Which resources should we recommend to each prospect?

A prospect's current challenge should determine which resources you recommend. UST had an extensive library of AI expertise, but prospects struggled to identify the material most relevant to their needs. NavigatorAI was developed for UST to guide prospects through tailored questions, identify individual challenges and generate personalised recommendations informed by UST's AI playbook and expertise. Publicly available business and audience data also helped shape each journey.

The practical approach is to ask about the problem a prospect is trying to solve, then connect the responses with relevant expertise rather than offer a standard resource list. Gartner argued in 2025 that recommendations can become irrelevant when buyers move from searching to selecting, because their immediate problem changes. Guided questions should therefore establish current goals and circumstances rather than rely only on inferred preferences.

Personalised recommendations need boundaries: structured rules, trusted content and human oversight. In UST's NavigatorAI, generative AI's flexibility was combined with carefully structured rules and UST's proprietary AI expertise. Recommendations were informed by UST's AI playbook, keeping the experience aligned with the company's services. Human input covered prompt design and optimisation as well as supporting content, while oversight kept the experience accurate and useful.

For a resource recommendation service, use proprietary expertise as the foundation for selection, and treat personalisation as a way to improve relevance rather than simply produce more variation. A 2025 Gartner study covering B2B buyers and consumers in North America, the UK, Australia and New Zealand found that customers experiencing personalisation were 2x more likely to feel overwhelmed by the volume of information received. A personalised selection still needs restraint.