This master thesis explores if and to what extent a dialogue and recommender system enhances conversion rate in the field of solar contracting. Currently, there is a lack of research on whether a chatbot using in-house enterprise knowledge, which is enriched with Open Data sources, enhances conversion rate in the field of solar contracting. Design Science Research was applied to conduct the results of this master thesis. The mixed method research followed pragmatism with a deductive reasoning approach. A semi-systematic literature review evaluated relevant data sources of the existing body of knowledge. An expert interview and a structured survey acted as the main data collection technique. The evaluation approach consisted of an experiment (A/B Testing) and validation with a Pearson Chi-Square statistical test. A dialogue and recommender system using relevant in-house enterprise knowledge of a company operating in the field of solar contracting was developed. It was found that the artefact enhanced the conversion rate by a factor of approximately 5.3 times and that there is a significant association between implementing the developed artefact and an enhancement of the conversion rate in solar contracting at p = 0.01037. This master thesis fills the research gap as that there is a lack of research on whether a chatbot using in-house enterprise knowledge, which is enriched with Open Data sources, enhances conversion rate in the field of solar contracting, and to what extent such an artefact enhances conversion rate.