Eng

flag-en

Eng

flag-en
Get a Demo

Tag: Pharmaceutical CRM

Platforce CRM’s Pharma Analytics for Customer Engagement & Growth

Posted on by Visarlini Velu

In today’s dynamic and highly competitive pharmaceutical industry, data has emerged as a game-changer. With the increasing availability of data and advancements in analytics technologies, pharmaceutical companies are harnessing the power of data-driven insights to drive efficiency, productivity, and innovation throughout the pharmaceutical manufacturing process. This is where Pharma Analytics comes into play.

What is Pharma Analytics?

Pharma analytics is the utilization and application of data analytics within the pharmaceutical industry. It empowers companies to unlock valuable insights, streamline operations, and make informed decisions that drive customer engagement and fuel business growth. 

By leveraging vast datasets encompassing scientific literature, clinical trial results, genetic information, patient data, and more pharmaceutical professionals can gain a lot.  

That being said, let’s look at

The Power Of Analytics.

1.1 Accelerate Research and Development

Pharma analytics plays a pivotal role in accelerating research and development (R&D) activities, which are critical for bringing new drugs and treatments to market. By analyzing vast datasets encompassing scientific literature, clinical trial results, genetic information, and patient data, companies can identify potential drug candidates with higher precision and efficiency. 

The ability to integrate and analyze disparate data sources enables researchers to make data-driven decisions, optimize clinical trial design, and identify patient populations that are most likely to benefit from specific treatments. 

This targeted approach 

  • minimizes costs
  • reduces time-to-market
  • increases the chances of successful product launches.

1.2 Enhance Supply Chain and Manufacturing Processes

Pharma analytics revolutionizes supply chain management and manufacturing processes within the pharmaceutical industry. 

By analyzing data related to procurement, inventory management, demand forecasting, and logistics, companies can optimize their supply chain operations. 

Real-time data insights enable proactive decision-making, ensuring adequate stock levels, minimizing stockouts, and optimizing distribution networks. 

Furthermore, analytics-driven predictive maintenance and quality control processes help identify potential equipment failures, reduce downtime, and ensure consistent product quality, ultimately leading to improved operational efficiency and customer satisfaction.

1.3 Personalize Customer Engagement and Marketing Strategies

Pharma analytics enables companies to understand their customers on a deeper level and deliver tailored experiences. By analyzing patient demographics, preferences, treatment outcomes, and feedback, companies can create personalized marketing campaigns, develop targeted patient support programs, and design customized treatment plans.

Advanced analytics techniques such as predictive modeling and segmentation enable companies to identify patient segments, predict patient behavior, and personalize interactions at scale. This level of customer-centricity not only enhances patient engagement and satisfaction but also contributes to improved health outcomes.

1.4 Ensure Regulatory Compliance and Patient Safety

Pharma analytics plays a critical role in ensuring regulatory compliance and patient safety within the pharmaceutical industry. By analyzing data related to adverse event reporting, pharmacovigilance, and regulatory compliance, companies can detect and respond to potential safety issues more efficiently. Early identification of safety signals allows for timely interventions and mitigation strategies, reducing the risk of harm to patients and ensuring compliance with regulatory requirements. Additionally, analytics-driven compliance monitoring ensures adherence to regulatory standards, streamlines reporting processes, and minimizes the risk of penalties or legal consequences.

1.5 Make Data-Driven Decision 

Overall, the power of pharma analytics lies in its ability to drive data-driven decision-making across all facets of the pharmaceutical industry. By transforming raw data into meaningful insights, companies can make informed decisions, identify market trends, seize opportunities, mitigate risks, and optimize their operations. The integration of analytics into strategic planning, resource allocation, and marketing campaigns ensures that decisions are based on evidence and aligned with business goals, leading to improved outcomes, increased profitability, and sustained growth.

While the benefits of pharma analytics are significant, it is important to acknowledge that there are challenges that pharmaceutical companies may encounter when deciding to implement and make use of pharma analytics. Understanding and addressing these challenges is crucial for the successful adoption and utilization of analytics-driven strategies. 

Let’s explore some of the;

Common Challenges Faced by Pharma Companies in Adopting CRM Pharma Analytics.

1.1 Data Quality and Integration.

One of the major challenges is ensuring the quality and reliability of data. It’s no surprise that the pharmaceutical industry generates vast amounts of data from various sources, including clinical trials, electronic health records, sales data, and research studies. 

However, ensuring the accuracy, consistency, and completeness of data can be complex. On top of that, integrating data from different systems and sources to create a unified view is also challenging, requiring robust data integration processes and technologies.

1.2 Data Privacy and Security.

Pharmaceutical companies handle sensitive and confidential data, including patient information, intellectual property, and clinical trial results. 

Protecting this data from unauthorized access, breaches, or misuse is of paramount importance. Compliance with data privacy regulations, such as GDPR and HIPAA, adds an additional layer of complexity. 

Implementing robust data privacy and security measures, including encryption, access controls, and anonymization techniques, is essential to maintain trust and meet regulatory requirements.

1.3 Technical Infrastructure and Expertise.

Implementing pharma analytics requires a robust technical infrastructure, including data storage, processing capabilities, and analytical tools. Pharmaceutical companies may face challenges in upgrading or building the necessary infrastructure to handle large volumes of data and perform complex analytics tasks. Additionally, there is a need for skilled personnel with expertise in data analytics, data science, and statistical modeling to extract meaningful insights from the data. Recruiting, training, and retaining such talent can be a challenge.

1.4 Change Management and Cultural Shift.

Integrating analytics into the decision-making processes of a pharmaceutical company often requires a cultural shift and change management. This involves breaking down silos and fostering a data-driven mindset across departments and functions. Resistance to change, lack of understanding about the benefits of analytics, and insufficient training can hinder the successful adoption of analytics-driven strategies. Effective change management, clear communication, and training programs are crucial to overcome these challenges and promote a data-driven culture.

1.5 Cost and Return on Investment.

Implementing and maintaining a robust pharma analytics infrastructure can involve significant upfront and ongoing costs. Investments may be required in hardware, software licenses, analytics tools, data management systems, and talent acquisition. Calculating and demonstrating the return on investment (ROI) of pharma analytics initiatives can also be challenging, especially in the early stages. Establishing key performance indicators (KPIs) and metrics to measure the impact of analytics on business outcomes is essential to justify investments and secure ongoing support.

Addressing these challenges requires a strategic approach, careful planning, and collaboration between IT, data analytics teams, and business stakeholders. Overcoming these obstacles is crucial for pharmaceutical companies to fully leverage the power of pharma analytics and reap its benefits in driving customer engagement and business growth.

In the following sections, we will discuss potential solutions and best practices for addressing these challenges and how a CRM like Platforce can help in ensuring the successful implementation and utilization of analytics in the pharmaceutical industry.

Overcoming Challenges in Adopting CRM Pharma Analytics.

Adopting CRM pharma analytics can present several challenges for pharmaceutical companies. However, with proper planning, strategy, and the right tools, these challenges can be met heads on. Here’s precisely how.

  1. Ensure Data Quality and Integration.

    Data quality and integration are key challenges in fully utilizing pharma analytics. Pharmaceutical companies deal with vast amounts of data from multiple sources, including sales data, customer interactions, and patient information. Ensuring the accuracy, consistency, and completeness of this data is crucial for obtaining reliable insights. 

    Implementing data governance practices, establishing data quality standards, and leveraging data integration tools from the start can help address these challenges. Plus, regular data validation and cleansing processes should be implemented to maintain data integrity.

  2. Address Data Privacy and Security Concerns.

    Pharmaceutical companies handle sensitive patient information and must comply with data privacy regulations such as GDPR and HIPAA. Protecting patient privacy and ensuring data security is a no-brainer under these regulations. Implementing robust data privacy and security measures, including encryption, access controls, and anonymization techniques, is essential. Conducting regular security audits, educating employees on data privacy practices, and adopting secure data storage and transmission protocols can help mitigate these concerns greatly.

  3.  Build Technical Infrastructure.

    Fully utilizing analytics in pharma requires a robust technical infrastructure capable of handling large volumes of data and performing complex analytics tasks. This infrastructure includes data storage, processing capabilities, and analytical tools. 

    Pharmaceutical companies may face challenges in upgrading their existing infrastructure or building a new one. Partnering with experienced technology providers, cloud-based solutions like Platforce, and leveraging scalable analytics platforms can help address these challenges. By utilizing the cloud, companies can avoid significant upfront investments in infrastructure and benefit from the scalability and flexibility offered by cloud-based analytics solutions.

  4. Cultivate a Data-Driven Culture.

    Integrating CRM analytics into a pharmaceutical company’s decision-making processes requires a cultural shift and change management. Employees may resist adopting new technologies or be hesitant to rely on data-driven insights. To address this challenge, it is essential to provide training and education on the benefits of CRM analytics. Engage employees at all levels and foster a culture that values data-driven decision-making. Encourage cross-functional collaboration and highlight success stories that demonstrate the positive impact of CRM analytics on business outcomes.

  5. Demonstrate Return on Investment (ROI)

    Justifying the investment in CRM analytics and demonstrating its ROI can be challenging. Pharmaceutical companies need to establish key performance indicators (KPIs) aligned with their business goals and track the impact of CRM analytics on these metrics. Conducting regular performance assessments, monitoring customer engagement, and measuring the success of marketing campaigns can help quantify the benefits of CRM analytics. Demonstrating tangible outcomes, such as increased customer satisfaction, improved sales, and enhanced marketing effectiveness, strengthens the case for continued investment in CRM analytics initiatives.

By addressing these challenges head-on, pharmaceutical companies can successfully unlock the full potential of their customer data. Furthermore, leveraging a comprehensive CRM like Platforce that can provide the necessary tools and functionalities tailored specifically for data analytics in the pharmaceutical industry, streamlines the implementation process and ensures a smooth transition.

Unpacking Platforce’s CRM Pharma Analytics

Platforce’s CRM Pharma Analytics is a powerful tool that empowers pharmaceutical companies to unlock actionable insights, anticipate customer needs, and enhance their marketing strategies. With a range of features designed specifically for the pharmaceutical industry, Platforce’s CRM Pharma Analytics offers a comprehensive solution for harnessing the power of data-driven decision-making.

 Let’s delve into the key features and benefits of Platforce’s CRM Pharma Analytics:

  1. Data Visualization

Platforce’s CRM Pharma Analytics provides robust data visualization capabilities that transform complex datasets into intuitive visual representations. Through interactive charts, graphs, and dashboards, pharmaceutical professionals can gain a comprehensive understanding of their customer data and identify meaningful patterns and trends. Visualizing data allows for quicker and easier interpretation, enabling users to extract actionable insights and make informed decisions.

Platforce's Analytic Dashboard
Platforce’s Analytic Dashboard With Relevant Insights
  1. Predictive Analytics

Platforce’s CRM Pharma Analytics leverages advanced predictive analytics algorithms to anticipate customer needs and behavior. By analyzing historical data, customer interactions, and market trends, the tool can predict future outcomes, such as customer preferences, medication adherence, and response to marketing campaigns. These predictive insights enable pharmaceutical companies to proactively tailor their strategies, personalize customer interactions, and optimize marketing efforts for improved engagement and higher conversion rates.

  1. Real-time Reporting

Platforce’s CRM Pharma Analytics provides real-time reporting capabilities, delivering up-to-date insights on key performance indicators (KPIs) and marketing metrics. This enables pharmaceutical professionals to monitor the effectiveness of their campaigns, track sales performance, and identify areas for improvement promptly. 

Plus, real-time reporting empowers agile decision-making, allowing companies to make data-driven adjustments and optimize their marketing strategies in real-time, resulting in more impactful and targeted customer engagement.

  1. Customer Segmentation and Targeting

Platforce’s CRM Pharma Analytics allows for effective customer segmentation and targeting. With advanced analytics techniques, such as clustering and segmentation algorithms, pharmaceutical companies can identify distinct customer groups based on 

  • Demographics
  • Behaviors
  • Treatment preferences
  • Other relevant criteria

This level of granular segmentation enables personalized communication and tailored marketing campaigns. By understanding the unique needs and preferences of different customer segments, pharmaceutical companies can enhance customer engagement, drive brand loyalty, and maximize the effectiveness of their marketing initiatives.

  1. Campaign Optimization

With Platforce’s CRM Pharma Analytics, companies can optimize their marketing campaigns by leveraging insights derived from customer data. The tool enables pharmaceutical professionals to evaluate campaign performance, measure return on investment (ROI), and identify the most effective channels and messages for different customer segments. By analyzing campaign data and performance metrics, companies can continuously refine their marketing strategies, allocate resources more effectively, and improve overall campaign effectiveness.

  1. Compliance and Regulatory Insights

Platforce’s CRM Pharma Analytics helps pharmaceutical companies ensure compliance with regulatory standards and guidelines. The tool provides insights into adherence to compliance requirements, such as tracking consent and permissions, managing data privacy, and maintaining regulatory documentation. By having a comprehensive view of compliance metrics and insights, companies can mitigate compliance risks and streamline their processes to meet regulatory obligations effectively.

Platforce’s CRM Pharma Analytics stands out as a comprehensive solution tailored specifically to the needs of the pharmaceutical industry. By leveraging the powerful combination of data visualization, predictive analytics, real-time reporting, customer segmentation, campaign optimization, and compliance insights, pharmaceutical companies can unlock the full potential of their customer data. With Platforce’s CRM Pharma Analytics, companies can make data-driven decisions, enhance customer engagement, optimize marketing strategies, and drive business growth in the dynamic and competitive pharmaceutical landscape.

Interested?

Platforce is the best CRM software for lead generation, order management, sales automation, and task management. Unlike other software, Platforce gives your company all it needs to optimize customer relations and boost customer experience. Try out the Platforce CRM system with a demo now. You can also stay updated on our Youtube and LinkedIn channels.

Predictive Analytics: Harnessing Historical Data for Accurate Future Forecasts

Posted on by Stefan Repin

Introduction to Predictive Analytics

Defining Predictive Analytics

Forecasting future events and trends is possible using predictive analytics. The results of this approach include better efficiency, reduced risks, and better outcomes due to better decision-making based on data-driven insights. In predictive analytics models, patterns and correlations are identified by examining past data. The models then use them to predict future events, such as sales trends or customer behavior.

Role of AI in Predictive Analytics

Machine learning and artificial intelligence (AI) are important components of predictive analytics. Using machine learning algorithms, computers can learn and adapt to new data without explicit programming. In contrast to traditional statistical models, these algorithms can analyze and process huge amounts of data much more efficiently. AI systems become more accurate as they process more data in predictive modeling techniques.

Predictive Analytics Models

There are several types of predictive data analytics and models, each with its unique approach to extracting insights from historical data. Some popular predictive analytics models include:

  1. Classification models: These models classify data or groups by categorizing data by specific attributes. A specific outcome can be predicted using them. For example, credit default risk or customer churn can be predicted with classification models.

  2. Clustering models: These models identify relationships between data points and group them based on similarities, unveiling hidden structures within the data. This technique can be used for market segmentation or detecting fraud patterns.

  3. Time-series models: These models analyze historical data trends across time. Sales and stock prices are forecasted using them.

Photo by Kenny Eliason on Unsplash

Businesses and organizations can benefit from predictive analytics by combining data scientists with AI, machine learning, and statistical methods. The result is better outcomes and increased efficiency because they are able to make informed, data-driven decisions.

Application of Predictive Analytics in Medical Fields

Predictive Analytics in Health Insurance

Predictive analytics plays a crucial role in health insurance by analyzing current and historical data to assess and forecast the risk associated with policyholders. Insurers use this information to price their policies better, identify high-risk clients, and develop preventative care programs tailored to their needs. They can also optimize marketing efforts by assessing the risk profiles of customers, which will lead to a higher customer retention rate and higher profitability.

Application in Pharmaceuticals

Due to predictive analytics, drug discovery and development processes in the pharmaceutical industry have become more efficient. Research can better predict new drug success by analyzing clinical trial data, discovering patterns that correlate with treatment effectiveness, and identifying potential adverse effects. Additionally, supply chain optimization can be achieved through accurate demand forecasting, allowing better management of inventories in retail and hospital pharmacies.

  • Applications of predictive analytics in pharmaceuticals:

    1. Forecasting drug demand

    2. Identifying drug-drug interactions

    3. Predicting treatment outcomes

    4. Optimizing clinical trial designs

Use in Hospitals

In hospitals, predictive analytics can make a significant impact on patient care. By leveraging historical patient data, medical professionals can identify early signs of patient deterioration in ICU wards, allowing for timely intervention. Similarly, advanced analytic modeling techniques can also help predict readmission rates, reduce emergency room wait times, and optimize staff assignments, thereby improving patient experiences and hospital efficiency.

Some common applications of predictive analytics in hospitals include:

  • Hospital-acquired infection prediction

  • Readmission rate prediction

  • Emergency department wait time forecasting

  • Staff scheduling optimization

Application in Healthcare

Beyond hospitals and insurance, such predictive modeling and analytics find applications throughout the broader healthcare sector, including telemedicine, wearable technology, and mental health. In telemedicine, for instance, remote patient monitoring backed by predictive analysis can help in the early identification of complications, allowing healthcare providers to intervene proactively.

Embracing predictive analytics can enable businesses across the insurance, pharmaceutical, hospital, and telemedicine sectors to make more informed decisions, optimize operations, and ultimately deliver better patient care.

Tools and Techniques in Predictive Analytics

Predictive analytics combines various strategies and techniques to analyze historical data and forecast future outcomes. This section focuses on two main approaches to predictive models: Data Mining and Regression Analysis and Decision Trees and Neural Networks.

Photo by fabio on Unsplash

Data Mining and Regression Analysis

Data mining or data science is a process of extracting valuable patterns and information from large sets of data, playing a pivotal role in making data-driven decisions. It includes techniques such as:

  • K-means clustering: K clusters partition data points from the cluster with the nearest mean.

  • Hierarchical clustering: This clustering builds a tree-like structure, allowing observations to be grouped based on similarities.

Regression analysis is another essential tool in the use of predictive analytics. It helps establish the relationship between a dependent variable and one or more independent variables. The two primary types of regression analysis are:

  1. Single linear regression: Determines the relationship between two variables.

  2. Multiple regression: Finds the association between three or more variables.

Decision Trees and Neural Networks

Decision trees are used to visually illustrate the decision-making process by breaking it down into a hierarchical structure. Key components of a decision tree include:

  • Nodes: Represent decisions and indicate where a choice or a condition must be evaluated.

  • Branches: Correspond to the possible outcomes of a decision and connect the nodes.

  • Leaves: Indicate the final output or decision reached at the end of the path.

Another powerful technique in predictive analytics is neural networks. Patterned like the human brain, these networks consist of interconnected nodes called neurons. They work together to solve complex problems and recognize patterns. Here’s an overview of its structure:

  • Input layer: Receives data and forwards it to the hidden layers.

  • Hidden layers: Process the information and apply transformations before passing it to the output layer.

  • Output layer: Generates the final result or prediction.

Predictive analytics takes historical data and forecasts future outcomes. They can forecast sales trends or customer behavior with various tools and techniques, such as data mining, regression analysis, decision trees, and neural networks. Businesses make well-informed, data-driven decisions and improve their strategies when using these methods.

Predictive Analytics in Customer Behavior Analysis

Understanding Customer Behavior

Predictive analytics is crucial in understanding customer behavior using historical data, statistical algorithms, and machine-learning techniques to forecast future trends, events, and behaviors. It enables businesses to gain deeper insights into their customers, allowing them actionable insights to make data-driven decisions that can improve marketing campaigns, segmentation, and customer retention.

One way predictive analytics helps understand customer behavior is by analyzing product revenue timelines, which can highlight patterns and preferences among customers. Marketing and pricing strategies can be tailored based on this data or targeted more effectively to certain customer groups based on this information.

Further, predictive analytics can help distinguish between long-term and short-term customers based on their revenue contribution. Marketing efforts can be focused on gaining new customers (to increase revenues), retaining existing customers (to ensure loyalty and satisfaction), and identifying potential re-engagement opportunities with lost customers (to understand revenue loss).

Segmentation and Marketing

Predictive analytics plays a significant role in customer segmentation and marketing by helping businesses that analyze data identify common traits, preferences, and behaviors among different customer groups. This process involves:

  • Data collection: Gathering data on customer demographics, purchase history, and online behavior helps create a comprehensive view of the customer base.

  • Data analysis: Analyzing this data helps identify patterns and trends among customers, allowing businesses to group them accordingly (e.g., age, gender, location, or spending habits).

  • Segmentation: Once the patterns are identified, customers can be divided into segments with distinct characteristics and preferences.

  • Personalization: Businesses can create personalized marketing campaigns tailored to each segment, improving customer responses and conversions by addressing their specific needs and preferences.

For example, let’s consider a table outlining some customer segments based on the data collected on their demographics and behavior:

SegmentAgeGenderSpending HabitsPreferred Channel
Young Professionals25-34M/FFrequent Small PurchasesSocial Media, Email
Busy Parents35-44M/FOccasional Large PurchasesDirect Mail, Email
Retired Leisure-seekers55+M/FInfrequent PurchasesTraditional Media

Businesses can use these predictive analytics techniques to create tailored marketing campaigns for each segment, resulting in higher customer engagement and satisfaction. For example, offering promotion codes through social media could be an effective strategy for the “Young Professionals” segment. In contrast, direct mail promotions may work better for “Busy Parents” and “Retired Leisure-seekers.”

Predictive analytics helps businesses better understand their customers, allowing for more effective segmentation and targeted marketing strategies. By leveraging these insights, businesses can improve customer retention, boost conversions, and maximize overall revenue.

Challenges and Opportunities of Predictive Analytics

Analyzing historical data to predict future outcomes enables organizations to make decisions based on data, foresee trends and patterns in sales or customer behavior, and identify relationships within multiple datasets. Despite the numerous advantages of predictive analytics, technical challenges need to be addressed for its effective implementation.

Technical Challenges

  1. Data Quality: The accuracy of predictive models mainly depends on the quality of the historical data being used. If the data is complete or contains correct values, it can lead to accurate results. Organizations must invest time and resources in data cleansing and preprocessing to ensure reliable outcomes.

  2. Data Volume: Dealing with vast amounts of data can be a challenge regarding storage, processing, and analysis. Predictive models can also become more complex when large datasets are used.

  3. Choice of Predictive Models: Many models in predictive analytics find patterns and make forecasts, including classification, clustering, and time-series analysis. When choosing the best model for a task, a thorough understanding of the underlying data, relationships, and desired outcomes is essential.

  4. Model Evaluation: In order for predictive models to accurately forecast inventory, sales trends, or customer behavior, it is necessary to evaluate their performance. Model evaluation can be a complex process requiring a thorough understanding of the domain and comparing various performance metrics.

The challenges in implementing predictive analytics should be considered in the significant opportunities it offers to organizations. By overcoming these technical obstacles, businesses can:

  • Accurately forecast inventory, which helps efficiently manage resources and reduces the risk of stockouts or overstocking.

  • Identify sales trends and customer behavior patterns to inform marketing strategies and enhance customer satisfaction.

  • Uncover relationships within datasets, leading to discovering new business opportunities or potential areas for improvement.

Embracing the challenges and opportunities of predictive analytics and big data can give organizations a competitive advantage, allowing them to make smarter, data-driven decisions and achieve better outcomes in various aspects of their operations.

Platforce is the best CRM software for lead generation, order management, sales automation, and task management. Unlike other software, Platforce gives your company all it needs to optimize customer relations and boost customer experience. Try out the Platforce CRM system with a demo now. You can also stay updated on our Youtube and LinkedIn channels.


Key Performance Indicators for Measuring ROI in Pharma

Posted on by Japheth Oseghale

Like any effective illness diagnosis, key performance indicators that can help identify symptoms are critical. In Pharma businesses, these symptoms are the Closed-loop Marketing (CLM) metrics and measuring ROI. Identifying these metrics is the first step towards mitigating medication errors and improving customer experiences. 

In your Closed-Loop Marketing (CLM) efforts, the symptoms to look out for are market share, customer satisfaction, sales revenue growth, return on investment, and so on. These metrics are borderline determinants and critical performance indicators of how successful your marketing efforts are and a pointer to the areas where you need to do better. 

Your ability to understand and identify these metrics will determine how much more of a success you can make your closed-loop marketing effort. This article may be the eye-opener you need. Please keep reading to discover how to measure your pharmaceutical KPIs and modify them for an increased ROI in Pharma.

Table of Contents

Why Big Pharma Should Choose Closed-Loop Marketing

As far as Pharmaceutical manufacturing and marketing is concerned, there’s been over a decade of decline in the efficiency of the traditional Pharma marketing approach. It faced challenges like reduced access to physicians, reduced efficiency of conventional sales force strategies, and constantly changing stakeholder preferences. 

The recurring theme was the need for an effective marketing strategy that was more customer-centric. Closed-loop marketing (CLM) emerged as the response to these prevailing Pharma marketing needs, especially the need for digital detailing which we have a dedicated post about that can be found here.

Simply by incorporating real-time consumer insight and other digital marketing metrics, Platforce CLM is a better-focused marketing campaign strategy that tracks and analyzes customer complaints and behaviour. It then uses the information to personalize unique user experiences based on customers’ preferences. 

What’s Closed-loop Marketing?

Map lying on wooden table by Freepik

For pharmaceutical companies focusing on patients, CLM is the tool that bridges the gap between healthcare professionals and those they serve. Interactive platforms enable patients to invest actively in their recovery processes and healthy care journey.

Closed-loop marketing (CLM) helps pharmaceutical companies track the buyer’s life cycle. By continuously gathering and analyzing data from real-time experience and customer interaction, pharmaceutical companies can gain the insight they need to make informed decisions on quality control that fulfills the needs of their customers.

12 Major Pharmaceutical KPIs and CLM Metrics that Affect Campaign Results

Although Closed-Loop Marketing might sound demanding, it’s not. Instead, it’s a process that helps pharmaceutical companies identify essential KPIs and other metrics from analysis of customer interactions.

The data collected from these key performance indicators (KPIs) are used to assess performance and improve quality and competitive advantages in the market. KPI helps pharmaceutical companies achieve their marketing and cash flow objectives.

Many CLM metrics exist in regular marketing campaigns that would not have any efficiency in Pharma. This makes following KPIs very difficult and almost impossible. To help you identify and implement the right KPIs, here are the CLM KPIs your pharmaceutical company should be focused on:

1. Physician Awareness 

Clinical trials are no jokes. In 2023, pharmaceutical companies that tried their new drugs had a success rate of less than 8%. As a result, many pharmaceutical companies put a lot of effort into ensuring their new drugs have successfully passed clinical trials. 

But it’s all for nothing if there’s zero market anticipation for the drug. Metrics like physician awareness help you Measure how many healthcare providers are aware of the new drug after your CLM campaign. This data enables you to build a unique buyer persona of your target market and helps you create a marketing strategy that onboards physicians who clamour for your new drug. 

2. Time to Market

Time to market can be a relevant KPI metric for Closed-Loop Marketing (CLM) in the pharmaceutical industry, but it may not be the primary or most critical metric. 

Time to market is a relevant KPI for Closed-Loop Marketing (CLM) in pharmaceuticals, measuring how quickly campaigns launch. While it offers advantages like a competitive edge and adaptability, it should be part of a broader set of KPIs. 

Effectiveness, compliance, and patience are the central focus for a comprehensive evaluation of CLM campaigns.

3. Manufacturing Efficiency

Like every metric we’ve mentioned, manufacturing efficiency isn’t one of the KPIs you’d track in traditional CLM metrics. But it contributes to your marketing efforts and results as a pharmaceutical company. However, manufacturing efficiency is more of an essential metric for a pharmaceutical company’s overall operations and manufacturing equipment.

It’s not a directly usable Key Performance Indicator (KPI) for Closed-Loop Marketing (CLM), mainly since CLM primarily focuses on marketing and sales-related metrics rather than operational or manufacturing aspects. However, it still can affect the product availability and pricing. 

3. Conversion Rate 

To improve the efficiency of your CLM, the conversion rate is a metric you must track. It provides valuable insights into the success rate of your CLM strategy and helps you track how well they influence healthcare decisions. 

A higher conversion rate implies that your CLM strategy successfully influences healthcare decisions.

4. Engagement Metrics

Metrics like click-through rates (CTR), open rates, and time spent interacting with your content reflect how engaged your audience is. A high engagement rate suggests that your content is resonating with healthcare providers, which can lead to better conversion rates and increase the efficiency of your campaign outcomes.

5. Compliance and Adherence

This is more like safety KPIs as it ensures that healthcare professionals comply with recommended treatment plans and prescriptions, which is crucial in pharmaceutical marketing. Big Pharma needs this KPI to eradicate non-compliance with the prescriptions filled. Monitoring KPIs related to compliance and adherence can help gauge the effectiveness of your campaign in improving patient outcomes.

6. Return on Investment (ROI)

Pharmaceutical CLM campaigns require significant financial resources. Measuring ROI helps determine if the campaign generates enough revenue to justify the investment. It’s essential to track sales growth, revenue generated, and cost per conversion to assess ROI accurately.

7. Customer Lifetime Value (CLV)

CLV is especially relevant in the pharmaceutical industry, focusing on the long-term relationship between the company and healthcare providers. High CLV indicates that your CLM campaign is attracting new customers and retaining them. 

8. Data Quality and Accuracy

In pharmaceutical marketing, data integrity is paramount. Ensure that KPIs related to data accuracy and quality are met to avoid targeting the wrong audience or making critical decisions based on flawed data.

9. Compliance and Regulatory Metrics

Pharmaceutical companies must adhere to strict regulations. KPIs related to compliance with industry guidelines and regulations, such as FDA guidelines, are vital to avoid legal issues and maintain a positive brand image.

10. Customer Feedback and Satisfaction

Feedback from healthcare providers is invaluable. Monitor KPIs related to customer satisfaction, gather feedback, and improve your CLM campaigns based on their input.

11. Competitive Benchmarking 

Compare your KPIs with industry benchmarks and competitors to gain insights into your campaign’s relative performance. This can help identify areas where you may need to improve.

12. Market Share and Share of Voice

Monitor your pharmaceutical product’s market share and your share of voice in the industry. These KPIs can provide a broader perspective on your campaign’s impact within the pharmaceutical landscape.

The Roles of Technology in Tracking KPIs

Person working HTML computer by Freepik

In today’s data-driven world, Key Performance Indicators (KPIs) are the guiding stars for the pharmaceutical industry and organizations. They provide valuable insights into performance, helping the pharmacy make informed decisions that drive success and contribute to their net profit. However, the complexity and volume of data tracking KPIs can only be overwhelming with the right technology solutions. 

These technologies play a crucial role in the implementation of data within the production process and Closed-Loop Marketing campaigns. Some of their functions include:

Data Collection and Integration

Technology is the foundation for collecting and integrating data from various sources within your marketing campaigns. Whether it’s sales figures, website analytics, equipment effectiveness, customer feedback, or operational metrics, technology allows businesses to aggregate and centralize these data points. 

Advanced data integration tools help ensure the information is up-to-date and consistent, providing a comprehensive view of performance.

Real-Time Monitoring

One of the significant advantages of technology in tracking KPIs is the ability to monitor performance in real-time. Dashboards and reporting tools can display KPIs visually intuitively, enabling stakeholders to access critical data instantly. This real-time visibility allows for proactive decision-making and rapid responses to changing circumstances.

Automation of Reporting

Gone are the days of manually compiling spreadsheets and reports. Technology automates the process of generating KPI reports, saving time and reducing the risk of errors. Automated reporting ensures that KPI data is consistently and accurately presented, facilitating more meaningful analysis.

Customization and Personalization

Not all KPIs are created equal, and technology allows for customization. Businesses can tailor their KPI tracking systems to align with their goals and objectives. This customization ensures the tracked KPIs are directly relevant to the organization’s success.

Scalability

As organizations grow, their KPI tracking needs to evolve. Technology solutions can scale with the business, accommodating increasing data volumes and more complex analytics requirements. This scalability ensures that KPI tracking remains practical and relevant in the long term.

Final Thoughts 

Closed-loop marketing has been a groundbreaking marketing campaign solution, and its adoption by reputable pharmaceutical businesses is celebrated for the improved efficiency and effortlessness it brings to marketing campaigns. 

For many pharmaceutical manufacturing industries, making the most out of it requires a strategic approach that involves understanding the metrics and KPIs that can directly influence the use and consumer interest in your Pharma products. 

With our CRM it’s now easier for pharmaceutical businesses to track invaluable KPIs and integrate them for a competitive edge in the market. Here’s a guide to help you get started.

Data-driven Decision Making in Pharma: Leveraging Closed-loop Marketing 

Posted on by Japheth Oseghale

It’s no wonder that without closed-loop marketing we see many pharma businesses launch out with so much promise but don’t appear to flourish after some years. Is it because the industry is too congested to allow the success of hardworking startup owners or that the barriers to entry are too high? You could say it is, but with proper preparation anything is possible.

As a digital marketing company, we’ve observed that many pharma businesses start energetically by collecting and analyzing raw facts (data) from the market before making decisions. 

However, this drive for precision in marketing efforts dropped after a few years, revealing that the initial energy was only to secure investment funding or other immediate benefits. There was no long time plan to sustain their initial meticulous approach!

Data is king when making Pharma business decisions – whether clinical data for a new drug product or market data to aid new marketing strategies. 

As you read, you’ll learn how data is involved in closed-loop marketing, some challenges you can expect in implementing data analytics in your business, and how you navigate through for success. Let’s jump in.

Table of Contents

How Closed-loop Marketing Works

A Business Woman Having an Online Meeting. Source: Freepik.com

John Wanamaker once said, “Half the money I spend on advertising is wasted; the trouble is I don’t know which half.” 

Decades have passed, and most digital marketers are still in his shoes. Even with efficient CRM tools like Platforce today, only a few folks use it to close that loop between their marketing efforts and revenue. 

Closed-loop marketing involves collecting data from a customer’s interactions with a product and analyzing it to discover how to serve customers better. In closed-loop marketing, the sales team provides the data and customer feedback they’ve obtained to the marketing team. 

The sales team monitors the customer’s journey up to the conversion point. This insight helps the marketing team to know what the customers want. The information is then used appropriately for lead generation. 

For effective closed-loop marketing, the sales and marketing teams must be collaborative. Both teams must share the same goal, and that is the success of the Pharma company. This kind of data-driven process is what leads to success.

The Role of Data in Closed-loop Marketing

Analyzing Business Activity. Source: Freepik.com

When there is enough data, a Pharmaceutical company has the foresight to support its decisions. They can easily predict the company’s marketing outcomes from different strategic choices.

It is better to acquire information on how your company should conduct sales and marketing rather than risking millions of dollars and a lot of time on research and development. 

Data analytics is a pharmaceutical company’s pathfinder. Analyzing market data allows you to transform acquired data into logical reasoning to reveal trends and the best action.

Not all drugs can be advertised the same way because of regulations. The pharmaceutical industry is a complex field. Hence, the industry should not embrace all marketing trends. 

Once the sales team has researched how the regulatory authorities want the medicine to be sold, the marketing team uses that strategy to advertise to the final consumers (HCPs or Patients). Here are a few factors to consider when leveraging data in pharma marketing: 

Closed-loop Marketing Helps You to Build A Targeted Marketing Strategy

Understanding the target market is crucial for pharmaceutical companies. The target market comprises customers who require specific products or services the most. Within the broader market, there exists a particular audience.

For the Pharmaceutical industry, identifying this subset through detailed demographics is essential. By tailoring marketing strategies to meet the needs of this specific audience, companies can maximize their profits effectively. 

Utilizing data analytics provides valuable insights into the demographics and pinpoints areas where the disease is most prevalent. 

This focused approach ensures that you direct resources efficiently, leading to better outcomes for the industry and the patients in need.

Monitoring the Return On Investment (ROI) of your Marketing Efforts

Receiving meager returns after investing staggering sums of money in drug research would be financially disastrous. Investors are drawn to drug research and development, mainly when there is a good chance that the study will be successful. 

Pharmaceutical companies may become overly focused on research and development without considering the commercial aspect. Tracking ROI is considerably more crucial than drug discovery, which is vital, too. Increased return on investment is one of the Pharma industry’s ultimate goals. Due to this, the expense and time are justified.

Nonetheless, the pharmaceutical industry’s business side can operate efficiently thanks to data analysis and closed-loop marketing. 

Utilizing Closed-loop Reporting Between Your Marketing and Sales Teams

This type of reporting is a collaborative effort between the sales and marketing teams, working hand-in-hand to boost a company’s success. They need to be in sync to create a seamless performance.

It helps both teams understand which marketing strategies resonate with customers and lead to actual sales. The sales team plays a crucial role here; they are like the eyes and ears on the ground, observing customer interactions and reporting to the marketing team.

This dynamic feedback loop ensures that marketing efforts are not just shots in the dark but are finely tuned based on fundamental customer interactions. 

It’s like a continuous conversation between both teams, where insights from the sales team guide the marketing strategies, creating a powerful synergy that drives business growth.

Challenges Pharma Industries face with Data-driven Closed Loop Marketing. 

Closed-loop marketing, especially in the pharmaceutical industry, is a challenging journey. Although it fills in sales gaps, navigating it can be difficult due to the industry’s unique nature, distinct from other sectors. 

Pharma businesses operate under stringent regulations and deal with sensitive patient data, making implementing closed-loop strategies complex. Additionally, it is tough to effectively gauge how marketing initiatives affect sales in this challenging environment. 

We want to consider a few specific challenges you may encounter when trying to leverage data analytics in your closed-loop marketing and how to navigate through them:

1. Training your Sales and Marketing Teams to Interpret Data Correctly

Smiling Man Presenting During a Business Meeting. Source: Freepik.com

Training your sales representatives to implement CLM tools and comprehend data insights effectively may pose a significant challenge. 

Many industries need to correct their CLM strategies due to the inability to leverage the collected data. Access to extensive data is only enough if the sales force has the knowledge to implement it successfully.

The way out of these is to employ professionals and experts to train your team members on standard data collection and analysis. It’s up to you to decide if you’ll train your whole marketing team or only your high-performing players.

2. Ensuring the Use of Current Data

Not all information out there is equally valuable for you. You must use both current and relevant data for the decision before you. Most companies start on the right foot in gathering current data, often to secure funding for their startup. Afterwards, the drive drops and the once-zealous efforts to collect data are nowhere to be found.

Context, markets, government, and technology evolve daily, making using last year’s data sets for today’s decisions unwise. Beware of the temptation to run a business on assumed sense and expertise; get the raw facts! Gut feelings in business would only lead to a colossal waste of time, energy, and resources.

3. Regulatory Compliance 

The pharmaceutical sector operates under stringent regulations, making it risky to follow market trends unthinkingly because they work for other industries. This challenge can restrict a marketing team’s strategic choices.

Your team can only comply with the regulations they know, so just like the first point, train them!

4. Data Security 

3d Internet Security Badge. Source: Freepik.com

Patients are at the center of product design in the pharmaceutical sector, which means the company gears every effort toward meeting their unique demands. 

This crucial relationship highlights the necessity for the highest level of confidentiality in the sector when dealing with sensitive patient data. 

However, when you need to exchange information across different teams, this secrecy poses a severe problem. It becomes challenging to balance the necessity for information sharing and patient privacy, exposing a major problem with data in the pharmaceutical industry.

Tackling the privacy challenge demands investments in cutting-edge technologies to secure confidentiality and a continuous commitment to adapting. With the right tools, you can ensure your patient’s privacy.

5. Starting with the Executive Team

Incorporating data-driven efforts into your closed-loop marketing strategies must flow from head to toe. To collect and analyze data effectively, the company’s leadership must instill a strong consciousness of its purpose and goals into every member. For some, this task may pose a significant challenge.

There must be a written vision and mission statement. Assessing the business’s strengths, weaknesses, and competition is equally crucial. The leaders mustn’t be afraid to have the “hard” discussions – this enables team members to ask critical questions (in data collection) that are essential to the company’s growth.

They should also do a thorough analysis of the market and ask questions like – how large or saturated is the market the company is playing in? What segment of that market are they zooming into, and why? Such data analysis and more are the way to thrive as a Pharma company if the leaders have the guts to do it.

Final Thoughts

Data-driven strategies in closed-loop marketing are vital to growing your pharmaceutical business. The importance of data analysis to provide information on market trends, patients’ preferences, and competitive activities cannot be overstated. Profitability while simultaneously enhancing patient outcomes and growing your Pharma businesses depends on it.

You need more than developing and marketing a product in the pharmaceutical industry. You need a tool that helps you implement and make sense of the market data. Also, it helps you make well-informed marketing decisions while ensuring data security and results that contribute to the profit and growth of your pharmaceutical business.

Get started by following our demo or tour now!

Transforming Customer Relationships with Pharmacy CRM: A Detailed Guide

Posted on by Stefan Repin

Planning And Development

When planning and developing a Pharmacy CRM, first, you need to understand the unique needs and challenges of the pharmaceutical industry. This includes tracking and managing customer relationships, detailing medical institutions, and providing segmented reports for better insights into customer behavior.

A well-structured Pharmacy CRM should enable you to organize your target audience into segmented lists. This helps in tailoring marketing efforts and improving your relationships with your clients. Additionally, you should be able to manage Point of Sale (POS) and patient feedback through a single platform, simplifying the process and ensuring real-time updates.

To streamline your internal operations, prioritize a collaborative approach. This can help you manage relationship-building activities effectively and ensure all team members are on the same page. In doing so, you can gauge the potential gain from each pharmaceutical relationship with accurate and detailed reports, allowing you to identify your top-performing partnerships and gold-standard clients.

During planning, you must familiarize yourself with standard CRM implementation terms and concepts and emerging customer-centred sales and marketing trends. 

Usability is essential, so opt for a CRM that is easy to use while still offering all important features and functionalities. This allows the team to adapt quickly to the new system.

Benefits Of Using Pharmacy CRM Software

Photo by Austin Distel on Unsplash

Build Better Relationships With The Customers

Pharma CRM software helps your company build better customer relationships by providing tailored communication and marketing efforts. It enables you to segment your customers and target them with personalized messages. This, in turn, leads to more substantial and more loyal customer relationships.

Common Features Of Pharmacy CRM Software

Pharmaceutical CRM software includes several standard features that help improve your business processes:

  • Mobile access for sales representatives to manage customer data on-the-go

  • Integration with various communication channels (e.g., email, phone, and chatbots)

  • Analytics and reporting to measure performance and optimize marketing strategies

  • Efficient data management to easily track customer interactions

Customer Cycle

By leveraging CRM, you can better manage the entire customer cycle, from lead generation to customer retention. This process includes identifying potential customers, creating marketing campaigns, tracking interactions, and maintaining relationships. Managing customer cycles effectively leads to increased sales and improved customer satisfaction.

Customer Account Management

CRM software simplifies customer account management by providing a centralized platform for storing and analyzing customer data. This allows you to easily monitor transactions, gain insights into customer behaviour, and spot trends. This invaluable customer information lets you make data-driven decisions and improve your offerings.

Closed Loop Marketing Campaigns

Pharmaceutical CRM software supports closed-loop marketing campaigns, ensuring your messaging meets customer needs. You can tailor future campaigns to maximize return on investment by identifying the most effective promotional efforts. Closed-loop marketing campaigns also provide valuable feedback to determine the success of current strategies.

Inventory Cycle Management

A comprehensive pharma CRM system offers end-to-end inventory cycle management, helping streamline ordering, managing, and distributing medications. By automating these processes, you can minimize errors and ensure timely and accurate order fulfilment, leading to more efficient operations and satisfied customers.

Order Management

Pharma CRM software simplifies order management by tracking order history and providing real-time order status updates. This helps your staff to process orders quickly and with fewer errors, ultimately achieving higher customer satisfaction. In addition, order data can be used to monitor sales trends and inform future marketing strategies.

Evaluating Pharmaceutical CRM Software

Photo by Markus Spiske on Unsplash

Research And Development

A good Pharmaceutical CRM software will support your research and development efforts. It should provide a platform to manage projects, collaborate with team members, and track the progress of experiments and clinical trials. You can focus on discovering and developing new pharmaceutical products by streamlining processes and communication.

Data Analysis

Pharmaceutical CRM software should offer significant data analysis tools. The tools will help you analyze sales, marketing, and customer data so you can identify trends, patterns, or areas needing improvement. With powerful analytics capabilities, you can make more informed decisions and drive growth for your business.

Enhance Data Privacy And Compliance

Managing sensitive data is crucial for pharmaceutical companies. A reliable CRM solution should have built-in features to help you keep customer and patient information secure and comply with regulations like HIPAA, GDPR, and others. This includes encryption, access control, and audit trails to track data usage and changes.

Better Customer Service

Your Pharmaceutical CRM software should enable you to provide exceptional customer service. It should organize and manage customer interactions, including tracking complaints, queries, and feedback. With a centralized database, your team can access customer information quickly and provide personalized, timely support.

Adverse Events Monitoring

Monitoring adverse events is critical for pharmaceutical companies to ensure product safety. A good CRM solution should have dedicated features for flagging, tracking, and resolving adverse events. This helps you proactively address issues and maintain regulatory compliance.

How To Choose The Right Pharmaceutical CRM?

Consider your company’s specific needs and requirements when evaluating Pharmaceutical CRM software. Look for features that support your business processes, such as sales force automation, marketing automation, and customer service capabilities. Additionally, ensure the software is scalable and adaptable to your growing business needs.

Competitor Analysis

Pharmaceutical CRM software should also offer competitor analysis tools. By monitoring the competition, you can see their strengths and weaknesses and adjust your strategies accordingly. This helps you stay ahead of the curve and achieve market success.

Visits And Route Planning

For field sales representatives, visits and route planning are a vital aspect. Pharmaceutical CRM software should provide tools for scheduling visits, mapping efficient routes, and tracking sales rep performance. This helps you optimize field operations, save time and resources, and improve customer relationships.

By evaluating Pharmaceutical CRM software based on these criteria, you can choose a solution that aligns with your business goals and supports your growth in the competitive pharmaceutical industry.

What Are The Benefits Of A Pharmaceutical CRM?

A Pharmaceutical CRM can offer significant advantages to your business by streamlining processes, improving customer interactions, and enhancing sales and marketing efforts. Here are some key benefits you can expect from a Pharmaceutical CRM:

  • Automated processes: CRM automation can make your operations more efficient. From intelligently assigning leads to sales reps to automatic scheduling for physician visits, CRM tools help ensure faster and more effective management of tasks.

  • Segmentation: Organize your target audience into segmented lists within the pharma CRM, which allows you to tailor your sales and marketing strategies for better results.

  • POS and patient feedback management: With an integrated CRM solution, you can manage all the Point-of-Sale (POS) activity and patient feedback through a single platform. This helps you to monitor ongoing sales activities and make data-driven decisions.

  • Mobile access: For pharmaceutical sales representatives who are always on the go, mobile CRM access enables them to access customer history, schedule appointments, and perform other tasks easily from their smartphones or tablets.

  • Increased efficiency and productivity: By incorporating automated workflows and processes designed specifically for customer service, sales, and marketing, CRM helps boost the overall efficiency and productivity of your pharmaceutical company.

  • Personalized communication: A Pharmaceutical CRM can help your business tailor your messages to customers with more relevant, proactive information. This ensures customer satisfaction and promotes a long-term business relationship.

  • Streamlining advanced therapies: CRMs can help streamline cell and gene therapy processes, improving outcomes and reducing costs.

Adopting a Pharmaceutical CRM tailored to your business needs will allow you to unlock these benefits and more, enhancing your operations and customer relationships in the long run.

Is The Software Designed To Handle Your Organization’s Needs?

When evaluating Pharmacy CRM software, it’s essential to consider whether the software is designed with your organization’s unique needs, size, and requirements in mind. Good pharmacy CRM solutions should be customizable, scalable, and easily integrated into your existing systems.

Firstly, consider the features and functionalities that are most important to your pharmacy business. A robust CRM should help streamline and automate tasks such as lead generation, client management, marketing, and sales. Ensuring these features align with your organization’s priorities and workflow is essential.

Integration with Existing Systems: The Pharmacy CRM should easily integrate with your existing pharmacy management software, billing systems, and inventory control platforms. Seamless integration ensures that your CRM solution enhances your workflow, allowing you to maintain accurate real-time data on patient interactions, prescriptions, and stock levels.

Customization and Scalability: As your pharmacy organization grows and evolves, your CRM should be able to adapt accordingly. Look for a CRM solution that can be easily customized to fit your unique business processes and can scale up to accommodate an increasing customer base without sacrificing performance or functionality.

Ease of Use: The CRM software should be user-friendly, allowing your team to quickly learn and utilize its features effectively. An intuitive interface will enable your employees to focus on providing excellent patient care, communication, and services instead of struggling with complex software programs.

Compliance and Security: The pharmaceutical industry is highly regulated, so your CRM solution must comply with all relevant legal and industry-specific requirements. Ensure the CRM has robust security features such as data encryption, password protection, and regular updates to protect sensitive patient data.

By carefully evaluating the compatibility and adaptability of various Pharmacy CRM solutions, you can confidently choose a software solution that meets your organization’s unique needs and helps you achieve better patient health outcomes, streamlined processes, and increased revenue.

Platforce is the best pharmacy CRM software for lead generation, order management, sales automation, and task management. Unlike other software, Platforce gives your company all it needs to optimize customer relations and boost customer experience. Try out the Platforce CRM system with a demo or tour now. You can also stay updated on our Youtube and LinkedIn channels.