Pharma Marketing Effectiveness at a glance:
Pharmaceutical companies face unique challenges when it comes to understanding customers, building informed and targeted brand and marketing strategies, and adopting a customer-centric go-to-market approach.
Gather, manage and extract pharma marketing insights from growing volumes of diverse patient, practitioner, and drug market data.
Align messaging with new patient expectations and build personalisation into their marketing journeys and plans.
Combine digital and physical marketing approaches and harness data gathered from both to evolve channel and brand strategy.
Comply with strict regulations that vary between countries, while still reaching the right patients and physicians at the right time.
The Smart Cube combines internal spend, sales rep, patient, practitioner, market and drug sales data with deep intelligence and analytics capabilities to help you plan and execute effective, well-targeted marketing and branding activities. We understand that large and growing pharmaceutical companies have different needs to small and mid-size – so we’ve designed a modular solution where you define what you need, based on your business size, drug product type and drug lifecycle stage. With Pharma Marketing Effectiveness from The Smart Cube, you can select capabilities and insights across three modular elements:
Identify the right marketing mix and budget allocation across marketing vehicles with analytics to optimise RoI and spend, omnichannel planning and sample distribution, and drug sales forecasts.
Enhance your knowledge of HCP and patient attributes to design the most effective marketing strategy by analysing physician churn, customer segmentation, patient sentiments and early signal detections.
Understand competitor positioning and your influencers to increase brand awareness, through analysis of physician prescribing behaviour, competitor activity, generic erosion impact and KOL mapping.
With Pharma Marketing Effectiveness from The Smart Cube, you can:
However large or small your organisation, wherever your drugs are in their lifecycle, and whatever market challenges you’re facing, we work with you to create a bespoke solution that delivers the marketing insights you need to meet your goals. Here’s how our process works:
We work with you to understand your requirements, map out your internal data sources, and identify and prioritise strategic use cases where our solution can deliver most value.
We bring in relevant external datasets and our proprietary pre-built assets, to create a solution proof of concept (POC) for the defined use cases.
The POC is scaled up and evolved, based on learnings from the initial insight projects.
We set up automated updates, and deploy self-service business tools and dashboards, to deliver ongoing actionable insights.
Our specialist team works closely with you and any external partners/ Agency on Record, to add capabilities and ask new questions of your data.
We review and refine the solution to ensure it supports your objectives and is delivering measurable marketing ROI.
When you choose Pharma Marketing Effectiveness from The Smart Cube, you always get:
A complete customer view: We analyse all relevant sources of data simultaneously to help you identify the best marketing opportunities across your patient and practitioner base, and enhance your GTM strategy.
A blend of human and artificial intelligence: We use the power of data science and AI for rapid insight delivery, and build on it with our team of specialists who provide contextualised recommendations.
Deep life sciences knowledge: When you work with The Smart Cube, you benefit from market, category and customer knowledge developed over 17 years of strong pharmaceutical client relationships.
Cutting edge algorithms: We use advanced ML algorithms to merge discrete data from diverse sources including Electronic Health Records, insurance claims and patient communities, and improve KPI predictions of the analytical models.
Rapid, measurable ROI: We use a combination of custom and pre-built reusable assets to develop tailored solutions at speed, and help you see value from your project immediately.
A nimble, agile, customised approach: We work as an extension of your team, and with external partners/Agency on Record – enabling collaborative innovation and answering new questions as business strategies evolve.
The client was facing a challenge in predicting churn within different physician segments; it wanted to identify physicians who were less likely to prescribe, or stop writing their products post 90 days, thus impacting its drug sales.
The Smart Cube performed exploratory data analysis and leveraged advanced Machine Learning techniques – such as naïve Bayes, random forest and support vector machines – to build a statistically sound customer churn production model. Using the churn probabilities, we segmented data into deciles, and recommended process improvement and suggested outreach to high churn customers with targeted marketing offers.
The predictive modelling on physician churn scenarios helped the client reduce 15% of physician churn, amounting to revenue contribution worth $8 million.
The client was facing issues regarding extreme variations in sample distribution to physicians, with over-sampling resulting in cannibalisation and under-sampling leading to untapped opportunities. Hence, it wanted to optimise sample distribution across its pool of targeted physicians to maximise the impact of sampling.
The Smart Cube conducted univariate and bivariate exploratory analyses of all the important variables to identify trends, and exclude irrelevant variables, and transformed M-o-M data to calculate TRx, NRx, Detailing, sampling, etc. We created different segments of health care providers (HCPs) via clustering techniques – such as k-means – and determined HCPs responses to different sampling levels (to plot a response curve).
The results helped the client gauge optimal sampling levels for each segment and helped formulate the next sampling strategy, with ROI maximised for sampling. The exercise helped in achieving 15% increment in sales.
The client was losing market share to competitors and wanted to ascertain overall market growth, impact of new entrants, structural changes, forecast drug sales as well as the market share of its product vis-à-vis the top 2 competitors.
The Smart Cube developed forecasting models by analysing 5-year historical client sales and external factors (competitive entry, seasonality, holidays and weather), etc. We used a variety of tools to perform exploratory data analysis (trend analysis, seasonal pattern, simple moving averages and correlation), time series forecasting (using exponential smoothing and ARIMA) and regression analysis.
The forecasting model highlighted predicted sales/market share vis-à-vis competitor brands, and helped the client create strategic plans by considering the impact of external factors such as competitive entry, seasonality and holidays.