Providing context behind customer feedback remains a challenge for company’s who rely on approaching Customer Experience (CX) through standardized Customer Satisfaction (CS) metrics like Net Promoter Score (NPS), Customer Satisfaction Score (CSAT), and Customer Effort Score (CES). Practical guidelines for monitoring CS throughout the customer journey are limited, creating a gap in academic research. This study addresses this gap by offering practical guidelines for CS, actionable insights, and alternative survey design strategies within the context of invoicing. Utilizing a Research-through-Design (RtD) approach guided by the Double Diamond design model, the study consists of four phases: Discover, Define, Develop, and Deliver. From a service design perspective using qualitative methods, the study acquires and analyzes both organizational and customer insights. Synthesized empirical findings emphasize the need for a more comprehensive approach that targets specific phases of the customer journey utilizing a more customer- centric approach, paving the way for alternative methods that reaches beyond just simply measuring CS. Introducing the concept of a personal companion, the study presents a dialogical approach where surveys are experienced as ongoing interactions rather mere tasks. By highlighting the importance of contextualization, alternative survey approaches, and a dialogical approach, this research aims to guide company’s in managing customer feedback strategies.

<p>Current watershed-scale, nonpoint source (NPS) pollution models do not represent the processes and impacts of agricultural best management practices (BMP) on water quality with sufficient detail. To begin addressing this gap, a novel process-based, watershed-scale, water quality model (WEPP-WQ) was developed based on the Water Erosion Prediction Project (WEPP) and the Soil and Water Assessment Tool (SWAT) models. The proposed model was validated at both hillslope and watershed scales for runoff, sediment, and both soluble and particulate forms of nitrogen and phosphorus. WEPP-WQ is now one of only two models which simulates BMP impacts on water quality in ‘high’ detail, and it is the only one not based on USLE sediment predictions. Model validations indicated that particulate nutrient predictions were better than soluble nutrient predictions for both nitrogen and phosphorus. Predictions of uniform conditions outperformed nonuniform conditions, and calibrated model simulations performed better than uncalibrated model simulations. Applications of these kinds of models in real-world, historical simulations are often limited by a lack of field-scale agricultural management inputs. Therefore, a prototype tool was developed to derive management inputs for hydrologic models from remotely sensed imagery at field-scale resolution. At present, only predictions of crop, cover crop, and tillage practice inference are supported and were validated at annual and average annual time intervals based on data availability for the various management endpoints. Extraction model training and validation were substantially limited by relatively small field areas in the observed management dataset. Both of these efforts contribute to computational modeling research and applications pertaining to agricultural systems and their impacts on the environment.</p>