine Learning can optimize customer engagement and loyalty programs by helping target the right offers and rewards to the right users, recommendation engines already power the world's top retail and streaming websites and apps, by leveraging the power of out of the box or bespoke recommendation engines to improve user engagement in your app or portal, we can help guide you to the correct solution for you. Recommendation engines use machine learning to model user behaviour and preferences to recommend relevant content, products, or services. By integrating recommendation engines into their platforms, companies have seen significant improvements in user engagement, customer satisfaction, and ultimately, revenue. For businesses looking to implement recommendation engines into their own apps or portals, there are two main options: out-of-the-box solutions and bespoke development. Out-of-the-box solutions offer pre-built recommendation engines that can be easily integrated into existing platforms, providing a cost-effective and efficient way to leverage the technology. However, these solutions may not offer the level of customization desired by some businesses. Bespoke recommendation engines, on the other hand, are tailored to meet the specific needs and goals of each individual business. While they require more time and resources to develop, they offer greater flexibility and control over the recommendation logic and user experience. Our team of experienced software consultants can help guide you in selecting the best option for your unique requirements and objectives. By implementing either an out-of-the-box or bespoke recommendation engine, businesses can enjoy numerous benefits, including:

• • Increased user engagement: Personalized offers and rewards encourage users to spend more time interacting with the app or portal, leading to higher engagement rates.
• • Improved customer satisfaction: Users receive relevant and appealing content, products, or services, enhancing their overall experience and building trust in the brand.
• • Enhanced loyalty: Targeted offers and rewards foster a sense of loyalty among users, encouraging them to continue using the platform and share their positive experiences with others.
• • Boosted conversions: Recommendation engines can lead to increased sales, sign-ups, or other desired actions, as users are exposed to targeted content that resonates with their interests.
• • Better data insights: By analysing user behaviour and preferences, businesses gain valuable insights into their audience's needs and preferences, allowing for data-driven decision making and strategic improvements.