Customer Need Research Articles

Two-stage deep learning framework for occlusal crown depth image generation

The generation of depth images of occlusal dental crowns is complicated by the need for customization in each case. To decrease the workload of skilled dental technicians, various computer vision models have been used to generate realistic occlusal crown depth images with definite crown surface structures that can ultimately be reconstructed to three-dimensional crowns and directly used in patient treatment. However, it has remained difficult to generate images of the structure of dental crowns in a fluid position using computer vision models. In this paper, we propose a two-stage model for generating depth images of occlusal crowns in diverse positions. The model is divided into two parts: segmentation and inpainting to obtain both shape and surface structure accuracy. The segmentation network focuses on the position and size of the crowns, which allows the model to adapt to diverse targets. The inpainting network based on a GAN generates curved structures of the crown surfaces based on the target jaw image and a binary mask made by the segmentation network. The performance of the model is evaluated via quantitative metrics for the area detection and pixel-value metrics. Compared to the baseline model, the proposed method reduced the MSE score from 0.007001 to 0.002618 and increased DICE score from 0.9333 to 0.9648. It indicates that the model showed better performance in terms of the binary mask from the addition of the segmentation network and the internal structure through the use of inpainting networks. Also, the results demonstrated an improved ability of the proposed model to restore realistic details compared to other models.

Statistical models and implant customization in hip arthroplasty: Seeking patient satisfaction through design

ObjectivesThis study conducts a systematic literature review to explore the role of statistical models and methods in the design of orthopedic implants, with a specific focus on hip arthroplasty. Through a comprehensive analysis of the scientific literature, it aims to understand the relevance and applicability of these models in implant development and research trends in the field of design. MethodsData analysis and co-occurrence mapping techniques were employed to investigate the statistical models used as predictors of satisfaction in hip arthroplasty and in implant design. This approach facilitated a detailed and objective assessment of existing literature, revealing key trends and identifying gaps in current knowledge. Key findingsThe review's findings underscore a burgeoning interest in implant customization, with a significant emphasis on leveraging statistical techniques for optimal design. The logistic model methodology was applied to analyze a survey of hip surgery specialists, revealing that the physician's age does not influence the decision to use a customized implant. Furthermore, the review highlighted a knowledge gap at the intersection of statistics and design discipline concerning implant customization. SignificanceDespite the recognized importance of customization in implant design, there remains a dearth of contributions from the design discipline perspective in the existing literature, indicating substantial room for improvement and the need for interdisciplinary integration. ConclusionThe integration of statistical methods in implant design is crucial, emphasizing the need for multidisciplinary approaches and customization to enhance patient satisfaction. This study provides a foundation for future research that could transform the field of hip arthroplasty through more personalized and effective solutions.

Augmented Reality and Virtual Reality: A New Way of Seeing the World

Technologies such as (AR) Augmented Reality &(VR) Virtual Reality, which provide immersive digital experiences, interactive environments, simulation, and engagement, have completely changed how we approach learning. However, in order to meet the huge demand in education, these technologies which are still in the emerging stage need to be heavily customized and heavily invested in. This thorough analysis seeks to contextualize the last few years of development of Virtual and Augmented Reality in the Education. For additional study, a total one thousand five hundred and thirty-six articles are chosen using text mining and theme analysis techniques. Based on earlier research on AR and VR in education, hypotheses were developed and are currently being processed and analysed to reveal the current development in literature via Augmented Reality and Virtual Reality, applications, benefits, and future directions. The findings show that wearable technology has contributed significantly to the exponential expansion in the use of Virtual and Augmented Reality in education in recent years. Results also highlight the need for faster adoption and customization of these technologies in educational institutions, based on secondary data. An increasing number of educational applications for the learning process are emerging as Virtual and Augmented Realityexp and quickly. It is advised that researchers stay up to date on the gaps in AR and VR’s Changeover to education &develop practical adaptation strategies to maximize the benefits of these technological development with significant developments in high-speed transmission and processing, AR &VR are developing as Display Platforms for Next Generation for more intimate human-digital interactions. Nonetheless, matching the extraordinary Human Vision Performance while keeping Near the Eye Display module tiny and lightweight presents unprecedented hurdles for optical engineering. Fortunately, new advances in Holographic Optical Elements HOEs and Lithography Enable Devices present novel approaches to overcoming these challenges in Virtual and Augmented Reality which would otherwise be problematic with traditional optics

An Investigation of Globe Temperature in Street Canyons: A Scaled Model Study Implementing Cool Materials

The measurement of globe temperature (GT) is essential for investigating pedestrian thermal comfort in street canyons. The globe thermometer is the most common instrument used to measure GT; however, its application in scale models has not been thoroughly investigated to date. Therefore, this study explicitly investigates globe thermometer measurements in scale models and analyzes the need for customization of the globe thermometer for more reliable measurements. Scaling down with respect to the size of the globe thermometer and the effect of solar orientation/envelope materials are investigated in this study. The initial experiments were carried out in an outdoor setting using a typical street canyon model (scale 1:100) with an east-west street orientation. The results of the experiment are presented to compare a low solar reflectance street canyon (albedo of 0.4) and a high solar reflectance canyon (albedo of 0.6) in terms of surface temperatures, heat flux, and globe temperature. It is observed that although the wall and road surface temperatures are lower for the high solar reflectance canyon compared to those for the low solar reflectance canyon, the GT (measured at pedestrian height) is higher in a high reflectance canyon during the daytime, which could be due to the combined effect of direct radiation and short-wave reflection. However, for the hours after sunset, a reverse effect is observed, i.e., the GT becomes lower (up to 0.8 °C) in the case of a high reflectance canyon compared to that for the low reflectance canyon. Furthermore, the study emphasizes the impact of solar reflectance of canyon surfaces on GT values, due to the view factors that the globe thermometer on those surfaces.

Predictive modelling of Immunogenicity to Botulinumtoxin A Treatments for Glabellar Lines.

Botulinum toxin A (BoNT-A), derived from Clostridium botulinum, is widely used in medical and aesthetic treatments. Its clinical application extends from managing chronic conditions like cervical dystonia and migraine to reducing facial wrinkles. Despite its efficacy, a significant challenge associated with BoNT-A therapy is immunogenicity, where the immune system produces neutralising antibodies (NAbs) against BoNT-A, reducing its effectiveness over time. This issue is critical for patients requiring repeated treatments. The study aims to compare FDA-approved BoNT-A products, examining the factors influencing NAbs development using advanced machine learning techniques. This research analysed data from randomised controlled trials (RCTs) involving five main BoNT-A products. The study selected trials based on detailed immunogenic responses to these treatments, particularly for glabellar lines. Machine learning models, including logistic regression, random forest classifiers, and Bayesian logistic regression, were employed to assess how treatment specifics and BoNT-A product types affect the development of NAbs. Analysis of 14 studies with 8,190 participants revealed that dosage and treatment frequency are key factors influencing the risk of NAbs development. Among BoNT-A products, IncobotulinumtoxinA shows the lowest, and AbobotulinumtoxinA the highest likelihood of inducing NAbs. The study's machine learning and logistic regression findings indicated that treatment planning must consider these variables to minimise immunogenicity. The study underscores the importance of understanding BoNT-A immunogenicity in clinical practice. By identifying the main predictors of NAbs development and differentiating the immunogenic potential of BoNT-A products, the research provides insights for clinicians in optimising treatment strategies. It highlights the need for careful treatment customisation to reduce immunogenic risks, advocating for further research into the mechanisms of BoNT-A immunogenicity.

Enhancing Anti-Cancer Immune Response by Acidosis-Sensitive Nanobody Display.

One of the main challenges with many cancer immunotherapies is that biomarkers are needed for targeting. These biomarkers are often associated with tumors but are not specific to a particular tumor and can lead to damage in healthy tissues, resistance to treatment, or the need for customization for different types of cancer due to variations in targets. A promising alternative approach is to target the acidic microenvironment found in most solid tumor types. This can be achieved using the pH (Low) Insertion Peptide (pHLIP), which inserts selectively into cell membranes under acidic conditions, sparing healthy tissues. pHLIP has shown potential for imaging, drug delivery, and surface display. For instance, we previously used pHLIP to display epitopes on the surfaces of cancer cells, enabling antibody-mediated immune cell recruitment and selective killing of cancer cells. In this study, we further explored this concept by directly fusing an anti-CD16 nanobody, which activates natural killer (NK) cells, to pHLIP, eliminating the need for antibody recruitment. Our results demonstrated the insertion of pH-sensitive agents into cancer cells, activation of the CD16 receptor on effector cells, and successful targeting and destruction of cancer cells by high-affinity CD16+ NK cells in two cancer cell lines.

Impact of Chatbots on Satisfaction and Loyalty in Lima's Telecom Sector

The migration towards digital environments has transformed the expectations of consumers, who now not only look for quality products and services, but also convenience, personalization and efficiency in each interaction with the brand. This change presents significant challenges for companies, as they need to constantly adapt to meet their needs and thus maintain loyalty in a highly competitive market. The pressure to offer added value and maintain customer preference is intensified by the ease with which consumers switch to competitors. which drives companies to innovate and adapt AI such as chatbots, which could be the answer to this challenge. The objective of this research work is to know if the use of chatbots positively influences the satisfaction and perceived loyalty of consumers of telephone services, since in this case the speed, quality of the service and the customer's need for understanding. They are critical and represent a greater challenge to differentiate. The methodology used for this research maintains a quantitative, correlational, non-experimental approach. The type of sampling was non-probabilistic, and the strategy was snowball. The instrument used was a questionnaire with a sample of around 130 consumers in the city of Metropolitan Lima in Peru. The findings suggest that chatbots are not only innovative tools, but also strategic ones for telephone companies seeking to improve customer satisfaction and loyalty. The implementation of appropriate chatbots can transform the customer experience, providing a more agile, personalized and effective service, thus seeing a close relationship between the dimensions of the chatbot with the satisfaction and loyalty perceived in consumers. In a world where these variables are key to business survival, chatbots represent an opportunity to create exceptional experiences. Uncover how cutting-edge AI chatbots are revolutionising customer satisfaction and loyalty in the competitive telephone service industry, offering transformative, personalised, and efficient interactions.

Comparative kinematic analysis of high-speed treadmill vs. overground sprinting across athletic levels and sex.

This investigation aimed to dissect the kinematic differences in sprinting between high-speed treadmill and overground conditions, examining how these variations are influenced by the athlete's training status and biological sex. A total of 40 participants, 20 NCAA Division 1 sprinters and 20 recreational runners, performed a series of maximal sprints on a high-speed treadmill and on a standardized competition overground track. Sprinting kinematic variables such as stride length, stride frequency, contact time, and flight time were collected via photoelectric sensors. Maximal sprinting kinematics were analyzed by linear mixed-effects models, considering the impacts of sprinting environment (treadmill vs. overground), training level, and sex, with leg length as fixed factors and individual athletes as random effects. Statistical significance was set at a significance level of 0.05. The statistical analysis revealed that high-speed treadmill sprinting significantly affects all measured kinematic variables, leading to increased stride frequency and contact time. Elite sprinters demonstrated enhanced kinematic efficiency over recreational runners, characterized by increased stride length and frequency and reduced contact time. Sex-based kinematic distinctions also emerged, with male athletes exhibiting superior stride length and frequency compared to female athletes. Leg length significantly influenced stride frequency, and an interaction effect was observed for flight time between sprint type and athletic group. These findings elucidate the distinct biomechanical profiles across sprinting modalities and athlete demographics, emphasizing the need for sprint training customization. This study's insights offer a valuable reference for coaches and athletes to refine training and performance assessment in varied sprinting environments.

Business Intelligence in E-Commerce

Now a days online shopping has become popular and E-commerce are a usual concept. However, companies still have little knowledge about their customers. It is important to merge e-commerce with business intelligence, because this would enable to obtain knowledge about e-commerce platforms, customers, discovering purchasing patterns, better financial performance and so on. Now a days it became more important to know the need and preference of customers and provide the required products to them. This paper provides a review on how business intelligence helps in the development of E-commerce and helps the businessmen to take decisions about their products.

Prediction of future customer needs using machine learning across multiple product categories.

In recent years, computational approaches for extracting customer needs from user generated content have been proposed. However, there is a lack of studies that focus on extracting unmet needs for future popular products. Therefore, this study presents a supervised keyphrase classification model which predicts needs that will become popular in real products in the marketplace. To do this, we utilize Trending Customer Needs (TCN)-a monthly dataset of trending keyphrase customer needs occurring in new products during 2011-2021 across multiple categories of Consumer Packaged Goods e.g. toothpaste, eyeliner, beer, etc. We are the first study to use this specific dataset and employ it by training a time series algorithm to learn the relationship between features we generate for each candidate keyphrase on Reddit to the ones in the dataset 1-3 years in the future. We show that our approach outperforms a baseline in the literature and through Multi-Task Learning can accurately predict needs for a category it wasn't trained on e.g. train on toothpaste, cereal, and beer products yet still predict for shampoo products. The findings from this research could provide many advantages to businesses such as gaining early access into markets.

Prototype strategy, market big data and identification of latent customer needs: an organizational learning perspective

PurposeAlthough the literature provides insights into the role of experiential learning based on prototypes in identification of latent customer need, it offers different views on the role of product prototypes in improving the efficacy of learning customer need, and also neglects the role of vicarious learning in prototype-based experiential learning. In a data-rich environment, market big data create new opportunities to learn from vicarious, digitalized experiences that are not observable with prototype-based learning. Therefore, the purpose of this study is to compare the effects of product prototype strategies – basic prototype strategy and enhanced prototype strategy – on identification of latent customer needs, and determine how each prototype strategy interacts with vicarious learning based on market big data to identify latent customer needs.Design/methodology/approachWe collected data from 299 Chinese manufacturing firms via on-site surveys to explore our research question. All of our hypotheses were supported by the regression results.FindingsThis study finds that both the enhanced and basic prototype strategies (experiential learning from direct market experience based on prototyping) have positive effects on latent need identification, but the effect of enhanced prototypes is stronger. Furthermore, the enhanced and basic prototype strategies have different interaction effects with market big data (vicarious learning from indirect market experiences) on latent need identification.Originality/valueThis research extends the literature on prototype-based learning for latent need identification. It also contributes to the experiential prototype-based learning literature by exploring the role of vicarious learning based on market big data.

Catering to Luxury Chinese Tourists Demand: Insights from Malaysian Inbound Travel Agencies

ABSTRACT The shift toward luxury tourism has engendered a new class of high-end Chinese tourists, presenting significant opportunities for generating substantial revenue through premium tourism products and services. This study specifically explores Malaysian inbound travel agencies’ perceptions, preparedness, and challenges in attracting luxury Chinese tourists. Through qualitative interviews and thematic analysis, this study delves into nine Malaysian inbound travel agencies’ perspectives on attracting luxury Chinese tourists. The qualitative findings reveal distinct characteristics and preferences of Chinese luxury tourists, notably their substantial financial capability, penchant for shopping activities, preference for authentic local Chinese cuisine, and the significance of Mandarin-speaking tour guides. The Chinese tourists also seek high standards and exclusivity, aspire for unique experiences, and often desire customization in their travel itineraries. However, challenges surface in meeting their unique preferences, including limited infrastructures, the need for customization in luxury services, and bureaucratic hurdles. Despite these challenges, travel agencies assert their readiness to cater to the demands of Chinese luxury tourists, actively promoting and enhancing their high-end offerings. By delving into these aspects, the study provides valuable practical and academic insights into industry strategies and the complexities of serving affluent tourist segments within a multicultural destination.

Customer involvement in co-development: problem-solving and decision-making in new product development

PurposeCustomers can participate in new product development (NPD) in many ways. Drawing on the knowledge-based view (KBV) and innovation literature, this study aims to contrast two main product development activity types, i.e. problem-solving and decision-making. It proposes customers play distinct roles if they get involved in these activities, which influence NPD outcomes differently. It also explores customer need specificity as a boundary condition for the above-mentioned relationships.Design/methodology/approachThe authors collected survey data from 308 managers in the innovation domain.FindingsCustomer involvement in problem-solving and decision-making distinctively influences new product innovativeness and development speed. Customer need specificity interacts with the two co-development types differently to impact these NPD outcomes further.Research limitations/implicationsThis research extends the KBV and addresses the inconsistent findings in the literature regarding customer involvement as co-developers in innovation. It also provides novel insights into how knowledge characteristics like customer need specificity can direct co-developing activities to generate distinct NPD results.Practical implicationsThis paper offers practical implications for firms on how to involve customers in developing innovative new products while managing development speed.Originality/valuePrior research has yet to distinguish customer responsibilities related to co-development activities. This research fills this gap and offers novel insights that problem-solving and decision-making have opposite impacts on different NPD outcomes. This research demonstrates that finer knowledge about customer involvement responsibilities is needed for critical NPD outcomes.

Assessment of Effects of Port Tariffs on Dar Es Salaam Port Cargo Traffic

The main objective of this study was to assess the effect of port tariffs on Dar es Salaam cargo traffic. Specifically, the study aimed to assess the current situation for cargo traffic at Dar es Salaam port, to assess the effect of port tariffs to importers and exporters of cargo, and to find out possible measure to mitigate the port tariffs challenges facing Dar es Salaam port. This study used descriptive layout to study, describe and record aspects of scenario as they arise in a given populace. The study was conducted in Dar es Salaam port, Shipping Company and Clearing and Forwarding agents of Dar es Salaam. The study employed the following respondents like Port officer, Importer, Exporter, Ship agents, clearing and Forwarding agents. Primary data were collected by using questionnaires, interviews and observations. Secondary data were also collected from various documentary sources, such as Annual Reports of TPA for five year back from 2016- 2020 but the primary data use to support secondary data. The research finding show that in assess the current situation for cargo traffic at Dar es Salaam port there is fluctuation of amount of cargo import and transshipment but cargo export increase for every year, in assess the effect of port tariffs to importers and exporter the number of ships call to Dar es Salaam port fluctuate. Also the possible measure to mitigate the port tariffs challenges facing Dar es Salaam port, the customer need port tariffs to be reviewed. Dar es Salaam port is the starting and ending point for maritime transport which links six surrounding land-locked countries. These countries depend on the port of Dar es Salaam for facilitating the passage of their exports and the importation of goods. The study recommends reviewing the port tariffs for at least for every two years for purposes of getting more customers which lead to increase government revenue and make Dar es Salaam port to be strong in competition of shipping business with other neighboring port.

Changes In People's Consumption Patterns In The Digital Era: A Study On The Millennial Generation

The millennial generation, born between the early 1980s and early 2000s, grew up in the era of digital technology that affects their consumption patterns. This study uses a qualitative approach with case study design, collecting data through in-depth interviews, case studies, and participatory observations, which are analyzed thematically. The results show that millennials prefer online shopping through e-commerce platforms, influenced by social media and influencers, and prioritizing experience over goods ownership. They are also sensitive to social and environmental values in choosing products. The use of mobile apps for transactions and product reviews is very dominant, although challenges related to data privacy and information reliability are major concerns. This research reveals the need for content-based marketing strategies, product and service customization, and increased transparency and data security to build consumer trust. These findings provide in-depth insights into the consumption dynamics of millennials in the digital era, offering guidance for companies to develop more adaptive and innovative strategies in the face of evolving consumption trends.

Marketing Strategy for Financial Institutions in Nepal

The Nepalese financial sector has undergone significant changes after the government’s financial sector reform programme. The reform programmes brought various changes yet bank and financial institutions (BFIs) lacks appropriate strategies in marketing financial services. However, the recent developments in financial sector and changing dynamics of consumer behaviour towards financial services have underscored the need of strategic orientation in discovering customer need, institutional promotional initiatives, customer satisfaction, employee motivation and customer data management practices. In this context, this study attempted to explore the marketing strategies of bank and financial institutions (BFIs) in selling/providing financial services to the customers using principal component analysis with varimax rotation adopting exploratory research design. To fulfil the purpose of the study, data were collected from 304 sales personnel of the bank and financial institutions (BFIs) using structured questionnaires. The study has identified 20 factors from the related literature. Through exploratory factor analysis, five most influential factors have been discovered and are instrumental in formulating the marketing strategies for bank and financial institutions (BFIs).

Technology modification, development, and demonstrations for future spaceflight medical systems at NASA

Throughout the history of human spaceflight, spacefarers have experienced and reported the occurrence of medical conditions, including various illnesses and injuries. Therefore, future spaceflight missions to the Moon and Mars will require the capabilities necessary for maintaining the health of these new space travelers. Mass, power, and volume available in the space vehicles used for these missions will be severely constrained. The ability to resupply or evacuate to Earth will be limited or non-existent, and ground-based support will no longer be immediate due to communication latencies and blackouts. These vehicle and mission constraints will necessitate healthcare be provided from an efficiently planned medical system. To provide the necessary care, these medical systems will need to include at a minimum, several different types of medical devices, consumable resources, centralized data management, procedural guidance, and decision support technologies. Medical devices needed for diagnosing and treating medical conditions that are expected to occur during future spaceflight missions may include real-time health monitoring, medical imaging capabilities, as well as blood and urine analysis. Novel methods for interacting with onboard patient medical records will be necessary, as will resource tracking. Terrestrial medicine shares many of these same needs, therefore a multitude of these required medical capabilities can likely be satisfied by currently available, Commercial-Off-The-Shelf (COTS) devices and methodologies; however, in some cases the unique space environment and increased mission durations will drive the need for modifications or customization of standard technologies and treatment procedures. This article will provide a review of medical devices and technologies that have been considered for inclusion within future spaceflight medical systems. It will also include a discussion about the modifications and customized development that have been performed, as well as descriptions of the technology demonstrations that have been conducted in analog and spaceflight environments.

Exploring the Integration of Artificial Intelligence-Based ChatGPT into Mathematics Instruction: Perceptions, Challenges, and Implications for Educators

This research investigates how secondary school mathematics educators in the Nsukka Education Zone, Enugu State, Nigeria, perceive the incorporation of artificial intelligence-based ChatGPT into teaching mathematics. The study employed a sequential exploratory mixed-methods strategy, starting with a systematic survey and followed by detailed interviews. The Mathematics Teachers’ Awareness and Perceptions of AI-based ChatGPT Questionnaire (MTAPACQ) used in this study was adapted from an existing online survey and administered to 80 mathematics teachers, who were selected using stratified random sampling to ensure varied representation across different local government areas. The survey explored teachers’ awareness, utilisation, and perceptions of ChatGPT. Following the quantitative phase, in-depth qualitative interviews were conducted with a subset of five teachers who were familiar with ChatGPT to gain deeper insights into their experiences. The findings indicate limited awareness of ChatGPT, with only 17% demonstrating familiarity with the technology. The infrequent utilisation of ChatGPT in mathematics teaching is mainly associated with this limited awareness. Teachers who integrate ChatGPT report positive outcomes, including improved teaching effectiveness, heightened student engagement, and enhanced comprehension of complex concepts. Nevertheless, the overall perceptions of the tool’s impact on mathematics teaching and learning are moderate. The identified challenges in relation to integration include technical adaptability, curriculum alignment, and the need for customisation to accommodate diverse learning styles. This study emphasises the significance of continuous professional development and ongoing support for teachers to integrate AI-based ChatGPT into mathematics instruction proficiently. The insights derived from the findings hold value for educators, policymakers, and technology developers aspiring to elevate the role of artificial intelligence in mathematics education.

Rental Clothing site (THE BORROW TREND)

Abstract – This research paper investigates the emerging trend of clothing rental websites, examining their impact on the fashion industry, consumer behavior, and environmental sustainability. The study aims to provide a thorough literature review, propose a conceptual model for clothing rental platforms, and offer insights into the future of this innovative business model. The creation of a business model that addresses the need for affordable clothing options, particularly for special occasions like weddings. The project aims to offer a solution for individuals from lower and middle-class backgrounds who find it challenging to purchase expensive attire for events due to high costs and limited utility. By introducing a rental clothing service called “Rent Attire,” the project targets a wide audience, including lower, middle, and upper classes, with a focus on providing various styles of clothing for different occasions. The long-term goal is to become a leader in the rental clothing industry, expanding services to include event organization like weddings. Marketing strategies involve advertising in magazines, social media, and television, along with offering discounts to attract and retain customers. The project emphasizes customer satisfaction, with plans to open stalls in universities and expo centers to reach a broader market. The business model includes physical stores for order placement and rental charges based on the completion of orders. Overall, the project aims to fill a market gap by providing affordable and stylish clothing options for various customer segments, with a focus on convenience and customer service. Keywords – Rental clothing-business model,Fashion business plan, Marketing analysis, Customer need, Managing customers, Search engine optimization (SEO), Custom HTML page templates.

CRIMP: a CRISPR/Cas9 insertional mutagenesis protocol and toolkit

Site-directed insertion is a powerful approach for generating mutant alleles, but low efficiency and the need for customisation for each target has limited its application. To overcome this, we developed a highly efficient targeted insertional mutagenesis system, CRIMP, and an associated plasmid toolkit, CRIMPkit, that disrupts native gene expression by inducing complete transcriptional termination, generating null mutant alleles without inducing genetic compensation. The protocol results in a high frequency of integration events and can generate very early targeted insertions, during the first cell division, producing embryos with expression in one or both halves of the body plan. Fluorescent readout of integration events facilitates selection of successfully mutagenized fish and, subsequently, visual identification of heterozygous and mutant animals. Together, these advances greatly improve the efficacy of generating and studying mutant lines. The CRIMPkit contains 24 ready-to-use plasmid vectors to allow easy and complete mutagenesis of any gene in any reading frame without requiring custom sequences, modification, or subcloning.