TAIGER Recommendation Engine Vision Paper
TAIGER Recommend: Grow your enterprise through personalised customer experiences
Companies today are going beyond pushing personalised content, which must no longer just be issued at the perfect time and place, but preempt customers’ needs before they even realise them. Top guns like Amazon and Netflix are succeeding in driving exponential growth, productivity and customer satisfaction with this tactic. Their secret? With recommendation engines.
According to McKinsey, 35% of Amazon’s purchases and 75% of Netflix’s viewings are made through recommendations.
Recommendation engines empower companies to glean insights into their customer behaviours and intentions systematically. Yet, in many industry solutions, the intelligence behind providing recommendations that transcend simple search falls short of clients’ needs. Even companies that have adopted these engines struggle with the cumbersome and costly endeavour of manually hard coding rules to refine their recommendations for customers. In our TAIGER Recommendation Engine Vision Paper, we unpack the mechanics of our personalisation engine – TAIGER Recommend, including:
- Why you need to be adopting recommendation engines
- How TAIGER Recommend works
- Advantages of TAIGER Recommend
- Limitations of Industry Solutions
- Use cases to value add to your organization
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